Multi-agent simulation of generation expansion in electricity markets.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Botterud, A; Mahalik, M. R.; Veselka, T. D.

2007-06-01

We present a new multi-agent model of generation expansion in electricity markets. The model simulates generation investment decisions of decentralized generating companies (GenCos) interacting in a complex, multidimensional environment. A probabilistic dispatch algorithm calculates prices and profits for new candidate units in different future states of the system. Uncertainties in future load, hydropower conditions, and competitors actions are represented in a scenario tree, and decision analysis is used to identify the optimal expansion decision for each individual GenCo. We test the model using real data for the Korea power system under different assumptions about market design, market concentration, and GenCo'smore » assumed expectations about their competitors investment decisions.« less

Multi-Agent simulation of generation capacity expansion decisions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Botterud, A.; Mahalik, M.; Conzelmann, G.

2008-01-01

In this paper, we use a multi-agent simulation model, EMCAS, to analyze generation expansion in the Iberian electricity market. The expansion model simulates generation investment decisions of decentralized generating companies (GenCos) interacting in a complex, multidimensional environment. A probabilistic dispatch algorithm calculates prices and profits for new candidate units in different future states of the system. Uncertainties in future load, hydropower conditions, and competitorspsila actions are represented in a scenario tree, and decision analysis is used to identify the optimal expansion decision for each individual GenCo. We run the model using detailed data for the Iberian market. In a scenariomore » analysis, we look at the impact of market design variables, such as the energy price cap and carbon emission prices. We also analyze how market concentration and GenCospsila risk preferences influence the timing and choice of new generating capacity.« less

Network model of bilateral power markets based on complex networks

NASA Astrophysics Data System (ADS)

Wu, Yang; Liu, Junyong; Li, Furong; Yan, Zhanxin; Zhang, Li

2014-06-01

The bilateral power transaction (BPT) mode becomes a typical market organization with the restructuring of electric power industry, the proper model which could capture its characteristics is in urgent need. However, the model is lacking because of this market organization's complexity. As a promising approach to modeling complex systems, complex networks could provide a sound theoretical framework for developing proper simulation model. In this paper, a complex network model of the BPT market is proposed. In this model, price advantage mechanism is a precondition. Unlike other general commodity transactions, both of the financial layer and the physical layer are considered in the model. Through simulation analysis, the feasibility and validity of the model are verified. At same time, some typical statistical features of BPT network are identified. Namely, the degree distribution follows the power law, the clustering coefficient is low and the average path length is a bit long. Moreover, the topological stability of the BPT network is tested. The results show that the network displays a topological robustness to random market member's failures while it is fragile against deliberate attacks, and the network could resist cascading failure to some extent. These features are helpful for making decisions and risk management in BPT markets.

Design of a National Skills Market Model for Air Force Enlisted Personnel

DTIC Science & Technology

1979-09-01

specific occupations, rather than merely by industrial sector, labor market behavior could be more clearly related to specific Air Force specialties. The ...distinguishable but related purposes. First, it is desired as an adjunct to the Integrated Simulation Evaluation Model (ISEM) currently being...corn- puter simulation model of the Air Force Manpower and Personnel System (AFM&PS) that integrates the behavioral relationships deter- mining the

The 1993 timber assessment market model: structure, projections, and policy simulations.

Treesearch

Darius M. Adams; Richard W. Haynes

1996-01-01

The 1993 timber assessment market model (TAMM) is a spatial model of the solidwood and timber inventory elements of the U.S. forest products sector. The TAMM model provides annual projections of volumes and prices in the solidwood products and sawtimber stumpage markets and estimates of total timber harvest and inventory by geographic region for periods of up to 50...

Customer social network affects marketing strategy: A simulation analysis based on competitive diffusion model

NASA Astrophysics Data System (ADS)

Hou, Rui; Wu, Jiawen; Du, Helen S.

2017-03-01

To explain the competition phenomenon and results between QQ and MSN (China) in the Chinese instant messaging software market, this paper developed a new population competition model based on customer social network. The simulation results show that the firm whose product with greater network externality effect will gain more market share than its rival when the same marketing strategy is used. The firm with the advantage of time, derived from the initial scale effect will become more competitive than its rival when facing a group of common penguin customers within a social network, verifying the winner-take-all phenomenon in this case.

Ising model of financial markets with many assets

NASA Astrophysics Data System (ADS)

Eckrot, A.; Jurczyk, J.; Morgenstern, I.

2016-11-01

Many models of financial markets exist, but most of them simulate single asset markets. We study a multi asset Ising model of a financial market. Each agent has two possible actions (buy/sell) for every asset. The agents dynamically adjust their coupling coefficients according to past market returns and external news. This leads to fat tails and volatility clustering independent of the number of assets. We find that a separation of news into different channels leads to sector structures in the cross correlations, similar to those found in real markets.

An Evaluation of the Synergistic Simulation of the Federal Open Market Committee.

ERIC Educational Resources Information Center

Bartlett, Robin Lynn; Amsler, Christine E.

The Federal Open Market Committee (FOMC) simulation employed three techniques: case study, role playing, and model building, in order to acquaint college students studying money and banking with the creation of monetary policy. The specific goals of the FOMC simulation were: (1) to familiarize students with the data used in monetary policy…

Building a Market Simulation to Teach Business Process Analysis: Effects of Realism on Engaged Learning

ERIC Educational Resources Information Center

Peng, Jacob; Abdullah, Ira

2018-01-01

The emphases of student involvement and meaningful engagement in the learner-centered education model have created a new paradigm in an effort to generate a more engaging learning environment. This study examines the success of using different simulation platforms in creating a market simulation to teach business processes in the accounting…

Crossed and Locked Quotes in a Multi-Market Simulation

PubMed Central

Todd, Andrew; Beling, Peter; Scherer, William

2016-01-01

Financial markets are often fragmented, introducing the possibility that quotes in identical securities may become crossed or locked. There are a number of theoretical explanations for the existence of crossed and locked quotes, including competition, simultaneous actions, inattentiveness, fee structure and market access. In this paper, we perform a simulation experiment designed to examine the effect of simple order routing procedures on the properties of a fragmented market consisting of a single security trading in two independent limit order books. The quotes in the two markets are connected solely by the routing decision of the market participants. We report on the health of the consolidated market as measured by the duration of crossed and locked states, as well as the spread and the volatility of transaction prices in the consolidated market. We aim to quantify exactly how the prevalence of order routing among a population of market participants affects properties of the consolidated market. Our model contributes to the zero-intelligence literature by treating order routing as an experimental variable. Additionally, we introduce a parsimonious heuristic for limit order routing, allowing us to study the effects of both market order routing and limit order routing. Our model refines intuition for the sometimes subtle relationships between the prevalence of order routing and various market measures. Our model also provides a benchmark for more complex agent-based models. PMID:26959416

Crossed and Locked Quotes in a Multi-Market Simulation.

PubMed

Todd, Andrew; Beling, Peter; Scherer, William

2016-01-01

Financial markets are often fragmented, introducing the possibility that quotes in identical securities may become crossed or locked. There are a number of theoretical explanations for the existence of crossed and locked quotes, including competition, simultaneous actions, inattentiveness, fee structure and market access. In this paper, we perform a simulation experiment designed to examine the effect of simple order routing procedures on the properties of a fragmented market consisting of a single security trading in two independent limit order books. The quotes in the two markets are connected solely by the routing decision of the market participants. We report on the health of the consolidated market as measured by the duration of crossed and locked states, as well as the spread and the volatility of transaction prices in the consolidated market. We aim to quantify exactly how the prevalence of order routing among a population of market participants affects properties of the consolidated market. Our model contributes to the zero-intelligence literature by treating order routing as an experimental variable. Additionally, we introduce a parsimonious heuristic for limit order routing, allowing us to study the effects of both market order routing and limit order routing. Our model refines intuition for the sometimes subtle relationships between the prevalence of order routing and various market measures. Our model also provides a benchmark for more complex agent-based models.

Understanding price discovery in interconnected markets: Generalized Langevin process approach and simulation

NASA Astrophysics Data System (ADS)

Schenck, Natalya A.; Horvath, Philip A.; Sinha, Amit K.

2018-02-01

While the literature on price discovery process and information flow between dominant and satellite market is exhaustive, most studies have applied an approach that can be traced back to Hasbrouck (1995) or Gonzalo and Granger (1995). In this paper, however, we propose a Generalized Langevin process with asymmetric double-well potential function, with co-integrated time series and interconnected diffusion processes to model the information flow and price discovery process in two, a dominant and a satellite, interconnected markets. A simulated illustration of the model is also provided.

From market games to real-world markets

NASA Astrophysics Data System (ADS)

Jefferies, P.; Hart, M. L.; Hui, P. M.; Johnson, N. F.

2001-04-01

This paper uses the development of multi-agent market models to present a unified approach to the joint questions of how financial market movements may be simulated, predicted, and hedged against. We first present the results of agent-based market simulations in which traders equipped with simple buy/sell strategies and limited information compete in speculatory trading. We examine the effect of different market clearing mechanisms and show that implementation of a simple Walrasian auction leads to unstable market dynamics. We then show that a more realistic out-of-equilibrium clearing process leads to dynamics that closely resemble real financial movements, with fat-tailed price increments, clustered volatility and high volume autocorrelation. We then show that replacing the `synthetic' price history used by these simulations with data taken from real financial time-series leads to the remarkable result that the agents can collectively learn to identify moments in the market where profit is attainable. Hence on real financial data, the system as a whole can perform better than random. We then employ the formalism of Bouchaud in conjunction with agent based models to show that in general risk cannot be eliminated from trading with these models. We also show that, in the presence of transaction costs, the risk of option writing is greatly increased. This risk, and the costs, can however be reduced through the use of a delta-hedging strategy with modified, time-dependent volatility structure.

Simulating partially illegal markets of private tanker water providers on the country level: A multi-agent, hydroeconomic case-study of Jordan

NASA Astrophysics Data System (ADS)

Klassert, C. J. A.; Yoon, J.; Gawel, E.; Klauer, B.; Sigel, K.; Talozi, S.; Lachaut, T.; Selby, P. D.; Knox, S.; Gorelick, S.; Tilmant, A.; Harou, J. J.; Mustafa, D.; Medellin-Azuara, J.; Rajsekhar, D.; Avisse, N.; Zhang, H.

2016-12-01

In arid countries around the world, markets of private small-scale water providers, mostly delivering water via tanker trucks, have emerged to balance the shortcomings of public water supply systems. While these markets can provide substantial contributions to meeting customers' water demands, they often partially rely on illegal water abstractions, thus imposing an unregulated and unmonitored strain on ground and surface water resources. Despite their important impacts on water users' welfare and resource sustainability, these markets are still poorly understood. We use a multi-agent, hydroeconomic simulation model, developed as part of the Jordan Water Project, to investigate the role of these markets in a country-wide case-study of Jordan. Jordan's water sector is characterized by a severe and growing scarcity of water resources, high intermittency in the public water network, and a strongly increasing demand due to an unprecedented refugee crisis. The tanker water market serves an important role in providing water from rural wells to households and commercial enterprises, especially during supply interruptions. In order to overcome the lack of direct data about this partially illegal market, we simulate demand and supply for tanker water. The demand for tanker water is conceptualized as a residual demand, remaining after a water user has depleted all available cheap and qualitatively reliable piped water. It is derived from residential and commercial demand functions on the basis of survey data. Tanker water supply is determined by farm simulation models calculating the groundwater pumping cost and the agricultural opportunity cost of tanker water. A market algorithm is then used to match rural supplies with users' demands, accounting for survey data on tanker operators' transport costs and profit expectations. The model is used to gain insights into the size of the tanker markets in all 89 subdistricts of Jordan and their responsiveness to various policy interventions. A dynamic coupling of the model with a country-wide groundwater model allows for projections of the spatial development of the tanker market over time. Accounting for this important supply source will be essential for the formulation of any policy aiming to reconcile the interests of water users with resource sustainability.

Distributed Generation Market Demand Model | NREL

Science.gov Websites

Demand Model The Distributed Generation Market Demand (dGen) model simulates the potential adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the dGen model can help develop deployment forecasts for distributed resources, including sensitivity to

Information driving force and its application in agent-based modeling

NASA Astrophysics Data System (ADS)

Chen, Ting-Ting; Zheng, Bo; Li, Yan; Jiang, Xiong-Fei

2018-04-01

Exploring the scientific impact of online big-data has attracted much attention of researchers from different fields in recent years. Complex financial systems are typical open systems profoundly influenced by the external information. Based on the large-scale data in the public media and stock markets, we first define an information driving force, and analyze how it affects the complex financial system. The information driving force is observed to be asymmetric in the bull and bear market states. As an application, we then propose an agent-based model driven by the information driving force. Especially, all the key parameters are determined from the empirical analysis rather than from statistical fitting of the simulation results. With our model, both the stationary properties and non-stationary dynamic behaviors are simulated. Considering the mean-field effect of the external information, we also propose a few-body model to simulate the financial market in the laboratory.

Numerical analysis for finite-range multitype stochastic contact financial market dynamic systems

NASA Astrophysics Data System (ADS)

Yang, Ge; Wang, Jun; Fang, Wen

2015-04-01

In an attempt to reproduce and study the dynamics of financial markets, a random agent-based financial price model is developed and investigated by the finite-range multitype contact dynamic system, in which the interaction and dispersal of different types of investment attitudes in a stock market are imitated by viruses spreading. With different parameters of birth rates and finite-range, the normalized return series are simulated by Monte Carlo simulation method and numerical studied by power-law distribution analysis and autocorrelation analysis. To better understand the nonlinear dynamics of the return series, a q-order autocorrelation function and a multi-autocorrelation function are also defined in this work. The comparisons of statistical behaviors of return series from the agent-based model and the daily historical market returns of Shanghai Composite Index and Shenzhen Component Index indicate that the proposed model is a reasonable qualitative explanation for the price formation process of stock market systems.

New approaches in agent-based modeling of complex financial systems

NASA Astrophysics Data System (ADS)

Chen, Ting-Ting; Zheng, Bo; Li, Yan; Jiang, Xiong-Fei

2017-12-01

Agent-based modeling is a powerful simulation technique to understand the collective behavior and microscopic interaction in complex financial systems. Recently, the concept for determining the key parameters of agent-based models from empirical data instead of setting them artificially was suggested. We first review several agent-based models and the new approaches to determine the key model parameters from historical market data. Based on the agents' behaviors with heterogeneous personal preferences and interactions, these models are successful in explaining the microscopic origination of the temporal and spatial correlations of financial markets. We then present a novel paradigm combining big-data analysis with agent-based modeling. Specifically, from internet query and stock market data, we extract the information driving forces and develop an agent-based model to simulate the dynamic behaviors of complex financial systems.

The value of information in a multi-agent market model. The luck of the uninformed

NASA Astrophysics Data System (ADS)

Tóth, B.; Scalas, E.; Huber, J.; Kirchler, M.

2007-01-01

We present an experimental and simulated model of a multi-agent stock market driven by a double auction order matching mechanism. Studying the effect of cumulative information on the performance of traders, we find a non monotonic relationship of net returns of traders as a function of information levels, both in the experiments and in the simulations. Particularly, averagely informed traders perform worse than the non informed and only traders with high levels of information (insiders) are able to beat the market. The simulations and the experiments reproduce many stylized facts of tick-by-tick stock-exchange data, such as fast decay of autocorrelation of returns, volatility clustering and fat-tailed distribution of returns. These results have an important message for everyday life. They can give a possible explanation why, on average, professional fund managers perform worse than the market index.

Machine learning in sentiment reconstruction of the simulated stock market

NASA Astrophysics Data System (ADS)

Goykhman, Mikhail; Teimouri, Ali

2018-02-01

In this paper we continue the study of the simulated stock market framework defined by the driving sentiment processes. We focus on the market environment driven by the buy/sell trading sentiment process of the Markov chain type. We apply the methodology of the Hidden Markov Models and the Recurrent Neural Networks to reconstruct the transition probabilities matrix of the Markov sentiment process and recover the underlying sentiment states from the observed stock price behavior. We demonstrate that the Hidden Markov Model can successfully recover the transition probabilities matrix for the hidden sentiment process of the Markov Chain type. We also demonstrate that the Recurrent Neural Network can successfully recover the hidden sentiment states from the observed simulated stock price time series.

Herding, minority game, market clearing and efficient markets in a simple spin model framework

NASA Astrophysics Data System (ADS)

Kristoufek, Ladislav; Vosvrda, Miloslav

2018-01-01

We present a novel approach towards the financial Ising model. Most studies utilize the model to find settings which generate returns closely mimicking the financial stylized facts such as fat tails, volatility clustering and persistence, and others. We tackle the model utility from the other side and look for the combination of parameters which yields return dynamics of the efficient market in the view of the efficient market hypothesis. Working with the Ising model, we are able to present nicely interpretable results as the model is based on only two parameters. Apart from showing the results of our simulation study, we offer a new interpretation of the Ising model parameters via inverse temperature and entropy. We show that in fact market frictions (to a certain level) and herding behavior of the market participants do not go against market efficiency but what is more, they are needed for the markets to be efficient.

Empirical validation of an agent-based model of wood markets in Switzerland

PubMed Central

Hilty, Lorenz M.; Lemm, Renato; Thees, Oliver

2018-01-01

We present an agent-based model of wood markets and show our efforts to validate this model using empirical data from different sources, including interviews, workshops, experiments, and official statistics. Own surveys closed gaps where data was not available. Our approach to model validation used a variety of techniques, including the replication of historical production amounts, prices, and survey results, as well as a historical case study of a large sawmill entering the market and becoming insolvent only a few years later. Validating the model using this case provided additional insights, showing how the model can be used to simulate scenarios of resource availability and resource allocation. We conclude that the outcome of the rigorous validation qualifies the model to simulate scenarios concerning resource availability and allocation in our study region. PMID:29351300

Pricing and Application of Electric Storage

NASA Astrophysics Data System (ADS)

Zhao, Jialin

Electric storage provides a vehicle to store power for future use. It contributes to the grids in multiple aspects. For instance, electric storage is a more effective approach to provide electricity ancillary services than conventional methods. Additionally, electric storage, especially fast-responding units, allows owners to implement high-frequency power transactions in settings such as the 5-min real-time trading market. Such high-frequency power trades were limited in the past. However, as technology advances, the power markets have evolved. For instance, the California Independent System Operator now supports the 5-min real-time trading and the hourly day-ahead ancillary services bidding. Existing valuation models of electric storage were not designed to accommodate these recent market developments. To fill this gap, I focus on the fast-responding grid-level electric storage that provides both the real-time trading and the day-ahead ancillary services bidding. To evaluate such an asset, I propose a Monte Carlo Simulation-based valuation model. The foundation of my model is simulations of power prices. This study develops a new simulation model of electric prices. It is worth noting that, unlike existing models, my proposed simulation model captures the dependency of the real-time markets on the day-ahead markets. Upon such simulations, this study investigates the pricing and the application of electric storage at a 5-min granularity. Essentially, my model is a Dynamic Programming system with both endogenous variables (i.e., the State-of-Charge of electric storage) and exogenous variables (i.e., power prices). My first numerical example is the valuation of a fictitious 4MWh battery. Similarly, my second example evaluates the application of two units of 2MWh batteries. By comparing these two experiments, I investigate the issues related to battery configurations, such as the impacts of splitting storage capability on the valuation of electric storage.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rudkevich, Aleksandr; Goldis, Evgeniy

This research conducted by the Newton Energy Group, LLC (NEG) is dedicated to the development of pCloud: a Cloud-based Power Market Simulation Environment. pCloud is offering power industry stakeholders the capability to model electricity markets and is organized around the Software as a Service (SaaS) concept -- a software application delivery model in which software is centrally hosted and provided to many users via the internet. During the Phase I of this project NEG developed a prototype design for pCloud as a SaaS-based commercial service offering, system architecture supporting that design, ensured feasibility of key architecture's elements, formed technological partnershipsmore » and negotiated commercial agreements with partners, conducted market research and other related activities and secured funding for continue development of pCloud between the end of Phase I and beginning of Phase II, if awarded. Based on the results of Phase I activities, NEG has established that the development of a cloud-based power market simulation environment within the Windows Azure platform is technologically feasible, can be accomplished within the budget and timeframe available through the Phase II SBIR award with additional external funding. NEG believes that pCloud has the potential to become a game-changing technology for the modeling and analysis of electricity markets. This potential is due to the following critical advantages of pCloud over its competition: - Standardized access to advanced and proven power market simulators offered by third parties. - Automated parallelization of simulations and dynamic provisioning of computing resources on the cloud. This combination of automation and scalability dramatically reduces turn-around time while offering the capability to increase the number of analyzed scenarios by a factor of 10, 100 or even 1000. - Access to ready-to-use data and to cloud-based resources leading to a reduction in software, hardware, and IT costs. - Competitive pricing structure, which will make high-volume usage of simulation services affordable. - Availability and affordability of high quality power simulators, which presently only large corporate clients can afford, will level the playing field in developing regional energy policies, determining prudent cost recovery mechanisms and assuring just and reasonable rates to consumers. - Users that presently do not have the resources to internally maintain modeling capabilities will now be able to run simulations. This will invite more players into the industry, ultimately leading to more transparent and liquid power markets.« less

Computers for real time flight simulation: A market survey

NASA Technical Reports Server (NTRS)

Bekey, G. A.; Karplus, W. J.

1977-01-01

An extensive computer market survey was made to determine those available systems suitable for current and future flight simulation studies at Ames Research Center. The primary requirement is for the computation of relatively high frequency content (5 Hz) math models representing powered lift flight vehicles. The Rotor Systems Research Aircraft (RSRA) was used as a benchmark vehicle for computation comparison studies. The general nature of helicopter simulations and a description of the benchmark model are presented, and some of the sources of simulation difficulties are examined. A description of various applicable computer architectures is presented, along with detailed discussions of leading candidate systems and comparisons between them.

Evaluation of wholesale electric power market rules and financial risk management by agent-based simulations

NASA Astrophysics Data System (ADS)

Yu, Nanpeng

As U.S. regional electricity markets continue to refine their market structures, designs and rules of operation in various ways, two critical issues are emerging. First, although much experience has been gained and costly and valuable lessons have been learned, there is still a lack of a systematic platform for evaluation of the impact of a new market design from both engineering and economic points of view. Second, the transition from a monopoly paradigm characterized by a guaranteed rate of return to a competitive market created various unfamiliar financial risks for various market participants, especially for the Investor Owned Utilities (IOUs) and Independent Power Producers (IPPs). This dissertation uses agent-based simulation methods to tackle the market rules evaluation and financial risk management problems. The California energy crisis in 2000-01 showed what could happen to an electricity market if it did not go through a comprehensive and rigorous testing before its implementation. Due to the complexity of the market structure, strategic interaction between the participants, and the underlying physics, it is difficult to fully evaluate the implications of potential changes to market rules. This dissertation presents a flexible and integrative method to assess market designs through agent-based simulations. Realistic simulation scenarios on a 225-bus system are constructed for evaluation of the proposed PJM-like market power mitigation rules of the California electricity market. Simulation results show that in the absence of market power mitigation, generation company (GenCo) agents facilitated by Q-learning are able to exploit the market flaws and make significantly higher profits relative to the competitive benchmark. The incorporation of PJM-like local market power mitigation rules is shown to be effective in suppressing the exercise of market power. The importance of financial risk management is exemplified by the recent financial crisis. In this dissertation, basic financial risk management concepts relevant for wholesale electric power markets are carefully explained and illustrated. In addition, the financial risk management problem in wholesale electric power markets is generalized as a four-stage process. Within the proposed financial risk management framework, the critical problem of financial bilateral contract negotiation is addressed. This dissertation analyzes a financial bilateral contract negotiation process between a generating company and a load-serving entity in a wholesale electric power market with congestion managed by locational marginal pricing. Nash bargaining theory is used to model a Pareto-efficient settlement point. The model predicts negotiation results under varied conditions and identifies circumstances in which the two parties might fail to reach an agreement. Both analysis and agent-based simulation are used to gain insight regarding how relative risk aversion and biased price estimates influence negotiated outcomes. These results should provide useful guidance to market participants in their bilateral contract negotiation processes.

A dynamic model of the marriage market-Part 2: simulation of marital states and application to empirical data.

PubMed

Matthews, A P; Garenne, M L

2013-09-01

A dynamic, two-sex, age-structured marriage model is presented. Part 1 focused on first marriage only and described a marriage market matching algorithm. In Part 2 the model is extended to include divorce, widowing, and remarriage. The model produces a self-consistent set of marital states distributed by age and sex in a stable population by means of a gender-symmetric numerical method. The model is compared with empirical data for the case of Zambia. Furthermore, a dynamic marriage function for a changing population is demonstrated in simulations of three hypothetical scenarios of elevated mortality in young to middle adulthood. The marriage model has its primary application to simulation of HIV-AIDS epidemics in African countries. Copyright © 2013 Elsevier Inc. All rights reserved.

Outflow dynamics in modeling oligopoly markets: the case of the mobile telecommunications market in Poland

NASA Astrophysics Data System (ADS)

Sznajd-Weron, Katarzyna; Weron, Rafał; Włoszczowska, Maja

2008-11-01

In this paper we introduce two models of opinion dynamics in oligopoly markets and apply them to a situation where a new entrant challenges two incumbents of the same size. The models differ in the way in which the two forces influencing consumer choice—(local) social interactions and (global) advertising—interact. We study the general behavior of the models using the mean field approach and Monte Carlo simulations and calibrate the models using data from the Polish telecommunications market. For one of the models criticality is observed—below a certain critical level of advertising the market approaches a lock-in situation, where one market leader dominates the market and all other brands disappear. Interestingly, for both models the best fits to real data are obtained for conformity level p \\in (0.3,0.4) . This agrees very well with the conformity level found by Solomon Asch in his famous social experiment.

Agent-based modeling: Methods and techniques for simulating human systems

PubMed Central

Bonabeau, Eric

2002-01-01

Agent-based modeling is a powerful simulation modeling technique that has seen a number of applications in the last few years, including applications to real-world business problems. After the basic principles of agent-based simulation are briefly introduced, its four areas of application are discussed by using real-world applications: flow simulation, organizational simulation, market simulation, and diffusion simulation. For each category, one or several business applications are described and analyzed. PMID:12011407

An agent-based model for an air emissions cap and trade program: A case study in Taiwan.

PubMed

Huang, Hsing-Fu; Ma, Hwong-Wen

2016-12-01

To determine the actual status of individuals in a system and the trading interaction between polluters, this study uses an agent-based model to set up a virtual world that represents the Kaohsiung and Pingtung regions in Taiwan, which are under the country's air emissions cap and trade program. The model can simulate each controlled industry's dynamic behavioral condition with the bottom-up method and can investigate the impact of the program and determine the industry's emissions reduction and trading condition. This model can be used elastically to predict the impact of the trading market through adjusting different settings of the program rules or combining the settings with other measures. The simulation results show that the emissions trading market has an oversupply, but we find that the market trading amounts are low. Additionally, we find that increasing the air pollution fee and offset rate restrains the agents' trading decision, according to the simulation results of each scenario. In particular, NO x and SO x trading amounts are easily impacted by the pollution fee, reduction rate, and offset rate. Also, the more transparent the market, the more it can help polluters trade. Therefore, if authorities want to intervene in the emissions trading market, they must be careful in adjusting the air pollution fee and program rules; otherwise, the trading market system cannot work effectively. We also suggest setting up a trading platform to help the dealers negotiate successfully. Copyright © 2016 Elsevier Ltd. All rights reserved.

Numerical analysis for finite-range multitype stochastic contact financial market dynamic systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Ge; Wang, Jun; Fang, Wen, E-mail: fangwen@bjtu.edu.cn

In an attempt to reproduce and study the dynamics of financial markets, a random agent-based financial price model is developed and investigated by the finite-range multitype contact dynamic system, in which the interaction and dispersal of different types of investment attitudes in a stock market are imitated by viruses spreading. With different parameters of birth rates and finite-range, the normalized return series are simulated by Monte Carlo simulation method and numerical studied by power-law distribution analysis and autocorrelation analysis. To better understand the nonlinear dynamics of the return series, a q-order autocorrelation function and a multi-autocorrelation function are also definedmore » in this work. The comparisons of statistical behaviors of return series from the agent-based model and the daily historical market returns of Shanghai Composite Index and Shenzhen Component Index indicate that the proposed model is a reasonable qualitative explanation for the price formation process of stock market systems.« less

Volatility behavior of visibility graph EMD financial time series from Ising interacting system

NASA Astrophysics Data System (ADS)

Zhang, Bo; Wang, Jun; Fang, Wen

2015-08-01

A financial market dynamics model is developed and investigated by stochastic Ising system, where the Ising model is the most popular ferromagnetic model in statistical physics systems. Applying two graph based analysis and multiscale entropy method, we investigate and compare the statistical volatility behavior of return time series and the corresponding IMF series derived from the empirical mode decomposition (EMD) method. And the real stock market indices are considered to be comparatively studied with the simulation data of the proposed model. Further, we find that the degree distribution of visibility graph for the simulation series has the power law tails, and the assortative network exhibits the mixing pattern property. All these features are in agreement with the real market data, the research confirms that the financial model established by the Ising system is reasonable.

Essays in energy policy and planning modeling under uncertainty: Value of information, optimistic biases, and simulation of capacity markets

NASA Astrophysics Data System (ADS)

Hu, Ming-Che

Optimization and simulation are popular operations research and systems analysis tools for energy policy modeling. This dissertation addresses three important questions concerning the use of these tools for energy market (and electricity market) modeling and planning under uncertainty. (1) What is the value of information and cost of disregarding different sources of uncertainty for the U.S. energy economy? (2) Could model-based calculations of the performance (social welfare) of competitive and oligopolistic market equilibria be optimistically biased due to uncertainties in objective function coefficients? (3) How do alternative sloped demand curves perform in the PJM capacity market under economic and weather uncertainty? How does curve adjustment and cost dynamics affect the capacity market outcomes? To address the first question, two-stage stochastic optimization is utilized in the U.S. national MARKAL energy model; then the value of information and cost of ignoring uncertainty are estimated for three uncertainties: carbon cap policy, load growth and natural gas prices. When an uncertainty is important, then explicitly considering those risks when making investments will result in better performance in expectation (positive expected cost of ignoring uncertainty). Furthermore, eliminating the uncertainty would improve strategies even further, meaning that improved forecasts of future conditions are valuable ( i.e., a positive expected value of information). Also, the value of policy coordination shows the difference between a strategy developed under the incorrect assumption of no carbon cap and a strategy correctly anticipating imposition of such a cap. For the second question, game theory models are formulated and the existence of optimistic (positive) biases in market equilibria (both competitive and oligopoly markets) are proved, in that calculated social welfare and producer profits will, in expectation, exceed the values that will actually be received. Theoretical analyses prove the general existence of this bias for both competitive and oligopolistic models when production costs and demand curves are uncertain. Also demonstrated is an optimistic bias for the net benefits of introducing a new technology into a market when the cost of the new technology is uncertainty. The optimistic biases are quantified for a model of the northwest European electricity market (including Belgium, France, Germany and the Netherlands). Demand uncertainty results in an optimistic bias of 150,000-220,000 [Euro]/hr of total surplus and natural gas price uncertainty yields a smaller bias of 8,000-10,000 [Euro]/hr for total surplus. Further, adding a new uncertain technology (biomass) to the set of possible generation methods almost doubles the optimistic bias (14,000-18,000 [Euro]/hr). The third question concerns ex ante evaluation of the Reliability Pricing Model (RPM)---the new PJM capacity market---launched in June 2007. A Monte Carlo simulation model is developed to simulate PJM capacity market and predict market performance, producer revenue, and consumer payments. An important input to RPM is a demand curve for capacity; several alternative demand curves are compared, and sensitivity analyses conducted of those conclusions. One conclusion is that the sloped demand curves are more robust because those demand curves gives higher reliability with lower consumer payments. In addition, the performance of the curves is evaluated for a more sophisticated market design in which the demand curve can be adjusted in response to previous market outcomes and where the capital costs may change unexpectedly. The simulation shows that curve adjustment increases system reliability with lower consumer payments. Also the effect of learning-by-doing, leading to lower plant capital costs, leads to higher average reserve margin and lower consumer payments. In contrast, a the sudden rise in capital costs causes a decrease in reliability and an increase in consumer payments.

Transferable Discharge Permit Trading Under Varying Stream Conditions: A Simulation of Multiperiod Permit Market Performance on the Fox River, Wisconsin

NASA Astrophysics Data System (ADS)

O'Neil, William B.

1983-06-01

The state of Wisconsin has recently established the legislative basis for what may be the first, operating water-pollution permit market in the United States. The efficient properties of such markets have been discussed widely in the theoretical literature, but little empirical work has been published regarding the potential cost savings attainable in specific situations. This paper describes part of the empirical analysis that supported the creation of a transferable discharge permit (TDP) market on the Fox River in Wisconsin. A multiperiod water quality planning model is developed to illustrate the performance of a TDP market under conditions of varying stream flow and temperature. The model is applied to the case of the Fox River and is used to compare the cost of achieving target water quality levels under conventional regulatory rules with the cost associated with operation of a TDP market. In addition to the cost estimates, the simulation of market performance yields information on the probable pattern of trading that may occur in the Fox River TDP market.

Topology of correlation-based minimal spanning trees in real and model markets

NASA Astrophysics Data System (ADS)

Bonanno, Giovanni; Caldarelli, Guido; Lillo, Fabrizio; Mantegna, Rosario N.

2003-10-01

We compare the topological properties of the minimal spanning tree obtained from a large group of stocks traded at the New York Stock Exchange during a 12-year trading period with the one obtained from surrogated data simulated by using simple market models. We find that the empirical tree has features of a complex network that cannot be reproduced, even as a first approximation, by a random market model and by the widespread one-factor model.

Does the market maker stabilize the market?

NASA Astrophysics Data System (ADS)

Zhu, Mei; Chiarella, Carl; He, Xue-Zhong; Wang, Duo

2009-08-01

The market maker plays an important role in price formation, but his/her behavior and stabilizing impact on the market are relatively unclear, in particular in speculative markets. This paper develops a financial market model that examines the impact on market stability of the market maker, who acts as both a liquidity provider and an active investor in a market consisting of two types of boundedly rational speculative investors-the fundamentalists and trend followers. We show that the market maker does not necessarily stabilize the market when he/she actively manages the inventory to maximize profits, and that rather the market maker’s impact depends on the behavior of the speculators. Numerical simulations show that the model is able to generate outcomes for asset returns and market inventories that are consistent with empirical findings.

Understanding agent-based models of financial markets: A bottom-up approach based on order parameters and phase diagrams

NASA Astrophysics Data System (ADS)

Lye, Ribin; Tan, James Peng Lung; Cheong, Siew Ann

2012-11-01

We describe a bottom-up framework, based on the identification of appropriate order parameters and determination of phase diagrams, for understanding progressively refined agent-based models and simulations of financial markets. We illustrate this framework by starting with a deterministic toy model, whereby N independent traders buy and sell M stocks through an order book that acts as a clearing house. The price of a stock increases whenever it is bought and decreases whenever it is sold. Price changes are updated by the order book before the next transaction takes place. In this deterministic model, all traders based their buy decisions on a call utility function, and all their sell decisions on a put utility function. We then make the agent-based model more realistic, by either having a fraction fb of traders buy a random stock on offer, or a fraction fs of traders sell a random stock in their portfolio. Based on our simulations, we find that it is possible to identify useful order parameters from the steady-state price distributions of all three models. Using these order parameters as a guide, we find three phases: (i) the dead market; (ii) the boom market; and (iii) the jammed market in the phase diagram of the deterministic model. Comparing the phase diagrams of the stochastic models against that of the deterministic model, we realize that the primary effect of stochasticity is to eliminate the dead market phase.

The Influence of the Number of Different Stocks on the Levy-Levy-Solomon Model

NASA Astrophysics Data System (ADS)

Kohl, R.

The stock market model of Levy, Levy, Solomon is simulated for more than one stock to analyze the behavior for a large number of investors. Small markets can lead to realistic looking prices for one and more stocks. A large number of investors leads to a semi-regular fashion simulating one stock. For many stocks, three of the stocks are semi-regular and dominant, the rest is chaotic. Aside from that we changed the utility function and checked the results.

Market power and the sale of Ontario residential natural gas: An institutional analysis and a laboratory experiment

NASA Astrophysics Data System (ADS)

Bloemhof, Barbara Lynn

2005-11-01

The Ontario residential natural gas market underwent a significant institutional change in 1986, after the federal government decontrolled natural gas prices. Currently, consumers may sign up for fixed-cost natural gas from a broker, or they may continue to be served by the regulated distribution company. This thesis examines the economic effects on consumers of the institutional change, and particularly whether or not market power was enhanced by the change. In the thesis, I first present the industrial organization of the residential natural gas sector, and explain the institutional evolution using an institutional economic approach. I then construct a model of the market environment, with sellers acting as middlemen in a well-defined Bertrand oligopoly setting with no production constraints and single-unit consumer demands. In this model, the only Nash equilibrium in the one-period game is the joint profit maximizing price, and its likelihood of obtaining depends on the nature of the cost of signing up new customers. I then take a version of this model into the laboratory with human subject sellers and simulated buyers and run six replications each of a balanced treatment design under a unique information mechanism that parallels individual customer canvassing used by sellers in the naturally-occurring market. Treatment variables are: number of sellers, number of simulated at-cost sellers present, and presence of input cost uncertainty for sellers. I find that adding any seller to the market has about the same impact on market price, irrespective of whether it is a human subject or a simulated at-cost seller. Although increasing the number of sellers does decrease the market price somewhat, it does not bring about the competitive outcome predicted by the benchmark microeconomic model. This research contributes to the literature on policy making and energy market design, as well as to experimental methodology aimed at policy evaluation.

Sensitivity of Rooftop PV Projections in the SunShot Vision Study to Market Assumptions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Drury, E.; Denholm, P.; Margolis, R.

2013-01-01

The SunShot Vision Study explored the potential growth of solar markets if solar prices decreased by about 75% from 2010 to 2020. The SolarDS model was used to simulate rooftop PV demand for this study, based on several PV market assumptions--future electricity rates, customer access to financing, and others--in addition to the SunShot PV price projections. This paper finds that modeled PV demand is highly sensitive to several non-price market assumptions, particularly PV financing parameters.

The Distributed Geothermal Market Demand Model (dGeo): Documentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCabe, Kevin; Mooney, Meghan E; Sigrin, Benjamin O

The National Renewable Energy Laboratory (NREL) developed the Distributed Geothermal Market Demand Model (dGeo) as a tool to explore the potential role of geothermal distributed energy resources (DERs) in meeting thermal energy demands in the United States. The dGeo model simulates the potential for deployment of geothermal DERs in the residential and commercial sectors of the continental United States for two specific technologies: ground-source heat pumps (GHP) and geothermal direct use (DU) for district heating. To quantify the opportunity space for these technologies, dGeo leverages a highly resolved geospatial database and robust bottom-up, agent-based modeling framework. This design is consistentmore » with others in the family of Distributed Generation Market Demand models (dGen; Sigrin et al. 2016), including the Distributed Solar Market Demand (dSolar) and Distributed Wind Market Demand (dWind) models. dGeo is intended to serve as a long-term scenario-modeling tool. It has the capability to simulate the technical potential, economic potential, market potential, and technology deployment of GHP and DU through the year 2050 under a variety of user-defined input scenarios. Through these capabilities, dGeo can provide substantial analytical value to various stakeholders interested in exploring the effects of various techno-economic, macroeconomic, financial, and policy factors related to the opportunity for GHP and DU in the United States. This report documents the dGeo modeling design, methodology, assumptions, and capabilities.« less

Research on Capacity Addition using Market Model with Transmission Congestion under Competitive Environment

NASA Astrophysics Data System (ADS)

Katsura, Yasufumi; Attaviriyanupap, Pathom; Kataoka, Yoshihiko

In this research, the fundamental premises for deregulation of the electric power industry are reevaluated. The authors develop a simple model to represent wholesale electricity market with highly congested network. The model is developed by simplifying the power system and market in New York ISO based on available data of New York ISO in 2004 with some estimation. Based on the developed model and construction cost data from the past, the economic impact of transmission line addition on market participants and the impact of deregulation on power plant additions under market with transmission congestion are studied. Simulation results show that the market signals may fail to facilitate proper capacity additions and results in the undesirable over-construction and insufficient-construction cycle of capacity addition.

SAMICS marketing and distribution model

NASA Technical Reports Server (NTRS)

1978-01-01

A SAMICS (Solar Array Manufacturing Industry Costing Standards) was formulated as a computer simulation model. Given a proper description of the manufacturing technology as input, this model computes the manufacturing price of solar arrays for a broad range of production levels. This report presents a model for computing these marketing and distribution costs, the end point of the model being the loading dock of the final manufacturer.

Complexity and multifractal behaviors of multiscale-continuum percolation financial system for Chinese stock markets

NASA Astrophysics Data System (ADS)

Zeng, Yayun; Wang, Jun; Xu, Kaixuan

2017-04-01

A new financial agent-based time series model is developed and investigated by multiscale-continuum percolation system, which can be viewed as an extended version of continuum percolation system. In this financial model, for different parameters of proportion and density, two Poisson point processes (where the radii of points represent the ability of receiving or transmitting information among investors) are applied to model a random stock price process, in an attempt to investigate the fluctuation dynamics of the financial market. To validate its effectiveness and rationality, we compare the statistical behaviors and the multifractal behaviors of the simulated data derived from the proposed model with those of the real stock markets. Further, the multiscale sample entropy analysis is employed to study the complexity of the returns, and the cross-sample entropy analysis is applied to measure the degree of asynchrony of return autocorrelation time series. The empirical results indicate that the proposed financial model can simulate and reproduce some significant characteristics of the real stock markets to a certain extent.

Large-Scale Simulation of Multi-Asset Ising Financial Markets

NASA Astrophysics Data System (ADS)

Takaishi, Tetsuya

2017-03-01

We perform a large-scale simulation of an Ising-based financial market model that includes 300 asset time series. The financial system simulated by the model shows a fat-tailed return distribution and volatility clustering and exhibits unstable periods indicated by the volatility index measured as the average of absolute-returns. Moreover, we determine that the cumulative risk fraction, which measures the system risk, changes at high volatility periods. We also calculate the inverse participation ratio (IPR) and its higher-power version, IPR6, from the absolute-return cross-correlation matrix. Finally, we show that the IPR and IPR6 also change at high volatility periods.

A multilayer approach for price dynamics in financial markets

NASA Astrophysics Data System (ADS)

Biondo, Alessio Emanuele; Pluchino, Alessandro; Rapisarda, Andrea

2017-02-01

We introduce a new Self-Organized Criticality (SOC) model for simulating price evolution in an artificial financial market, based on a multilayer network of traders. The model also implements, in a quite realistic way with respect to previous studies, the order book dynamics, by considering two assets with variable fundamental prices. Fat tails in the probability distributions of normalized returns are observed, together with other features of real financial markets.

Macroeconomics and oil-supply disruptions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hubbard, R.G.; Fry, R.C. Jr.

1981-04-01

Energy-economy interactions and domestic linkages have been used in a system of models. Domestic economic aggregates are linked with a model of the world oil market by a core macroeconomic model with real and financial sectors. The model can be used to examine the policy ramifications of various short-run scenarios. Demand factors are not taken as exogenous to the world oil market, nor are oil prices taken as exogenous to the US economy. Simulations of the model have generated endogenous cycles in the world oil market; which then affect the US economy primarily through output and inflation channels. Policy simulationmore » was centered around the short-run imposition of a disruption tariff. The disruption tariff exhibited at least some of the desirable features noted by its proponents, though it did not function as a shield against the short-run output loss forced by the disruption. One might also simulate the rebate of tariff revenues as a reduction in the social security payroll tax. Other possible simulations include the use of any of the fiscal and monetary instruments included in the model. The effectiveness of these other policy instruments will be examined in a later paper.« less

Price Formation Based on Particle-Cluster Aggregation

NASA Astrophysics Data System (ADS)

Wang, Shijun; Zhang, Changshui

In the present work, we propose a microscopic model of financial markets based on particle-cluster aggregation on a two-dimensional small-world information network in order to simulate the dynamics of the stock markets. "Stylized facts" of the financial market time series, such as fat-tail distribution of returns, volatility clustering and multifractality, are observed in the model. The results of the model agree with empirical data taken from historical records of the daily closures of the NYSE composite index.

Initial value sensitivity of the Chinese stock market and its relationship with the investment psychology

NASA Astrophysics Data System (ADS)

Ying, Shangjun; Li, Xiaojun; Zhong, Xiuqin

2015-04-01

This paper discusses the initial value sensitivity (IVS) of Chinese stock market, including the single stock market and the Chinese A-share stock market, with respect to real markets and evolving models. The aim is to explore the relationship between IVS of the Chinese A-share stock market and the investment psychology based on the evolving model of genetic cellular automaton (GCA). We find: (1) The Chinese stock market is sensitively dependent on the initial conditions. (2) The GCA model provides a considerable reliability in complexity simulation (e.g. the IVS). (3) The IVS of stock market is positively correlated with the imitation probability when the intensity of the imitation psychology reaches a certain threshold. The paper suggests that the government should seek to keep the imitation psychology under a certain level, otherwise it may induce severe fluctuation to the market.

Modeling and simulation of consumer response to dynamic pricing.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Valenzuela, J.; Thimmapuram, P.; Kim, J

2012-08-01

Assessing the impacts of dynamic-pricing under the smart grid concept is becoming extremely important for deciding its full deployment. In this paper, we develop a model that represents the response of consumers to dynamic pricing. In the model, consumers use forecasted day-ahead prices to shift daily energy consumption from hours when the price is expected to be high to hours when the price is expected to be low while maintaining the total energy consumption as unchanged. We integrate the consumer response model into the Electricity Market Complex Adaptive System (EMCAS). EMCAS is an agent-based model that simulates restructured electricity markets.more » We explore the impacts of dynamic-pricing on price spikes, peak demand, consumer energy bills, power supplier profits, and congestion costs. A simulation of an 11-node test network that includes eight generation companies and five aggregated consumers is performed for a period of 1 month. In addition, we simulate the Korean power system.« less

System-of-Systems Approach for Integrated Energy Systems Modeling and Simulation: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mittal, Saurabh; Ruth, Mark; Pratt, Annabelle

Today’s electricity grid is the most complex system ever built—and the future grid is likely to be even more complex because it will incorporate distributed energy resources (DERs) such as wind, solar, and various other sources of generation and energy storage. The complexity is further augmented by the possible evolution to new retail market structures that provide incentives to owners of DERs to support the grid. To understand and test new retail market structures and technologies such as DERs, demand-response equipment, and energy management systems while providing reliable electricity to all customers, an Integrated Energy System Model (IESM) is beingmore » developed at NREL. The IESM is composed of a power flow simulator (GridLAB-D), home energy management systems implemented using GAMS/Pyomo, a market layer, and hardware-in-the-loop simulation (testing appliances such as HVAC, dishwasher, etc.). The IESM is a system-of-systems (SoS) simulator wherein the constituent systems are brought together in a virtual testbed. We will describe an SoS approach for developing a distributed simulation environment. We will elaborate on the methodology and the control mechanisms used in the co-simulation illustrated by a case study.« less

MUSE--Model for University Strategic Evaluation. AIR 2002 Forum Paper.

ERIC Educational Resources Information Center

Kutina, Kenneth L.; Zullig, Craig M.; Starkman, Glenn D.; Tanski, Laura E.

A model for simulating college and university operations, finances, program investments, and market response in terms of applicants, acceptances, and retention has been developed and implemented using the system dynamics approach. The Model for University Strategic Evaluation (MUSE) is a simulation of the total operations of the university,…

Marketing percolation

NASA Astrophysics Data System (ADS)

Goldenberg, J.; Libai, B.; Solomon, S.; Jan, N.; Stauffer, D.

2000-09-01

A percolation model is presented, with computer simulations for illustrations, to show how the sales of a new product may penetrate the consumer market. We review the traditional approach in the marketing literature, which is based on differential or difference equations similar to the logistic equation (Bass, Manage. Sci. 15 (1969) 215). This mean-field approach is contrasted with the discrete percolation on a lattice, with simulations of "social percolation" (Solomon et al., Physica A 277 (2000) 239) in two to five dimensions giving power laws instead of exponential growth, and strong fluctuations right at the percolation threshold.

Emissions markets, power markets and market power: A study of the interactions between contemporary emissions markets and deregulated electricity markets

NASA Astrophysics Data System (ADS)

Dormady, Noah Christopher

Chapter 1: A Monte Carlo Approach. The use of auctions to distribute tradeable property rights to firms in already heavily concentrated markets may further exacerbate the problems of market power that exist within those markets. This chapter provides a model of a two-stage emissions market modeled after a contemporary regional permit trading market in the United States, the Regional Greenhouse Gas Initiative, Inc. (RGGI). It then introduces Oligopsony 1.0, a C# software package constructed in the .NET environment that simulates uniform-price auctions using stochastic Monte Carlo simulation for modeling market power in tradeable property rights auctions. Monte Carlo methods add a probabilistic element to standard auction theoretic equilibria. The results of these simulations indicate that there can be significant non-linearities between profit and market power as exercised through strategic demand reduction. This analysis finds the optimum point of strategic demand reduction that enables the firm to exploit these non-linearities, and it determines the probability distributions of these optima using kernel density analysis. Chapter 2: An Experimental Approach. How will emerging auction-based emissions markets function within the context of today's deregulated auction-based electricity markets? This chapter provides an experimental analysis of a joint energy-emissions market. The impact of market power and collusion among dominant firms is evaluated to determine the extent to which an auction-based tradeable permit market influences performance in an adjacent electricity market. The experimental treatment design controls for a variety of real-world institutional features, including variable demand, permit banking, inter-temporal (multi-round) dynamics, a tightening cap, and resale. Results suggest that the exercise of market power significantly increases electricity auction clearing prices, without significantly increasing emissions auction clearing prices, and in some cases, even significantly suppresses them. The institution of auction-based carbon markets in the already-concentrated energy sector can further strengthen the market position of dominant firms who can leverage energy-emissions market linkages to their operational advantage. Chapter 3: Regulatory Mechanisms and Policy Approaches. Contemporary deregulated electricity markets are defined by a complex array of multi-settlement markets, with additional market-based mechanisms designed, to a large extent, to limit the exercise of market power by dominant firms. On top of the already complex nature of these markets, policymakers are also adding market-based mechanisms to curtail greenhouse gases. Key linkages exist between electricity and emissions markets that may be utilized by dominant firms. This chapter provides an analysis of three specific policy mechanisms that are utilized in contemporary markets to effectively reduce the incentive of dominant firms to exercise market power. These include convergence bidding, consignment auctions and multilevel holding accounts.

Simulation of economic agents interaction in a trade chain

NASA Astrophysics Data System (ADS)

Gimanova, I. A.; Dulesov, A. S.; Litvin, N. V.

2017-01-01

The mathematical model of economic agents interaction is offered in the work. It allowsconsidering the change of price and sales volumesin dynamics according to the process of purchase and sale in the single-product market of the trade and intermediary network. The description of data-flow processes is based on the use of the continuous dynamic market model. The application of ordinary differential equations during the simulation allows one to define areas of coefficients - characteristics of agents - and to investigate their interaction in a chain on stability.

The structure of a market containing boundedly rational firms

NASA Astrophysics Data System (ADS)

Ibrahim, Adyda; Zura, Nerda; Saaban, Azizan

2017-11-01

The structure of a market is determined by the number of active firms in it. Over time, this number is affected by the exit of existing firms, called incumbents, and entries of new firms, called entrant. In this paper, we considered a market governed by the Cobb-Douglas utility function such that the demand function is isoelastic. Each firm is assumed to produce a single homogenous product under a constant unit cost. Furthermore, firms are assumed to be boundedly rational in adjusting their outputs at each period. A firm is considered to exit the market if its output is negative. In this paper, the market is assumed to have zero barrier-to-entry. Therefore, the exiting firm can reenter the market if its output is positive again, and new firms can enter the market easily. Based on these assumptions and rules, a mathematical model was developed and numerical simulations were run using Matlab. By setting certain values for the parameters in the model, initial numerical simulations showed that in the long run, the number of firms that manages to survive the market varies between zero to 30. This initial result is consistent with the idea that a zero barrier-to-entry may produce a perfectly competitive market.

Statistical power of intervention analyses: simulation and empirical application to treated lumber prices

Treesearch

Jeffrey P. Prestemon

2009-01-01

Timber product markets are subject to large shocks deriving from natural disturbances and policy shifts. Statistical modeling of shocks is often done to assess their economic importance. In this article, I simulate the statistical power of univariate and bivariate methods of shock detection using time series intervention models. Simulations show that bivariate methods...

Novel indexes based on network structure to indicate financial market

NASA Astrophysics Data System (ADS)

Zhong, Tao; Peng, Qinke; Wang, Xiao; Zhang, Jing

2016-02-01

There have been various achievements to understand and to analyze the financial market by complex network model. However, current studies analyze the financial network model but seldom present quantified indexes to indicate or forecast the price action of market. In this paper, the stock market is modeled as a dynamic network, in which the vertices refer to listed companies and edges refer to their rank-based correlation based on price series. Characteristics of the network are analyzed and then novel indexes are introduced into market analysis, which are calculated from maximum and fully-connected subnets. The indexes are compared with existing ones and the results confirm that our indexes perform better to indicate the daily trend of market composite index in advance. Via investment simulation, the performance of our indexes is analyzed in detail. The results indicate that the dynamic complex network model could not only serve as a structural description of the financial market, but also work to predict the market and guide investment by indexes.

Reducing the Complexity of an Agent-Based Local Heroin Market Model

PubMed Central

Heard, Daniel; Bobashev, Georgiy V.; Morris, Robert J.

2014-01-01

This project explores techniques for reducing the complexity of an agent-based model (ABM). The analysis involved a model developed from the ethnographic research of Dr. Lee Hoffer in the Larimer area heroin market, which involved drug users, drug sellers, homeless individuals and police. The authors used statistical techniques to create a reduced version of the original model which maintained simulation fidelity while reducing computational complexity. This involved identifying key summary quantities of individual customer behavior as well as overall market activity and replacing some agents with probability distributions and regressions. The model was then extended to allow external market interventions in the form of police busts. Extensions of this research perspective, as well as its strengths and limitations, are discussed. PMID:25025132

a Statistical Dynamic Approach to Structural Evolution of Complex Capital Market Systems

NASA Astrophysics Data System (ADS)

Shao, Xiao; Chai, Li H.

As an important part of modern financial systems, capital market has played a crucial role on diverse social resource allocations and economical exchanges. Beyond traditional models and/or theories based on neoclassical economics, considering capital markets as typical complex open systems, this paper attempts to develop a new approach to overcome some shortcomings of the available researches. By defining the generalized entropy of capital market systems, a theoretical model and nonlinear dynamic equation on the operations of capital market are proposed from statistical dynamic perspectives. The US security market from 1995 to 2001 is then simulated and analyzed as a typical case. Some instructive results are discussed and summarized.

Spatial analysis of private tanker water markets in Jordan: Using a hydroeconomic multi-agent model to simulate non-observed water transfers

NASA Astrophysics Data System (ADS)

Klassert, Christian; Yoon, Jim; Gawel, Erik; Sigel, Katja; Klauer, Bernd; Talozi, Samer; Lachaut, Thibaut; Selby, Philip; Knox, Stephen; Gorelick, Steven; Tilmant, Amaury; Harou, Julien; Mustafa, Daanish; Medellin-Azuara, Josue; Rajsekhar, Deepthi; Avisse, Nicolas; Zhang, Hua

2017-04-01

The country of Jordan is characterized by severe water scarcity and deficient public water supply networks. To address these issues, Jordan's water sector authorities have adopted a water rationing scheme implemented by interrupting piped water supply for several days per week. As in many arid countries around the world, this has led to the emergence of private markets of small-scale providers, delivering water via tanker trucks. On the one hand, these markets play a crucial role in meeting residential and commercial water demands by balancing the shortcomings of the public supply system. On the other hand, providers partially rely on illegal abstractions from rural ground and surface water sources, thereby circumventing regulatory efforts to conserve these resources. Private tanker water markets, therefore, provide a substantial contribution to consumer welfare while jeopardizing freshwater resource sustainability. Thus, a better understanding of these markets is of great importance for the formulation of policy interventions pursuing freshwater sustainability in a socially acceptable manner. Direct assessments of the size of these markets or their responses to policy interventions are, however, impeded by their partially illegal nature and the resulting lack of available information. To overcome this data collection challenge, we use a hydroeconomic multi-agent model developed in the Jordan Water Project to indirectly simulate country-wide tanker water market activities on the basis of demand and supply estimates. The demand for tanker water is conceptualized as a residual demand, remaining after a water user has depleted all available cheap and qualitatively reliable piped water. It is derived from residential and commercial demand functions on the basis of survey data. Tanker water supply is determined by farm simulation models calculating the groundwater pumping cost and the agricultural opportunity cost of tanker water. Finally, a spatial market algorithm matches rural supplies with users' demands across the 89 subdistricts of Jordan. This algorithm is parameterized with survey data we collected on tanker operators' transport costs and profit expectations. The model is successfully validated with available data on tanker truck registrations and tanker water prices. Model results reveal the spatial distribution of the private tanker markets' freshwater extractions, sales quantities, and economic impacts on different water user groups across all of Jordan. The results confirm the quantitative importance of these markets for consumer welfare. A dynamic coupling of farm agents with a country-wide groundwater model allows us to capture feedbacks between tanker water markets and groundwater levels. This enables us to assess policy impacts over time. Model analyses show that policies aiming to mitigate the negative sustainability impacts of private tanker water markets need to simultaneously address the shortcomings of the piped water supply system in order to avoid undue burdens on water users.

RESTSIM: A Simulation Model That Highlights Decision Making under Conditions of Uncertainty.

ERIC Educational Resources Information Center

Zinkhan, George M.; Taylor, James R.

1983-01-01

Describes RESTSIM, an interactive computer simulation program for graduate and upper-level undergraduate management, marketing, and retailing courses, which introduces naive users to simulation as a decision support technique, and provides a vehicle for studying various statistical procedures for evaluating simulation output. (MBR)

Understanding the complex dynamics of stock markets through cellular automata

NASA Astrophysics Data System (ADS)

Qiu, G.; Kandhai, D.; Sloot, P. M. A.

2007-04-01

We present a cellular automaton (CA) model for simulating the complex dynamics of stock markets. Within this model, a stock market is represented by a two-dimensional lattice, of which each vertex stands for a trader. According to typical trading behavior in real stock markets, agents of only two types are adopted: fundamentalists and imitators. Our CA model is based on local interactions, adopting simple rules for representing the behavior of traders and a simple rule for price updating. This model can reproduce, in a simple and robust manner, the main characteristics observed in empirical financial time series. Heavy-tailed return distributions due to large price variations can be generated through the imitating behavior of agents. In contrast to other microscopic simulation (MS) models, our results suggest that it is not necessary to assume a certain network topology in which agents group together, e.g., a random graph or a percolation network. That is, long-range interactions can emerge from local interactions. Volatility clustering, which also leads to heavy tails, seems to be related to the combined effect of a fast and a slow process: the evolution of the influence of news and the evolution of agents’ activity, respectively. In a general sense, these causes of heavy tails and volatility clustering appear to be common among some notable MS models that can confirm the main characteristics of financial markets.

Nonlinear complexity of random visibility graph and Lempel-Ziv on multitype range-intensity interacting financial dynamics

NASA Astrophysics Data System (ADS)

Zhang, Yali; Wang, Jun

2017-09-01

In an attempt to investigate the nonlinear complex evolution of financial dynamics, a new financial price model - the multitype range-intensity contact (MRIC) financial model, is developed based on the multitype range-intensity interacting contact system, in which the interaction and transmission of different types of investment attitudes in a stock market are simulated by viruses spreading. Two new random visibility graph (VG) based analyses and Lempel-Ziv complexity (LZC) are applied to study the complex behaviors of return time series and the corresponding random sorted series. The VG method is the complex network theory, and the LZC is a non-parametric measure of complexity reflecting the rate of new pattern generation of a series. In this work, the real stock market indices are considered to be comparatively studied with the simulation data of the proposed model. Further, the numerical empirical study shows the similar complexity behaviors between the model and the real markets, the research confirms that the financial model is reasonable to some extent.

Analysis of Spin Financial Market by GARCH Model

NASA Astrophysics Data System (ADS)

Takaishi, Tetsuya

2013-08-01

A spin model is used for simulations of financial markets. To determine return volatility in the spin financial market we use the GARCH model often used for volatility estimation in empirical finance. We apply the Bayesian inference performed by the Markov Chain Monte Carlo method to the parameter estimation of the GARCH model. It is found that volatility determined by the GARCH model exhibits "volatility clustering" also observed in the real financial markets. Using volatility determined by the GARCH model we examine the mixture-of-distribution hypothesis (MDH) suggested for the asset return dynamics. We find that the returns standardized by volatility are approximately standard normal random variables. Moreover we find that the absolute standardized returns show no significant autocorrelation. These findings are consistent with the view of the MDH for the return dynamics.

System dynamics of behaviour-evolutionary mix-game models

NASA Astrophysics Data System (ADS)

Gou, Cheng-Ling; Gao, Jie-Ping; Chen, Fang

2010-11-01

In real financial markets there are two kinds of traders: one is fundamentalist, and the other is a trend-follower. The mix-game model is proposed to mimic such phenomena. In a mix-game model there are two groups of agents: Group 1 plays the majority game and Group 2 plays the minority game. In this paper, we investigate such a case that some traders in real financial markets could change their investment behaviours by assigning the evolutionary abilities to agents: if the winning rates of agents are smaller than a threshold, they will join the other group; and agents will repeat such an evolution at certain time intervals. Through the simulations, we obtain the following findings: (i) the volatilities of systems increase with the increase of the number of agents in Group 1 and the times of behavioural changes of all agents; (ii) the performances of agents in both groups and the stabilities of systems become better if all agents take more time to observe their new investment behaviours; (iii) there are two-phase zones of market and non-market and two-phase zones of evolution and non-evolution; (iv) parameter configurations located within the cross areas between the zones of markets and the zones of evolution are suited for simulating the financial markets.

National forest timber supply and stumpage markets in the western United States.

Treesearch

Darius M. Adams; Richard W. Haynes

1991-01-01

This paper presents an aggregate regional model of the National Forest timber supply process and the interaction of National Forest and non-National Forest supply in determining regional stumpage prices and harvest volumes. Model simulations track actual behavior in the Douglas-fir regional stumpage market with reasonable accuracy; projections for the next two decades...

Prediction Markets and Beliefs about Climate: Results from Agent-Based Simulations

NASA Astrophysics Data System (ADS)

Gilligan, J. M.; John, N. J.; van der Linden, M.

2015-12-01

Climate scientists have long been frustrated by persistent doubts a large portion of the public expresses toward the scientific consensus about anthropogenic global warming. The political and ideological polarization of this doubt led Vandenbergh, Raimi, and Gilligan [1] to propose that prediction markets for climate change might influence the opinions of those who mistrust the scientific community but do trust the power of markets.We have developed an agent-based simulation of a climate prediction market in which traders buy and sell future contracts that will pay off at some future year with a value that depends on the global average temperature at that time. The traders form a heterogeneous population with different ideological positions, different beliefs about anthropogenic global warming, and different degrees of risk aversion. We also vary characteristics of the market, including the topology of social networks among the traders, the number of traders, and the completeness of the market. Traders adjust their beliefs about climate according to the gains and losses they and other traders in their social network experience. This model predicts that if global temperature is predominantly driven by greenhouse gas concentrations, prediction markets will cause traders' beliefs to converge toward correctly accepting anthropogenic warming as real. This convergence is largely independent of the structure of the market and the characteristics of the population of traders. However, it may take considerable time for beliefs to converge. Conversely, if temperature does not depend on greenhouse gases, the model predicts that traders' beliefs will not converge. We will discuss the policy-relevance of these results and more generally, the use of agent-based market simulations for policy analysis regarding climate change, seasonal agricultural weather forecasts, and other applications.[1] MP Vandenbergh, KT Raimi, & JM Gilligan. UCLA Law Rev. 61, 1962 (2014).

Crop Monitoring as a Tool for Modelling the Genesis of Millet Prices in Senegal

NASA Astrophysics Data System (ADS)

Jacques, D.; Marinho, E.; Defourny, P.; Waldner, F.; d'Andrimont, R.

2015-12-01

Food security in Sahelian countries strongly relies on the ability of markets to transfer staplesfrom surplus to deficit areas. Market failures, leading to the inefficient geographical allocation of food,are expected to emerge from high transportation costs and information asymmetries that are commonin moderately developed countries. As a result, important price differentials are observed betweenproducing and consuming areas which damages both poor producers and food insecure consumers. Itis then vital for policy makers to understand how the prices of agricultural commodities are formed byaccounting for the existing market imperfections in addition to local demand and supply considerations. To address this issue, we have gathered an unique and diversified set of data for Senegal andintegrated it in a spatially explicit model that simulates the functioning of agricultural markets, that isfully consistent with the economic theory. Our departure point is a local demand and supply modelaround each market having its catchment areas determined by the road network. We estimate the localsupply of agricultural commodities from satellite imagery while the demand is assumed to be a functionof the population living in the area. From this point on, profitable transactions between areas with lowprices to areas with high prices are simulated for different levels of per kilometer transportation costand information flows (derived from call details records i.e. mobile phone data). The simulated prices are then comparedwith the actual millet prices. Despite the parsimony of the model that estimates only two parameters, i.e. the per kilometertransportation cost and the information asymmetry resulting from low levels of mobile phone activitybetween markets, it impressively explains more than 80% of the price differentials observed in the 40markets included in the analysis. In one hand these results can be used in the assessment of the socialwelfare impacts of the further development of both road and mobile phone networks in the country. Onthe other hand, the model could be further developed as a precious tool for the prediction of futurestaple prices in the country.

Marketing technology in macroeconomics.

PubMed

Tamegawa, Kenichi

2012-01-01

In this paper, we incorporate a marketing technology into a dynamic stochastic general equilibrium model by assuming a matching friction for consumption. An improvement in matching can be interpreted as an increase in matching technology, which we call marketing technology because of similar properties. Using a simulation analysis, we confirm that a positive matching technology shock can increase output and consumption.

Large Scale Simulation Platform for NODES Validation Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sotorrio, P.; Qin, Y.; Min, L.

2017-04-27

This report summarizes the Large Scale (LS) simulation platform created for the Eaton NODES project. The simulation environment consists of both wholesale market simulator and distribution simulator and includes the CAISO wholesale market model and a PG&E footprint of 25-75 feeders to validate the scalability under a scenario of 33% RPS in California with additional 17% of DERS coming from distribution and customers. The simulator can generate hourly unit commitment, 5-minute economic dispatch, and 4-second AGC regulation signals. The simulator is also capable of simulating greater than 10k individual controllable devices. Simulated DERs include water heaters, EVs, residential and lightmore » commercial HVAC/buildings, and residential-level battery storage. Feeder-level voltage regulators and capacitor banks are also simulated for feeder-level real and reactive power management and Vol/Var control.« less

Minority game and anomalies in financial markets

NASA Astrophysics Data System (ADS)

Liu, Xinghua; Liang, Xiaobei; Tang, Bingyong

2004-02-01

The minority game (MG), which is intrinsically associated with financial markets, is an agent-based model of a competing population with limited resources. We find that the fluctuation features of MG in crowded region are more similar to real market than that of in perfect cooperation region. So we propose and study a modified model based on the MG in which agents accumulate virtual points for their strategies from the last H steps instead of from the beginning of the game. The results of numerical simulations on our new model show that agents will be more intelligent, and the types of features of fluctuations are the same in real-world market. We also give a numerical explanation of the high adaptability of agents in new model.

An empirical and model study on automobile market in Taiwan

NASA Astrophysics Data System (ADS)

Tang, Ji-Ying; Qiu, Rong; Zhou, Yueping; He, Da-Ren

2006-03-01

We have done an empirical investigation on automobile market in Taiwan including the development of the possession rate of the companies in the market from 1979 to 2003, the development of the largest possession rate, and so on. A dynamic model for describing the competition between the companies is suggested based on the empirical study. In the model each company is given a long-term competition factor (such as technology, capital and scale) and a short-term competition factor (such as management, service and advertisement). Then the companies play games in order to obtain more possession rate in the market under certain rules. Numerical simulation based on the model display a competition developing process, which qualitatively and quantitatively agree with our empirical investigation results.

Simulating water markets with transaction costs

NASA Astrophysics Data System (ADS)

Erfani, Tohid; Binions, Olga; Harou, Julien J.

2014-06-01

This paper presents an optimization model to simulate short-term pair-wise spot-market trading of surface water abstraction licenses (water rights). The approach uses a node-arc multicommodity formulation that tracks individual supplier-receiver transactions in a water resource network. This enables accounting for transaction costs between individual buyer-seller pairs and abstractor-specific rules and behaviors using constraints. Trades are driven by economic demand curves that represent each abstractor's time-varying water demand. The purpose of the proposed model is to assess potential hydrologic and economic outcomes of water markets and aid policy makers in designing water market regulations. The model is applied to the Great Ouse River basin in Eastern England. The model assesses the potential weekly water trades and abstractions that could occur in a normal and a dry year. Four sectors (public water supply, energy, agriculture, and industrial) are included in the 94 active licensed water diversions. Each license's unique environmental restrictions are represented and weekly economic water demand curves are estimated. Rules encoded as constraints represent current water management realities and plausible stakeholder-informed water market behaviors. Results show buyers favor sellers who can supply large volumes to minimize transactions. The energy plant cooling and agricultural licenses, often restricted from obtaining water at times when it generates benefits, benefit most from trades. Assumptions and model limitations are discussed. This article was corrected on 13 JUN 2014. See the end of the full text for details.

How the ownership structures cause epidemics in financial markets: A network-based simulation model

NASA Astrophysics Data System (ADS)

Dastkhan, Hossein; Gharneh, Naser Shams

2018-02-01

Analysis of systemic risks and contagions is one of the main challenges of policy makers and researchers in the recent years. Network theory is introduced as a main approach in the modeling and simulation of financial and economic systems. In this paper, a simulation model is introduced based on the ownership network to analyze the contagion and systemic risk events. For this purpose, different network structures with different values for parameters are considered to investigate the stability of the financial system in the presence of different kinds of idiosyncratic and aggregate shocks. The considered network structures include Erdos-Renyi, core-periphery, segregated and power-law networks. Moreover, the results of the proposed model are also calculated for a real ownership network. The results show that the network structure has a significant effect on the probability and the extent of contagion in the financial systems. For each network structure, various values for the parameters results in remarkable differences in the systemic risk measures. The results of real case show that the proposed model is appropriate in the analysis of systemic risk and contagion in financial markets, identification of systemically important firms and estimation of market loss when the initial failures occur. This paper suggests a new direction in the modeling of contagion in the financial markets, in particular that the effects of new kinds of financial exposure are clarified. This paper's idea and analytical results may also be useful for the financial policy makers, portfolio managers and the firms to conduct their investment in the right direction.

A general equilibrium model of a production economy with asset markets

NASA Astrophysics Data System (ADS)

Raberto, Marco; Teglio, Andrea; Cincotti, Silvano

2006-10-01

In this paper, a general equilibrium model of a monetary production economy is presented. The model is characterized by three classes of agents: a representative firm, heterogeneous households, and the government. Two markets (i.e., a labour market and a goods market, are considered) and two assets are traded in exchange of money, namely, government bonds and equities. Households provide the labour force and decide on consumption and savings, whereas the firm provides consumption goods and demands labour. The government receives taxes from households and pays interests on debt. The Walrasian equilibrium is derived analytically. The dynamics through quantity constrained equilibria out from the Walrasian equilibrium is also studied by means of computer simulations.

Renewable generation technology choice and policies in a competitive electricity supply industry

NASA Astrophysics Data System (ADS)

Sarkar, Ashok

Renewable energy generation technologies have lower externality costs but higher private costs than fossil fuel-based generation. As a result, the choice of renewables in the future generation mix could be affected by the industry's future market-oriented structure because market objectives based on private value judgments may conflict with social policy objectives toward better environmental quality. This research assesses how renewable energy generation choices would be affected in a restructured electricity generation market. A multi-period linear programming-based model (Resource Planning Model) is used to characterize today's electricity supply market in the United States. The model simulates long-range (2000-2020) generation capacity planning and operation decisions under alternative market paradigms. Price-sensitive demand is used to simulate customer preferences in the market. Dynamically changing costs for renewables and a two-step load duration curve are used. A Reference Case represents the benchmark for a socially-optimal diffusion of renewables and a basis for comparing outcomes under alternative market structures. It internalizes externality costs associated with emissions of sulfur dioxide (SOsb2), nitrous oxides (NOsbx), and carbon dioxide (COsb2). A Competitive Case represents a market with many generation suppliers and decision-making based on private costs. Finally, a Market Power Case models the extreme case of market power: monopoly. The results suggest that the share of renewables would decrease (and emissions would increase) considerably in both the Competitive and the Market Power Cases with respect to the Reference Case. The reduction is greater in the Market Power Case due to pricing decisions under existing supply capability. The research evaluates the following environmental policy options that could overcome market failures in achieving an appropriate level of renewable generation: COsb2 emissions tax, SOsb2 emissions cap, renewable portfolio standards (RPS), and enhanced research and development (R&D). RPS would best ensure an appropriate share of renewables, whereas SOsb2 emissions caps would not support a shift to renewables in an era of inexpensive natural gas. The effectiveness of the policies are dependent on the market structure. If market power exists, the analyses indicate that generally higher levels of intervention would be necessary to achieve a shift to renewables.

Evaluation on Influence of Unstable Primary-Energy Price in a Deregulated Electric Power Market—Analysis based on a simulation model approach—

NASA Astrophysics Data System (ADS)

Maitani, Tatsuyuki; Tezuka, Tetsuo

The electric power market of Japan has been locally monopolized for a long time. But, like many countries, Japan is moving forward with the deregulation of its electric power industry so that any power generation company could sell electric power in the market. The power price, however, will fluctuate inevitably to balance the power supply and demand. A new appropriate market design is indispensable when introducing new market mechanisms in the electric power market to avoid undesirable results of the market. The first stage of deregulation will be the competition between an existing large-scaled power utility and a new power generation company. In this paper we have investigated the wholesale market with competition of these two power companies based on a simulation model approach. Under the competitive situation the effects of exogenous disturbance may bring serious results and we estimated the influence on the market when the price of fossil fuel rises. The conclusion of this study is that several types of Nash equilibriums have been found in the market: the larger the new power generation company becomes, the higher the electricity price under the Nash equilibriums rises. Because of the difference in their structure of generation capacity, the existing large-scaled power utility gets more profit while the new power generation company loses its profit when the price of fossil fuel rises.

Network evolution model for supply chain with manufactures as the core.

PubMed

Fang, Haiyang; Jiang, Dali; Yang, Tinghong; Fang, Ling; Yang, Jian; Li, Wu; Zhao, Jing

2018-01-01

Building evolution model of supply chain networks could be helpful to understand its development law. However, specific characteristics and attributes of real supply chains are often neglected in existing evolution models. This work proposes a new evolution model of supply chain with manufactures as the core, based on external market demand and internal competition-cooperation. The evolution model assumes the external market environment is relatively stable, considers several factors, including specific topology of supply chain, external market demand, ecological growth and flow conservation. The simulation results suggest that the networks evolved by our model have similar structures as real supply chains. Meanwhile, the influences of external market demand and internal competition-cooperation to network evolution are analyzed. Additionally, 38 benchmark data sets are applied to validate the rationality of our evolution model, in which, nine manufacturing supply chains match the features of the networks constructed by our model.

Network evolution model for supply chain with manufactures as the core

PubMed Central

Jiang, Dali; Fang, Ling; Yang, Jian; Li, Wu; Zhao, Jing

2018-01-01

Building evolution model of supply chain networks could be helpful to understand its development law. However, specific characteristics and attributes of real supply chains are often neglected in existing evolution models. This work proposes a new evolution model of supply chain with manufactures as the core, based on external market demand and internal competition-cooperation. The evolution model assumes the external market environment is relatively stable, considers several factors, including specific topology of supply chain, external market demand, ecological growth and flow conservation. The simulation results suggest that the networks evolved by our model have similar structures as real supply chains. Meanwhile, the influences of external market demand and internal competition-cooperation to network evolution are analyzed. Additionally, 38 benchmark data sets are applied to validate the rationality of our evolution model, in which, nine manufacturing supply chains match the features of the networks constructed by our model. PMID:29370201

Simulation of ridesourcing using agent-based demand and supply regional models : potential market demand for first-mile transit travel and reduction in vehicle miles traveled in the San Francisco Bay Area.

DOT National Transportation Integrated Search

2016-01-01

In this study, we use existing modeling tools and data from the San Francisco Bay Area : (California) to understand the potential market demand for a first mile transit access service : and possible reductions in vehicle miles traveled (VMT) (a...

Is there any connection between the network morphology and the fluctuations of the stock market index?

NASA Astrophysics Data System (ADS)

Stefan, F. M.; Atman, A. P. F.

2015-02-01

Models which consider behavioral aspects of the investors have attracted increasing interest in the Finance and Econophysics literature in the last years. Different behavioral profiles (imitation, anti-imitation, indifference) were proposed for the investors, which take their decision based on their trust network (neighborhood). Results from agent-based models have shown that most of the features observed in actual stock market indices can be replicated in simulations. Here, we present a deeper investigation of an agent based model considering different network morphologies (regular, random, small-world) for the investors' trust network, in an attempt to answer the question raised in the title. We study the model by considering four scenarios for the investors and different initial conditions to analyze their influence in the stock market fluctuations. We have characterized the stationary limit for each scenario tested, focusing on the changes introduced when complex networks were used, and calculated the Hurst exponent in some cases. Simulations showed interesting results suggesting that the fluctuations of the stock market index are strongly affected by the network morphology, a remarkable result which we believe was never reported or predicted before.

A study of a diffusive model of asset returns and an empirical analysis of financial markets

NASA Astrophysics Data System (ADS)

Alejandro Quinones, Angel Luis

A diffusive model for market dynamics is studied and the predictions of the model are compared to real financial markets. The model has a non-constant diffusion coefficient which depends both on the asset value and the time. A general solution for the distribution of returns is obtained and shown to match the results of computer simulations for two simple cases, piecewise linear and quadratic diffusion. The effects of discreteness in the market dynamics on the model are also studied. For the quadratic diffusion case, a type of phase transition leading to fat tails is observed as the discrete distribution approaches the continuum limit. It is also found that the model captures some of the empirical stylized facts observed in real markets, including fat-tails and scaling behavior in the distribution of returns. An analysis of empirical data for the EUR/USD currency exchange rate and the S&P 500 index is performed. Both markets show time scaling behavior consistent with a value of 1/2 for the Hurst exponent. Finally, the results show that the distribution of returns for the two markets is well fitted by the model, and the corresponding empirical diffusion coefficients are determined.

On the battleground of environmental and competition policy: The renewable electricity market

NASA Astrophysics Data System (ADS)

Meszaros, Matyas Tamas

Renewable energy sources have become increasingly important in the efforts to provide energy security and to fight global warming. In the last decade environmental policy has increased the support for renewable electricity. At the same time the electricity sector was often subject of antitrust investigation because of relevant market concentration, and market power. This dissertation looks at the renewable electricity market to analyze the effect of environmental policy on competition. The first chapter provides a short introduction into the regulatory schemes of electricity markets. The second chapter analyzes the demand side of the electricity market. The estimations show that there was no significant change in the income and price elasticity in the electricity consumption of the US households between 1993 an 2001, although there was several policy initiatives to increase energy efficiency and decrease consumption. The third chapter derives a theoretical model where the feed-in tariff and the tradable green certificate system can be analyzed under oligopolistic market structure. The results of the model suggest that the introduction of the environmentally friendly regulatory schemes can decrease the electricity prices compared to the case when there is no support for renewable energy. The other findings of this model is that the price of electricity rises when the requirement for renewable energy increases. In the fourth chapter a simulation model of the UK electricity market is used to test the effect of mergers and acquisitions under the environmental support scheme. The results emphasize the importance of the capacity limit, because it can constrain the strategic action of the electricity producers. The results of the simulation also suggest that the increasing concentration can increase the production and lower the price of electricity and renewable energy certificates in the British Renewable Obligation system.

A study of design approach of spreading schemes for viral marketing based on human dynamics

NASA Astrophysics Data System (ADS)

Yang, Jianmei; Zhuang, Dong; Xie, Weicong; Chen, Guangrong

2013-12-01

Before launching a real viral marketing campaign, it is needed to design a spreading scheme by simulations. Based on a categorization of spreading patterns in real world and models, we point out that the existing research (especially Yang et al. (2010) Ref. [16]) implicitly assume that if a user decides to post a received message (is activated), he/she will take the reposting action promptly (Prompt Action After Activation, or PAAA). After a careful analysis on a real dataset however, it is found that the observed time differences between action and activation exhibit a heavy-tailed distribution. A simulation model for heavy-tailed pattern is then proposed and performed. Similarities and differences of spreading processes between the heavy-tailed and PAAA patterns are analyzed. Consequently, a more practical design approach of spreading scheme for viral marketing on QQ platform is proposed. The design approach can be extended and applied to the contexts of non-heavy-tailed pattern, and viral marketing on other instant messaging platforms.

Using Intelligent System Approaches for Simulation of Electricity Markets

NASA Astrophysics Data System (ADS)

Hamagami, Tomoki

Significances and approaches of applying intelligent systems to artificial electricity market is discussed. In recent years, with the moving into restructuring of electric system in Japan, the deregulation for the electric market is progressing. The most major change of the market is a founding of JEPX (Japan Electric Power eXchange.) which is expected to help lower power bills through effective use of surplus electricity. The electricity market designates exchange of electric power between electric power suppliers (supplier agents) themselves. In the market, the goal of each supplier agents is to maximize its revenue for the entire trading period, and shows complex behavior, which can model by a multiagent platform. Using the multiagent simulations which have been studied as “artificial market" helps to predict the spot prices, to plan investments, and to discuss the rules of market. Moreover, intelligent system approaches provide for constructing more reasonable policies of each agents. This article, first, makes a brief summary of the electricity market in Japan and the studies of artificial markets. Then, a survey of tipical studies of artificial electricity market is listed. Through these topics, the future vision is presented for the studies.

Simulation of Teacher Demand, Demographics, and Mobility: A Preliminary Report.

ERIC Educational Resources Information Center

Baugh, William H.; Stone, Joe A.

A Markov chain is used to construct a simulation model of the educator labor market in Oregon. The variables crucial to this study, drawn from the University of Southern California faculty planning model, include factors such as appointment rate; age; probability of attaining promotion; retirement, resignation and mortality rates; length of…

GridLAB-D: An Agent-Based Simulation Framework for Smart Grids

DOE PAGES

Chassin, David P.; Fuller, Jason C.; Djilali, Ned

2014-01-01

Simulation of smart grid technologies requires a fundamentally new approach to integrated modeling of power systems, energy markets, building technologies, and the plethora of other resources and assets that are becoming part of modern electricity production, delivery, and consumption systems. As a result, the US Department of Energy’s Office of Electricity commissioned the development of a new type of power system simulation tool called GridLAB-D that uses an agent-based approach to simulating smart grids. This paper presents the numerical methods and approach to time-series simulation used by GridLAB-D and reviews applications in power system studies, market design, building control systemmore » design, and integration of wind power in a smart grid.« less

GridLAB-D: An Agent-Based Simulation Framework for Smart Grids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chassin, David P.; Fuller, Jason C.; Djilali, Ned

2014-06-23

Simulation of smart grid technologies requires a fundamentally new approach to integrated modeling of power systems, energy markets, building technologies, and the plethora of other resources and assets that are becoming part of modern electricity production, delivery, and consumption systems. As a result, the US Department of Energy’s Office of Electricity commissioned the development of a new type of power system simulation tool called GridLAB-D that uses an agent-based approach to simulating smart grids. This paper presents the numerical methods and approach to time-series simulation used by GridLAB-D and reviews applications in power system studies, market design, building control systemmore » design, and integration of wind power in a smart grid.« less

A queueing theory description of fat-tailed price returns in imperfect financial markets

NASA Astrophysics Data System (ADS)

Lamba, H.

2010-09-01

In a financial market, for agents with long investment horizons or at times of severe market stress, it is often changes in the asset price that act as the trigger for transactions or shifts in investment position. This suggests the use of price thresholds to simulate agent behavior over much longer timescales than are currently used in models of order-books. We show that many phenomena, routinely ignored in efficient market theory, can be systematically introduced into an otherwise efficient market, resulting in models that robustly replicate the most important stylized facts. We then demonstrate a close link between such threshold models and queueing theory, with large price changes corresponding to the busy periods of a single-server queue. The distribution of the busy periods is known to have excess kurtosis and non-exponential decay under various assumptions on the queue parameters. Such an approach may prove useful in the development of mathematical models for rapid deleveraging and panics in financial markets, and the stress-testing of financial institutions.

Buying on margin, selling short in an agent-based market model

NASA Astrophysics Data System (ADS)

Zhang, Ting; Li, Honggang

2013-09-01

Credit trading, or leverage trading, which includes buying on margin and selling short, plays an important role in financial markets, where agents tend to increase their leverages for increased profits. This paper presents an agent-based asset market model to study the effect of the permissive leverage level on traders’ wealth and overall market indicators. In this model, heterogeneous agents can assume fundamental value-converging expectations or trend-persistence expectations, and their effective demands of assets depend both on demand willingness and wealth constraints, where leverage can relieve the wealth constraints to some extent. The asset market price is determined by a market maker, who watches the market excess demand, and is influenced by noise factors. By simulations, we examine market results for different leverage ratios. At the individual level, we focus on how the leverage ratio influences agents’ wealth accumulation. At the market level, we focus on how the leverage ratio influences changes in the asset price, volatility, and trading volume. Qualitatively, our model provides some meaningful results supported by empirical facts. More importantly, we find a continuous phase transition as we increase the leverage threshold, which may provide a further prospective of credit trading.

An optimization model to agroindustrial sector in antioquia (Colombia, South America)

NASA Astrophysics Data System (ADS)

Fernandez, J.

2015-06-01

This paper develops a proposal of a general optimization model for the flower industry, which is defined by using discrete simulation and nonlinear optimization, whose mathematical models have been solved by using ProModel simulation tools and Gams optimization. It defines the operations that constitute the production and marketing of the sector, statistically validated data taken directly from each operation through field work, the discrete simulation model of the operations and the linear optimization model of the entire industry chain are raised. The model is solved with the tools described above and presents the results validated in a case study.

Simulation of demand management and grid balancing with electric vehicles

NASA Astrophysics Data System (ADS)

Druitt, James; Früh, Wolf-Gerrit

2012-10-01

This study investigates the potential role of electric vehicles in an electricity network with a high contribution from variable generation such as wind power. Electric vehicles are modelled to provide demand management through flexible charging requirements and energy balancing for the network. Balancing applications include both demand balancing and vehicle-to-grid discharging. This study is configured to represent the UK grid with balancing requirements derived from wind generation calculated from weather station wind speeds on the supply side and National Grid data from on the demand side. The simulation models 1000 individual vehicle entities to represent the behaviour of larger numbers of vehicles. A stochastic trip generation profile is used to generate realistic journey characteristics, whilst a market pricing model allows charging and balancing decisions to be based on realistic market price conditions. The simulation has been tested with wind generation capacities representing up to 30% of UK consumption. Results show significant improvements to load following conditions with the introduction of electric vehicles, suggesting that they could substantially facilitate the uptake of intermittent renewable generation. Electric vehicle owners would benefit from flexible charging and selling tariffs, with the majority of revenue derived from vehicle-to-grid participation in balancing markets.

Model of wealth and goods dynamics in a closed market

NASA Astrophysics Data System (ADS)

Ausloos, Marcel; Peķalski, Andrzej

2007-01-01

A simple computer simulation model of a closed market on a fixed network with free flow of goods and money is introduced. The model contains only two variables: the amount of goods and money beside the size of the system. An initially flat distribution of both variables is presupposed. We show that under completely random rules, i.e. through the choice of interacting agent pairs on the network and of the exchange rules that the market stabilizes in time and shows diversification of money and goods. We also indicate that the difference between poor and rich agents increases for small markets, as well as for systems in which money is steadily deduced from the market through taxation. It is also found that the price of goods decreases when taxes are introduced, likely due to the less availability of money.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoeschele, Marc; Weitzel, Elizabeth; Backman, Christine

This project completed a modeling evaluation of a hybrid gas water heater that combines a reduced capacity tankless unit with a downsized storage tank. This product would meet a significant market need by providing a higher efficiency gas water heater solution for retrofit applications while maintaining compatibility with the 1/2 inch gas lines and standard B vents found in most homes. The TRNSYS simulation tool was used to model a base case 0.60 EF atmospheric gas storage water, a 0.82 EF non-condensing gas tankless water heater, an existing (high capacity) hybrid unit on the market, and an alternative hybrid unitmore » with lower storage volume and reduced gas input requirements. Simulations were completed under a 'peak day' sizing scenario with 183 gpd hot water loads in a Minnesota winter climate case. Full-year simulations were then completed in three climates (ranging from Phoenix to Minneapolis) for three hot water load scenarios (36, 57, and 96 gpd). Model projections indicate that the alternative hybrid offers an average 4.5% efficiency improvement relative to the 0.60 EF gas storage unit across all scenarios modeled. The alternative hybrid water heater evaluated does show promise, but the current low cost of natural gas across much of the country and the relatively small incremental efficiency improvement poses challenges in initially building a market demand for the product.« less

Simulation Modeling of Software Development Processes

NASA Technical Reports Server (NTRS)

Calavaro, G. F.; Basili, V. R.; Iazeolla, G.

1996-01-01

A simulation modeling approach is proposed for the prediction of software process productivity indices, such as cost and time-to-market, and the sensitivity analysis of such indices to changes in the organization parameters and user requirements. The approach uses a timed Petri Net and Object Oriented top-down model specification. Results demonstrate the model representativeness, and its usefulness in verifying process conformance to expectations, and in performing continuous process improvement and optimization.

Researching a local heroin market as a complex adaptive system.

PubMed

Hoffer, Lee D; Bobashev, Georgiy; Morris, Robert J

2009-12-01

This project applies agent-based modeling (ABM) techniques to better understand the operation, organization, and structure of a local heroin market. The simulation detailed was developed using data from an 18-month ethnographic case study. The original research, collected in Denver, CO during the 1990s, represents the historic account of users and dealers who operated in the Larimer area heroin market. Working together, the authors studied the behaviors of customers, private dealers, street-sellers, brokers, and the police, reflecting the core elements pertaining to how the market operated. After evaluating the logical consistency between the data and agent behaviors, simulations scaled-up interactions to observe their aggregated outcomes. While the concept and findings from this study remain experimental, these methods represent a novel way in which to understand illicit drug markets and the dynamic adaptations and outcomes they generate. Extensions of this research perspective, as well as its strengths and limitations, are discussed.

Investor structure and the price-volume relationship in a continuous double auction market: An agent-based modeling perspective

NASA Astrophysics Data System (ADS)

Zhang, Wei; Bi, Zhengzheng; Shen, Dehua

2017-02-01

This paper investigates the impact of investor structure on the price-volume relationship by simulating a continuous double auction market. Connected with the underlying mechanisms of the price-volume relationship, i.e., the Mixture of Distribution Hypothesis (MDH) and the Sequential Information Arrival Hypothesis (SIAH), the simulation results show that: (1) there exists a strong lead-lag relationship between the return volatility and trading volume when the number of informed investors is close to the number of uninformed investors in the market; (2) as more and more informed investors entering the market, the lead-lag relationship becomes weaker and weaker, while the contemporaneous relationship between the return volatility and trading volume becomes more prominent; (3) when the informed investors are in absolute majority, the market can achieve the new equilibrium immediately. Therefore, we can conclude that the investor structure is a key factor in affecting the price-volume relationship.

Network marketing with bounded rationality and partial information

NASA Astrophysics Data System (ADS)

Kiet, Hoang Anh Tuan; Kim, Beom Jun

2008-08-01

Network marketing has been proposed and used as a way to spread the product information to consumers through social connections. We extend the previous game model of the network marketing on a small-world tree network and propose two games: In the first model with the bounded rationality, each consumer makes purchase decision stochastically, while in the second model, consumers get only partial information due to the finite length of social connections. Via extensive numerical simulations, we find that as the rationality is enhanced not only the consumer surplus but also the firm’s profit is increased. The implication of our results is also discussed.

A model of the impact of reimbursement schemes on health plan choice.

PubMed

Keeler, E B; Carter, G; Newhouse, J P

1998-06-01

Flat capitation (uniform prospective payments) makes enrolling healthy enrollees profitable to health plans. Plans with relatively generous benefits may attract the sick and fail through a premium spiral. We simulate a model of idealized managed competition to explore the effect on market performance of alternatives to flat capitation such as severity-adjusted capitation and reduced supply-side cost-sharing. In our model flat capitation causes severe market problems. Severity adjustment and to a lesser extent reduced supply-side cost-sharing improve market performance, but outcomes are efficient only in cases in which people bear the marginal costs of their choices.

Research on Mechanism and Model of Centralized Bidding for Pumped Storage Power in Shanghai

NASA Astrophysics Data System (ADS)

Hua, Zhong; Ying, Zhiwei; Lv, Zhengyu; Jianlin, Yang; Huang, Yupeng; Li, Dong

2017-05-01

China is now in the transition stage toward power market and in some specific area, market approach has already been adopted to improve the overall efficiency. In this paper, Bidding and trading modes of pumped storage energy in various regions of China are analysed. Based on the constraints of bidding price and electricity, as well as the system power flow, the trading model is established to collect the capacity cost of pumped storage energy in Shanghai. With the trading model proposed, that the generators who actively undertake the capacity cost of pumped storage energy and bid enough electricity with lower price can be rewarded, while those attempts to conspire and manipulate the market will be penalized. Finally, using seven generators in Shanghai as examples to simulate the market operation, the effectiveness of the proposed model is verified.

Consumer preferences for telemedicine devices and services in South Korea.

PubMed

Ahn, Joongha; Shin, Jungwoo; Lee, Jongsu; Shin, Kwangsoo; Park, Hayoung

2014-02-01

The scope of healthcare has been expanding from caring for sick people to keeping people from becoming sick, and telemedicine will play a significant role in this new healthcare paradigm. This study investigated consumer preferences and willingness to pay for attributes of telemedicine services in South Korea. A market simulation was conducted to examine the market shares of alternative services and their relationships to the perceived usefulness of service types and preferred device types. Using a conjoint survey, we collected data on consumer preferences for six telemedicine service attributes. Data analysis used the Bayesian mixed logit model. The market simulation estimated the probabilities of a specific service alternative being chosen using estimated model coefficients. Wearable devices were the most preferred, followed by smart-home and smartphone devices. Consumers perceived managing blood glucose to be the most useful telemedicine service, followed by monitoring oxygen saturation and blood pressure. The market simulation indicated that consumer preferences for device types were associated with the types of chronic diseases for which management through telemedicine services is perceived to be useful. As the focus of healthcare moves from treating patients to keeping individuals healthy, a key factor for the successful deployment of telemedicine services is understanding consumer perceptions and attitudes. The results of this study revealed the dynamics of consumer preferences with regard to service attributes.

Influence of the Investor's Behavior on the Complexity of the Stock Market

NASA Astrophysics Data System (ADS)

Atman, A. P. F.; Gonçalves, Bruna Amin

2012-04-01

One of the pillars of the finance theory is the efficient-market hypothesis, which is used to analyze the stock market. However, in recent years, this hypothesis has been questioned by a number of studies showing evidence of unusual behaviors in the returns of financial assets ("anomalies") caused by behavioral aspects of the economic agents. Therefore, it is time to initiate a debate about the efficient-market hypothesis and the "behavioral finances." We here introduce a cellular automaton model to study the stock market complexity, considering different behaviors of the economical agents. From the analysis of the stationary standard of investment observed in the simulations and the Hurst exponents obtained for the term series of stock index, we draw conclusions concerning the complexity of the model compared to real markets. We also investigate which conditions of the investors are able to influence the efficient market hypothesis statements.

Increasing market efficiency in the stock markets

NASA Astrophysics Data System (ADS)

Yang, Jae-Suk; Kwak, Wooseop; Kaizoji, Taisei; Kim, In-Mook

2008-01-01

We study the temporal evolutions of three stock markets; Standard and Poor's 500 index, Nikkei 225 Stock Average, and the Korea Composite Stock Price Index. We observe that the probability density function of the log-return has a fat tail but the tail index has been increasing continuously in recent years. We have also found that the variance of the autocorrelation function, the scaling exponent of the standard deviation, and the statistical complexity decrease, but that the entropy density increases as time goes over time. We introduce a modified microscopic spin model and simulate the model to confirm such increasing and decreasing tendencies in statistical quantities. These findings indicate that these three stock markets are becoming more efficient.

How effective is advertising in duopoly markets?

NASA Astrophysics Data System (ADS)

Sznajd-Weron, K.; Weron, R.

2003-06-01

A simple Ising spin model which can describe the mechanism of advertising in a duopoly market is proposed. In contrast to other agent-based models, the influence does not flow inward from the surrounding neighbors to the center site, but spreads outward from the center to the neighbors. The model thus describes the spread of opinions among customers. It is shown via standard Monte Carlo simulations that very simple rules and inclusion of an external field-an advertising campaign-lead to phase transitions.

A marketing approach to carpool demand analysis. Technical memorandum III. Tradeoff model and policy simulation. Conservation paper. [Commuter survey in 3 major urban areas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1976-07-01

The memorandum discusses the theoretical basis of the trade-off model and its adaptation particularly in the simulation procedures used in evaluating specific policies. Two published articles dealing with the development and application of the trade-off model for market research are included as appendices to this memorandum. This model was the primary instrument used in connection with a research effort examining the role of individuals attitudes and perceptions in deciding whether or not to carpool. The research was based upon a survey of commuters in 3 major urban areas and has resulted in a sizeable new data base on respondents' socio-economicmore » and worktrip characteristics, travel perceptions, and travel preferences. Research is contained in the Summary Report, also available through NTIS.« less

Morphological similarities between DBM and a microeconomic model of sprawl

NASA Astrophysics Data System (ADS)

Caruso, Geoffrey; Vuidel, Gilles; Cavailhès, Jean; Frankhauser, Pierre; Peeters, Dominique; Thomas, Isabelle

2011-03-01

We present a model that simulates the growth of a metropolitan area on a 2D lattice. The model is dynamic and based on microeconomics. Households show preferences for nearby open spaces and neighbourhood density. They compete on the land market. They travel along a road network to access the CBD. A planner ensures the connectedness and maintenance of the road network. The spatial pattern of houses, green spaces and road network self-organises, emerging from agents individualistic decisions. We perform several simulations and vary residential preferences. Our results show morphologies and transition phases that are similar to Dieletric Breakdown Models (DBM). Such similarities were observed earlier by other authors, but we show here that it can be deducted from the functioning of the land market and thus explicitly connected to urban economic theory.

Benefits of full scope simulators during solar thermal power plants design and construction

NASA Astrophysics Data System (ADS)

Gallego, José F.; Gil, Elena; Rey, Pablo

2017-06-01

In order to efficiently develop high-precision dynamic simulators for solar thermal power plants, Tecnatom adapted its simulation technology to consider solar thermal models. This effort and the excellent response of the simulation market have allowed Tecnatom to develop simulators with both parabolic trough and solar power tower technologies, including molten salt energy storage. These simulators may pursue different objectives, giving rise to training or engineering simulators. Solar thermal power market combines the need for the training of the operators with the potential benefits associated to the improvement of the design of the plants. This fact along with the simulation capabilities enabled by the current technology and the broad experience of Tecnatom present the development of an engineering+training simulator as a very advantageous option. This paper describes the challenge of the development and integration of a full scope simulator during the design and construction stages of a solar thermal power plant, showing the added value to the different engineering areas.

Mars Colony in situ resource utilization: An integrated architecture and economics model

NASA Astrophysics Data System (ADS)

Shishko, Robert; Fradet, René; Do, Sydney; Saydam, Serkan; Tapia-Cortez, Carlos; Dempster, Andrew G.; Coulton, Jeff

2017-09-01

This paper reports on our effort to develop an ensemble of specialized models to explore the commercial potential of mining water/ice on Mars in support of a Mars Colony. This ensemble starts with a formal systems architecting framework to describe a Mars Colony and capture its artifacts' parameters and technical attributes. The resulting database is then linked to a variety of ;downstream; analytic models. In particular, we integrated an extraction process (i.e., ;mining;) model, a simulation of the colony's environmental control and life support infrastructure known as HabNet, and a risk-based economics model. The mining model focuses on the technologies associated with in situ resource extraction, processing, storage and handling, and delivery. This model computes the production rate as a function of the systems' technical parameters and the local Mars environment. HabNet simulates the fundamental sustainability relationships associated with establishing and maintaining the colony's population. The economics model brings together market information, investment and operating costs, along with measures of market uncertainty and Monte Carlo techniques, with the objective of determining the profitability of commercial water/ice in situ mining operations. All told, over 50 market and technical parameters can be varied in order to address ;what-if; questions, including colony location.

Using Simulations in the Marketing Classroom

ERIC Educational Resources Information Center

Kietzmann, Jan; Pitt, Leyland

2016-01-01

This special issue of "Journal of Marketing Education" was intended to engage as broad a perspective on simulations in the marketing classroom as possible. While some of the articles deal with the use of computerized marketing simulations, there are also articles that view simulations as imitating and pretending. The evidence from the…

Building America Case Study: Assessment of a Hybrid Retrofit Gas Water Heater

DOE Office of Scientific and Technical Information (OSTI.GOV)

This project completed a modeling evaluation of a hybrid gas water heater that combines a reduced capacity tankless unit with a downsized storage tank. This product would meet a significant market need by providing a higher efficiency gas water heater solution for retrofit applications while maintaining compatibility with the half-inch gas lines and standard B vents found in most homes. The TRNSYS simulation tool was used to model a base case 0.60 EF atmospheric gas storage water, a 0.82 EF non-condensing gas tankless water heater, an existing (high capacity) hybrid unit on the market, and an alternative hybrid unit withmore » lower storage volume and reduced gas input requirements. Simulations were completed under a 'peak day' sizing scenario with 183 gpd hot water loads in a Minnesota winter climate case. Full-year simulations were then completed in three climates (ranging from Phoenix to Minneapolis) for three hot water load scenarios (36, 57, and 96 gpd). Model projections indicate that the alternative hybrid offers an average 4.5% efficiency improvement relative to the 0.60 EF gas storage unit across all scenarios modeled. The alternative hybrid water heater evaluated does show promise, but the current low cost of natural gas across much of the country and the relatively small incremental efficiency improvement poses challenges in initially building a market demand for the product.« less

Assessment of a Hybrid Retrofit Gas Water Heater

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoeschele, Marc; Weitzel, Elizabeth; Backman, Christine

2017-02-28

This project completed a modeling evaluation of a hybrid gas water heater that combines a reduced capacity tankless unit with a downsized storage tank. This product would meet a significant market need by providing a higher efficiency gas water heater solution for retrofit applications while maintaining compatibility with the 1/2 inch gas lines and standard B vents found in most homes. The TRNSYS simulation tool was used to model a base case 0.60 EF atmospheric gas storage water, a 0.82 EF non-condensing gas tankless water heater, an existing (high capacity) hybrid unit on the market, and an alternative hybrid unitmore » with lower storage volume and reduced gas input requirements. Simulations were completed under a 'peak day' sizing scenario with 183 gpd hot water loads in a Minnesota winter climate case. Full-year simulations were then completed in three climates (ranging from Phoenix to Minneapolis) for three hot water load scenarios (36, 57, and 96 gpd). Model projections indicate that the alternative hybrid offers an average 4.5% efficiency improvement relative to the 0.60 EF gas storage unit across all scenarios modeled. The alternative hybrid water heater evaluated does show promise, but the current low cost of natural gas across much of the country and the relatively small incremental efficiency improvement poses challenges in initially building a market demand for the product.« less

A Dynamic Competition Simulation for Worldwide Big-size TV Market Using Lotka-Volterra Model

NASA Astrophysics Data System (ADS)

Chen, Wu-Tung Terry; Li, Yiming; Hung, Chih-Young

2009-08-01

Technological innovation is characterized by the substitution of new technologies for full-fledged ones in the development of new products, processes and techniques. Global TV market is seeing a price down-spiral for FPD(Flat Panel Display)-TVs, replacement of CRT by LCD, and consumer's defection to larger screen. The LCD-TV market started in Japan from 2003 and took off globally from 2005. LCD panel production is moving toward larger sizes. In the 35″-39″ size market, the price/performance ratio of LCD-TV is better than that of PDP. The purpose of this paper is to estimate the demand function of worldwide big-size (35″-39″) TVs including LCD and PDP with an explicit consideration of market competition. The demand function was estimated using Lotka-Volterra model, a famous competitive diffusion model. The results exhibit a kind of predator-prey relationship, in which the PDP market was hunted by LCD product. In addition, the coefficients of difference equations of Lotka-Volterra model in this analysis are also used to forecast the future market of the big-size LCD and PDP.

Quantitative model of price diffusion and market friction based on trading as a mechanistic random process.

PubMed

Daniels, Marcus G; Farmer, J Doyne; Gillemot, László; Iori, Giulia; Smith, Eric

2003-03-14

We model trading and price formation in a market under the assumption that order arrival and cancellations are Poisson random processes. This model makes testable predictions for the most basic properties of markets, such as the diffusion rate of prices (which is the standard measure of financial risk) and the spread and price impact functions (which are the main determinants of transaction cost). Guided by dimensional analysis, simulation, and mean-field theory, we find scaling relations in terms of order flow rates. We show that even under completely random order flow the need to store supply and demand to facilitate trading induces anomalous diffusion and temporal structure in prices.

Quantitative Model of Price Diffusion and Market Friction Based on Trading as a Mechanistic Random Process

NASA Astrophysics Data System (ADS)

Daniels, Marcus G.; Farmer, J. Doyne; Gillemot, László; Iori, Giulia; Smith, Eric

2003-03-01

We model trading and price formation in a market under the assumption that order arrival and cancellations are Poisson random processes. This model makes testable predictions for the most basic properties of markets, such as the diffusion rate of prices (which is the standard measure of financial risk) and the spread and price impact functions (which are the main determinants of transaction cost). Guided by dimensional analysis, simulation, and mean-field theory, we find scaling relations in terms of order flow rates. We show that even under completely random order flow the need to store supply and demand to facilitate trading induces anomalous diffusion and temporal structure in prices.

Designing an International Joint Venture Negotiation Game.

ERIC Educational Resources Information Center

Kenkel, Phil; And Others

1996-01-01

Evaluates a simulation game that models management problems encountered in negotiating and managing international joint ventures. Designed to instruct executives of state-owned agribusinesses in Indonesia in abstract concepts such as partner rapport, transfer price conflicts, and marketing disagreements, its success suggests that simulation games…

DOE Office of Scientific and Technical Information (OSTI.GOV)

TESP combines existing domain simulators in the electric power grid, with new transactive agents, growth models and evaluation scripts. The existing domain simulators include GridLAB-D for the distribution grid and single-family residential buildings, MATPOWER for transmission and bulk generation, and EnergyPlus for large buildings. More are planned for subsequent versions of TESP. The new elements are: TEAgents - simulate market participants and transactive systems for market clearing. Some of this functionality was extracted from GridLAB-D and implemented in Python for customization by PNNL and others; Growth Model - a means for simulating system changes over a multiyear period, including bothmore » normal load growth and specific investment decisions. Customizable in Python code; and Evaluation Script - a means of evaluating different transactive systems through customizable post-processing in Python code. TESP provides a method for other researchers and vendors to design transactive systems, and test them in a virtual environment. It allows customization of the key components by modifying Python code.« less

Modeling Market Shares of Competing (e)Care Providers

NASA Astrophysics Data System (ADS)

van Ooteghem, Jan; Tesch, Tom; Verbrugge, Sofie; Ackaert, Ann; Colle, Didier; Pickavet, Mario; Demeester, Piet

In order to address the increasing costs of providing care to the growing group of elderly, efficiency gains through eCare solutions seem an obvious solution. Unfortunately not many techno-economic business models to evaluate the return of these investments are available. The construction of a business case for care for the elderly as they move through different levels of dependency and the effect of introducing an eCare service, is the intended application of the model. The simulation model presented in this paper allows for modeling evolution of market shares of competing care providers. Four tiers are defined, based on the dependency level of the elderly, for which the market shares are determined. The model takes into account available capacity of the different care providers, in- and outflow distribution between tiers and churn between providers within tiers.

Evolutionary Development of the Simulation by Logical Modeling System (SIBYL)

NASA Technical Reports Server (NTRS)

Wu, Helen

1995-01-01

Through the evolutionary development of the Simulation by Logical Modeling System (SIBYL) we have re-engineered the expensive and complex IBM mainframe based Long-term Hardware Projection Model (LHPM) to a robust cost-effective computer based mode that is easy to use. We achieved significant cost reductions and improved productivity in preparing long-term forecasts of Space Shuttle Main Engine (SSME) hardware. The LHPM for the SSME is a stochastic simulation model that projects the hardware requirements over 10 years. SIBYL is now the primary modeling tool for developing SSME logistics proposals and Program Operating Plan (POP) for NASA and divisional marketing studies.

Bose-Einstein distribution of money in a free-market economy. II

NASA Astrophysics Data System (ADS)

Kürten, K. E.; Kusmartsev, F. V.

2011-01-01

We argue about the application of methods of statistical mechanics to free economy (Kusmartsev F. V., Phys. Lett. A, 375 (2011) 966) and find that the most general distribution of money or income in a free-market economy has a general Bose-Einstein distribution form. Therewith the market is described by three parameters: temperature, chemical potential and the space dimensionality. Numerical simulations and a detailed analysis of a generic model confirm this finding.

Helicopter training simulators: Key market factors

NASA Technical Reports Server (NTRS)

Mcintosh, John

1992-01-01

Simulators will gain an increasingly important role in training helicopter pilots only if the simulators are of sufficient fidelity to provide positive transfer of skills to the aircraft. This must be done within an economic model of return on investment. Although rotor pilot demand is still only a small percentage of overall pilot requirements, it will grow in significance. This presentation described the salient factors influencing the use of helicopter training simulators.

Financial instability from local market measures

NASA Astrophysics Data System (ADS)

Bardoscia, Marco; Livan, Giacomo; Marsili, Matteo

2012-08-01

We study the emergence of instabilities in a stylized model of a financial market, when different market actors calculate prices according to different (local) market measures. We derive typical properties for ensembles of large random markets using techniques borrowed from statistical mechanics of disordered systems. We show that, depending on the number of financial instruments available and on the heterogeneity of local measures, the market moves from an arbitrage-free phase to an unstable one, where the complexity of the market—as measured by the diversity of financial instruments—increases, and arbitrage opportunities arise. A sharp transition separates the two phases. Focusing on two different classes of local measures inspired by real market strategies, we are able to analytically compute the critical lines, corroborating our findings with numerical simulations.

Scaling and efficiency determine the irreversible evolution of a market

PubMed Central

Baldovin, F.; Stella, A. L.

2007-01-01

In setting up a stochastic description of the time evolution of a financial index, the challenge consists in devising a model compatible with all stylized facts emerging from the analysis of financial time series and providing a reliable basis for simulating such series. Based on constraints imposed by market efficiency and on an inhomogeneous-time generalization of standard simple scaling, we propose an analytical model which accounts simultaneously for empirical results like the linear decorrelation of successive returns, the power law dependence on time of the volatility autocorrelation function, and the multiscaling associated to this dependence. In addition, our approach gives a justification and a quantitative assessment of the irreversible character of the index dynamics. This irreversibility enters as a key ingredient in a novel simulation strategy of index evolution which demonstrates the predictive potential of the model.

With string model to time series forecasting

NASA Astrophysics Data System (ADS)

Pinčák, Richard; Bartoš, Erik

2015-10-01

Overwhelming majority of econometric models applied on a long term basis in the financial forex market do not work sufficiently well. The reason is that transaction costs and arbitrage opportunity are not included, as this does not simulate the real financial markets. Analyses are not conducted on the non equidistant date but rather on the aggregate date, which is also not a real financial case. In this paper, we would like to show a new way how to analyze and, moreover, forecast financial market. We utilize the projections of the real exchange rate dynamics onto the string-like topology in the OANDA market. The latter approach allows us to build the stable prediction models in trading in the financial forex market. The real application of the multi-string structures is provided to demonstrate our ideas for the solution of the problem of the robust portfolio selection. The comparison with the trend following strategies was performed, the stability of the algorithm on the transaction costs for long trade periods was confirmed.

Real and financial market interactions in a multiplier-accelerator model: Nonlinear dynamics, multistability and stylized facts

NASA Astrophysics Data System (ADS)

Cavalli, F.; Naimzada, A.; Pecora, N.

2017-10-01

In the present paper, we investigate the dynamics of a model in which the real part of the economy, described within a multiplier-accelerator framework, interacts with a financial market with heterogeneous speculators, in order to study the channels through which the two sectors influence each other. Employing analytical and numerical tools, we investigate stability conditions as well as bifurcations and possible periodic, quasi-periodic, and chaotic dynamics, enlightening how the degree of market interaction, together with the accelerator parameter and the intervention of the fiscal authority, may affect the business cycle and the course of the financial market. In particular, we show that even if the steady state is locally stable, multistability phenomena can occur, with several and complex dynamic structures coexisting with the steady state. Finally, simulations reveal that the proposed model is able to explain several statistical properties and stylized facts observed in real financial markets, including persistent high volatility, fat-tailed return distributions, volatility clustering, and positive autocorrelation of absolute returns.

Real and financial market interactions in a multiplier-accelerator model: Nonlinear dynamics, multistability and stylized facts.

PubMed

Cavalli, F; Naimzada, A; Pecora, N

2017-10-01

In the present paper, we investigate the dynamics of a model in which the real part of the economy, described within a multiplier-accelerator framework, interacts with a financial market with heterogeneous speculators, in order to study the channels through which the two sectors influence each other. Employing analytical and numerical tools, we investigate stability conditions as well as bifurcations and possible periodic, quasi-periodic, and chaotic dynamics, enlightening how the degree of market interaction, together with the accelerator parameter and the intervention of the fiscal authority, may affect the business cycle and the course of the financial market. In particular, we show that even if the steady state is locally stable, multistability phenomena can occur, with several and complex dynamic structures coexisting with the steady state. Finally, simulations reveal that the proposed model is able to explain several statistical properties and stylized facts observed in real financial markets, including persistent high volatility, fat-tailed return distributions, volatility clustering, and positive autocorrelation of absolute returns.

A multi agent model for the limit order book dynamics

NASA Astrophysics Data System (ADS)

Bartolozzi, M.

2010-11-01

In the present work we introduce a novel multi-agent model with the aim to reproduce the dynamics of a double auction market at microscopic time scale through a faithful simulation of the matching mechanics in the limit order book. The agents follow a noise decision making process where their actions are related to a stochastic variable, the market sentiment, which we define as a mixture of public and private information. The model, despite making just few basic assumptions over the trading strategies of the agents, is able to reproduce several empirical features of the high-frequency dynamics of the market microstructure not only related to the price movements but also to the deposition of the orders in the book.

Equilibrium pricing in electricity markets with wind power

NASA Astrophysics Data System (ADS)

Rubin, Ofir David

Estimates from the World Wind Energy Association assert that world total wind power installed capacity climbed from 18 Gigawatt (GW) to 152 GW from 2000 to 2009. Moreover, according to their predictions, by the end of 2010 global wind power capacity will reach 190 GW. Since electricity is a unique commodity, this remarkable expansion brings forward several key economic questions regarding the integration of significant amount of wind power capacity into deregulated electricity markets. The overall dissertation objective is to develop a comprehensive theoretical framework that enables the modeling of the performance and outcome of wind-integrated electricity markets. This is relevant because the state of knowledge of modeling electricity markets is insufficient for the purpose of wind power considerations. First, there is a need to decide about a consistent representation of deregulated electricity markets. Surprisingly, the related body of literature does not agree on the very economic basics of modeling electricity markets. That is important since we need to capture the fundamentals of electricity markets before we introduce wind power to our study. For example, the structure of the electric industry is a key. If market power is present, the integration of wind power has large consequences on welfare distribution. Since wind power uncertainty changes the dynamics of information it also impacts the ability to manipulate market prices. This is because the quantity supplied by wind energy is not a decision variable. Second, the intermittent spatial nature of wind over a geographical region is important because the market value of wind power capacity is derived from its statistical properties. Once integrated into the market, the distribution of wind will impact the price of electricity produced from conventional sources of energy. Third, although wind power forecasting has improved in recent years, at the time of trading short-term electricity forwards, forecasting precision is still low. Therefore, it is crucial that the uncertainty in forecasting wind power is considered when modeling trading behavior. Our theoretical framework is based on finding a symmetric Cournot-Nash equilibrium in double-sided auctions in both forwards and spot electricity markets. The theoretical framework allows for the first time, to the best of our knowledge, a model of electricity markets that explain two main empirical findings; the existence of forwards premium and spot market mark-ups. That is a significant contribution since so far forward premiums have been explained exclusively by the assumption of risk-averse behavior while spot mark-ups are the outcome of the body of literature assuming oligopolistic competition. In the next step, we extend the theoretical framework to account for deregulated electricity markets with wind power. Modeling a wind-integrated electricity market allows us to analyze market outcomes with respect to three main factors; the introduction of uncertainty from the supply side, ownership of wind power capacity and the geographical diversification of wind power capacity. For the purpose of modeling trade in electricity forwards one should simulate the information agents have regarding future availability of aggregate wind power. This is particularly important for modeling accurately traders' ability to predict the spot price distribution. We develop a novel numerical methodology for the simulation of the conditional distribution of regional wind power at the time of trading short-term electricity forwards. Finally, we put the theoretical framework and the numerical methodology developed in this study to work by providing a detailed computational experiment examining electricity market outcomes for a particular expansion path of wind power capacity.

Simulation of financial market via nonlinear Ising model

NASA Astrophysics Data System (ADS)

Ko, Bonggyun; Song, Jae Wook; Chang, Woojin

2016-09-01

In this research, we propose a practical method for simulating the financial return series whose distribution has a specific heaviness. We employ the Ising model for generating financial return series to be analogous to those of the real series. The similarity between real financial return series and simulated one is statistically verified based on their stylized facts including the power law behavior of tail distribution. We also suggest the scheme for setting the parameters in order to simulate the financial return series with specific tail behavior. The simulation method introduced in this paper is expected to be applied to the other financial products whose price return distribution is fat-tailed.

Foreign exchange market data analysis reveals statistical features that predict price movement acceleration.

PubMed

Nacher, Jose C; Ochiai, Tomoshiro

2012-05-01

Increasingly accessible financial data allow researchers to infer market-dynamics-based laws and to propose models that are able to reproduce them. In recent years, several stylized facts have been uncovered. Here we perform an extensive analysis of foreign exchange data that leads to the unveiling of a statistical financial law. First, our findings show that, on average, volatility increases more when the price exceeds the highest (or lowest) value, i.e., breaks the resistance line. We call this the breaking-acceleration effect. Second, our results show that the probability P(T) to break the resistance line in the past time T follows power law in both real data and theoretically simulated data. However, the probability calculated using real data is rather lower than the one obtained using a traditional Black-Scholes (BS) model. Taken together, the present analysis characterizes a different stylized fact of financial markets and shows that the market exceeds a past (historical) extreme price fewer times than expected by the BS model (the resistance effect). However, when the market does, we predict that the average volatility at that time point will be much higher. These findings indicate that any Markovian model does not faithfully capture the market dynamics.

Foreign exchange market data analysis reveals statistical features that predict price movement acceleration

NASA Astrophysics Data System (ADS)

Nacher, Jose C.; Ochiai, Tomoshiro

2012-05-01

Increasingly accessible financial data allow researchers to infer market-dynamics-based laws and to propose models that are able to reproduce them. In recent years, several stylized facts have been uncovered. Here we perform an extensive analysis of foreign exchange data that leads to the unveiling of a statistical financial law. First, our findings show that, on average, volatility increases more when the price exceeds the highest (or lowest) value, i.e., breaks the resistance line. We call this the breaking-acceleration effect. Second, our results show that the probability P(T) to break the resistance line in the past time T follows power law in both real data and theoretically simulated data. However, the probability calculated using real data is rather lower than the one obtained using a traditional Black-Scholes (BS) model. Taken together, the present analysis characterizes a different stylized fact of financial markets and shows that the market exceeds a past (historical) extreme price fewer times than expected by the BS model (the resistance effect). However, when the market does, we predict that the average volatility at that time point will be much higher. These findings indicate that any Markovian model does not faithfully capture the market dynamics.

Growing a market economy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Basu, N.; Pryor, R.J.

1997-09-01

This report presents a microsimulation model of a transition economy. Transition is defined as the process of moving from a state-enterprise economy to a market economy. The emphasis is on growing a market economy starting from basic microprinciples. The model described in this report extends and modifies the capabilities of Aspen, a new agent-based model that is being developed at Sandia National Laboratories on a massively parallel Paragon computer. Aspen is significantly different from traditional models of the economy. Aspen`s emphasis on disequilibrium growth paths, its analysis based on evolution and emergent behavior rather than on a mechanistic view ofmore » society, and its use of learning algorithms to simulate the behavior of some agents rather than an assumption of perfect rationality make this model well-suited for analyzing economic variables of interest from transition economies. Preliminary results from several runs of the model are included.« less

Building-to-Grid Integration through Commercial Building Portfolios Participating in Energy and Frequency Regulation Markets

NASA Astrophysics Data System (ADS)

Pavlak, Gregory S.

Building energy use is a significant contributing factor to growing worldwide energy demands. In pursuit of a sustainable energy future, commercial building operations must be intelligently integrated with the electric system to increase efficiency and enable renewable generation. Toward this end, a model-based methodology was developed to estimate the capability of commercial buildings to participate in frequency regulation ancillary service markets. This methodology was integrated into a supervisory model predictive controller to optimize building operation in consideration of energy prices, demand charges, and ancillary service revenue. The supervisory control problem was extended to building portfolios to evaluate opportunities for synergistic effect among multiple, centrally-optimized buildings. Simulation studies performed showed that the multi-market optimization was able to determine appropriate opportunities for buildings to provide frequency regulation. Total savings were increased by up to thirteen percentage points, depending on the simulation case. Furthermore, optimizing buildings as a portfolio achieved up to seven additional percentage points of savings, depending on the case. Enhanced energy and cost savings opportunities were observed by taking the novel perspective of optimizing building portfolios in multiple grid markets, motivating future pursuits of advanced control paradigms that enable a more intelligent electric grid.

Using and comparing metaheuristic algorithms for optimizing bidding strategy viewpoint of profit maximization of generators

NASA Astrophysics Data System (ADS)

Mousavi, Seyed Hosein; Nazemi, Ali; Hafezalkotob, Ashkan

2015-03-01

With the formation of the competitive electricity markets in the world, optimization of bidding strategies has become one of the main discussions in studies related to market designing. Market design is challenged by multiple objectives that need to be satisfied. The solution of those multi-objective problems is searched often over the combined strategy space, and thus requires the simultaneous optimization of multiple parameters. The problem is formulated analytically using the Nash equilibrium concept for games composed of large numbers of players having discrete and large strategy spaces. The solution methodology is based on a characterization of Nash equilibrium in terms of minima of a function and relies on a metaheuristic optimization approach to find these minima. This paper presents some metaheuristic algorithms to simulate how generators bid in the spot electricity market viewpoint of their profit maximization according to the other generators' strategies, such as genetic algorithm (GA), simulated annealing (SA) and hybrid simulated annealing genetic algorithm (HSAGA) and compares their results. As both GA and SA are generic search methods, HSAGA is also a generic search method. The model based on the actual data is implemented in a peak hour of Tehran's wholesale spot market in 2012. The results of the simulations show that GA outperforms SA and HSAGA on computing time, number of function evaluation and computing stability, as well as the results of calculated Nash equilibriums by GA are less various and different from each other than the other algorithms.

Structural Evolutions of STOCK Markets Controlled by Generalized Entropy Principles of Complex Systems

NASA Astrophysics Data System (ADS)

Wang, Yi Jiao; Feng, Qing Yi; Chai, Li He

As one of the most important financial markets and one of the main parts of economic system, the stock market has become the research focus in economics. The stock market is a typical complex open system far from equilibrium. Many available models that make huge contribution to researches on market are strong in describing the market however, ignoring strong nonlinear interactions among active agents and weak in reveal underlying dynamic mechanisms of structural evolutions of market. From econophysical perspectives, this paper analyzes the complex interactions among agents and defines the generalized entropy in stock markets. Nonlinear evolutionary dynamic equation for the stock markets is then derived from Maximum Generalized Entropy Principle. Simulations are accordingly conducted for a typical case with the given data, by which the structural evolution of the stock market system is demonstrated. Some discussions and implications are finally provided.

Scientific analysis is essential to assess biofuel policy effects: in response to the paper by Kim and Dale on "Indirect land use change for biofuels: Testing predictions and improving analytical methodologies"

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kline, Keith L; Oladosu, Gbadebo A; Dale, Virginia H

2011-01-01

Vigorous debate on the effects of biofuels derives largely from the changes in land use estimated using economic models designed mainly for the analysis of agricultural trade and markets. The models referenced for land-use change (LUC) analysis in the U.S. Environmental Protection Agency Final Rule on the Renewable Fuel Standard include GTAP, FAPRI-CARD, and FASOM. To address bioenergy impacts, these models were expanded and modified to facilitate simulations of hypothesized LUC. However, even when models use similar basic assumptions and data, the range of LUC results can vary by ten-fold or more. While the market dynamics simulated in these modelsmore » include processes that are important in estimating effects of biofuel policies, the models have not been validated for estimating land-use changes and employ crucial assumptions and simplifications that contradict empirical evidence.« less

A stochastic hybrid model for pricing forward-start variance swaps

NASA Astrophysics Data System (ADS)

Roslan, Teh Raihana Nazirah

2017-11-01

Recently, market players have been exposed to the astounding increase in the trading volume of variance swaps. In this paper, the forward-start nature of a variance swap is being inspected, where hybridizations of equity and interest rate models are used to evaluate the price of discretely-sampled forward-start variance swaps. The Heston stochastic volatility model is being extended to incorporate the dynamics of the Cox-Ingersoll-Ross (CIR) stochastic interest rate model. This is essential since previous studies on variance swaps were mainly focusing on instantaneous-start variance swaps without considering the interest rate effects. This hybrid model produces an efficient semi-closed form pricing formula through the development of forward characteristic functions. The performance of this formula is investigated via simulations to demonstrate how the formula performs for different sampling times and against the real market scenario. Comparison done with the Monte Carlo simulation which was set as our main reference point reveals that our pricing formula gains almost the same precision in a shorter execution time.

Integration of Artificial Market Simulation and Text Mining for Market Analysis

NASA Astrophysics Data System (ADS)

Izumi, Kiyoshi; Matsui, Hiroki; Matsuo, Yutaka

We constructed an evaluation system of the self-impact in a financial market using an artificial market and text-mining technology. Economic trends were first extracted from text data circulating in the real world. Then, the trends were inputted into the market simulation. Our simulation revealed that an operation by intervention could reduce over 70% of rate fluctuation in 1995. By the simulation results, the system was able to help for its user to find the exchange policy which can stabilize the yen-dollar rate.

Microscopic Spin Model for the STOCK Market with Attractor Bubbling on Regular and Small-World Lattices

NASA Astrophysics Data System (ADS)

Krawiecki, A.

A multi-agent spin model for changes of prices in the stock market based on the Ising-like cellular automaton with interactions between traders randomly varying in time is investigated by means of Monte Carlo simulations. The structure of interactions has topology of a small-world network obtained from regular two-dimensional square lattices with various coordination numbers by randomly cutting and rewiring edges. Simulations of the model on regular lattices do not yield time series of logarithmic price returns with statistical properties comparable with the empirical ones. In contrast, in the case of networks with a certain degree of randomness for a wide range of parameters the time series of the logarithmic price returns exhibit intermittent bursting typical of volatility clustering. Also the tails of distributions of returns obey a power scaling law with exponents comparable to those obtained from the empirical data.

A market systems analysis of the U.S. Sport Utility Vehicle market considering frontal crash safety technology and policy.

PubMed

Hoffenson, Steven; Frischknecht, Bart D; Papalambros, Panos Y

2013-01-01

Active safety features and adjustments to the New Car Assessment Program (NCAP) consumer-information crash tests have the potential to decrease the number of serious traffic injuries each year, according to previous studies. However, literature suggests that risk reductions, particularly in the automotive market, are often accompanied by adjusted consumer risk tolerance, and so these potential safety benefits may not be fully realized due to changes in consumer purchasing or driving behavior. This article approaches safety in the new vehicle market, particularly in the Sport Utility Vehicle and Crossover Utility Vehicle segments, from a market systems perspective. Crash statistics and simulations are used to predict the effects of design and policy changes on occupant crash safety, and discrete choice experiments are conducted to estimate the values consumers place on vehicle attributes. These models are combined in a market simulation that forecasts how consumers respond to the available vehicle alternatives, resulting in predictions of the market share of each vehicle and how the change in fleet mixture influences societal outcomes including injuries, fuel consumption, and firm profits. The model is tested for a scenario where active safety features are implemented across the new vehicle fleet and a scenario where the U.S. frontal NCAP test speed is modified. While results exhibit evidence of consumer risk adjustment, they support adding active safety features and lowering the NCAP frontal test speed, as these changes are predicted to improve the welfare of both firms and society. Copyright © 2012 Elsevier Ltd. All rights reserved.

Study on Market Stability and Price Limit of Chinese Stock Index Futures Market: An Agent-Based Modeling Perspective.

PubMed

Xiong, Xiong; Nan, Ding; Yang, Yang; Yongjie, Zhang

2015-01-01

This paper explores a method of managing the risk of the stock index futures market and the cross-market through analyzing the effectiveness of price limits on the Chinese Stock Index 300 futures market. We adopt a cross-market artificial financial market (include the stock market and the stock index futures market) as a platform on which to simulate the operation of the CSI 300 futures market by changing the settings of price limits. After comparing the market stability under different price limits by appropriate liquidity and volatility indicators, we find that enhancing price limits or removing price limits both play a negative impact on market stability. In contrast, a positive impact exists on market stability if the existing price limit is maintained (increase of limit by10%, down by 10%) or it is broadened to a proper extent. Our study provides reasonable advice for a price limit setting and risk management for CSI 300 futures.

Study on Market Stability and Price Limit of Chinese Stock Index Futures Market: An Agent-Based Modeling Perspective

PubMed Central

2015-01-01

This paper explores a method of managing the risk of the stock index futures market and the cross-market through analyzing the effectiveness of price limits on the Chinese Stock Index 300 futures market. We adopt a cross-market artificial financial market (include the stock market and the stock index futures market) as a platform on which to simulate the operation of the CSI 300 futures market by changing the settings of price limits. After comparing the market stability under different price limits by appropriate liquidity and volatility indicators, we find that enhancing price limits or removing price limits both play a negative impact on market stability. In contrast, a positive impact exists on market stability if the existing price limit is maintained (increase of limit by10%, down by 10%) or it is broadened to a proper extent. Our study provides reasonable advice for a price limit setting and risk management for CSI 300 futures. PMID:26571135

Structurally Dynamic Spin Market Networks

NASA Astrophysics Data System (ADS)

Horváth, Denis; Kuscsik, Zoltán

The agent-based model of stock price dynamics on a directed evolving complex network is suggested and studied by direct simulation. The stationary regime is maintained as a result of the balance between the extremal dynamics, adaptivity of strategic variables and reconnection rules. The inherent structure of node agent "brain" is modeled by a recursive neural network with local and global inputs and feedback connections. For specific parametric combination the complex network displays small-world phenomenon combined with scale-free behavior. The identification of a local leader (network hub, agent whose strategies are frequently adapted by its neighbors) is carried out by repeated random walk process through network. The simulations show empirically relevant dynamics of price returns and volatility clustering. The additional emerging aspects of stylized market statistics are Zipfian distributions of fitness.

Solving wood chip transport problems with computer simulation.

Treesearch

Dennis P. Bradley; Sharon A. Winsauer

1976-01-01

Efficient chip transport operations are difficult to achieve due to frequent and often unpredictable changes in distance to market, chipping rate, time spent at the mill, and equipment costs. This paper describes a computer simulation model that allows a logger to design an efficient transport system in response to these changing factors.

International Oil Supplies and Demands

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1992-04-01

The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--1990 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world's dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single viewmore » of the likely future path for oil prices. The model results guided the group's thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.« less

International Oil Supplies and Demands

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1991-09-01

The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--90 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world's dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single viewmore » of the likely future path for oil prices. The model results guided the group's thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.« less

Review of the WECC EDT phase 2 EIM benefits analysis and results report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Veselka, T.D.; Poch, L.A.; Botterud, A.

A region-wide Energy Imbalance Market (EIM) was recently proposed by the Western Electricity Coordinating Council (WECC). In order for the Western Area Power Administration (Western) to make more informed decisions regarding its involvement in the EIM, Western asked Argonne National Laboratory (Argonne) to review the EIM benefits study (the October 2011 revision) performed by Energy and Environmental Economics, Inc. (E3). Key components of the E3 analysis made use of results from a study conducted by the National Renewable Energy Laboratory (NREL); therefore, we also reviewed the NREL work. This report examines E3 and NREL methods and models used in themore » EIM study. Estimating EIM benefits is very challenging because of the complex nature of the Western Interconnection (WI), the variability and uncertainty of renewable energy resources, and the complex decisions and potentially strategic bidding of market participants. Furthermore, methodologies used for some of the more challenging aspects of the EIM have not yet matured. This review is complimentary of several components of the EIM study. Analysts and modelers clearly took great care when conducting detailed simulations of the WI using well-established industry tools under stringent time and budget constraints. However, it is our opinion that the following aspects of the study and the interpretation of model results could be improved upon in future analyses. The hurdle rate methodology used to estimate current market inefficiencies does not directly model the underlying causes of sub-optimal dispatch and power flows. It assumes that differences between historical flows and modeled flows can be attributed solely to market inefficiencies. However, flow differences between model results and historical data can be attributed to numerous simplifying assumptions used in the model and in the input data. We suggest that alternative approaches be explored in order to better estimate the benefits of introducing market structures like the EIM. In addition to more efficient energy transactions in the WI, the EIM would reduce the amount of flexibility reserves needed to accommodate forecast errors associated with variable production from wind and solar energy resources. The modeling approach takes full advantage of variable resource diversity over the entire market footprint, but the projected reduction in flexibility reserves may be overly optimistic. While some reduction would undoubtedly occur, the EIM is only an energy market and would therefore not realize the same reduction in reserves as an ancillary services market. In our opinion the methodology does not adequately capture the impact of transmission constraints on the deployment of flexibility reserves. Estimates of flexibility reserves assume that forecast errors follow a normal distribution. Improved estimates could be obtained by using other probability distributions to estimate up and down reserves to capture the underlying uncertainty of these resources under specific operating conditions. Also, the use of a persistence forecast method for solar is questionable, because solar insolation follows a deterministic pattern dictated by the sun's path through the sky. We suggest a more rigorous method for forecasting solar insolation using the sun's relatively predictable daily pattern at specific locations. The EIM study considered only one scenario for hydropower resources. While this scenario is within the normal range over the WI footprint, it represents a severe drought condition in the Colorado River Basin from which Western schedules power. Given hydropower's prominent role in the WI, we recommend simulating a range of hydropower conditions since the relationship between water availability and WI dispatch costs is nonlinear. Also, the representation of specific operational constraints faced by hydropower operators in the WI needs improvements. The model used in the study cannot fully capture all of the EIM impacts and complexities of power system operations. In particular, a primary benefit of the EIM is a shorter dispatch interval; namely, 5 minutes. However, the model simulates the dispatch hourly. Therefore it cannot adequately measure the benefits of a more frequent dispatch. A tool with a finer time resolution would significantly improve simulation accuracy. When the study was conducted, the rules for the EIM were not clearly defined and it was appropriate to estimate societal benefits of the EIM assuming a perfect market without a detailed specification of the market design. However, incorporating a more complete description of market rules will allow for better estimates of EIM benefits. Furthermore, performing analyses using specific market rules can identify potential design flaws that may be difficult and expensive to correct after the market is established. Estimated cost savings from a more efficient dispatch are less than one percent of the total cost of electricity production.« less

The returns and risks of investment portfolio in stock market crashes

NASA Astrophysics Data System (ADS)

Li, Jiang-Cheng; Long, Chao; Chen, Xiao-Dan

2015-06-01

The returns and risks of investment portfolio in stock market crashes are investigated by considering a theoretical model, based on a modified Heston model with a cubic nonlinearity, proposed by Spagnolo and Valenti. Through numerically simulating probability density function of returns and the mean escape time of the model, the results indicate that: (i) the maximum stability of returns is associated with the maximum dispersion of investment portfolio and an optimal stop-loss position; (ii) the maximum risks are related with a worst dispersion of investment portfolio and the risks of investment portfolio are enhanced by increasing stop-loss position. In addition, the good agreements between the theoretical result and real market data are found in the behaviors of the probability density function and the mean escape time.

Climate variability and change scenarios for a marine commodity: Modelling small pelagic fish, fisheries and fishmeal in a globalized market

NASA Astrophysics Data System (ADS)

Merino, Gorka; Barange, Manuel; Mullon, Christian

2010-04-01

The world's small pelagic fish populations, their fisheries, fishmeal and fish oil production industries and markets are part of a globalised production and consumption system. The potential for climate variability and change to alter the balance in this system is explored by means of bioeconomic models at two different temporal scales, with the objective of investigating the interactive nature of environmental and human-induced changes on this globalised system. Short-term (interannual) environmental impacts on fishmeal production are considered by including an annual variable production rate on individual small pelagic fish stocks over a 10-year simulation period. These impacts on the resources are perceived by the fishmeal markets, where they are confronted by two aquaculture expansion hypotheses. Long-term (2080) environmental impacts on the same stocks are estimated using long-term primary production predictions as proxies for the species' carrying capacities, rather than using variable production rates, and are confronted on the market side by two alternative fishmeal management scenarios consistent with IPCC-type storylines. The two scenarios, World Markets and Global Commons, are parameterized through classic equilibrium solutions for a global surplus production bioeconomic model, namely maximum sustainable yield and open access, respectively. The fisheries explicitly modelled in this paper represent 70% of total fishmeal production, thus encapsulating the expected dynamics of the global production and consumption system. Both short and long-term simulations suggest that the sustainability of the small pelagic resources, in the face of climate variability and change, depends more on how society responds to climate impacts than on the magnitude of climate alterations per se.

Federal timber restrictions, interregional spillovers, and the impact on US softwood markets

Treesearch

David N. Wear; Brian C. Murray

2004-01-01

An econometric model of the US softwood lumber and timber markets is estimated and used to simulate the price, trade, and welfare effects of reductions in federal timber sales in the western US commencing in the late 1980s. Results indicate that the timber sale reductions increased lumber prices by roughly 15 percent in the mid-1990s. Lumber consumers were the...

Analyzing Strategic Business Rules through Simulation Modeling

NASA Astrophysics Data System (ADS)

Orta, Elena; Ruiz, Mercedes; Toro, Miguel

Service Oriented Architecture (SOA) holds promise for business agility since it allows business process to change to meet new customer demands or market needs without causing a cascade effect of changes in the underlying IT systems. Business rules are the instrument chosen to help business and IT to collaborate. In this paper, we propose the utilization of simulation models to model and simulate strategic business rules that are then disaggregated at different levels of an SOA architecture. Our proposal is aimed to help find a good configuration for strategic business objectives and IT parameters. The paper includes a case study where a simulation model is built to help business decision-making in a context where finding a good configuration for different business parameters and performance is too complex to analyze by trial and error.

Integration of scheduling and discrete event simulation systems to improve production flow planning

NASA Astrophysics Data System (ADS)

Krenczyk, D.; Paprocka, I.; Kempa, W. M.; Grabowik, C.; Kalinowski, K.

2016-08-01

The increased availability of data and computer-aided technologies such as MRPI/II, ERP and MES system, allowing producers to be more adaptive to market dynamics and to improve production scheduling. Integration of production scheduling and computer modelling, simulation and visualization systems can be useful in the analysis of production system constraints related to the efficiency of manufacturing systems. A integration methodology based on semi-automatic model generation method for eliminating problems associated with complexity of the model and labour-intensive and time-consuming process of simulation model creation is proposed. Data mapping and data transformation techniques for the proposed method have been applied. This approach has been illustrated through examples of practical implementation of the proposed method using KbRS scheduling system and Enterprise Dynamics simulation system.

Simulation of Ultra-Small MOSFETs Using a 2-D Quantum-Corrected Drift-Diffusion Model

NASA Technical Reports Server (NTRS)

Biegal, Bryan A.; Rafferty, Connor S.; Yu, Zhiping; Ancona, Mario G.; Dutton, Robert W.; Saini, Subhash (Technical Monitor)

1998-01-01

The continued down-scaling of electronic devices, in particular the commercially dominant MOSFET, will force a fundamental change in the process of new electronics technology development in the next five to ten years. The cost of developing new technology generations is soaring along with the price of new fabrication facilities, even as competitive pressure intensifies to bring this new technology to market faster than ever before. To reduce cost and time to market, device simulation must become a more fundamental, indeed dominant, part of the technology development cycle. In order to produce these benefits, simulation accuracy must improve markedly. At the same time, device physics will become more complex, with the rapid increase in various small-geometry and quantum effects. This work describes both an approach to device simulator development and a physical model which advance the effort to meet the tremendous electronic device simulation challenge described above. The device simulation approach is to specify the physical model at a high level to a general-purpose (but highly efficient) partial differential equation solver (in this case PROPHET, developed by Lucent Technologies), which then simulates the model in 1-D, 2-D, or 3-D for a specified device and test regime. This approach allows for the rapid investigation of a wide range of device models and effects, which is certainly essential for device simulation to catch up with, and then stay ahead of, electronic device technology of the present and future. The physical device model used in this work is the density-gradient (DG) quantum correction to the drift-diffusion model [Ancona, Phys. Rev. B 35(5), 7959 (1987)]. This model adds tunneling and quantum smoothing of carrier density profiles to the drift-diffusion model. We used the DG model in 1-D and 2-D (for the first time) to simulate both bipolar and unipolar devices. Simulations of heavily-doped, short-base diodes indicated that the DG quantum corrections do not have a large effect on the IN characteristics of electronic devices without heteroj unction s. On the other hand, ultra-small MOSFETs certainly exhibit important quantum effects that the DG model will include: quantum repulsion of the inversion and gate charges from the oxide interfaces, and quantum tunneling through thin gate oxides. We present initial results of 2-D DG simulations of ultra-small MOSFETs. Subtle but important issues involving the specification of the model, boundary conditions, and interface constraints for DG simulation of MOSFETs will also be illuminated.

Impact of Market Behavior, Fleet Composition, and Ancillary Services on Revenue Sufficiency

DOE Office of Scientific and Technical Information (OSTI.GOV)

Frew, Bethany; Gallo, Giulia; Brinkman, Gregory

Revenue insufficiency, or the missing money problem, occurs when the revenues that generators earn from the market are not sufficient to cover both fixed and variable costs to remain in the market and/or justify investments in new capacity, which may be needed for reliability. The near-zero marginal cost of variable renewable generators further exacerbates these revenue challenges. Estimating the extent of the missing money problem in current electricity markets is an important, nontrivial task that requires representing both how the power system operates and how market participants behave. This paper explores the missing money problem using a production cost modelmore » that represented a simplified version of the Electric Reliability Council of Texas (ERCOT) energy-only market for the years 2012-2014. We evaluate how various market structures -- including market behavior, ancillary services, and changing fleet compositions -- affect net revenues in this ERCOT-like system. In most production cost modeling exercises, resources are assumed to offer their marginal capabilities at marginal costs. Although this assumption is reasonable for feasibility studies and long-term planning, it does not adequately consider the market behaviors that impact revenue sufficiency. In this work, we simulate a limited set of market participant strategic bidding behaviors by means of different sets of markups; these markups are applied to the true production costs of all gas generators, which are the most prominent generators in ERCOT. Results show that markups can help generators increase their net revenues overall, although net revenues may increase or decrease depending on the technology and the year under study. Results also confirm that conventional, variable-cost-based production cost simulations do not capture prices accurately, and this particular feature calls for proxies for strategic behaviors (e.g., markups) and more accurate representations of how electricity markets work. The analysis also shows that generators face revenue sufficiency challenges in this ERCOT-like energy-only market model; net revenues provided by the market in all base markup cases and sensitivity scenarios (except when a large fraction of the existing coal fleet is retired) are not sufficient to justify investments in new capacity for thermal and nuclear power units. Overall, the work described in this paper points to the need for improved behavioral models of electricity markets to more accurately study current and potential market design issues that could arise in systems with high penetrations of renewable generation.« less

Transaction costs and sequential bargaining in transferable discharge permit markets.

PubMed

Netusil, N R; Braden, J B

2001-03-01

Market-type mechanisms have been introduced and are being explored for various environmental programs. Several existing programs, however, have not attained the cost savings that were initially projected. Modeling that acknowledges the role of transactions costs and the discrete, bilateral, and sequential manner in which trades are executed should provide a more realistic basis for calculating potential cost savings. This paper presents empirical evidence on potential cost savings by examining a market for the abatement of sediment from farmland. Empirical results based on a market simulation model find no statistically significant change in mean abatement costs under several transaction cost levels when contracts are randomly executed. An alternative method of contract execution, gain-ranked, yields similar results. At the highest transaction cost level studied, trading reduces the total cost of compliance relative to a uniform standard that reflects current regulations.

Short-memory traders and their impact on group learning in financial markets

PubMed Central

LeBaron, Blake

2002-01-01

This article highlights several issues from simulating agent-based financial markets. These all center around the issue of learning in a multiagent setting, and specifically the question of whether the trading behavior of short-memory agents could interfere with the learning process of the market as whole. It is shown in a simple example that short-memory traders persist in generating excess volatility and other features common to actual markets. Problems related to short-memory trader behavior can be eliminated by using several different methods. These are discussed along with their relevance to agent-based models in general. PMID:11997443

A water market simulator considering pair-wise trades between agents

NASA Astrophysics Data System (ADS)

Huskova, I.; Erfani, T.; Harou, J. J.

2012-04-01

In many basins in England no further water abstraction licences are available. Trading water between water rights holders has been recognized as a potentially effective and economically efficient strategy to mitigate increasing scarcity. A screening tool that could assess the potential for trade through realistic simulation of individual water rights holders would help assess the solution's potential contribution to local water management. We propose an optimisation-driven water market simulator that predicts pair-wise trade in a catchment and represents its interaction with natural hydrology and engineered infrastructure. A model is used to emulate licence-holders' willingness to engage in short-term trade transactions. In their simplest form agents are represented using an economic benefit function. The working hypothesis is that trading behaviour can be partially predicted based on differences in marginal values of water over space and time and estimates of transaction costs on pair-wise trades. We discuss the further possibility of embedding rules, norms and preferences of the different water user sectors to more realistically represent the behaviours, motives and constraints of individual licence holders. The potential benefits and limitations of such a social simulation (agent-based) approach is contrasted with our simulator where agents are driven by economic optimization. A case study based on the Dove River Basin (UK) demonstrates model inputs and outputs. The ability of the model to suggest impacts of water rights policy reforms on trading is discussed.

Carbon emission trading system of China: a linked market vs. separated markets

NASA Astrophysics Data System (ADS)

Liu, Yu; Feng, Shenghao; Cai, Songfeng; Zhang, Yaxiong; Zhou, Xiang; Chen, Yanbin; Chen, Zhanming

2013-12-01

The Chinese government intends to upgrade its current provincial carbon emission trading pilots to a nationwide scheme by 2015. This study investigates two of scenarios: separated provincial markets and a linked inter-provincial market. The carbon abatement effects of separated and linked markets are compared using two pilot provinces of Hubei and Guangdong based on a computable general equilibrium model termed Sino-TERMCo2. Simulation results show that the linked market can improve social welfare and reduce carbon emission intensity for the nation as well as for the Hubei-Guangdong bloc compared to the separated market. However, the combined system also distributes welfare more unevenly and thus increases social inequity. On the policy ground, the current results suggest that a well-constructed, nationwide carbon market complemented with adequate welfare transfer policies can be employed to replace the current top-down abatement target disaggregation practice.

Modeling ecohydrological dynamics of smallholder strategies for food production in dryland agricultural systems

NASA Astrophysics Data System (ADS)

Gower, Drew B.; Dell'Angelo, Jampel; McCord, Paul F.; Caylor, Kelly K.; Evans, Tom P.

2016-11-01

In dryland environments, characterized by low and frequently variable rainfall, smallholder farmers must take crop water sensitivity into account along with other characteristics like seed availability and market price when deciding what to plant. In this paper we use the results of surveys conducted among smallholders located near Mount Kenya to identify clusters of farmers devoting different fractions of their land to subsistence and market crops. Additionally, we explore the tradeoffs between water-insensitive but low-value subsistence crops and a water-sensitive but high-value market crop using a numerical model that simulates soil moisture dynamics and crop production over multiple growing seasons. The cluster analysis shows that most farmers prefer to plant either only subsistence crops or only market crops, with a minority choosing to plant substantial fractions of both. The model output suggests that the value a farmer places on a successful growing season, a measure of risk aversion, plays a large role in whether the farmer chooses a subsistence or market crop strategy. Furthermore, access to irrigation, makes market crops more appealing, even to very risk-averse farmers. We then conclude that the observed clustering may result from different levels of risk aversion and access to irrigation.

7 CFR 400.705 - Contents required for a new submission or changes to a previously approved submission.

Code of Federal Regulations, 2014 CFR

2014-01-01

... information from market research, producers or producer groups, agents, lending institutions, and other... reliability of the data; (5) An analysis of the results of simulations or modeling showing the performance of proposed rates and commodity prices, as applicable, based on one or more of the following (Such simulations...

7 CFR 400.705 - Contents required for a new submission or changes to a previously approved submission.

Code of Federal Regulations, 2012 CFR

2012-01-01

... information from market research, producers or producer groups, agents, lending institutions, and other... reliability of the data; (5) An analysis of the results of simulations or modeling showing the performance of proposed rates and commodity prices, as applicable, based on one or more of the following (Such simulations...

7 CFR 400.705 - Contents required for a new submission or changes to a previously approved submission.

Code of Federal Regulations, 2011 CFR

2011-01-01

... information from market research, producers or producer groups, agents, lending institutions, and other... reliability of the data; (5) An analysis of the results of simulations or modeling showing the performance of proposed rates and commodity prices, as applicable, based on one or more of the following (Such simulations...

7 CFR 400.705 - Contents required for a new submission or changes to a previously approved submission.

Code of Federal Regulations, 2013 CFR

2013-01-01

... information from market research, producers or producer groups, agents, lending institutions, and other... reliability of the data; (5) An analysis of the results of simulations or modeling showing the performance of proposed rates and commodity prices, as applicable, based on one or more of the following (Such simulations...

A deterministic computer simulation model of life-cycle lamb and wool production.

PubMed

Wang, C T; Dickerson, G E

1991-11-01

A deterministic mathematical computer model was developed to simulate effects on life-cycle efficiency of lamb and wool production from genetic improvement of performance traits under alternative management systems. Genetic input parameters can be varied for age at puberty, length of anestrus, fertility, precocity of fertility, number born, milk yield, mortality, growth rate, body fat, and wool growth. Management options include mating systems, lambing intervals, feeding levels, creep feeding, weaning age, marketing age or weight, and culling policy. Simulated growth of animals is linear from birth to inflection point, then slows asymptotically to specified mature empty BW and fat content when nutrition is not limiting. The ME intake requirement to maintain normal condition is calculated daily or weekly for maintenance, protein and fat deposition, wool growth, gestation, and lactation. Simulated feed intake is the minimum of availability, DM physical limit, or ME physiological limit. Tissue catabolism occurs when intake is below the requirement for essential functions. Mortality increases when BW is depressed. Equations developed for calculations of biological functions were validated with published and unpublished experimental data. Lifetime totals are accumulated for TDN, DM, and protein intake and for market lamb equivalent output values of empty body or carcass lean and wool from both lambs and ewes. These measures of efficiency for combinations of genetic, management, and marketing variables can provide the relative economic weighting of traits needed to derive optimal criteria for genetic selection among and within breeds under defined industry production systems.

International Oil Supplies and Demands. Volume 1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1991-09-01

The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--90 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world`s dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single viewmore » of the likely future path for oil prices. The model results guided the group`s thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.« less

International Oil Supplies and Demands. Volume 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1992-04-01

The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--1990 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world`s dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single viewmore » of the likely future path for oil prices. The model results guided the group`s thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.« less

The long memory and the transaction cost in financial markets

NASA Astrophysics Data System (ADS)

Li, Daye; Nishimura, Yusaku; Men, Ming

2016-01-01

In the present work, we investigate the fractal dimensions of 30 important stock markets from 2006 to 2013; the analysis indicates that the Hurst exponent of emerging markets shifts significantly away from the standard Brownian motion. We propose a model based on the Hurst exponent to explore the considerable profits from the predictable long-term memory. We take the transaction cost into account to justify why the market inefficiency has not been arbitraged away in the majority of cases. The empirical evidence indicates that the majority of the markets are efficient with a certain transaction cost under the no-arbitrage assumption. Furthermore, we use the Monte Carlo simulation to display "the efficient frontier" of the Hurst exponent with different transaction costs.

Understanding the Future Market for NovaSAR-S Flood Mapping Products Using Data Mining and Simulation

NASA Astrophysics Data System (ADS)

Lavender, Samantha; Haria, Kajal; Cooksley, Geraint; Farman, Alex; Beaton, Thomas

2016-08-01

The aim was to understand a future market for NovaSAR-S, with a particular focus on flood mapping, through developing a simple Synthetic Aperture Radar (SAR) simulator that can be used in advance of NovaSAR-S data becoming available.The return signal was determined from a combination of a terrain or elevation model, Envisat S-Band Radar Altimeter (RA)-2, Landsat and CORINE land cover information; allowing for a simulation of a SAR image that's influenced by both the geometry and surface type. The test sites correspond to data from the 2014 AirSAR campaign, and validation is performed by using AirSAR together with Envisat Advanced (ASAR) and Advanced Land Observing Satellite "Daichi" (ALOS) Phased Array type L-Band Synthetic Aperture Radar (PALSAR) data.It's envisaged that the resulting simulated data, and the simulator, will not only aid early understanding of NovaSAR-S, but will also aid the development of flood mapping applications.

Market-oriented Programming Using Small-world Networks for Controlling Building Environments

NASA Astrophysics Data System (ADS)

Shigei, Noritaka; Miyajima, Hiromi; Osako, Tsukasa

The market model, which is one of the economic activity models, is modeled as an agent system, and applying the model to the resource allocation problem has been studied. For air conditioning control of building, which is one of the resource allocation problems, an effective method based on the agent system using auction has been proposed for traditional PID controller. On the other hand, it has been considered that this method is performed by decentralized control. However, its decentralization is not perfect, and its performace is not enough. In this paper, firstly, we propose a perfectly decentralized agent model and show its performance. Secondly, in order to improve the model, we propose the agent model based on small-world model. The effectiveness of the proposed model is shown by simulation.

Some new results on the Levy, Levy and Solomon microscopic stock market model

NASA Astrophysics Data System (ADS)

Zschischang, Elmar; Lux, Thomas

2001-03-01

We report some findings from our simulations of the Levy, Levy and Solomon microscopic stock market model. Our results cast doubts on some of the results published in the original papers (i.e., chaotic stock price movements). We also point out the possibility of sensitive dependence on initial conditions of the emerging wealth distribution among agents. Extensions of the model set-up show that with varying degrees of risk aversion, the less risk averse traders will tend to dominate the market. Similarly, when introducing a new trader group (or even a single trader) with a constant share of stocks in their portfolio, the latter will eventually take over and marginalize the other groups. The better performance of the more sober investors is in accordance with traditional perceptions in financial economics. Hence, the survival of ‘noise traders’ looking at short-term trends and patterns remains as much of a puzzle in this framework as in the traditional Efficient Market Theory.

Applying Modern Marketing Concepts to Military Recruiting

DTIC Science & Technology

2000-03-03

new to military recruiting or are an updated version of currently used concepts. The concepts and systems include social marketing, marketing ... research , market planning and product development, pricing and management. New simulated application including a strategic planning war game and a simulated

Simulating market dynamics: interactions between consumer psychology and social networks.

PubMed

Janssen, Marco A; Jager, Wander

2003-01-01

Markets can show different types of dynamics, from quiet markets dominated by one or a few products, to markets with continual penetration of new and reintroduced products. In a previous article we explored the dynamics of markets from a psychological perspective using a multi-agent simulation model. The main results indicated that the behavioral rules dominating the artificial consumer's decision making determine the resulting market dynamics, such as fashions, lock-in, and unstable renewal. Results also show the importance of psychological variables like social networks, preferences, and the need for identity to explain the dynamics of markets. In this article we extend this work in two directions. First, we will focus on a more systematic investigation of the effects of different network structures. The previous article was based on Watts and Strogatz's approach, which describes the small-world and clustering characteristics in networks. More recent research demonstrated that many large networks display a scale-free power-law distribution for node connectivity. In terms of market dynamics this may imply that a small proportion of consumers may have an exceptional influence on the consumptive behavior of others (hubs, or early adapters). We show that market dynamics is a self-organized property depending on the interaction between the agents' decision-making process (heuristics), the product characteristics (degree of satisfaction of unit of consumption, visibility), and the structure of interactions between agents (size of network and hubs in a social network).

Electricity market pricing, risk hedging and modeling

NASA Astrophysics Data System (ADS)

Cheng, Xu

In this dissertation, we investigate the pricing, price risk hedging/arbitrage, and simplified system modeling for a centralized LMP-based electricity market. In an LMP-based market model, the full AC power flow model and the DC power flow model are most widely used to represent the transmission system. We investigate the differences of dispatching results, congestion pattern, and LMPs for the two power flow models. An appropriate LMP decomposition scheme to quantify the marginal costs of the congestion and real power losses is critical for the implementation of financial risk hedging markets. However, the traditional LMP decomposition heavily depends on the slack bus selection. In this dissertation we propose a slack-independent scheme to break LMP down into energy, congestion, and marginal loss components by analyzing the actual marginal cost of each bus at the optimal solution point. The physical and economic meanings of the marginal effect at each bus provide accurate price information for both congestion and losses, and thus the slack-dependency of the traditional scheme is eliminated. With electricity priced at the margin instead of the average value, the market operator typically collects more revenue from power sellers than that paid to power buyers. According to the LMP decomposition results, the revenue surplus is then divided into two parts: congestion charge surplus and marginal loss revenue surplus. We apply the LMP decomposition results to the financial tools, such as financial transmission right (FTR) and loss hedging right (LHR), which have been introduced to hedge against price risks associated to congestion and losses, to construct a full price risk hedging portfolio. The two-settlement market structure and the introduction of financial tools inevitably create market manipulation opportunities. We investigate several possible market manipulation behaviors by virtual bidding and propose a market monitor approach to identify and quantify such behavior. Finally, the complexity of the power market and size of the transmission grid make it difficult for market participants to efficiently analyze the long-term market behavior. We propose a simplified power system commercial model by simulating the PTDFs of critical transmission bottlenecks of the original system.

Establishing politically feasible water markets: a multi-criteria approach.

PubMed

Ballestero, Enrique; Alarcón, Silverio; García-Bernabeu, Ana

2002-08-01

A multiple criteria decision-making (MCDM) model to simulate the establishment of water markets is developed. The environment is an irrigated area governed by a non-profit agency, which is responsible for water production, allocation, and pricing. There is a traditional situation of historical rights, average-cost pricing for water allocation, large quantities of water used, and inefficiency. A market-oriented policy could be implemented by accounting for ecological and political objectives such as saving groundwater and safeguarding historical rights while promoting economic efficiency. In this paper, a problem is solved by compromise programming, a multi-criteria technique based on the principles of Simonian logic. The model is theoretically developed and applied to the Lorca region in Spain near the Mediterranean Sea.

Projecting the effects of long-term care policy on the labor market participation of primary informal family caregivers of elderly with disability: insights from a dynamic simulation model.

PubMed

Ansah, John P; Matchar, David B; Malhotra, Rahul; Love, Sean R; Liu, Chang; Do, Young

2016-03-23

Using Singapore as a case study, this paper aims to understand the effects of the current long-term care policy and various alternative policy options on the labor market participation of primary informal family caregivers of elderly with disability. A model of the long-term care system in Singapore was developed using System Dynamics methodology. Under the current long-term care policy, by 2030, 6.9 percent of primary informal family caregivers (0.34 percent of the domestic labor supply) are expected to withdraw from the labor market. Alternative policy options reduce primary informal family caregiver labor market withdrawal; however, the number of workers required to scale up long-term care services is greater than the number of caregivers who can be expected to return to the labor market. Policymakers may face a dilemma between admitting more foreign workers to provide long-term care services and depending on primary informal family caregivers.

A network model of the interbank market

NASA Astrophysics Data System (ADS)

Li, Shouwei; He, Jianmin; Zhuang, Yaming

2010-12-01

This work introduces a network model of an interbank market based on interbank credit lending relationships. It generates some network features identified through empirical analysis. The critical issue to construct an interbank network is to decide the edges among banks, which is realized in this paper based on the interbank’s degree of trust. Through simulation analysis of the interbank network model, some typical structural features are identified in our interbank network, which are also proved to exist in real interbank networks. They are namely, a low clustering coefficient and a relatively short average path length, community structures, and a two-power-law distribution of out-degree and in-degree.

Health, Economic Resources and the Work Decisions of Older Men

PubMed Central

Bound, John; Stinebrickner, Todd; Waidmann, Timothy

2016-01-01

We specify a dynamic programming model that addresses the interplay among health, financial resources, and the labor market behavior of men late in their working lives. We model health as a latent variable, for which self reported disability status is an indicator, and allow self-reported disability to be endogenous to labor market behavior. We use panel data from the Health and Retirement Study. While we find large impacts of health on behavior, they are substantially smaller than in models that treat self-reports as exogenous. We also simulate the impacts of several potential reforms to the Social Security program. PMID:27158180

Application of Complex Adaptive Systems in Portfolio Management

ERIC Educational Resources Information Center

Su, Zheyuan

2017-01-01

Simulation-based methods are becoming a promising research tool in financial markets. A general Complex Adaptive System can be tailored to different application scenarios. Based on the current research, we built two models that would benefit portfolio management by utilizing Complex Adaptive Systems (CAS) in Agent-based Modeling (ABM) approach.…

Comprehensive framework for sustainable container ports development on the US east coast in the 21st century, year two

DOT National Transportation Integrated Search

2002-08-01

Building upon the conceptual framework developed during our year one research, a container port and multimodal transportation demand simulation model is applied. The model selects the least-cost (vessel-port-rail-truck) route from sources to markets,...

Experiences Integrating Transmission and Distribution Simulations for DERs with the Integrated Grid Modeling System (IGMS)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Palmintier, Bryan; Hale, Elaine; Hodge, Bri-Mathias

2016-08-11

This paper discusses the development of, approaches for, experiences with, and some results from a large-scale, high-performance-computer-based (HPC-based) co-simulation of electric power transmission and distribution systems using the Integrated Grid Modeling System (IGMS). IGMS was developed at the National Renewable Energy Laboratory (NREL) as a novel Independent System Operator (ISO)-to-appliance scale electric power system modeling platform that combines off-the-shelf tools to simultaneously model 100s to 1000s of distribution systems in co-simulation with detailed ISO markets, transmission power flows, and AGC-level reserve deployment. Lessons learned from the co-simulation architecture development are shared, along with a case study that explores the reactivemore » power impacts of PV inverter voltage support on the bulk power system.« less

Design of the HELICS High-Performance Transmission-Distribution-Communication-Market Co-Simulation Framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Palmintier, Bryan S; Krishnamurthy, Dheepak; Top, Philip

This paper describes the design rationale for a new cyber-physical-energy co-simulation framework for electric power systems. This new framework will support very large-scale (100,000+ federates) co-simulations with off-the-shelf power-systems, communication, and end-use models. Other key features include cross-platform operating system support, integration of both event-driven (e.g. packetized communication) and time-series (e.g. power flow) simulation, and the ability to co-iterate among federates to ensure model convergence at each time step. After describing requirements, we begin by evaluating existing co-simulation frameworks, including HLA and FMI, and conclude that none provide the required features. Then we describe the design for the new layeredmore » co-simulation architecture.« less

Design of the HELICS High-Performance Transmission-Distribution-Communication-Market Co-Simulation Framework: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Palmintier, Bryan S; Krishnamurthy, Dheepak; Top, Philip

This paper describes the design rationale for a new cyber-physical-energy co-simulation framework for electric power systems. This new framework will support very large-scale (100,000+ federates) co-simulations with off-the-shelf power-systems, communication, and end-use models. Other key features include cross-platform operating system support, integration of both event-driven (e.g. packetized communication) and time-series (e.g. power flow) simulation, and the ability to co-iterate among federates to ensure model convergence at each time step. After describing requirements, we begin by evaluating existing co-simulation frameworks, including HLA and FMI, and conclude that none provide the required features. Then we describe the design for the new layeredmore » co-simulation architecture.« less

Asset price and trade volume relation in artificial market impacted by value investors

NASA Astrophysics Data System (ADS)

Tangmongkollert, K.; Suwanna, S.

2016-05-01

The relationship between return and trade volume has been of great interests in a financial market. The appearance of asymmetry in the price-volume relation in the bull and bear market is still unsettled. We present a model of the value investor traders (VIs) in the double auction system, in which agents make trading decision based on the pseudo fundamental price modelled by sawtooth oscillations. We investigate the system by two different time series for the asset fundamental price: one corresponds to the fundamental price in a growing phase; and the other corresponds to that in a declining phase. The simulation results show that the trade volume is proportional to the difference between the market price and the fundamental price, and that there is asymmetry between the buying and selling phases. Furthermore, the selling phase has more significant impact of price on the trade volume than the buying phase.

The Evolution of ICT Markets: An Agent-Based Model on Complex Networks

NASA Astrophysics Data System (ADS)

Zhao, Liangjie; Wu, Bangtao; Chen, Zhong; Li, Li

Information and communication technology (ICT) products exhibit positive network effects.The dynamic process of ICT markets evolution has two intrinsic characteristics: (1) customers are influenced by each others’ purchasing decision; (2) customers are intelligent agents with bounded rationality.Guided by complex systems theory, we construct an agent-based model and simulate on complex networks to examine how the evolution can arise from the interaction of customers, which occur when they make expectations about the future installed base of a product by the fraction of neighbors who are using the same product in his personal network.We demonstrate that network effects play an important role in the evolution of markets share, which make even an inferior product can dominate the whole market.We also find that the intensity of customers’ communication can influence whether the best initial strategy for firms is to improve product quality or expand their installed base.

A systems approach to college drinking: development of a deterministic model for testing alcohol control policies.

PubMed

Scribner, Richard; Ackleh, Azmy S; Fitzpatrick, Ben G; Jacquez, Geoffrey; Thibodeaux, Jeremy J; Rommel, Robert; Simonsen, Neal

2009-09-01

The misuse and abuse of alcohol among college students remain persistent problems. Using a systems approach to understand the dynamics of student drinking behavior and thus forecasting the impact of campus policy to address the problem represents a novel approach. Toward this end, the successful development of a predictive mathematical model of college drinking would represent a significant advance for prevention efforts. A deterministic, compartmental model of college drinking was developed, incorporating three processes: (1) individual factors, (2) social interactions, and (3) social norms. The model quantifies these processes in terms of the movement of students between drinking compartments characterized by five styles of college drinking: abstainers, light drinkers, moderate drinkers, problem drinkers, and heavy episodic drinkers. Predictions from the model were first compared with actual campus-level data and then used to predict the effects of several simulated interventions to address heavy episodic drinking. First, the model provides a reasonable fit of actual drinking styles of students attending Social Norms Marketing Research Project campuses varying by "wetness" and by drinking styles of matriculating students. Second, the model predicts that a combination of simulated interventions targeting heavy episodic drinkers at a moderately "dry" campus would extinguish heavy episodic drinkers, replacing them with light and moderate drinkers. Instituting the same combination of simulated interventions at a moderately "wet" campus would result in only a moderate reduction in heavy episodic drinkers (i.e., 50% to 35%). A simple, five-state compartmental model adequately predicted the actual drinking patterns of students from a variety of campuses surveyed in the Social Norms Marketing Research Project study. The model predicted the impact on drinking patterns of several simulated interventions to address heavy episodic drinking on various types of campuses.

A Systems Approach to College Drinking: Development of a Deterministic Model for Testing Alcohol Control Policies*

PubMed Central

Scribner, Richard; Ackleh, Azmy S.; Fitzpatrick, Ben G.; Jacquez, Geoffrey; Thibodeaux, Jeremy J.; Rommel, Robert; Simonsen, Neal

2009-01-01

Objective: The misuse and abuse of alcohol among college students remain persistent problems. Using a systems approach to understand the dynamics of student drinking behavior and thus forecasting the impact of campus policy to address the problem represents a novel approach. Toward this end, the successful development of a predictive mathematical model of college drinking would represent a significant advance for prevention efforts. Method: A deterministic, compartmental model of college drinking was developed, incorporating three processes: (1) individual factors, (2) social interactions, and (3) social norms. The model quantifies these processes in terms of the movement of students between drinking compartments characterized by five styles of college drinking: abstainers, light drinkers, moderate drinkers, problem drinkers, and heavy episodic drinkers. Predictions from the model were first compared with actual campus-level data and then used to predict the effects of several simulated interventions to address heavy episodic drinking. Results: First, the model provides a reasonable fit of actual drinking styles of students attending Social Norms Marketing Research Project campuses varying by “wetness” and by drinking styles of matriculating students. Second, the model predicts that a combination of simulated interventions targeting heavy episodic drinkers at a moderately “dry” campus would extinguish heavy episodic drinkers, replacing them with light and moderate drinkers. Instituting the same combination of simulated interventions at a moderately “wet” campus would result in only a moderate reduction in heavy episodic drinkers (i.e., 50% to 35%). Conclusions: A simple, five-state compartmental model adequately predicted the actual drinking patterns of students from a variety of campuses surveyed in the Social Norms Marketing Research Project study. The model predicted the impact on drinking patterns of several simulated interventions to address heavy episodic drinking on various types of campuses. PMID:19737506

Discovering the influential users oriented to viral marketing based on online social networks

NASA Astrophysics Data System (ADS)

Zhu, Zhiguo

2013-08-01

The target of viral marketing on the platform of popular online social networks is to rapidly propagate marketing information at lower cost and increase sales, in which a key problem is how to precisely discover the most influential users in the process of information diffusion. A novel method is proposed in this paper for helping companies to identify such users as seeds to maximize information diffusion in the viral marketing. Firstly, the user trust network oriented to viral marketing and users’ combined interest degree in the network including isolated users are extensively defined. Next, we construct a model considering the time factor to simulate the process of information diffusion in viral marketing and propose a dynamic algorithm description. Finally, experiments are conducted with a real dataset extracted from the famous SNS website Epinions. The experimental results indicate that the proposed algorithm has better scalability and is less time-consuming. Compared with the classical model, the proposed algorithm achieved a better performance than does the classical method on the two aspects of network coverage rate and time-consumption in our four sub-datasets.

Analysis of the Automobile Market : Modeling the Long-Run Determinants of the Demand for Automobiles : Volume 2. Simulation Analysis Using the Wharton EFA Automobile Demand Model

DOT National Transportation Integrated Search

1979-12-01

An econometric model is developed which provides long-run policy analysis and forecasting of annual trends, for U.S. auto stock, new sales, and their composition by auto size-class. The concept of "desired" (equilibrium) stock is introduced. "Desired...

Forest product trade impacts of an invasive species: modeling structure and intervention trade-offs

Treesearch

Jeffrey Prestemon; Shushuai Zhu; James A. Turner; Joseph Buongiorno; Ruhong Li

2006-01-01

Asian gypsy and nun moth introductions into the United States, possibly arriving on imported Siberian coniferous logs, threaten domestic forests and product markers and could have global market consequences. We simulate, using the Global Forest Products Model (a spatial equilibrium model of the world forest sector), the consequences under current policies of a...

Multi-agent simulation of the von Thunen model formation mechanism

NASA Astrophysics Data System (ADS)

Tao, Haiyan; Li, Xia; Chen, Xiaoxiang; Deng, Chengbin

2008-10-01

This research tries to explain the internal driving forces of circular structure formation in urban geography via the simulation of interaction between individual behavior and market. On the premise of single city center, unchanged scale merit and complete competition, enterprise migration theory as well, an R-D algorithm, that has agents searched the best behavior rules in some given locations, is introduced with agent-based modeling technique. The experiment conducts a simulation on Swarm platform, whose result reflects and replays the formation process of Von Thünen circular structure. Introducing and considering some heterogeneous factors, such as traffic roads, the research verifies several landuse models and discusses the self-adjustment function of price mechanism.

Evaluating the impacts of farmers' behaviors on a hypothetical agricultural water market based on double auction

NASA Astrophysics Data System (ADS)

Du, Erhu; Cai, Ximing; Brozović, Nicholas; Minsker, Barbara

2017-05-01

Agricultural water markets are considered effective instruments to mitigate the impacts of water scarcity and to increase crop production. However, previous studies have limited understanding of how farmers' behaviors affect the performance of water markets. This study develops an agent-based model to explicitly incorporate farmers' behaviors, namely irrigation behavior (represented by farmers' sensitivity to soil water deficit λ) and bidding behavior (represented by farmers' rent seeking μ and learning rate β), in a hypothetical water market based on a double auction. The model is applied to the Guadalupe River Basin in Texas to simulate a hypothetical agricultural water market under various hydrological conditions. It is found that the joint impacts of the behavioral parameters on the water market are strong and complex. In particular, among the three behavioral parameters, λ affects the water market potential and its impacts on the performance of the water market are significant under most scenarios. The impacts of μ or β on the performance of the water market depend on the other two parameters. The water market could significantly increase crop production only when the following conditions are satisfied: (1) λ is small and (2) μ is small and/or β is large. The first condition requires efficient irrigation scheduling, and the second requires well-developed water market institutions that provide incentives to bid true valuation of water permits.

A Mathematical Model of Demand-Supply Dynamics with Collectability and Saturation Factors

NASA Astrophysics Data System (ADS)

Li, Y. Charles; Yang, Hong

We introduce a mathematical model on the dynamics of demand and supply incorporating collectability and saturation factors. Our analysis shows that when the fluctuation of the determinants of demand and supply is strong enough, there is chaos in the demand-supply dynamics. Our numerical simulation shows that such a chaos is not an attractor (i.e. dynamics is not approaching the chaos), instead a periodic attractor (of period-3 under the Poincaré period map) exists near the chaos, and coexists with another periodic attractor (of period-1 under the Poincaré period map) near the market equilibrium. Outside the basins of attraction of the two periodic attractors, the dynamics approaches infinity indicating market irrational exuberance or flash crash. The period-3 attractor represents the product’s market cycle of growth and recession, while period-1 attractor near the market equilibrium represents the regular fluctuation of the product’s market. Thus our model captures more market phenomena besides Marshall’s market equilibrium. When the fluctuation of the determinants of demand and supply is strong enough, a three leaf danger zone exists where the basins of attraction of all attractors intertwine and fractal basin boundaries are formed. Small perturbations in the danger zone can lead to very different attractors. That is, small perturbations in the danger zone can cause the market to experience oscillation near market equilibrium, large growth and recession cycle, and irrational exuberance or flash crash.

Experiential Learning--A Case Study of the Use of Computerised Stock Market Trading Simulation in Finance Education

ERIC Educational Resources Information Center

Marriott, Pru; Tan, Siew Min; Marriott, Neil

2015-01-01

Finance is a popular programme of study in UK higher education despite it being a challenging subject that requires students to understand and apply complex and abstract mathematical models and academic theories. Educational simulation is an active learning method found to be useful in enhancing students' learning experience, but there has been…

A mini-review on econophysics: Comparative study of Chinese and western financial markets

NASA Astrophysics Data System (ADS)

Zheng, Bo; Jiang, Xiong-Fei; Ni, Peng-Yun

2014-07-01

We present a review of our recent research in econophysics, and focus on the comparative study of Chinese and western financial markets. By virtue of concepts and methods in statistical physics, we investigate the time correlations and spatial structure of financial markets based on empirical high-frequency data. We discover that the Chinese stock market shares common basic properties with the western stock markets, such as the fat-tail probability distribution of price returns, the long-range auto-correlation of volatilities, and the persistence probability of volatilities, while it exhibits very different higher-order time correlations of price returns and volatilities, spatial correlations of individual stock prices, and large-fluctuation dynamic behaviors. Furthermore, multi-agent-based models are developed to simulate the microscopic interaction and dynamic evolution of the stock markets.

Aspen: A microsimulation model of the economy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Basu, N.; Pryor, R.J.; Quint, T.

1996-10-01

This report presents, Aspen. Sandia National Laboratories is developing this new agent-based microeconomic simulation model of the U.S. economy. The model is notable because it allows a large number of individual economic agents to be modeled at a high level of detail and with a great degree of freedom. Some features of Aspen are (a) a sophisticated message-passing system that allows individual pairs of agents to communicate, (b) the use of genetic algorithms to simulate the learning of certain agents, and (c) a detailed financial sector that includes a banking system and a bond market. Results from runs of themore » model are also presented.« less

NREL Improves Building Energy Simulation Programs Through Diagnostic Testing (Fact Sheet)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

2012-01-01

This technical highlight describes NREL research to develop Building Energy Simulation Test for Existing Homes (BESTEST-EX) to increase the quality and accuracy of energy analysis tools for the building retrofit market. Researchers at the National Renewable Energy Laboratory (NREL) have developed a new test procedure to increase the quality and accuracy of energy analysis tools for the building retrofit market. The Building Energy Simulation Test for Existing Homes (BESTEST-EX) is a test procedure that enables software developers to evaluate the performance of their audit tools in modeling energy use and savings in existing homes when utility bills are available formore » model calibration. Similar to NREL's previous energy analysis tests, such as HERS BESTEST and other BESTEST suites included in ANSI/ASHRAE Standard 140, BESTEST-EX compares software simulation findings to reference results generated with state-of-the-art simulation tools such as EnergyPlus, SUNREL, and DOE-2.1E. The BESTEST-EX methodology: (1) Tests software predictions of retrofit energy savings in existing homes; (2) Ensures building physics calculations and utility bill calibration procedures perform to a minimum standard; and (3) Quantifies impacts of uncertainties in input audit data and occupant behavior. BESTEST-EX includes building physics and utility bill calibration test cases. The diagram illustrates the utility bill calibration test cases. Participants are given input ranges and synthetic utility bills. Software tools use the utility bills to calibrate key model inputs and predict energy savings for the retrofit cases. Participant energy savings predictions using calibrated models are compared to NREL predictions using state-of-the-art building energy simulation programs.« less

Stock price change rate prediction by utilizing social network activities.

PubMed

Deng, Shangkun; Mitsubuchi, Takashi; Sakurai, Akito

2014-01-01

Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.

Stock Price Change Rate Prediction by Utilizing Social Network Activities

PubMed Central

Mitsubuchi, Takashi; Sakurai, Akito

2014-01-01

Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques. PMID:24790586

Study on Bidding Strategy and Market Clearing Price in Electric Power Day-ahead Market using Market Simulation

NASA Astrophysics Data System (ADS)

Sasaki, Tetsuo; Kadoya, Toshihisa

In an electric power day-ahead market, market prices are not always cleared at marginal cost caused by the strategic bidding of generators. This paper presents the results of day-ahead market simulation that analyzes profits depending upon bidding strategies in an electric power day-ahead market. It is clarified that MCP (Market Clearing Price) is easily managed by only one player and does not easily decline after it has gone up once. Moreover the mutual interference among day-ahead markets, future markets, increase of generators, etc. are also discussed.

eShopper modeling and simulation

NASA Astrophysics Data System (ADS)

Petrushin, Valery A.

2001-03-01

The advent of e-commerce gives an opportunity to shift the paradigm of customer communication into a highly interactive mode. The new generation of commercial Web servers, such as the Blue Martini's server, combines the collection of data on a customer behavior with real-time processing and dynamic tailoring of a feedback page. The new opportunities for direct product marketing and cross selling are arriving. The key problem is what kind of information do we need to achieve these goals, or in other words, how do we model the customer? The paper is devoted to customer modeling and simulation. The focus is on modeling an individual customer. The model is based on the customer's transaction data, click stream data, and demographics. The model includes the hierarchical profile of a customer's preferences to different types of products and brands; consumption models for the different types of products; the current focus, trends, and stochastic models for time intervals between purchases; product affinity models; and some generalized features, such as purchasing power, sensitivity to advertising, price sensitivity, etc. This type of model is used for predicting the date of the next visit, overall spending, and spending for different types of products and brands. For some type of stores (for example, a supermarket) and stable customers, it is possible to forecast the shopping lists rather accurately. The forecasting techniques are discussed. The forecasting results can be used for on- line direct marketing, customer retention, and inventory management. The customer model can also be used as a generative model for simulating the customer's purchasing behavior in different situations and for estimating customer's features.

Evaluating the Impacts of an Agricultural Water Market in the Guadalupe River Basin, Texas: An Agent-based Modeling Approach

NASA Astrophysics Data System (ADS)

Du, E.; Cai, X.; Minsker, B. S.

2014-12-01

Agriculture comprises about 80 percent of the total water consumption in the US. Under conditions of water shortage and fully committed water rights, market-based water allocations could be promising instruments for agricultural water redistribution from marginally profitable areas to more profitable ones. Previous studies on water market have mainly focused on theoretical or statistical analysis. However, how water users' heterogeneous physical attributes and decision rules about water use and water right trading will affect water market efficiency has been less addressed. In this study, we developed an agent-based model to evaluate the benefits of an agricultural water market in the Guadalupe River Basin during drought events. Agricultural agents with different attributes (i.e., soil type for crops, annual water diversion permit and precipitation) are defined to simulate the dynamic feedback between water availability, irrigation demand and water trading activity. Diversified crop irrigation rules and water bidding rules are tested in terms of crop yield, agricultural profit, and water-use efficiency. The model was coupled with a real-time hydrologic model and run under different water scarcity scenarios. Preliminary results indicate that an agricultural water market is capable of increasing crop yield, agricultural profit, and water-use efficiency. This capability is more significant under moderate drought scenarios than in mild and severe drought scenarios. The water market mechanism also increases agricultural resilience to climate uncertainty by reducing crop yield variance in drought events. The challenges of implementing an agricultural water market under climate uncertainty are also discussed.

Transactive Control of Commercial Buildings for Demand Response

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hao, He; Corbin, Charles D.; Kalsi, Karanjit

Transactive control is a type of distributed control strategy that uses market mechanism to engage self-interested responsive loads to achieve power balance in the electrical power grid. In this paper, we propose a transactive control approach of commercial building Heating, Ventilation, and Air- Conditioning (HVAC) systems for demand response. We first describe the system models, and identify their model parameters using data collected from Systems Engineering Building (SEB) located on our Pacific Northwest National Laboratory (PNNL) campus. We next present a transactive control market structure for commercial building HVAC system, and describe its agent bidding and market clearing strategies. Severalmore » case studies are performed in a simulation environment using Building Control Virtual Test Bed (BCVTB) and calibrated SEB EnergyPlus model. We show that the proposed transactive control approach is very effective at peak clipping, load shifting, and strategic conservation for commercial building HVAC systems.« less

Understanding Air Transportation Market Dynamics Using a Search Algorithm for Calibrating Travel Demand and Price

NASA Technical Reports Server (NTRS)

Kumar, Vivek; Horio, Brant M.; DeCicco, Anthony H.; Hasan, Shahab; Stouffer, Virginia L.; Smith, Jeremy C.; Guerreiro, Nelson M.

2015-01-01

This paper presents a search algorithm based framework to calibrate origin-destination (O-D) market specific airline ticket demands and prices for the Air Transportation System (ATS). This framework is used for calibrating an agent based model of the air ticket buy-sell process - Airline Evolutionary Simulation (Airline EVOS) -that has fidelity of detail that accounts for airline and consumer behaviors and the interdependencies they share between themselves and the NAS. More specificially, this algorithm simultaneous calibrates demand and airfares for each O-D market, to within specified threshold of a pre-specified target value. The proposed algorithm is illustrated with market data targets provided by the Transportation System Analysis Model (TSAM) and Airline Origin and Destination Survey (DB1B). Although we specify these models and datasources for this calibration exercise, the methods described in this paper are applicable to calibrating any low-level model of the ATS to some other demand forecast model-based data. We argue that using a calibration algorithm such as the one we present here to synchronize ATS models with specialized forecast demand models, is a powerful tool for establishing credible baseline conditions in experiments analyzing the effects of proposed policy changes to the ATS.

The Stock Market Game: A Simulation of Stock Market Trading. Grades 5-8.

ERIC Educational Resources Information Center

Draze, Dianne

This guide to a unit on a simulation game about the stock market contains an instructional text and two separate simulations. Through directed lessons and reproducible worksheets, the unit teaches students about business ownership, stock exchanges, benchmarks, commissions, why prices change, the logistics of buying and selling stocks, and how to…

Aggregate age-at-marriage patterns from individual mate-search heuristics.

PubMed

Todd, Peter M; Billari, Francesco C; Simão, Jorge

2005-08-01

The distribution of age at first marriage shows well-known strong regularities across many countries and recent historical periods. We accounted for these patterns by developing agent-based models that simulate the aggregate behavior of individuals who are searching for marriage partners. Past models assumed fully rational agents with complete knowledge of the marriage market; our simulated agents used psychologically plausible simple heuristic mate search rules that adjust aspiration levels on the basis of a sequence of encounters with potential partners. Substantial individual variation must be included in the models to account for the demographically observed age-at-marriage patterns.

Entry, concentration and market efficiency: A simulation of the PJM energy market

NASA Astrophysics Data System (ADS)

Harvill, Terry

The rapid and substantial expansion of the PJM energy market during 2004 and 2005 provides a unique opportunity to test the theory of market concentration and its effect on market efficiency. With ten years of operational experience, the PJM energy market is uniquely suited to test the theories of market concentration and efficiency in a natural experiment. This research tests the hypothesis that, for a given number of generating units in the industry, system marginal price will be a decreasing function of the number of owners or generators controlling the units (i.e., the industry concentration ratio). Market simulations are utilized to assess price-cost markups in the PJM energy market during three distinct periods of expansion: (1) pre-Commonwealth Edison integration, (2) pre-American Electric Power (AEP), Dayton Power and Light (DPL), Duquesne Light (Duquesne), and Dominion Virginia Power (Dominion) integration, and (3) post-AFT, DPL. Duquesne, and Dominion Integration. The results of the market simulations for the May 1 to August 31 periods for 2003, 2004, and 2005, indicate that the performance of the market improved with the addition of new market participants in 2004 and 2005. The results of the simulation indicate that the load-weighted Lerner index decreased to -3.70 percent in 2005 from 0.92 percent in 2003. Clearly, the addition of Commonwealth Edison in 2004 significantly increased constraints within the PJM energy market and likely impacted the observed prices in PJM during 2004 due to the lack of a significant link to the other PJM market participants. This deficiency was address in 2005 with the addition of American Electric Power. The market simulations also highlight the prevalence of computed negative markups in the simulation results. Many of the off-peak periods in particular are characterized by negative markups where the expected marginal cost exceeds the observed price. Unit commitment constraints are believed to largely account for these results. Overall, the results of the analysis validate the regional transmission organization expansion polices of the Federal Energy Regulatory Commission.

Design of a multi-agent hydroeconomic model to simulate a complex human-water system: Early insights from the Jordan Water Project

NASA Astrophysics Data System (ADS)

Yoon, J.; Klassert, C. J. A.; Lachaut, T.; Selby, P. D.; Knox, S.; Gorelick, S.; Rajsekhar, D.; Tilmant, A.; Avisse, N.; Harou, J. J.; Gawel, E.; Klauer, B.; Mustafa, D.; Talozi, S.; Sigel, K.

2015-12-01

Our work focuses on development of a multi-agent, hydroeconomic model for purposes of water policy evaluation in Jordan. The model adopts a modular approach, integrating biophysical modules that simulate natural and engineered phenomena with human modules that represent behavior at multiple levels of decision making. The hydrologic modules are developed using spatially-distributed groundwater and surface water models, which are translated into compact simulators for efficient integration into the multi-agent model. For the groundwater model, we adopt a response matrix method approach in which a 3-dimensional MODFLOW model of a complex regional groundwater system is converted into a linear simulator of groundwater response by pre-processing drawdown results from several hundred numerical simulation runs. Surface water models for each major surface water basin in the country are developed in SWAT and similarly translated into simple rainfall-runoff functions for integration with the multi-agent model. The approach balances physically-based, spatially-explicit representation of hydrologic systems with the efficiency required for integration into a complex multi-agent model that is computationally amenable to robust scenario analysis. For the multi-agent model, we explicitly represent human agency at multiple levels of decision making, with agents representing riparian, management, supplier, and water user groups. The agents' decision making models incorporate both rule-based heuristics as well as economic optimization. The model is programmed in Python using Pynsim, a generalizable, open-source object-oriented code framework for modeling network-based water resource systems. The Jordan model is one of the first applications of Pynsim to a real-world water management case study. Preliminary results from a tanker market scenario run through year 2050 are presented in which several salient features of the water system are investigated: competition between urban and private farmer agents, the emergence of a private tanker market, disparities in economic wellbeing to different user groups caused by unique supply conditions, and response of the complex system to various policy interventions.

Identification of market trends with string and D2-brane maps

NASA Astrophysics Data System (ADS)

Bartoš, Erik; Pinčák, Richard

2017-08-01

The multidimensional string objects are introduced as a new alternative for an application of string models for time series forecasting in trading on financial markets. The objects are represented by open string with 2-endpoints and D2-brane, which are continuous enhancement of 1-endpoint open string model. We show how new object properties can change the statistics of the predictors, which makes them the candidates for modeling a wide range of time series systems. String angular momentum is proposed as another tool to analyze the stability of currency rates except the historical volatility. To show the reliability of our approach with application of string models for time series forecasting we present the results of real demo simulations for four currency exchange pairs.

A Marketing Perspective on Educational Games, Simulations and Workshops.

ERIC Educational Resources Information Center

Cryer, Patricia

1989-01-01

Examines the literature on marketing and uses the four elements of product, price, place, and promotion to elicit guidance for those who wish to market educational games, simulations, and workshops. Devising a marketing strategy centered on the customer is discussed, and the distinction between goods and services is described. (11 references)…

Can physical joint simulators be used to anticipate clinical wear problems of new joint replacement implants prior to market release?

PubMed

Medley, John B

2016-05-01

One of the most important mandates of physical joint simulators is to provide test results that allow the implant manufacturer to anticipate and perhaps avoid clinical wear problems with their new products. This is best done before market release. This study gives four steps to follow in conducting such wear simulator testing. Two major examples involving hip wear simulators are discussed in which attempts had been made to predict clinical wear performance prior to market release. The second one, involving the DePuy ASR implant systems, is chosen for more extensive treatment by making it an illustrative example to explore whether wear simulator testing can anticipate clinical wear problems. It is concluded that hip wear simulator testing did provide data in the academic literature that indicated some risk of clinical wear problems prior to market release of the ASR implant systems. This supports the idea that physical joint simulators have an important role in the pre-market testing of new joint replacement implants. © IMechE 2016.

Stylized facts from a threshold-based heterogeneous agent model

NASA Astrophysics Data System (ADS)

Cross, R.; Grinfeld, M.; Lamba, H.; Seaman, T.

2007-05-01

A class of heterogeneous agent models is investigated where investors switch trading position whenever their motivation to do so exceeds some critical threshold. These motivations can be psychological in nature or reflect behaviour suggested by the efficient market hypothesis (EMH). By introducing different propensities into a baseline model that displays EMH behaviour, one can attempt to isolate their effects upon the market dynamics. The simulation results indicate that the introduction of a herding propensity results in excess kurtosis and power-law decay consistent with those observed in actual return distributions, but not in significant long-term volatility correlations. Possible alternatives for introducing such long-term volatility correlations are then identified and discussed.

SIM Life: a new surgical simulation device using a human perfused cadaver.

PubMed

Faure, J P; Breque, C; Danion, J; Delpech, P O; Oriot, D; Richer, J P

2017-02-01

In primary and continuing medical education, simulation is becoming a mandatory technique. In surgery, simulation spreading is slowed down by the distance which exists between the devices currently available on the market and the reality, in particular anatomical, of an operating room. We propose a new model for surgical simulation with the use of cadavers in a circulation model mimicking pulse and artificial respiration available for both open and laparoscopic surgery. The model was a task trainer designed by four experts in our simulation laboratory combining plastic, electronic, and biologic material. The cost of supplies needed for the construction was evaluated. The model was used and tested over 24 months on 35 participants, of whom 20 were surveyed regarding the realism of the model. The model involved a cadaver, connected to a specific device that permits beating circulation and artificial respiration. The demonstration contributed to teaching small groups of up to four participants and was reproducible over 24 months of courses. Anatomic correlation, realism, and learning experience were highly rated by users CONCLUSION: This model for surgical simulation in both open and laparoscopic surgery was found to be realistic, available to assessed objectively performance in a pedagogic program.

Effect of External Economic-Field Cycle and Market Temperature on Stock-Price Hysteresis: Monte Carlo Simulation on the Ising Spin Model

NASA Astrophysics Data System (ADS)

Punya Jaroenjittichai, Atchara; Laosiritaworn, Yongyut

2017-09-01

In this work, the stock-price versus economic-field hysteresis was investigated. The Ising spin Hamiltonian was utilized as the level of ‘disagreement’ in describing investors’ behaviour. The Ising spin directions were referred to an investor’s intention to perform his action on trading his stock. The periodic economic variation was also considered via the external economic-field in the Ising model. The stochastic Monte Carlo simulation was performed on Ising spins, where the steady-state excess demand and supply as well as the stock-price were extracted via the magnetization. From the results, the economic-field parameters and market temperature were found to have significant effect on the dynamic magnetization and stock-price behaviour. Specifically, the hysteresis changes from asymmetric to symmetric loops with increasing market temperature and economic-field strength. However, the hysteresis changes from symmetric to asymmetric loops with increasing the economic-field frequency, when either temperature or economic-field strength is large enough, and returns to symmetric shape at very high frequencies. This suggests competitive effects among field and temperature factors on the hysteresis characteristic, implying multi-dimensional complicated non-trivial relationship among inputs-outputs. As is seen, the results reported (over extensive range) can be used as basis/guideline for further analysis/quantifying how economic-field and market-temperature affect the stock-price distribution on the course of economic cycle.

Pharmacodynamic analysis of eribulin safety in breast cancer patients using real-world post-marketing surveillance data.

PubMed

Kawamura, Takahisa; Kasai, Hidefumi; Fermanelli, Valentina; Takahashi, Toshiaki; Sakata, Yukinori; Matsuoka, Toshiyuki; Ishii, Mika; Tanigawara, Yusuke

2018-06-22

Post-marketing surveillance is useful to collect safety data in real-world clinical settings. In this study, we firstly applied the post-marketing real-world data on a mechanistic model analysis for neutropenic profiles of eribulin in patients with recurrent or metastatic breast cancer (RBC/MBC). Demographic and safety data were collected using an active surveillance method from eribulin-treated RBC/MBC patients. Changes in neutrophil counts over time were analyzed using a mechanistic pharmacodynamic model. Pathophysiological factors that may affect the severity of neutropenia were investigated and neutropenic patterns were simulated for different treatment schedules. Clinical and laboratory data were collected from 401 patients (5199 neutrophil count measurements) who had not received granulocyte colony stimulating factor and were eligible for pharmacodynamic analysis. The estimated mean parameters were: mean transit time = 104.5 h, neutrophil proliferation rate constant = 0.0377 h -1 , neutrophil elimination rate constant = 0.0295 h -1 , and linear coefficient of drug effect = 0.0413 mL/ng. Low serum albumin levels and low baseline neutrophil counts were associated with severe neutropenia. The probability of grade ≥3 neutropenia was predicted to be 69%, 27%, and 27% for patients on standard, biweekly, and triweekly treatment scenarios, respectively, based on virtual simulations using the developed pharmacodynamic model. In conclusion, this is the first application of post-marketing surveillance data to a model-based safety analysis. This analysis of safety data reflecting authentic clinical settings will provide useful information on the safe use and potential risk factors of eribulin. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Confidence and self-attribution bias in an artificial stock market.

PubMed

Bertella, Mario A; Pires, Felipe R; Rego, Henio H A; Silva, Jonathas N; Vodenska, Irena; Stanley, H Eugene

2017-01-01

Using an agent-based model we examine the dynamics of stock price fluctuations and their rates of return in an artificial financial market composed of fundamentalist and chartist agents with and without confidence. We find that chartist agents who are confident generate higher price and rate of return volatilities than those who are not. We also find that kurtosis and skewness are lower in our simulation study of agents who are not confident. We show that the stock price and confidence index-both generated by our model-are cointegrated and that stock price affects confidence index but confidence index does not affect stock price. We next compare the results of our model with the S&P 500 index and its respective stock market confidence index using cointegration and Granger tests. As in our model, we find that stock prices drive their respective confidence indices, but that the opposite relationship, i.e., the assumption that confidence indices drive stock prices, is not significant.

Research on Simulation Requirements and Business Architecture of Automated Demand Response in Power Sales Side Market Liberalization

NASA Astrophysics Data System (ADS)

Liu, Yiqun; Zhou, Pengcheng; Zeng, Ming; Chen, Songsong

2018-01-01

With the gradual reform of the electricity market, the power sale side liberalization has become the focus of attention as the key task of reform. The open power market provides a good environment for DR (Demand Response). It is of great significance to research the simulation requirements and business architecture of ADR (Automatic Demand Response) in power sale side market liberalization. Firstly, this paper analyzes the simulation requirements of ADR. Secondly, it analyzes the influence factors that the business development of ADR from five aspects after power sale side market liberalization. Finally, Based on ADR technology support system, the business architecture of ADR after power sale side market liberalization is constructed.

Design and analysis of electricity markets

NASA Astrophysics Data System (ADS)

Sioshansi, Ramteen Mehr

Restructured competitive electricity markets rely on designing market-based mechanisms which can efficiently coordinate the power system and minimize the exercise of market power. This dissertation is a series of essays which develop and analyze models of restructured electricity markets. Chapter 2 studies the incentive properties of a co-optimized market for energy and reserves that pays reserved generators their implied opportunity cost---which is the difference between their stated energy cost and the market-clearing price for energy. By analyzing the market as a competitive direct revelation mechanism we examine the properties of efficient equilibria and demonstrate that generators have incentives to shade their stated costs below actual costs. We further demonstrate that the expected energy payments of our mechanism is less than that in a disjoint market for energy only. Chapter 3 is an empirical validation of a supply function equilibrium (SFE) model. By comparing theoretically optimal supply functions and actual generation offers into the Texas spot balancing market, we show the SFE to fit the actual behavior of the largest generators in market. This not only serves to validate the model, but also demonstrates the extent to which firms exercise market power. Chapters 4 and 5 examine equity, incentive, and efficiency issues in the design of non-convex commitment auctions. We demonstrate that different near-optimal solutions to a central unit commitment problem which have similar-sized optimality gaps will generally yield vastly different energy prices and payoffs to individual generators. Although solving the mixed integer program to optimality will overcome such issues, we show that this relies on achieving optimality of the commitment---which may not be tractable for large-scale problems within the allotted timeframe. We then simulate and compare a competitive benchmark for a market with centralized and self commitment in order to bound the efficiency losses stemming from coordination losses (cost of anarchy) in a decentralized market.

Software-In-the-Loop based Modeling and Simulation of Unmanned Semi-submersible Vehicle for Performance Verification of Autonomous Navigation

NASA Astrophysics Data System (ADS)

Lee, Kwangkook; Jeong, Mijin; Kim, Dong Hun

2017-12-01

Since an unmanned semi-submersible is mainly used for the purpose of carrying out dangerous missions in the sea, it is possible to work in a region where it is difficult to access due to safety reasons. In this study, an USV hull design was determined using Myring hull profile, and reinforcement work was performed by designing and implementing inner stiffener member for 3D printing. In order to simulate a sea state 5.0 or more at sea, which is difficult to implement in practice, a regular and irregular wave equation was implemented in Matlab / Simulink. We performed modeling and simulation of semi - submersible simulation based on DMWorks considering the rolling motion in wave. To verify and improve unpredicted errors, we implemented a numeric and physical simulation model of the USV based on software-in-the-loop (SIL) method. This simulation allows shipbuilders to participate in new value-added markets such as engineering, procurement, construction, installation, commissioning, operation, and maintenance for the USV.

Evolutionary game analysis and regulatory strategies for online group-buying based on system dynamics

NASA Astrophysics Data System (ADS)

Jiang, Zhong-Zhong; He, Na; Qin, Xuwei; Ip, W. H.; Wu, C. H.; Yung, K. L.

2018-07-01

The emergence of online group-buying provides a new consumption pattern for consumers in e-commerce era. However, many consumers realize that their own interests sometimes can't be guaranteed in the group-buying market due to the lack of being regulated. This paper aims to develop effective regulation strategies for online group-buying market. To the best of our knowledge, most existing studies assume that three parties in online group-buying market, i.e. the retailer, the group-buying platform and the consumer, are perfectly rational. To better understand the decision process, in this paper, we incorporate the concept of bounded rationality into consideration. Firstly, a three-parties evolutionary game model is established to study each player's game strategy based on bounded rationality. Secondly, the game model is simulated as a whole by adopting system dynamics to analyze its stability. Finally, theoretical analysis and extensive computational experiments are conducted to obtain the managerial insights and regulation strategies for online group-buying market. Our results clearly demonstrate that a suitable bonus-penalty measure can promote the healthy development of online group-buying market.

Attention competition with advertisement

NASA Astrophysics Data System (ADS)

Cetin, Uzay; Bingol, Haluk O.

2014-09-01

In the new digital age, information is available in large quantities. Since information consumes primarily the attention of its recipients, the scarcity of attention is becoming the main limiting factor. In this study, we investigate the impact of advertisement pressure on a cultural market where consumers have a limited attention capacity. A model of competition for attention is developed and investigated analytically and by simulation. Advertisement is found to be much more effective when the attention capacity of agents is extremely scarce. We have observed that the market share of the advertised item improves if dummy items are introduced to the market while the strength of the advertisement is kept constant.

Attention competition with advertisement.

PubMed

Cetin, Uzay; Bingol, Haluk O

2014-09-01

In the new digital age, information is available in large quantities. Since information consumes primarily the attention of its recipients, the scarcity of attention is becoming the main limiting factor. In this study, we investigate the impact of advertisement pressure on a cultural market where consumers have a limited attention capacity. A model of competition for attention is developed and investigated analytically and by simulation. Advertisement is found to be much more effective when the attention capacity of agents is extremely scarce. We have observed that the market share of the advertised item improves if dummy items are introduced to the market while the strength of the advertisement is kept constant.

Agent-Based Model with Asymmetric Trading and Herding for Complex Financial Systems

PubMed Central

Chen, Jun-Jie; Zheng, Bo; Tan, Lei

2013-01-01

Background For complex financial systems, the negative and positive return-volatility correlations, i.e., the so-called leverage and anti-leverage effects, are particularly important for the understanding of the price dynamics. However, the microscopic origination of the leverage and anti-leverage effects is still not understood, and how to produce these effects in agent-based modeling remains open. On the other hand, in constructing microscopic models, it is a promising conception to determine model parameters from empirical data rather than from statistical fitting of the results. Methods To study the microscopic origination of the return-volatility correlation in financial systems, we take into account the individual and collective behaviors of investors in real markets, and construct an agent-based model. The agents are linked with each other and trade in groups, and particularly, two novel microscopic mechanisms, i.e., investors’ asymmetric trading and herding in bull and bear markets, are introduced. Further, we propose effective methods to determine the key parameters in our model from historical market data. Results With the model parameters determined for six representative stock-market indices in the world, respectively, we obtain the corresponding leverage or anti-leverage effect from the simulation, and the effect is in agreement with the empirical one on amplitude and duration. At the same time, our model produces other features of the real markets, such as the fat-tail distribution of returns and the long-term correlation of volatilities. Conclusions We reveal that for the leverage and anti-leverage effects, both the investors’ asymmetric trading and herding are essential generation mechanisms. Among the six markets, however, the investors’ trading is approximately symmetric for the five markets which exhibit the leverage effect, thus contributing very little. These two microscopic mechanisms and the methods for the determination of the key parameters can be applied to other complex systems with similar asymmetries. PMID:24278146

Agent-based model with asymmetric trading and herding for complex financial systems.

PubMed

Chen, Jun-Jie; Zheng, Bo; Tan, Lei

2013-01-01

For complex financial systems, the negative and positive return-volatility correlations, i.e., the so-called leverage and anti-leverage effects, are particularly important for the understanding of the price dynamics. However, the microscopic origination of the leverage and anti-leverage effects is still not understood, and how to produce these effects in agent-based modeling remains open. On the other hand, in constructing microscopic models, it is a promising conception to determine model parameters from empirical data rather than from statistical fitting of the results. To study the microscopic origination of the return-volatility correlation in financial systems, we take into account the individual and collective behaviors of investors in real markets, and construct an agent-based model. The agents are linked with each other and trade in groups, and particularly, two novel microscopic mechanisms, i.e., investors' asymmetric trading and herding in bull and bear markets, are introduced. Further, we propose effective methods to determine the key parameters in our model from historical market data. With the model parameters determined for six representative stock-market indices in the world, respectively, we obtain the corresponding leverage or anti-leverage effect from the simulation, and the effect is in agreement with the empirical one on amplitude and duration. At the same time, our model produces other features of the real markets, such as the fat-tail distribution of returns and the long-term correlation of volatilities. We reveal that for the leverage and anti-leverage effects, both the investors' asymmetric trading and herding are essential generation mechanisms. Among the six markets, however, the investors' trading is approximately symmetric for the five markets which exhibit the leverage effect, thus contributing very little. These two microscopic mechanisms and the methods for the determination of the key parameters can be applied to other complex systems with similar asymmetries.

Financial Symmetry and Moods in the Market

PubMed Central

Savona, Roberto; Soumare, Maxence; Andersen, Jørgen Vitting

2015-01-01

This paper studies how certain speculative transitions in financial markets can be ascribed to a symmetry break that happens in the collective decision making. Investors are assumed to be bounded rational, using a limited set of information including past price history and expectation on future dividends. Investment strategies are dynamically changed based on realized returns within a game theoretical scheme with Nash equilibria. In such a setting, markets behave as complex systems whose payoff reflect an intrinsic financial symmetry that guarantees equilibrium in price dynamics (fundamentalist state) until the symmetry is broken leading to bubble or anti-bubble scenarios (speculative state). We model such two-phase transition in a micro-to-macro scheme through a Ginzburg-Landau-based power expansion leading to a market temperature parameter which modulates the state transitions in the market. Via simulations we prove that transitions in the market price dynamics can be phenomenologically explained by the number of traders, the number of strategies and amount of information used by agents, all included in our market temperature parameter. PMID:25856392

Financial symmetry and moods in the market.

PubMed

Savona, Roberto; Soumare, Maxence; Andersen, Jørgen Vitting

2015-01-01

This paper studies how certain speculative transitions in financial markets can be ascribed to a symmetry break that happens in the collective decision making. Investors are assumed to be bounded rational, using a limited set of information including past price history and expectation on future dividends. Investment strategies are dynamically changed based on realized returns within a game theoretical scheme with Nash equilibria. In such a setting, markets behave as complex systems whose payoff reflect an intrinsic financial symmetry that guarantees equilibrium in price dynamics (fundamentalist state) until the symmetry is broken leading to bubble or anti-bubble scenarios (speculative state). We model such two-phase transition in a micro-to-macro scheme through a Ginzburg-Landau-based power expansion leading to a market temperature parameter which modulates the state transitions in the market. Via simulations we prove that transitions in the market price dynamics can be phenomenologically explained by the number of traders, the number of strategies and amount of information used by agents, all included in our market temperature parameter.

Preferred supplier contracts in post-patent prescription drug markets.

PubMed

Blankart, Carl Rudolf; Stargardt, Tom

2016-02-22

In recent years, the expiration of patents for large drug classes has increased the importance of post-patent drug markets. However, previous research has focused solely on patent drug markets. In this study, the authors evaluate the influence of preferred supplier contracts, the German approach to tendering, in post-patent drug markets using a hierarchical market share attraction model. The authors find that preferred supplier contracts are a powerful strategic instrument for generic manufacturers in a highly competitive environment. They quantify the effects of signing a preferred supplier contract and show that brand-name manufacturers are vulnerable to tendering. Therefore, brand-name manufacturers should readjust their strategies and consider including preferred supplier contracts in their marketing mix. In addition, the authors employ a simulation to demonstrate that a first-mover advantage might be gained from signing a preferred supplier contract. Furthermore, their results can be used as a blueprint for decision makers in the pharmaceutical industry to assess the market share effects of different contracting strategies regarding preferred supplier contracts.

Effects of global climate change on the US forest sector: response functions derived from a dynamic resource and market simulator.

Treesearch

Bruce A. McCarl; Darius M. Adams; Ralph J. Alig; Diana Burton; Chi-Chung. Chen

2000-01-01

A multiperiod, regional, mathematical programming economic model is used to evaluate the potential economic impacts of global climatic change on the US forest sector. A wide range of scenarios for the biological response of forests to climate change are developed, ranging from small to large changes in forest growth rates. These scenarios are simulated in the economic...

Hierarchical Engine for Large-scale Infrastructure Co-Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

2017-04-24

HELICS is designed to support very-large-scale (100,000+ federates) cosimulations with off-the-shelf power-system, communication, market, and end-use tools. Other key features include cross platform operating system support, the integration of both event driven (e.g., packetized communication) and time-series (e.g., power flow) simulations, and the ability to co-iterate among federates to ensure physical model convergence at each time step.

Timber product implications of a program of mechanical fuel treatments applied on public timberland in the Western United States

Treesearch

Barbour R. James.; Xiaoping Zhou; Jeffrey P. Prestemon

2008-01-01

This study reports the results from a 5 year simulation of forest thinning intended to reduce fire hazard on publicly managed lands in the western United States. A state simulation model of interrelated timber markets was used to evaluate the timber product outputs. Approximately 84 million acres (34 million hectares), or 66% of total timberland in the western United...

Successful technical trading agents using genetic programming.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Othling, Andrew S.; Kelly, John A.; Pryor, Richard J.

2004-10-01

Genetic programming (GP) has proved to be a highly versatile and useful tool for identifying relationships in data for which a more precise theoretical construct is unavailable. In this project, we use a GP search to develop trading strategies for agent based economic models. These strategies use stock prices and technical indicators, such as the moving average convergence/divergence and various exponentially weighted moving averages, to generate buy and sell signals. We analyze the effect of complexity constraints on the strategies as well as the relative performance of various indicators. We also present innovations in the classical genetic programming algorithm thatmore » appear to improve convergence for this problem. Technical strategies developed by our GP algorithm can be used to control the behavior of agents in economic simulation packages, such as ASPEN-D, adding variety to the current market fundamentals approach. The exploitation of arbitrage opportunities by technical analysts may help increase the efficiency of the simulated stock market, as it does in the real world. By improving the behavior of simulated stock markets, we can better estimate the effects of shocks to the economy due to terrorism or natural disasters.« less

Analysis of Foreign Exchange Interventions by Intervention Agent with an Artificial Market Approach

NASA Astrophysics Data System (ADS)

Matsui, Hiroki; Tojo, Satoshi

We propose a multi-agent system which learns intervention policies and evaluates the effect of interventions in an artificial foreign exchange market. Izumi et al. had presented a system called AGEDASI TOF to simulate artificial market, together with a support system for the government to decide foreign exchange policies. However, the system needed to fix the amount of governmental intervention prior to the simulation, and was not realistic. In addition, the interventions in the system did not affect supply and demand of currencies; thus we could not discuss the effect of intervention correctly. First, we improve the system so as to make much of the weights of influential factors. Thereafter, we introduce an intervention agent that has the role of the central bank to stabilize the market. We could show that the agent learned the effective intervention policies through the reinforcement learning, and that the exchange rate converged to a certain extent in the expected range. We could also estimate the amount of intervention, showing the efficacy of signaling. In this model, in order to investigate the aliasing of the perception of the intervention agent, we introduced a pseudo-agent who was supposed to be able to observe all the behaviors of dealer agents; with this super-agent, we discussed the adequate granularity for a market state description.

Reducing domestic heating demand: Managing the impact of behavior-changing feedback devices via marketing.

PubMed

Jensen, Thorben; Chappin, Émile J L

2017-07-15

Feedback devices can be used to inform households about their energy-consumption behavior. This may persuade them to practice energy conservation. The use of feedback devices can also-via word of mouth-spread among households and thereby support the spread of the incentivized behavior, e.g. energy-efficient heating behavior. This study investigates how to manage the impact of these environmental innovations via marketing. Marketing activities can support the diffusion of devices. This study aims to identify the most effective strategies of marketing feedback devices. We did this by adapting an agent-based model to simulate the roll-out of a novel feedback technology and heating behavior within households in a virtual city. The most promising marketing strategies were simulated and their impacts were analyzed. We found it particularly effective to lend out feedback devices to consumers, followed by leveraging the social influence of well-connected individuals, and giving away the first few feedback devices for free. Making households aware of the possibility of purchasing feedback devices was found to be least effective. However, making households aware proved to be most cost-efficient. This study shows that actively managing the roll-out of feedback devices can increase their impacts on energy-conservation both effectively and cost-efficiently. Copyright © 2017 Elsevier Ltd. All rights reserved.

Betting and Belief: Modeling the Impact of Prediction Markets on Public Attribution of Climate Change

NASA Astrophysics Data System (ADS)

Gilligan, J. M.; Nay, J. J.; van der Linden, M.

2016-12-01

Despite overwhelming scientific evidence and an almost complete consensus among scientists, a large fraction of the American public is not convinced that global warming is anthropogenic. This doubt correlates strongly with political, ideological, and cultural orientation. [1] It has been proposed that people who do not trust climate scientists tend to trust markets, so prediction markets might be able to influence their beliefs about the causes of climate change. [2] We present results from an agent-based simulation of a prediction market in which traders invest based on their beliefs about what drives global temperature change (here, either CO2 concentration or total solar irradiance (TSI), which is a popular hypothesis among many who doubt the dominant role of CO2). At each time step, traders use historical and observed temperatures and projected future forcings (CO2 or TSI) to update Bayesian posterior probability distributions for future temperatures, conditional on their belief about what drives climate change. Traders then bet on future temperatures by trading in climate futures. Trading proceeds by a continuous double auction. Traders are randomly assigned initial beliefs about climate change, and they have some probability of changing their beliefs to match those of the most successful traders in their social network. We simulate two alternate realities in which the global temperature is controlled either by CO2 or by TSI, with stochastic noise. In both cases traders' beliefs converge, with a large majority reaching agreement on the actual cause of climate change. This convergence is robust, but the speed with which consensus emerges depends on characteristics of the traders' psychology and the structure of the market. Our model can serve as a test-bed for studying how beliefs might evolve under different market structures and different modes of decision-making and belief-change. We will report progress on studying alternate models of belief-change. This work was partially supported by National Science Foundation grants EAR-1416964, EAR-1204685, and IIS-1526860. The model code is available at https://github.com/JohnNay/predMarket [1] A Leiserowitz, E Maibach, & C Roser-Renouf, Global Warming's Six Americas (Yale U., 2009). [2] MP Vandenbergh, KT Raimi, & JM Gilligan. UCLA Law Rev. 61, 1962 (2014).

Modeling of market segmentation for new IT product development

NASA Astrophysics Data System (ADS)

Nasiopoulos, Dimitrios K.; Sakas, Damianos P.; Vlachos, D. S.; Mavrogianni, Amanda

2015-02-01

Businesses from all Information Technology sectors use market segmentation[1] in their product development[2] and strategic planning[3]. Many studies have concluded that market segmentation is considered as the norm of modern marketing. With the rapid development of technology, customer needs are becoming increasingly diverse. These needs can no longer be satisfied by a mass marketing approach and follow one rule. IT Businesses can face with this diversity by pooling customers[4] with similar requirements and buying behavior and strength into segments. The result of the best choices about which segments are the most appropriate to serve can then be made, thus making the best of finite resources. Despite the attention which segmentation gathers and the resources that are invested in it, growing evidence suggests that businesses have problems operationalizing segmentation[5]. These problems take various forms. There may have been a rule that the segmentation process necessarily results in homogeneous groups of customers for whom appropriate marketing programs and procedures for dealing with them can be developed. Then the segmentation process, that a company follows, can fail. This increases concerns about what causes segmentation failure and how it might be overcome. To prevent the failure, we created a dynamic simulation model of market segmentation[6] based on the basic factors leading to this segmentation.

Bidding strategy for microgrid in day-ahead market based on hybrid stochastic/robust optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Guodong; Xu, Yan; Tomsovic, Kevin

In this paper, we propose an optimal bidding strategy in the day-ahead market of a microgrid consisting of intermittent distributed generation (DG), storage, dispatchable DG and price responsive loads. The microgrid coordinates the energy consumption or production of its components and trades electricity in both the day-ahead and real-time markets to minimize its operating cost as a single entity. The bidding problem is challenging due to a variety of uncertainties, including power output of intermittent DG, load variation, day-ahead and real-time market prices. A hybrid stochastic/robust optimization model is proposed to minimize the expected net cost, i.e., expected total costmore » of operation minus total benefit of demand. This formulation can be solved by mixed integer linear programming. The uncertain output of intermittent DG and day-ahead market price are modeled via scenarios based on forecast results, while a robust optimization is proposed to limit the unbalanced power in real-time market taking account of the uncertainty of real-time market price. Numerical simulations on a microgrid consisting of a wind turbine, a PV panel, a fuel cell, a micro-turbine, a diesel generator, a battery and a responsive load show the advantage of stochastic optimization in addition to robust optimization.« less

Bidding strategy for microgrid in day-ahead market based on hybrid stochastic/robust optimization

DOE PAGES

Liu, Guodong; Xu, Yan; Tomsovic, Kevin

2016-01-01

In this paper, we propose an optimal bidding strategy in the day-ahead market of a microgrid consisting of intermittent distributed generation (DG), storage, dispatchable DG and price responsive loads. The microgrid coordinates the energy consumption or production of its components and trades electricity in both the day-ahead and real-time markets to minimize its operating cost as a single entity. The bidding problem is challenging due to a variety of uncertainties, including power output of intermittent DG, load variation, day-ahead and real-time market prices. A hybrid stochastic/robust optimization model is proposed to minimize the expected net cost, i.e., expected total costmore » of operation minus total benefit of demand. This formulation can be solved by mixed integer linear programming. The uncertain output of intermittent DG and day-ahead market price are modeled via scenarios based on forecast results, while a robust optimization is proposed to limit the unbalanced power in real-time market taking account of the uncertainty of real-time market price. Numerical simulations on a microgrid consisting of a wind turbine, a PV panel, a fuel cell, a micro-turbine, a diesel generator, a battery and a responsive load show the advantage of stochastic optimization in addition to robust optimization.« less

Market Mechanism Design for Renewable Energy based on Risk Theory

NASA Astrophysics Data System (ADS)

Yang, Wu; Bo, Wang; Jichun, Liu; Wenjiao, Zai; Pingliang, Zeng; Haobo, Shi

2018-02-01

Generation trading between renewable energy and thermal power is an efficient market means for transforming supply structure of electric power into sustainable development pattern. But the trading is hampered by the output fluctuations of renewable energy and the cost differences between renewable energy and thermal power at present. In this paper, the external environmental cost (EEC) is defined and the EEC is introduced into the generation cost. At same time, the incentive functions of renewable energy and low-emission thermal power are designed, which are decreasing functions of EEC. On these bases, for the market risks caused by the random variability of EEC, the decision-making model of generation trading between renewable energy and thermal power is constructed according to the risk theory. The feasibility and effectiveness of the proposed model are verified by simulation results.

Development of U-Mart System with Plural Brands and Plural Markets

NASA Astrophysics Data System (ADS)

Akimoto, Yoshihito; Mori, Naoki; Ono, Isao; Nakajima, Yoshihiro; Kita, Hajime; Matsumoto, Keinosuke

In this paper, we first discuss the notion that artificial market systems should meet the requirements of fidelity, transparency, reproducibility, and traceability. Next, we introduce history of development of the artificial market system named U-Mart system that meet the requirements well, which have been developed by the U-Mart project. We have already developed the U-Mart system called “U-Mart system version 3.0” to solve problems of old U-Mart systems. In version 3.0 system, trading process is modularized and universal market system can be easily introduced.
However, U-Mart system version 3.0 only simulates the single brand futures market. The simulation of the plural brands and plural markets has been required by lot of users. In this paper, we proposed a novel U-Mart system called “U-Mart system version 4.0” to solve this problem of U-Mart system version 3.0. We improve the server system, machine agents and GUI in order to simulate plural brands and plural markets in U-Mart system version 4.0. The effectiveness of the proposed system is confirmed by statistical analysis of results of spot market simulation with random agents.

Simulating economic effects of disruptions in the telecommunications infrastructure.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cox, Roger Gary; Barton, Dianne Catherine; Reinert, Rhonda K.

2004-01-01

CommAspen is a new agent-based model for simulating the interdependent effects of market decisions and disruptions in the telecommunications infrastructure on other critical infrastructures in the U.S. economy such as banking and finance, and electric power. CommAspen extends and modifies the capabilities of Aspen-EE, an agent-based model previously developed by Sandia National Laboratories to analyze the interdependencies between the electric power system and other critical infrastructures. CommAspen has been tested on a series of scenarios in which the communications network has been disrupted, due to congestion and outages. Analysis of the scenario results indicates that communications networks simulated by themore » model behave as their counterparts do in the real world. Results also show that the model could be used to analyze the economic impact of communications congestion and outages.« less

Linking agent-based models and stochastic models of financial markets

PubMed Central

Feng, Ling; Li, Baowen; Podobnik, Boris; Preis, Tobias; Stanley, H. Eugene

2012-01-01

It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that “fat” tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting. PMID:22586086

Linking agent-based models and stochastic models of financial markets.

PubMed

Feng, Ling; Li, Baowen; Podobnik, Boris; Preis, Tobias; Stanley, H Eugene

2012-05-29

It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that "fat" tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting.

Analysis and Design of International Emission Trading Markets Applying System Dynamics Techniques

NASA Astrophysics Data System (ADS)

Hu, Bo; Pickl, Stefan

2010-11-01

The design and analysis of international emission trading markets is an important actual challenge. Time-discrete models are needed to understand and optimize these procedures. We give an introduction into this scientific area and present actual modeling approaches. Furthermore, we develop a model which is embedded in a holistic problem solution. Measures for energy efficiency are characterized. The economic time-discrete "cap-and-trade" mechanism is influenced by various underlying anticipatory effects. With a systematic dynamic approach the effects can be examined. First numerical results show that fair international emissions trading can only be conducted with the use of protective export duties. Furthermore a comparatively high price which evokes emission reduction inevitably has an inhibiting effect on economic growth according to our model. As it always has been expected it is not without difficulty to find a balance between economic growth and emission reduction. It can be anticipated using our System Dynamics model simulation that substantial changes must be taken place before international emissions trading markets can contribute to global GHG emissions mitigation.

Application of a forest-simulation model to assess the energy yield and ecological impact of forest utilization for energy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Doyle, T W; Shugart, H H; West, D C

1981-01-01

This study examines the utilization and management of natural forest lands to meet growing wood-energy demands. An application of a forest simulation model is described for assessing energy returns and long-term ecological impacts of wood-energy harvesting under four general silvicultural practices. Results indicate that moderate energy yields could be expected from mild cutting operations which would significantly effect neither the commercial timber market nor the composition, structure, or diversity of these forests. Forest models can provide an effective tool for determining optimal management strategies that maximize energy returns, minimize environmental detriment, and complement existing land-use plans.

Measuring the coupled risks: A copula-based CVaR model

NASA Astrophysics Data System (ADS)

He, Xubiao; Gong, Pu

2009-01-01

Integrated risk management for financial institutions requires an approach for aggregating risk types (such as market and credit) whose distributional shapes vary considerably. The financial institutions often ignore risks' coupling influence so as to underestimate the financial risks. We constructed a copula-based Conditional Value-at-Risk (CVaR) model for market and credit risks. This technique allows us to incorporate realistic marginal distributions that capture essential empirical features of these risks, such as skewness and fat-tails while allowing for a rich dependence structure. Finally, the numerical simulation method is used to implement the model. Our results indicate that the coupled risks for the listed company's stock maybe are undervalued if credit risk is ignored, especially for the listed company with bad credit quality.

Edgeworth expansions of stochastic trading time

NASA Astrophysics Data System (ADS)

Decamps, Marc; De Schepper, Ann

2010-08-01

Under most local and stochastic volatility models the underlying forward is assumed to be a positive function of a time-changed Brownian motion. It relates nicely the implied volatility smile to the so-called activity rate in the market. Following Young and DeWitt-Morette (1986) [8], we propose to apply the Duru-Kleinert process-cum-time transformation in path integral to formulate the transition density of the forward. The method leads to asymptotic expansions of the transition density around a Gaussian kernel corresponding to the average activity in the market conditional on the forward value. The approximation is numerically illustrated for pricing vanilla options under the CEV model and the popular normal SABR model. The asymptotics can also be used for Monte Carlo simulations or backward integration schemes.

Supporting the Development and Adoption of Automatic Lameness Detection Systems in Dairy Cattle: Effect of System Cost and Performance on Potential Market Shares.

PubMed

Van De Gucht, Tim; Van Weyenberg, Stephanie; Van Nuffel, Annelies; Lauwers, Ludwig; Vangeyte, Jürgen; Saeys, Wouter

2017-10-08

Most automatic lameness detection system prototypes have not yet been commercialized, and are hence not yet adopted in practice. Therefore, the objective of this study was to simulate the effect of detection performance (percentage missed lame cows and percentage false alarms) and system cost on the potential market share of three automatic lameness detection systems relative to visual detection: a system attached to the cow, a walkover system, and a camera system. Simulations were done using a utility model derived from survey responses obtained from dairy farmers in Flanders, Belgium. Overall, systems attached to the cow had the largest market potential, but were still not competitive with visual detection. Increasing the detection performance or lowering the system cost led to higher market shares for automatic systems at the expense of visual detection. The willingness to pay for extra performance was €2.57 per % less missed lame cows, €1.65 per % less false alerts, and €12.7 for lame leg indication, respectively. The presented results could be exploited by system designers to determine the effect of adjustments to the technology on a system's potential adoption rate.

Evidence from a Large Sample on the Effects of Group Size and Decision-Making Time on Performance in a Marketing Simulation Game

ERIC Educational Resources Information Center

Treen, Emily; Atanasova, Christina; Pitt, Leyland; Johnson, Michael

2016-01-01

Marketing instructors using simulation games as a way of inducing some realism into a marketing course are faced with many dilemmas. Two important quandaries are the optimal size of groups and how much of the students' time should ideally be devoted to the game. Using evidence from a very large sample of teams playing a simulation game, the study…

Can hydro-economic river basin models simulate water shadow prices under asymmetric access?

PubMed

Kuhn, A; Britz, W

2012-01-01

Hydro-economic river basin models (HERBM) based on mathematical programming are conventionally formulated as explicit 'aggregate optimization' problems with a single, aggregate objective function. Often unintended, this format implicitly assumes that decisions on water allocation are made via central planning or functioning markets such as to maximize social welfare. In the absence of perfect water markets, however, individually optimal decisions by water users will differ from the social optimum. Classical aggregate HERBMs cannot simulate that situation and thus might be unable to describe existing institutions governing access to water and might produce biased results for alternative ones. We propose a new solution format for HERBMs, based on the format of the mixed complementarity problem (MCP), where modified shadow price relations express spatial externalities resulting from asymmetric access to water use. This new problem format, as opposed to commonly used linear (LP) or non-linear programming (NLP) approaches, enables the simultaneous simulation of numerous 'independent optimization' decisions by multiple water users while maintaining physical interdependences based on water use and flow in the river basin. We show that the alternative problem format allows the formulation HERBMs that yield more realistic results when comparing different water management institutions.

A model for simulating adaptive, dynamic flows on networks: Application to petroleum infrastructure

DOE PAGES

Corbet, Thomas F.; Beyeler, Walt; Wilson, Michael L.; ...

2017-10-03

Simulation models can greatly improve decisions meant to control the consequences of disruptions to critical infrastructures. We describe a dynamic flow model on networks purposed to inform analyses by those concerned about consequences of disruptions to infrastructures and to help policy makers design robust mitigations. We conceptualize the adaptive responses of infrastructure networks to perturbations as market transactions and business decisions of operators. We approximate commodity flows in these networks by a diffusion equation, with nonlinearities introduced to model capacity limits. To illustrate the behavior and scalability of the model, we show its application first on two simple networks, thenmore » on petroleum infrastructure in the United States, where we analyze the effects of a hypothesized earthquake.« less

A model for simulating adaptive, dynamic flows on networks: Application to petroleum infrastructure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Corbet, Thomas F.; Beyeler, Walt; Wilson, Michael L.

Simulation models can greatly improve decisions meant to control the consequences of disruptions to critical infrastructures. We describe a dynamic flow model on networks purposed to inform analyses by those concerned about consequences of disruptions to infrastructures and to help policy makers design robust mitigations. We conceptualize the adaptive responses of infrastructure networks to perturbations as market transactions and business decisions of operators. We approximate commodity flows in these networks by a diffusion equation, with nonlinearities introduced to model capacity limits. To illustrate the behavior and scalability of the model, we show its application first on two simple networks, thenmore » on petroleum infrastructure in the United States, where we analyze the effects of a hypothesized earthquake.« less

Applications of statistical and atomic physics to the spectral line broadening and stock markets

NASA Astrophysics Data System (ADS)

Volodko, Dmitriy

The purpose of this investigation is the application of time correlation function methodology on the theoretical research of the shift of hydrogen and hydrogen-like spectral lines due to electrons and ions interaction with the spectral line emitters-dipole ionic-electronic shift (DIES) and the describing a behavior of stock-market in terms of a simple physical model simulation which obeys Levy statistical distribution---the same as that of the real stock-market index. Using Generalized Theory of Stark broadening of electrons in plasma we discovered a new source of the shift of hydrogen and hydrogen-like spectral lines that we called a dipole ionic-electronic shift (DIES). This shift results from the indirect coupling of electron and ion microfields in plasmas which is facilitated by the radiating atom/ion. We have shown that the DIES, unlike all previously known shifts, is highly nonlinear and has a different sign for different ranges of plasma parameters. The most favorable conditions for observing the DIES correspond to plasmas of high densities, but of relatively low temperature. For the Balmer-alpha line of hydrogen with the most favorable observational conditions Ne > 1018 cm-3, T < 2 eV, the DIES has been already confirmed experimentally. Based on the study of the time correlations and of the probability distribution of fluctuations in the stock market, we developed a relatively simple physical model, which simulates the Dow Jones Industrials index and makes short-term (a couple of days) predictions of its trend.

Simulation of trading strategies in the electricity market

NASA Astrophysics Data System (ADS)

Charkiewicz, Kamil; Nowak, Robert

2011-10-01

The main objective of the energy market existence is reduction of the total cost of production, transport and distribution of energy, and so the prices paid by terminal consumers. Energy market contains few markets that are varying on operational rules, the important segments: the Futures Contract Market and Next Day Market are analyzed in presented approach. The computer system was developed to simulate the Polish Energy Market. This system use the multi-agent approach, where each agent is the separate shared library with defined interface. The software was used to compare strategies for players in energy market, where the strategies uses auto-regression, k-nearest neighbours, neural network and mixed algorithm, to predict the next price.

Atmospheric Modeling And Sensor Simulation (AMASS) study

NASA Technical Reports Server (NTRS)

Parker, K. G.

1985-01-01

A 4800 band synchronous communications link was established between the Perkin-Elmer (P-E) 3250 Atmospheric Modeling and Sensor Simulation (AMASS) system and the Cyber 205 located at the Goddard Space Flight Center. An extension study of off-the-shelf array processors offering standard interface to the Perkin-Elmer was conducted to determine which would meet computational requirements of the division. A Floating Point Systems AP-120B was borrowed from another Marshall Space Flight Center laboratory for evaluation. It was determined that available array processors did not offer significantly more capabilities than the borrowed unit, although at least three other vendors indicated that standard Perkin-Elmer interfaces would be marketed in the future. Therefore, the recommendation was made to continue to utilize the 120B ad to keep monitoring the AP market. Hardware necessary to support requirements of the ASD as well as to enhance system performance was specified and procured. Filters were implemented on the Harris/McIDAS system including two-dimensional lowpass, gradient, Laplacian, and bicubic interpolation routines.

Modelling the perennial energy crop market: the role of spatial diffusion

PubMed Central

Alexander, Peter; Moran, Dominic; Rounsevell, Mark D. A.; Smith, Pete

2013-01-01

Biomass produced from energy crops, such as Miscanthus and short rotation coppice is expected to contribute to renewable energy targets, but the slower than anticipated development of the UK market implies the need for greater understanding of the factors that govern adoption. Here, we apply an agent-based model of the UK perennial energy crop market, including the contingent interaction of supply and demand, to understand the spatial and temporal dynamics of energy crop adoption. Results indicate that perennial energy crop supply will be between six and nine times lower than previously published, because of time lags in adoption arising from a spatial diffusion process. The model simulates time lags of at least 20 years, which is supported empirically by the analogue of oilseed rape adoption in the UK from the 1970s. This implies the need to account for time lags arising from spatial diffusion in evaluating land-use change, climate change (mitigation or adaptation) or the adoption of novel technologies. PMID:24026474

Confidence and self-attribution bias in an artificial stock market

PubMed Central

Bertella, Mario A.; Pires, Felipe R.; Rego, Henio H. A.; Vodenska, Irena; Stanley, H. Eugene

2017-01-01

Using an agent-based model we examine the dynamics of stock price fluctuations and their rates of return in an artificial financial market composed of fundamentalist and chartist agents with and without confidence. We find that chartist agents who are confident generate higher price and rate of return volatilities than those who are not. We also find that kurtosis and skewness are lower in our simulation study of agents who are not confident. We show that the stock price and confidence index—both generated by our model—are cointegrated and that stock price affects confidence index but confidence index does not affect stock price. We next compare the results of our model with the S&P 500 index and its respective stock market confidence index using cointegration and Granger tests. As in our model, we find that stock prices drive their respective confidence indices, but that the opposite relationship, i.e., the assumption that confidence indices drive stock prices, is not significant. PMID:28231255

Stochastic cellular automata model for stock market dynamics

NASA Astrophysics Data System (ADS)

Bartolozzi, M.; Thomas, A. W.

2004-04-01

In the present work we introduce a stochastic cellular automata model in order to simulate the dynamics of the stock market. A direct percolation method is used to create a hierarchy of clusters of active traders on a two-dimensional grid. Active traders are characterized by the decision to buy, σi (t)=+1 , or sell, σi (t)=-1 , a stock at a certain discrete time step. The remaining cells are inactive, σi (t)=0 . The trading dynamics is then determined by the stochastic interaction between traders belonging to the same cluster. Extreme, intermittent events, such as crashes or bubbles, are triggered by a phase transition in the state of the bigger clusters present on the grid, where almost all the active traders come to share the same spin orientation. Most of the stylized aspects of the financial market time series, including multifractal proprieties, are reproduced by the model. A direct comparison is made with the daily closures of the S&P500 index.

Modelling the perennial energy crop market: the role of spatial diffusion.

PubMed

Alexander, Peter; Moran, Dominic; Rounsevell, Mark D A; Smith, Pete

2013-11-06

Biomass produced from energy crops, such as Miscanthus and short rotation coppice is expected to contribute to renewable energy targets, but the slower than anticipated development of the UK market implies the need for greater understanding of the factors that govern adoption. Here, we apply an agent-based model of the UK perennial energy crop market, including the contingent interaction of supply and demand, to understand the spatial and temporal dynamics of energy crop adoption. Results indicate that perennial energy crop supply will be between six and nine times lower than previously published, because of time lags in adoption arising from a spatial diffusion process. The model simulates time lags of at least 20 years, which is supported empirically by the analogue of oilseed rape adoption in the UK from the 1970s. This implies the need to account for time lags arising from spatial diffusion in evaluating land-use change, climate change (mitigation or adaptation) or the adoption of novel technologies.

Agent-based simulation of a financial market

NASA Astrophysics Data System (ADS)

Raberto, Marco; Cincotti, Silvano; Focardi, Sergio M.; Marchesi, Michele

2001-10-01

This paper introduces an agent-based artificial financial market in which heterogeneous agents trade one single asset through a realistic trading mechanism for price formation. Agents are initially endowed with a finite amount of cash and a given finite portfolio of assets. There is no money-creation process; the total available cash is conserved in time. In each period, agents make random buy and sell decisions that are constrained by available resources, subject to clustering, and dependent on the volatility of previous periods. The model proposed herein is able to reproduce the leptokurtic shape of the probability density of log price returns and the clustering of volatility. Implemented using extreme programming and object-oriented technology, the simulator is a flexible computational experimental facility that can find applications in both academic and industrial research projects.

Ensuring the Reliable Operation of the Power Grid: State-Based and Distributed Approaches to Scheduling Energy and Contingency Reserves

NASA Astrophysics Data System (ADS)

Prada, Jose Fernando

Keeping a contingency reserve in power systems is necessary to preserve the security of real-time operations. This work studies two different approaches to the optimal allocation of energy and reserves in the day-ahead generation scheduling process. Part I presents a stochastic security-constrained unit commitment model to co-optimize energy and the locational reserves required to respond to a set of uncertain generation contingencies, using a novel state-based formulation. The model is applied in an offer-based electricity market to allocate contingency reserves throughout the power grid, in order to comply with the N-1 security criterion under transmission congestion. The objective is to minimize expected dispatch and reserve costs, together with post contingency corrective redispatch costs, modeling the probability of generation failure and associated post contingency states. The characteristics of the scheduling problem are exploited to formulate a computationally efficient method, consistent with established operational practices. We simulated the distribution of locational contingency reserves on the IEEE RTS96 system and compared the results with the conventional deterministic method. We found that assigning locational spinning reserves can guarantee an N-1 secure dispatch accounting for transmission congestion at a reasonable extra cost. The simulations also showed little value of allocating downward reserves but sizable operating savings from co-optimizing locational nonspinning reserves. Overall, the results indicate the computational tractability of the proposed method. Part II presents a distributed generation scheduling model to optimally allocate energy and spinning reserves among competing generators in a day-ahead market. The model is based on the coordination between individual generators and a market entity. The proposed method uses forecasting, augmented pricing and locational signals to induce efficient commitment of generators based on firm posted prices. It is price-based but does not rely on multiple iterations, minimizes information exchange and simplifies the market clearing process. Simulations of the distributed method performed on a six-bus test system showed that, using an appropriate set of prices, it is possible to emulate the results of a conventional centralized solution, without need of providing make-whole payments to generators. Likewise, they showed that the distributed method can accommodate transactions with different products and complex security constraints.

Transition from coherence to bistability in a model of financial markets

NASA Astrophysics Data System (ADS)

D'Hulst, R.; Rodgers, G. J.

2001-04-01

We present a model describing the competition between information transmission and decision making in financial markets. The solution of this simple model is recalled, and possible variations discussed. It is shown numerically that despite its simplicity, it can mimic a size effect comparable to a crash localized in time. Two extensions of this model are presented that allow to simulate the demand process. One of these extensions has a coherent stable equilibrium and is self-organized, while the other has a bistable equilibrium, with a spontaneous segregation of the population of agents. A new model is introduced to generate a transition between those two equilibriums. We show that the coherent state is dominant up to an equal mixing of the two extensions. We focus our attention on the microscopic structure of the investment rate, which is the main parameter of the original model. A constant investment rate seems to be a very good approximation.

Computable general equilibrium model fiscal year 2013 capability development report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Edwards, Brian Keith; Rivera, Michael Kelly; Boero, Riccardo

This report documents progress made on continued developments of the National Infrastructure Simulation and Analysis Center (NISAC) Computable General Equilibrium Model (NCGEM), developed in fiscal year 2012. In fiscal year 2013, NISAC the treatment of the labor market and tests performed with the model to examine the properties of the solutions computed by the model. To examine these, developers conducted a series of 20 simulations for 20 U.S. States. Each of these simulations compared an economic baseline simulation with an alternative simulation that assumed a 20-percent reduction in overall factor productivity in the manufacturing industries of each State. Differences inmore » the simulation results between the baseline and alternative simulations capture the economic impact of the reduction in factor productivity. While not every State is affected in precisely the same way, the reduction in manufacturing industry productivity negatively affects the manufacturing industries in each State to an extent proportional to the reduction in overall factor productivity. Moreover, overall economic activity decreases when manufacturing sector productivity is reduced. Developers ran two additional simulations: (1) a version of the model for the State of Michigan, with manufacturing divided into two sub-industries (automobile and other vehicle manufacturing as one sub-industry and the rest of manufacturing as the other subindustry); and (2) a version of the model for the United States, divided into 30 industries. NISAC conducted these simulations to illustrate the flexibility of industry definitions in NCGEM and to examine the simulation properties of in more detail.« less

Assessing the comparative effectiveness of newly marketed medications: methodological challenges and implications for drug development.

PubMed

Schneeweiss, S; Gagne, J J; Glynn, R J; Ruhl, M; Rassen, J A

2011-12-01

Comparative-effectiveness research (CER) aims to produce actionable evidence regarding the effectiveness and safety of medical products and interventions as they are used outside of controlled research settings. Although CER evidence regarding medications is particularly needed shortly after market approval, key methodological challenges include (i) potential bias due to channeling of patients to the newly marketed medication because of various patient-, physician-, and system-related factors; (ii) rapid changes in the characteristics of the user population during the early phase of marketing; and (iii) lack of timely data and the often small number of users in the first few months of marketing. We propose a mix of approaches to generate comparative-effectiveness data in the early marketing period, including sequential cohort monitoring with secondary health-care data and propensity score (PS) balancing, as well as extended follow-up of phase III and phase IV trials, indirect comparisons of placebo-controlled trials, and modeling and simulation of virtual trials.

Climate Change and Future U.S. Electricity Infrastructure: the Nexus between Water Availability, Land Suitability, and Low-Carbon Technologies

NASA Astrophysics Data System (ADS)

Rice, J.; Halter, T.; Hejazi, M. I.; Jensen, E.; Liu, L.; Olson, J.; Patel, P.; Vernon, C. R.; Voisin, N.; Zuljevic, N.

2014-12-01

Integrated assessment models project the future electricity generation mix under different policy, technology, and socioeconomic scenarios, but they do not directly address site-specific factors such as interconnection costs, population density, land use restrictions, air quality, NIMBY concerns, or water availability that might affect the feasibility of achieving the technology mix. Moreover, since these factors can change over time due to climate, policy, socioeconomics, and so on, it is important to examine the dynamic feasibility of integrated assessment scenarios "on the ground." This paper explores insights from coupling an integrated assessment model (GCAM-USA) with a geospatial power plant siting model (the Capacity Expansion Regional Feasibility model, CERF) within a larger multi-model framework that includes regional climate, hydrologic, and water management modeling. GCAM-USA is a dynamic-recursive market equilibrium model simulating the impact of carbon policies on global and national markets for energy commodities and other goods; one of its outputs is the electricity generation mix and expansion at the state-level. It also simulates water demands from all sectors that are downscaled as input to the water management modeling. CERF simulates siting decisions by dynamically representing suitable areas for different generation technologies with geospatial analyses (informed by technology-specific siting criteria, such as required mean streamflow per the Clean Water Act), and then choosing siting locations to minimize interconnection costs (to electric transmission and gas pipelines). CERF results are compared across three scenarios simulated by GCAM-USA: 1) a non-mitigation scenario (RCP8.5) in which conventional fossil-fueled technologies prevail, 2) a mitigation scenario (RCP4.5) in which the carbon price causes a shift toward nuclear, carbon capture and sequestration (CCS), and renewables, and 3) a repeat of scenario (2) in which CCS technologies are made unavailable—resulting in a large increase in the nuclear fraction of the mix.

Medigap premiums and Medicare HMO enrollment.

PubMed

McLaughlin, Catherine G; Chernew, Michael; Taylor, Erin Fries

2002-12-01

Markets for Medicare HMOs (health maintenance organizations) and supplemental Medicare coverage are often treated separately in existing literature. Yet because managed care plans and Medigap plans both cover services not covered by basic Medicare, these markets are clearly interrelated. We examine the extent to which Medigap premiums affect the likelihood of the elderly joining managed care plans. The analysis is based on a sample of Medicare beneficiaries drawn from the 1996-1997 Community Tracking Study (CTS) Household Survey by the Center for Studying Health System Change. Respondents span 56 different CTS sites from 30 different states. Measures of premiums for privately-purchased Medigap policies were collected from a survey of large insurers serving this market. Data for individual, market, and HMO characteristics were collected from the CTS, InterStudy, and HCFA (Health Care Financing Administration). Our analysis uses a reduced-form logit model to estimate the probability of Medicare HMO participation as a function of Medigap premiums controlling for other market- and individual-level characteristics. The logit coefficients were then used to simulate changes in Medicare participation in response to changes in Medigap premiums. We found that Medigap premiums vary considerably among the geographic markets included in our sample. Measures of premiums from different insurers and for different types of Medigap policies were generally highly correlated across markets. Our models consistently indicate a strong positive relationship between Medigap premiums and HMO participation. This result is robust across several specifications. Simulations suggest that a one standard deviation increase in Medigap premiums would increase HMO participation by more than 8 percentage points. This research provides strong evidence that Medigap premiums have a significant effect on seniors' participation in Medicare HMOs. Policy initiatives aimed at lowering Medigap premiums will likely discourage enrollment in Medicare HMOs, holding other factors constant. Although the Medigap premiums are just one factor affecting the future penetration rate of Medicare HMOs, they are an important driver of HMO enrollment and should be considered carefully when creating policy related to seniors' supplemental coverage. Similarly, our results imply that reforms to the Medicare HMO market would influence the demand for Medigap policies.

Medigap Premiums and Medicare HMO Enrollment

PubMed Central

McLaughlin, Catherine G; Chernew, Michael; Taylor, Erin Fries

2002-01-01

Objective Markets for Medicare HMOs (health maintenance organizations) and supplemental Medicare coverage are often treated separately in existing literature. Yet because managed care plans and Medigap plans both cover services not covered by basic Medicare, these markets are clearly interrelated. We examine the extent to which Medigap premiums affect the likelihood of the elderly joining managed care plans. Data Sources The analysis is based on a sample of Medicare beneficiaries drawn from the 1996–1997 Community Tracking Study (CTS) Household Survey by the Center for Studying Health System Change. Respondents span 56 different CTS sites from 30 different states. Measures of premiums for privately-purchased Medigap policies were collected from a survey of large insurers serving this market. Data for individual, market, and HMO characteristics were collected from the CTS, InterStudy, and HCFA (Health Care Financing Administration). Study Design Our analysis uses a reduced-form logit model to estimate the probability of Medicare HMO participation as a function of Medigap premiums controlling for other market- and individual-level characteristics. The logit coefficients were then used to simulate changes in Medicare participation in response to changes in Medigap premiums. Principal Findings We found that Medigap premiums vary considerably among the geographic markets included in our sample. Measures of premiums from different insurers and for different types of Medigap policies were generally highly correlated across markets. Our models consistently indicate a strong positive relationship between Medigap premiums and HMO participation. This result is robust across several specifications. Simulations suggest that a one standard deviation increase in Medigap premiums would increase HMO participation by more than 8 percentage points. Conclusions This research provides strong evidence that Medigap premiums have a significant effect on seniors' participation in Medicare HMOs. Policy initiatives aimed at lowering Medigap premiums will likely discourage enrollment in Medicare HMOs, holding other factors constant. Although the Medigap premiums are just one factor affecting the future penetration rate of Medicare HMOs, they are an important driver of HMO enrollment and should be considered carefully when creating policy related to seniors' supplemental coverage. Similarly, our results imply that reforms to the Medicare HMO market would influence the demand for Medigap policies. PMID:12546281

Market-Based Coordination of Thermostatically Controlled Loads—Part I: A Mechanism Design Formulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Sen; Zhang, Wei; Lian, Jianming

This paper focuses on the coordination of a population of Thermostatically Controlled Loads (TCLs) with unknown parameters to achieve group objectives. The problem involves designing the bidding and market clearing strategy to motivate self-interested users to realize efficient energy allocation subject to a peak power constraint. Using the mechanism design approach, we propose a market-based coordination framework, which can effectively incorporate heterogeneous load dynamics, systematically deal with user preferences, account for the unknown load model parameters, and enable the real-world implementation with limited communication resources. This paper is divided into two parts. Part I presents a mathematical formulation of themore » problem and develops a coordination framework using the mechanism design approach. Part II presents a learning scheme to account for the unknown load model parameters, and evaluates the proposed framework through realistic simulations.« less

Essays on pricing dynamics, price dispersion, and nested logit modelling

NASA Astrophysics Data System (ADS)

Verlinda, Jeremy Alan

The body of this dissertation comprises three standalone essays, presented in three respective chapters. Chapter One explores the possibility that local market power contributes to the asymmetric relationship observed between wholesale costs and retail prices in gasoline markets. I exploit an original data set of weekly gas station prices in Southern California from September 2002 to May 2003, and take advantage of highly detailed station and local market-level characteristics to determine the extent to which spatial differentiation influences price-response asymmetry. I find that brand identity, proximity to rival stations, bundling and advertising, operation type, and local market features and demographics each influence a station's predicted asymmetric relationship between prices and wholesale costs. Chapter Two extends the existing literature on the effect of market structure on price dispersion in airline fares by modeling the effect at the disaggregate ticket level. Whereas past studies rely on aggregate measures of price dispersion such as the Gini coefficient or the standard deviation of fares, this paper estimates the entire empirical distribution of airline fares and documents how the shape of the distribution is determined by market structure. Specifically, I find that monopoly markets favor a wider distribution of fares with more mass in the tails while duopoly and competitive markets exhibit a tighter fare distribution. These findings indicate that the dispersion of airline fares may result from the efforts of airlines to practice second-degree price discrimination. Chapter Three adopts a Bayesian approach to the problem of tree structure specification in nested logit modelling, which requires a heavy computational burden in calculating marginal likelihoods. I compare two different techniques for estimating marginal likelihoods: (1) the Laplace approximation, and (2) reversible jump MCMC. I apply the techniques to both a simulated and a travel mode choice data set, and find that model selection is invariant to prior specification, while model derivatives like willingness-to-pay are notably sensitive to model choice. I also find that the Laplace approximation is remarkably accurate in spite of the potential for nested logit models to have irregular likelihood surfaces.

Capacity withholding in wholesale electricity markets: The experience in England and Wales

NASA Astrophysics Data System (ADS)

Quinn, James Arnold

This thesis examines the incentives wholesale electricity generators face to withhold generating capacity from centralized electricity spot markets. The first chapter includes a brief history of electricity industry regulation in England and Wales and in the United States, including a description of key institutional features of England and Wales' restructured electricity market. The first chapter also includes a review of the literature on both bid price manipulation and capacity bid manipulation in centralized electricity markets. The second chapter details a theoretical model of wholesale generator behavior in a single price electricity market. A duopoly model is specified under the assumption that demand is non-stochastic. This model assumes that duopoly generators offer to sell electricity at their marginal cost, but can withhold a continuous segment of their capacity from the market. The Nash equilibrium withholding strategy of this model involves each duopoly generator withholding so that it produces the Cournot equilibrium output. A monopoly model along the lines of the duopoly model is specified and simulated under the assumption that demand is stochastic. The optimal strategy depends on the degree of demand uncertainty. When there is a moderate degree of demand uncertainty, the optimal withholding strategy involves production inefficiencies. When there is a high degree of demand uncertainty, the optimal monopoly quantity is greater than the optimal output level when demand is non-stochastic. The third chapter contains an empirical examination of the behavior of generators in the wholesale electricity market in England and Wales in the early 1990's. The wholesale market in England and Wales is analyzed because the industry structure in the early 1990's created a natural experiment, which is described in this chapter, whereby one of the two dominant generators had no incentive to behave non-competitively. This chapter develops a classification methodology consistent with the equilibrium identified in the second chapter. The availability of generating units owned by the two dominant generators is analyzed based on this classification system. This analysis includes the use of sample statistics as well as estimates from a dynamic random effects probit model. The analysis suggests a minimal degree of capacity withholding.

Learner Satisfaction in Marketing Simulation Games: Antecedents and Influencers

ERIC Educational Resources Information Center

Caruana, Albert; La Rocca, Antonella; Snehota, Ivan

2016-01-01

Simulation games have become widespread in business courses, yet the understanding of their learning effects remains limited. The effectiveness of using simulation in marketing classes is not uniform, and not all students welcome it to the same extent. Drawing on a survey among 173 students engaged in a simulation game as part of a course in a…

Simulation of an Asynchronous Machine by using a Pseudo Bond Graph

NASA Astrophysics Data System (ADS)

Romero, Gregorio; Felez, Jesus; Maroto, Joaquin; Martinez, M. Luisa

2008-11-01

For engineers, computer simulation, is a basic tool since it enables them to understand how systems work without actually needing to see them. They can learn how they work in different circumstances and optimize their design with considerably less cost in terms of time and money than if they had to carry out tests on a physical system. However, if computer simulation is to be reliable it is essential for the simulation model to be validated. There is a wide range of commercial brands on the market offering products for electrical domain simulation (SPICE, LabVIEW PSCAD,Dymola, Simulink, Simplorer,...). These are powerful tools, but require the engineer to have a perfect knowledge of the electrical field. This paper shows an alternative methodology to can simulate an asynchronous machine using the multidomain Bond Graph technique and apply it in any program that permit the simulation of models based in this technique; no extraordinary knowledge of this technique and electric field are required to understand the process .

Three essays on agricultural price volatility and the linkages between agricultural and energy markets

NASA Astrophysics Data System (ADS)

Wu, Feng

This dissertation contains three essays. In the first essay I use a volatility spillover model to find evidence of significant spillovers from crude oil prices to corn cash and futures prices, and that these spillover effects are time-varying. Results reveal that corn markets have become much more connected to crude oil markets after the introduction of the Energy Policy Act of 2005. Furthermore, crude oil prices transmit positive volatility spillovers into corn prices and movements in corn prices become more energy-driven as the ethanol gasoline consumption ratio increases. Based on this strong volatility link between crude oil and corn prices, a new cross hedging strategy for managing corn price risk using oil futures is examined and its performance studied. Results show that this cross hedging strategy provides only slightly better hedging performance compared to traditional hedging in corn futures markets alone. The implication is that hedging corn price risk in corn futures markets alone can still provide relatively satisfactory performance in the biofuel era. The second essay studies the spillover effect of biofuel policy on participation in the Conservation Reserve Program. Landowners' participation decisions are modeled using a real options framework. A novel aspect of the model is that it captures the structural change in agriculture caused by rising biofuel production. The resulting model is used to simulate the spillover effect under various conditions. In particular, I simulate how increased growth in agricultural returns, persistence of the biofuel production boom, and the volatility surrounding agricultural returns, affect conservation program participation decisions. Policy implications of these results are also discussed. The third essay proposes a methodology to construct a risk-adjusted implied volatility measure that removes the forecasting bias of the model-free implied volatility measure. The risk adjustment is based on a closed-form relationship between the expectation of future volatility and the model-free implied volatility assuming a jump-diffusion model. I use a GMM estimation framework to identify the key model parameters needed to apply the model. An empirical application to corn futures implied volatility is used to illustrate the methodology and demonstrate differences between my approach and the model-free implied volatility using observed corn option prices. I compare the risk-adjusted forecast with the unadjusted forecast as well as other alternatives; and results suggest that the risk-adjusted volatility is unbiased, informationally more efficient, and has superior predictive power over the alternatives considered.

Optimal strategies for electric energy contract decision making

NASA Astrophysics Data System (ADS)

Song, Haili

2000-10-01

The power industry restructuring in various countries in recent years has created an environment where trading of electric energy is conducted in a market environment. In such an environment, electric power companies compete for the market share through spot and bilateral markets. Being profit driven, electric power companies need to make decisions on spot market bidding, contract evaluation, and risk management. New methods and software tools are required to meet these upcoming needs. In this research, bidding strategy and contract pricing are studied from a market participant's viewpoint; new methods are developed to guide a market participant in spot and bilateral market operation. A supplier's spot market bidding decision is studied. Stochastic optimization is formulated to calculate a supplier's optimal bids in a single time period. This decision making problem is also formulated as a Markov Decision Process. All the competitors are represented by their bidding parameters with corresponding probabilities. A systematic method is developed to calculate transition probabilities and rewards. The optimal strategy is calculated to maximize the expected reward over a planning horizon. Besides the spot market, a power producer can also trade in the bilateral markets. Bidding strategies in a bilateral market are studied with game theory techniques. Necessary and sufficient conditions of Nash Equilibrium (NE) bidding strategy are derived based on the generators' cost and the loads' willingness to pay. The study shows that in any NE, market efficiency is achieved. Furthermore, all Nash equilibria are revenue equivalent for the generators. The pricing of "Flexible" contracts, which allow delivery flexibility over a period of time with a fixed total amount of electricity to be delivered, is analyzed based on the no-arbitrage pricing principle. The proposed algorithm calculates the price based on the optimality condition of the stochastic optimization formulation. Simulation examples illustrate the tradeoffs between prices and scheduling flexibility. Spot bidding and contract pricing are not independent decision processes. The interaction between spot bidding and contract evaluation is demonstrated with game theory equilibrium model and market simulation results. It leads to the conclusion that a market participant's contract decision making needs to be further investigated as an integrated optimization formulation.

Statistical mechanics of human resource allocation

NASA Astrophysics Data System (ADS)

Inoue, Jun-Ichi; Chen, He

2014-03-01

We provide a mathematical platform to investigate the network topology of agents, say, university graduates who are looking for their positions in labor markets. The basic model is described by the so-called Potts spin glass which is well-known in the research field of statistical physics. In the model, each Potts spin (a tiny magnet in atomic scale length) represents the action of each student, and it takes a discrete variable corresponding to the company he/she applies for. We construct the energy to include three distinct effects on the students' behavior, namely, collective effect, market history and international ranking of companies. In this model system, the correlations (the adjacent matrix) between students are taken into account through the pairwise spin-spin interactions. We carry out computer simulations to examine the efficiency of the model. We also show that some chiral representation of the Potts spin enables us to obtain some analytical insights into our labor markets. This work was financially supported by Grant-in-Aid for Scientific Research (C) of Japan Society for the Promotion of Science No. 25330278.

A fractional reaction-diffusion description of supply and demand

NASA Astrophysics Data System (ADS)

Benzaquen, Michael; Bouchaud, Jean-Philippe

2018-02-01

We suggest that the broad distribution of time scales in financial markets could be a crucial ingredient to reproduce realistic price dynamics in stylised Agent-Based Models. We propose a fractional reaction-diffusion model for the dynamics of latent liquidity in financial markets, where agents are very heterogeneous in terms of their characteristic frequencies. Several features of our model are amenable to an exact analytical treatment. We find in particular that the impact is a concave function of the transacted volume (aka the "square-root impact law"), as in the normal diffusion limit. However, the impact kernel decays as t-β with β = 1/2 in the diffusive case, which is inconsistent with market efficiency. In the sub-diffusive case the decay exponent β takes any value in [0, 1/2], and can be tuned to match the empirical value β ≈ 1/4. Numerical simulations confirm our theoretical results. Several extensions of the model are suggested. Contribution to the Topical Issue "Continuous Time Random Walk Still Trendy: Fifty-year History, Current State and Outlook", edited by Ryszard Kutner and Jaume Masoliver.

Research on multi-level decision game strategy of electricity sales market considering ETS and block chain

NASA Astrophysics Data System (ADS)

Liu, Jinjie

2017-08-01

In order to fully consider the impact of future policies and technologies on the electricity sales market, improve the efficiency of electricity market operation, realize the dual goal of power reform and energy saving and emission reduction, this paper uses multi-level decision theory to put forward the double-layer game model under the consideration of ETS and block chain. We set the maximization of electricity sales profit as upper level objective and establish a game strategy model of electricity purchase; while we set maximization of user satisfaction as lower level objective and build a choice behavior model based on customer satisfaction. This paper applies the strategy to the simulation of a sales company's transaction, and makes a horizontal comparison of the same industry competitors as well as a longitudinal comparison of game strategies considering different factors. The results show that Double-layer game model is reasonable and effective, it can significantly improve the efficiency of the electricity sales companies and user satisfaction, while promoting new energy consumption and achieving energy-saving emission reduction.

Research on monocentric model of urbanization by agent-based simulation

NASA Astrophysics Data System (ADS)

Xue, Ling; Yang, Kaizhong

2008-10-01

Over the past years, GIS have been widely used for modeling urbanization from a variety of perspectives such as digital terrain representation and overlay analysis using cell-based data platform. Similarly, simulation of urban dynamics has been achieved with the use of Cellular Automata. In contrast to these approaches, agent-based simulation provides a much more powerful set of tools. This allows researchers to set up a counterpart for real environmental and urban systems in computer for experimentation and scenario analysis. This Paper basically reviews the research on the economic mechanism of urbanization and an agent-based monocentric model is setup for further understanding the urbanization process and mechanism in China. We build an endogenous growth model with dynamic interactions between spatial agglomeration and urban development by using agent-based simulation. It simulates the migration decisions of two main types of agents, namely rural and urban households between rural and urban area. The model contains multiple economic interactions that are crucial in understanding urbanization and industrial process in China. These adaptive agents can adjust their supply and demand according to the market situation by a learning algorithm. The simulation result shows this agent-based urban model is able to perform the regeneration and to produce likely-to-occur projections of reality.

Sociophysics — a Review of Recent Monte Carlo Simulations

NASA Astrophysics Data System (ADS)

Stauffer, D.

Computational models for social phenomena are reviewed: Bonabeau et al. for the formation of social hierarchies, Donangelo and Sneppen for the replacement of barter by money, Solomon and Weisbuch for marketing percolation, and Sznajd for political persuasion. Finally we review how to destroy the internet.

Biofuel supply chain, market, and policy analysis

NASA Astrophysics Data System (ADS)

Zhang, Leilei

Renewable fuel is receiving an increasing attention as a substitute for fossil based energy. The US Department of Energy (DOE) has employed increasing effort on promoting the advanced biofuel productions. Although the advanced biofuel remains at its early stage, it is expected to play an important role in climate policy in the future in the transportation sector. This dissertation studies the emerging biofuel supply chain and markets by analyzing the production cost, and the outcomes of the biofuel market, including blended fuel market price and quantity, biofuel contract price and quantity, profitability of each stakeholder (farmers, biofuel producers, biofuel blenders) in the market. I also address government policy impacts on the emerging biofuel market. The dissertation is composed with three parts, each in a paper format. The first part studies the supply chain of emerging biofuel industry. Two optimization-based models are built to determine the number of facilities to deploy, facility locations, facility capacities, and operational planning within facilities. Cost analyses have been conducted under a variety of biofuel demand scenarios. It is my intention that this model will shed light on biofuel supply chain design considering operational planning under uncertain demand situations. The second part of the dissertation work focuses on analyzing the interaction between the key stakeholders along the supply chain. A bottom-up equilibrium model is built for the emerging biofuel market to study the competition in the advanced biofuel market, explicitly formulating the interactions between farmers, biofuel producers, blenders, and consumers. The model simulates the profit maximization of multiple market entities by incorporating their competitive decisions in farmers' land allocation, biomass transportation, biofuel production, and biofuel blending. As such, the equilibrium model is capable of and appropriate for policy analysis, especially for those policies that have complex ramifications and result in sophisticate interactions among multiple stakeholders. The third part of the dissertation investigates the impacts of flexible fuel vehicles (FFVs) market penetration levels on the market outcomes, including cellulosic biofuel production and price, blended fuel market price, and profitability of each stakeholder in the biofuel supply chain for imperfectly competitive biofuel markets. In this paper, I investigate the penetration levels of FFVs by incorporating the substitution among different fuels in blended fuel demand functions through "cross price elasticity" in a bottom-up equilibrium model framework. The complementarity based problem is solved by a Taylor expansion-based iterative procedure. At each step of the iteration, the highly nonlinear complementarity problems with constant elasticity of demand functions are linearized into linear complimentarity problems and solved until it converges. This model can be applied to investigate the interaction between the stakeholders in the biofuel market, and to assist decision making for both cellulosic biofuel investors and government.

Recruitment of Foreigners in the Market for Computer Scientists in the United States

PubMed Central

Bound, John; Braga, Breno; Golden, Joseph M.

2016-01-01

We present and calibrate a dynamic model that characterizes the labor market for computer scientists. In our model, firms can recruit computer scientists from recently graduated college students, from STEM workers working in other occupations or from a pool of foreign talent. Counterfactual simulations suggest that wages for computer scientists would have been 2.8–3.8% higher, and the number of Americans employed as computers scientists would have been 7.0–13.6% higher in 2004 if firms could not hire more foreigners than they could in 1994. In contrast, total CS employment would have been 3.8–9.0% lower, and consequently output smaller. PMID:27170827

Warranty optimisation based on the prediction of costs to the manufacturer using neural network model and Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Stamenkovic, Dragan D.; Popovic, Vladimir M.

2015-02-01

Warranty is a powerful marketing tool, but it always involves additional costs to the manufacturer. In order to reduce these costs and make use of warranty's marketing potential, the manufacturer needs to master the techniques for warranty cost prediction according to the reliability characteristics of the product. In this paper a combination free replacement and pro rata warranty policy is analysed as warranty model for one type of light bulbs. Since operating conditions have a great impact on product reliability, they need to be considered in such analysis. A neural network model is used to predict light bulb reliability characteristics based on the data from the tests of light bulbs in various operating conditions. Compared with a linear regression model used in the literature for similar tasks, the neural network model proved to be a more accurate method for such prediction. Reliability parameters obtained in this way are later used in Monte Carlo simulation for the prediction of times to failure needed for warranty cost calculation. The results of the analysis make possible for the manufacturer to choose the optimal warranty policy based on expected product operating conditions. In such a way, the manufacturer can lower the costs and increase the profit.

Short and long term investor synchronization caused by decoupling.

PubMed

Roszczynska-Kurasinska, Magda; Nowak, Andrzej; Kamieniarz, Daniel; Solomon, Sorin; Andersen, Jørgen Vitting

2012-01-01

The dynamics of collective decision making is not yet well understood. Its practical relevance however can be of utmost importance, as experienced by people who lost their fortunes in turbulent moments of financial markets. In this paper we show how spontaneous collective "moods" or "biases" emerge dynamically among human participants playing a trading game in a simple model of the stock market. Applying theory and computer simulations to the experimental data generated by humans, we are able to predict the onset of such moments before they actually happen.

Short and Long Term Investor Synchronization Caused by Decoupling

PubMed Central

Roszczynska-Kurasinska, Magda; Nowak, Andrzej; Kamieniarz, Daniel; Solomon, Sorin; Andersen, Jørgen Vitting

2012-01-01

The dynamics of collective decision making is not yet well understood. Its practical relevance however can be of utmost importance, as experienced by people who lost their fortunes in turbulent moments of financial markets. In this paper we show how spontaneous collective “moods” or “biases” emerge dynamically among human participants playing a trading game in a simple model of the stock market. Applying theory and computer simulations to the experimental data generated by humans, we are able to predict the onset of such moments before they actually happen. PMID:23236385

A geographic information system-based 3D city estate modeling and simulation system

NASA Astrophysics Data System (ADS)

Chong, Xiaoli; Li, Sha

2015-12-01

This paper introduces a 3D city simulation system which is based on geographic information system (GIS), covering all commercial housings of the city. A regional- scale, GIS-based approach is used to capture, describe, and track the geographical attributes of each house in the city. A sorting algorithm of "Benchmark + Parity Rate" is developed to cluster houses with similar spatial and construction attributes. This system is applicable for digital city modeling, city planning, housing evaluation, housing monitoring, and visualizing housing transaction. Finally, taking Jingtian area of Shenzhen as an example, the each unit of 35,997 houses in the area could be displayed, tagged, and easily tracked by the GIS-based city modeling and simulation system. The match market real conditions well and can be provided to house buyers as reference.

Are Price Limits Effective? An Examination of an Artificial Stock Market.

PubMed

Zhang, Xiaotao; Ping, Jing; Zhu, Tao; Li, Yuelei; Xiong, Xiong

2016-01-01

We investigated the inter-day effects of price limits policies that are employed in agent-based simulations. To isolate the impact of price limits from the impact of other factors, we built an artificial stock market with higher frequency price limits hitting. The trading mechanisms in this market are the same as the trading mechanisms in China's stock market. Then, we designed a series of simulations with and without price limits policy. The results of these simulations demonstrate that both upper and lower price limits can cause a volatility spillover effect and a trading interference effect. The process of price discovery will be delayed if upper price limits are imposed on a stock market; however, this phenomenon does not occur when lower price limits are imposed.

Are Price Limits Effective? An Examination of an Artificial Stock Market

PubMed Central

Zhu, Tao; Li, Yuelei; Xiong, Xiong

2016-01-01

We investigated the inter-day effects of price limits policies that are employed in agent-based simulations. To isolate the impact of price limits from the impact of other factors, we built an artificial stock market with higher frequency price limits hitting. The trading mechanisms in this market are the same as the trading mechanisms in China’s stock market. Then, we designed a series of simulations with and without price limits policy. The results of these simulations demonstrate that both upper and lower price limits can cause a volatility spillover effect and a trading interference effect. The process of price discovery will be delayed if upper price limits are imposed on a stock market; however, this phenomenon does not occur when lower price limits are imposed. PMID:27513330

Time series analysis for minority game simulations of financial markets

NASA Astrophysics Data System (ADS)

Ferreira, Fernando F.; Francisco, Gerson; Machado, Birajara S.; Muruganandam, Paulsamy

2003-04-01

The minority game (MG) model introduced recently provides promising insights into the understanding of the evolution of prices, indices and rates in the financial markets. In this paper we perform a time series analysis of the model employing tools from statistics, dynamical systems theory and stochastic processes. Using benchmark systems and a financial index for comparison, several conclusions are obtained about the generating mechanism for this kind of evolution. The motion is deterministic, driven by occasional random external perturbation. When the interval between two successive perturbations is sufficiently large, one can find low dimensional chaos in this regime. However, the full motion of the MG model is found to be similar to that of the first differences of the SP500 index: stochastic, nonlinear and (unit root) stationary.

Research on the Complexity of Dual-Channel Supply Chain Model in Competitive Retailing Service Market

NASA Astrophysics Data System (ADS)

Ma, Junhai; Li, Ting; Ren, Wenbo

2017-06-01

This paper examines the optimal decisions of dual-channel game model considering the inputs of retailing service. We analyze how adjustment speed of service inputs affect the system complexity and market performance, and explore the stability of the equilibrium points by parameter basin diagrams. And chaos control is realized by variable feedback method. The numerical simulation shows that complex behavior would trigger the system to become unstable, such as double period bifurcation and chaos. We measure the performances of the model in different periods by analyzing the variation of average profit index. The theoretical results show that the percentage share of the demand and cross-service coefficients have important influence on the stability of the system and its feasible basin of attraction.

A Simulation Model for Measuring Customer Satisfaction through Employee Satisfaction

NASA Astrophysics Data System (ADS)

Zondiros, Dimitris; Konstantopoulos, Nikolaos; Tomaras, Petros

2007-12-01

Customer satisfaction is defined as a measure of how a firm's product or service performs compared to customer's expectations. It has long been a subject of research due to its importance for measuring marketing and business performance. A lot of models have been developed for its measurement. This paper propose a simulation model using employee satisfaction as one of the most important factors leading to customer satisfaction (the others being expectations and disconfirmation of expectations). Data obtained from a two-year survey in customers of banks in Greece were used. The application of three approaches regarding employee satisfaction resulted in greater customer satisfaction when there is serious effort to keep employees satisfied.

Instructional Simulation of a Commercial Banking System.

ERIC Educational Resources Information Center

Hester, Donald D.

1991-01-01

Describes an instructional simulation of a commercial banking system. Identifies the teaching of portfolio theory, market robustness, and the subtleties of institutional constraints and decision making under uncertainty as the project's goals. Discusses the results of applying the simulation in an environment of local and national markets and a…

An Agent-Based Model of Farmer Decision Making in Jordan

NASA Astrophysics Data System (ADS)

Selby, Philip; Medellin-Azuara, Josue; Harou, Julien; Klassert, Christian; Yoon, Jim

2016-04-01

We describe an agent based hydro-economic model of groundwater irrigated agriculture in the Jordan Highlands. The model employs a Multi-Agent-Simulation (MAS) framework and is designed to evaluate direct and indirect outcomes of climate change scenarios and policy interventions on farmer decision making, including annual land use, groundwater use for irrigation, and water sales to a water tanker market. Land use and water use decisions are simulated for groups of farms grouped by location and their behavioural and economic similarities. Decreasing groundwater levels, and the associated increase in pumping costs, are important drivers for change within Jordan'S agricultural sector. We describe how this is considered by coupling of agricultural and groundwater models. The agricultural production model employs Positive Mathematical Programming (PMP), a method for calibrating agricultural production functions to observed planted areas. PMP has successfully been used with disaggregate models for policy analysis. We adapt the PMP approach to allow explicit evaluation of the impact of pumping costs, groundwater purchase fees and a water tanker market. The work demonstrates the applicability of agent-based agricultural decision making assessment in the Jordan Highlands and its integration with agricultural model calibration methods. The proposed approach is designed and implemented with software such that it could be used to evaluate a variety of physical and human influences on decision making in agricultural water management.

Exploring the impact of co-varying water availability and energy price on productivity and profitability of Alpine hydropower

NASA Astrophysics Data System (ADS)

Anghileri, Daniela; Botter, Martina; Castelletti, Andrea; Burlando, Paolo

2016-04-01

Alpine hydropower systems are experiencing dramatic changes both from the point of view of hydrological conditions, e.g., water availability and frequency of extremes events, and of energy market conditions, e.g., partial or total liberalization of the market and increasing share of renewable power sources. Scientific literature has, so far, mostly focused on the analysis of climate change impacts and associated uncertainty on hydropower operation, underlooking the consequences that socio-economic changes, e.g., energy demand and/or price changes, can have on hydropower productivity and profitability. In this work, we analyse how hydropower reservoir operation is affected by changes in both water availability and energy price. We consider stochastically downscaled climate change scenarios of precipitation and temperature to simulate reservoir inflows using a physically explicit hydrological model. We consider different scenarios of energy demand and generation mix to simulate energy prices using an electricity market model, which includes different generation sources, demand sinks, and features of the transmission lines. We then use Multi-Objective optimization techniques to design the operation of hydropower reservoirs for different purposes, e.g. maximization of revenue and/or energy production. The objective of the work is to assess how the tradeoffs between the multiple operating objectives evolve under different co-varying climate change and socio-economic scenarios and to assess the adaptive capacity of the system. The modeling framework is tested on the real-world case study of the Mattmark reservoir in Switzerland.

Marine and Hydrokinetic Research | Water Power | NREL

Science.gov Websites

. Resource Characterization and Maps NREL develops measurement systems, simulation tools, and web-based models and tools to evaluate the economic potential of power-generating devices for all technology Acceleration NREL analysts study the potential impacts that developing a robust MHK market could have on

Simulating and Optimizing Preparative Protein Chromatography with ChromX

ERIC Educational Resources Information Center

Hahn, Tobias; Huuk, Thiemo; Heuveline, Vincent; Hubbuch, Ju¨rgen

2015-01-01

Industrial purification of biomolecules is commonly based on a sequence of chromatographic processes, which are adapted slightly to new target components, as the time to market is crucial. To improve time and material efficiency, modeling is increasingly used to determine optimal operating conditions, thus providing new challenges for current and…

Price subsidies and the market for mosquito nets in developing countries: A study of Tanzania's discount voucher scheme.

PubMed

Gingrich, Chris D; Hanson, Kara; Marchant, Tanya; Mulligan, Jo-Ann; Mponda, Hadji

2011-07-01

This study uses a partial equilibrium simulation model to explore how price subsidies for insecticide-treated mosquito nets (ITNs) affect households' purchases of ITNs. The model describes the ITN market in a typical developing country and is applied to the situation in Tanzania, where the Tanzania National Voucher Scheme (TNVS) provides a targeted subsidy to vulnerable population groups by means of a discount voucher. The data for this study come from a nationally-representative household survey completed July-August 2006 covering over 4300 households in 21 districts. The simulation results show the impact of the voucher program on ITN coverage among target households, namely those that experienced the birth of a child. More specifically, the share of target households purchasing an ITN increased from 18 to 62 percent because of the discount voucher. The model also suggests that the voucher program could cause the retail ITN price to rise due to an overall increase in demand. As a result, ITN purchases by households without a voucher may actually decline. The simulation model suggests that additional increases toward the stated goal of 80 percent ITN coverage for pregnant women and children could best be achieved through a combination of "catch up" mass distribution programs and expanding the target group for the voucher program to cover additional households. The model can be employed in other countries considering use of a targeted price subsidy for ITNs, and could be adapted to assess the impact of subsidies for other public health commodities. Copyright © 2011 Elsevier Ltd. All rights reserved.

Agent-based models of financial markets

NASA Astrophysics Data System (ADS)

Samanidou, E.; Zschischang, E.; Stauffer, D.; Lux, T.

2007-03-01

This review deals with several microscopic ('agent-based') models of financial markets which have been studied by economists and physicists over the last decade: Kim-Markowitz, Levy-Levy-Solomon, Cont-Bouchaud, Solomon-Weisbuch, Lux-Marchesi, Donangelo-Sneppen and Solomon-Levy-Huang. After an overview of simulation approaches in financial economics, we first give a summary of the Donangelo-Sneppen model of monetary exchange and compare it with related models in economics literature. Our selective review then outlines the main ingredients of some influential early models of multi-agent dynamics in financial markets (Kim-Markowitz, Levy-Levy-Solomon). As will be seen, these contributions draw their inspiration from the complex appearance of investors' interactions in real-life markets. Their main aim is to reproduce (and, thereby, provide possible explanations) for the spectacular bubbles and crashes seen in certain historical episodes, but they lack (like almost all the work before 1998 or so) a perspective in terms of the universal statistical features of financial time series. In fact, awareness of a set of such regularities (power-law tails of the distribution of returns, temporal scaling of volatility) only gradually appeared over the nineties. With the more precise description of the formerly relatively vague characteristics (e.g. moving from the notion of fat tails to the more concrete one of a power law with index around three), it became clear that financial market dynamics give rise to some kind of universal scaling law. Showing similarities with scaling laws for other systems with many interacting sub-units, an exploration of financial markets as multi-agent systems appeared to be a natural consequence. This topic has been pursued by quite a number of contributions appearing in both the physics and economics literature since the late nineties. From the wealth of different flavours of multi-agent models that have appeared up to now, we discuss the Cont-Bouchaud, Solomon-Levy-Huang and Lux-Marchesi models. Open research questions are discussed in our concluding section.

Multi-step-ahead crude oil price forecasting using a hybrid grey wave model

NASA Astrophysics Data System (ADS)

Chen, Yanhui; Zhang, Chuan; He, Kaijian; Zheng, Aibing

2018-07-01

Crude oil is crucial to the operation and economic well-being of the modern society. Huge changes of crude oil price always cause panics to the global economy. There are many factors influencing crude oil price. Crude oil price prediction is still a difficult research problem widely discussed among researchers. Based on the researches on Heterogeneous Market Hypothesis and the relationship between crude oil price and macroeconomic factors, exchange market, stock market, this paper proposes a hybrid grey wave forecasting model, which combines Random Walk (RW)/ARMA to forecast multi-step-ahead crude oil price. More specifically, we use grey wave forecasting model to model the periodical characteristics of crude oil price and ARMA/RW to simulate the daily random movements. The innovation also comes from using the information of the time series graph to forecast crude oil price, since grey wave forecasting is a graphical prediction method. The empirical results demonstrate that based on the daily data of crude oil price, the hybrid grey wave forecasting model performs well in 15- to 20-step-ahead prediction and it always dominates ARMA and Random Walk in correct direction prediction.

Computable General Equilibrium Model Fiscal Year 2013 Capability Development Report - April 2014

DOE Office of Scientific and Technical Information (OSTI.GOV)

Edwards, Brian Keith; Rivera, Michael K.; Boero, Riccardo

2014-04-01

This report documents progress made on continued developments of the National Infrastructure Simulation and Analysis Center (NISAC) Computable General Equilibrium Model (NCGEM), developed in fiscal year 2012. In fiscal year 2013, NISAC the treatment of the labor market and tests performed with the model to examine the properties of the solutions computed by the model. To examine these, developers conducted a series of 20 simulations for 20 U.S. States. Each of these simulations compared an economic baseline simulation with an alternative simulation that assumed a 20-percent reduction in overall factor productivity in the manufacturing industries of each State. Differences inmore » the simulation results between the baseline and alternative simulations capture the economic impact of the reduction in factor productivity. While not every State is affected in precisely the same way, the reduction in manufacturing industry productivity negatively affects the manufacturing industries in each State to an extent proportional to the reduction in overall factor productivity. Moreover, overall economic activity decreases when manufacturing sector productivity is reduced. Developers ran two additional simulations: (1) a version of the model for the State of Michigan, with manufacturing divided into two sub-industries (automobile and other vehicle manufacturing as one sub-industry and the rest of manufacturing as the other subindustry); and (2) a version of the model for the United States, divided into 30 industries. NISAC conducted these simulations to illustrate the flexibility of industry definitions in NCGEM and to examine the simulation properties of in more detail.« less

An integrated modeling framework of socio-economic, biophysical, and hydrological processes in Midwest landscapes: Remote sensing data, agro-hydrological model, and agent-based model

NASA Astrophysics Data System (ADS)

Ding, Deng

Intensive human-environment interactions are taking place in Midwestern agricultural systems. An integrated modeling framework is suitable for predicting dynamics of key variables of the socio-economic, biophysical, hydrological processes as well as exploring the potential transitions of system states in response to changes of the driving factors. The purpose of this dissertation is to address issues concerning the interacting processes and consequent changes in land use, water balance, and water quality using an integrated modeling framework. This dissertation is composed of three studies in the same agricultural watershed, the Clear Creek watershed in East-Central Iowa. In the first study, a parsimonious hydrologic model, the Threshold-Exceedance-Lagrangian Model (TELM), is further developed into RS-TELM (Remote Sensing TELM) to integrate remote sensing vegetation data for estimating evapotranspiration. The goodness of fit of RS-TELM is comparable to a well-calibrated SWAT (Soil and Water Assessment Tool) and even slightly superior in capturing intra-seasonal variability of stream flow. The integration of RS LAI (Leaf Area Index) data improves the model's performance especially over the agriculture dominated landscapes. The input of rainfall datasets with spatially explicit information plays a critical role in increasing the model's goodness of fit. In the second study, an agent-based model is developed to simulate farmers' decisions on crop type and fertilizer application in response to commodity and biofuel crop prices. The comparison between simulated crop land percentage and crop rotations with satellite-based land cover data suggest that farmers may be underestimating the effects that continuous corn production has on yields (yield drag). The simulation results given alternative market scenarios based on a survey of agricultural land owners and operators in the Clear Creek Watershed show that, farmers see cellulosic biofuel feedstock production in the form of perennial grasses or corn stover as a more risky enterprise than their current crop production systems, likely because of market and production risks and lock in effects. As a result farmers do not follow a simple farm-profit maximization rule. In the third study, the consequent water quantity and quality change of the potential land use transitions given alternative biofuel crop market scenarios is explored in a case study in the Clear Creek watershed. A computer program is developed to implement the loose-coupling strategy to couple an agent-based land use model with SWAT. The simulation results show that watershed-scale water quantity (water yield and runoff) and quality variables (sediment and nutrient loads) decrease in values as switchgrass price increases. However, negligence of farmers risk aversions towards biofuel crop adoption would cause overestimation of the impacts of switchgrass price on water quantity and quality.

Adding Badging to a Marketing Simulation to Increase Motivation to Learn

ERIC Educational Resources Information Center

Saxton, M. Kim

2015-01-01

Badging has become a popular tool for obtaining social recognition for personal accomplishments. This innovation describes a way to add badging to a marketing simulation to increase student motivation to achieve the simulation's goals. Assessments indicate that badging both motivates students to perform better and helps explain students' perceived…

The Impacts of Information-Sharing Mechanisms on Spatial Market Formation Based on Agent-Based Modeling

PubMed Central

Li, Qianqian; Yang, Tao; Zhao, Erbo; Xia, Xing’ang; Han, Zhangang

2013-01-01

There has been an increasing interest in the geographic aspects of economic development, exemplified by P. Krugman’s logical analysis. We show in this paper that the geographic aspects of economic development can be modeled using multi-agent systems that incorporate multiple underlying factors. The extent of information sharing is assumed to be a driving force that leads to economic geographic heterogeneity across locations without geographic advantages or disadvantages. We propose an agent-based market model that considers a spectrum of different information-sharing mechanisms: no information sharing, information sharing among friends and pheromone-like information sharing. Finally, we build a unified model that accommodates all three of these information-sharing mechanisms based on the number of friends who can share information. We find that the no information-sharing model does not yield large economic zones, and more information sharing can give rise to a power-law distribution of market size that corresponds to the stylized fact of city size and firm size distributions. The simulations show that this model is robust. This paper provides an alternative approach to studying economic geographic development, and this model could be used as a test bed to validate the detailed assumptions that regulate real economic agglomeration. PMID:23484007

Mining for Data

NASA Technical Reports Server (NTRS)

1998-01-01

AbTech Corporation used an F-18 HARV (High Alpha Research Vehicle) simulation developed by NASA to create an interactive computer-based prototype of the MQ (Model Quest) SV (System Validator) tool. Dryden Flight Research Center provided support to develop, test, and rapidly reprogram the validation function. AbTech's ModelQuest Enterprises highly automated and outperforms other modeling techniques to quickly discover meaningful relationships, patterns, and trends in databases. Applications include technical and business professionals in finance, marketing, business, banking, retail, healthcare, and aerospace.

Scramjet Combustor Simulations Using Reduced Chemical Kinetics for Practical Fuels

DTIC Science & Technology

2003-12-01

the aerospace industry in reducing prototype and testing costs and the time needed to bring products to market . Accurate simulation of chemical...JP-8 kinetics and soot models into the UNICORN CFD code (Montgomery et al., 2003a) NSF Phase I and II SBIRs for development of a computer-assisted...divided by diameter QSS quasi-steady state REI Reaction Engineering International UNICORN UNsteady Ignition and COmbustion with ReactioNs VULCAN Viscous Upwind aLgorithm for Complex flow ANalysis

A dynamic simulation based water resources education tool.

PubMed

Williams, Alison; Lansey, Kevin; Washburne, James

2009-01-01

Educational tools to assist the public in recognizing impacts of water policy in a realistic context are not generally available. This project developed systems with modeling-based educational decision support simulation tools to satisfy this need. The goal of this model is to teach undergraduate students and the general public about the implications of common water management alternatives so that they can better understand or become involved in water policy and make more knowledgeable personal or community decisions. The model is based on Powersim, a dynamic simulation software package capable of producing web-accessible, intuitive, graphic, user-friendly interfaces. Modules are included to represent residential, agricultural, industrial, and turf uses, as well as non-market values, water quality, reservoir, flow, and climate conditions. Supplementary materials emphasize important concepts and lead learners through the model, culminating in an open-ended water management project. The model is used in a University of Arizona undergraduate class and within the Arizona Master Watershed Stewards Program. Evaluation results demonstrated improved understanding of concepts and system interactions, fulfilling the project's objectives.

Pharmaceutical industry and trade liberalization using computable general equilibrium model.

PubMed

Barouni, M; Ghaderi, H; Banouei, Aa

2012-01-01

Computable general equilibrium models are known as a powerful instrument in economic analyses and widely have been used in order to evaluate trade liberalization effects. The purpose of this study was to provide the impacts of trade openness on pharmaceutical industry using CGE model. Using a computable general equilibrium model in this study, the effects of decrease in tariffs as a symbol of trade liberalization on key variables of Iranian pharmaceutical products were studied. Simulation was performed via two scenarios in this study. The first scenario was the effect of decrease in tariffs of pharmaceutical products as 10, 30, 50, and 100 on key drug variables, and the second was the effect of decrease in other sectors except pharmaceutical products on vital and economic variables of pharmaceutical products. The required data were obtained and the model parameters were calibrated according to the social accounting matrix of Iran in 2006. The results associated with simulation demonstrated that the first scenario has increased import, export, drug supply to markets and household consumption, while import, export, supply of product to market, and household consumption of pharmaceutical products would averagely decrease in the second scenario. Ultimately, society welfare would improve in all scenarios. We presents and synthesizes the CGE model which could be used to analyze trade liberalization policy issue in developing countries (like Iran), and thus provides information that policymakers can use to improve the pharmacy economics.

Market Impact of Foot-and-Mouth Disease Control Strategies: A UK Case Study

PubMed Central

Feng, Siyi; Patton, Myles; Davis, John

2017-01-01

Foot-and-mouth disease (FMD) poses a serious threat to the agricultural sector due to its highly contagious nature. Outbreaks of FMD can lead to substantial disruptions to livestock markets due to loss of production and access to international markets. In a previously FMD-free country, the use of vaccination to augment control of an FMD outbreak is increasingly being recognized as an alternative control strategy to direct slaughtering [stamping-out (SO)]. The choice of control strategy has implications on production, trade, and hence prices of the sector. Specific choice of eradication strategies depends on their costs and benefits. Economic impact assessments are often based on benefit–cost framework, which provide detailed information on the changes in profit for a farm or budget implications for a government (1). However, this framework cannot capture price effects caused by changes in production due to culling of animals; access to international markets; and consumers’ reaction. These three impacts combine to affect equilibrium within commodity markets (2). This paper provides assessment of sectoral level impacts of the eradication choices of FMD outbreaks, which are typically not available from benefit–cost framework, in the context of the UK. The FAPRI-UK model, a partial equilibrium model of the agricultural sector, is utilized to investigate market outcomes of different control strategies (namely SO and vaccinate-to-die) in the case of FMD outbreaks. The outputs from the simulations of the EXODIS epidemiological model (number of animals culled/vaccinated and duration of outbreak) are used as inputs within the economic model to capture the overall price impact of the animal destruction, export ban, and consumers’ response. PMID:28920059

Quantifying the Sensitivity of the Production of Environmental Externalities to Market-Based Interventions in the Power Sector

NASA Astrophysics Data System (ADS)

Peer, R.; Sanders, K.

2017-12-01

The optimization function that governs the dispatching of power generators to meet electricity demand minimizes the marginal cost of electricity generation without regard to the environmental or public health damages caused by power production. Although technologies exist for reducing the externalities resulting from electricity generation at power plants, current solutions typically raise the cost of power production or introduce operational challenges for the grid. This research quantifies the trade-offs and couplings between the cooling water, greenhouse gas emissions, and air quality impacts of different power generating technologies under business as usual market conditions, as well as a series of market-based interventions aimed to reduce the production of those externalities. Using publicly available data from the US Environmental Protection Agency (EPA) and the US Energy Information Administration (EIA) for power plant water use and emissions, a unit commitment and dispatch power market simulation model is modified to evaluate the production of environmental externalities from power production. Scenarios are developed to apply a set of fees for cooling water, carbon dioxide, nitrous oxide and sulfur oxide emissions, respectively. Trade-offs between environmental performance, overall generation costs, and shifts in the power plants dispatched to meet demand are quantified for each power market simulation. The results from this study will provide insight into the development of a novel market-based framework that modifies the optimization algorithms governing the dispatching of electricity onto the grid in efforts to achieve cost-effective improvements in its environmental performance without the need for new infrastructure investments.

Support vector machine for day ahead electricity price forecasting

NASA Astrophysics Data System (ADS)

Razak, Intan Azmira binti Wan Abdul; Abidin, Izham bin Zainal; Siah, Yap Keem; Rahman, Titik Khawa binti Abdul; Lada, M. Y.; Ramani, Anis Niza binti; Nasir, M. N. M.; Ahmad, Arfah binti

2015-05-01

Electricity price forecasting has become an important part of power system operation and planning. In a pool- based electric energy market, producers submit selling bids consisting in energy blocks and their corresponding minimum selling prices to the market operator. Meanwhile, consumers submit buying bids consisting in energy blocks and their corresponding maximum buying prices to the market operator. Hence, both producers and consumers use day ahead price forecasts to derive their respective bidding strategies to the electricity market yet reduce the cost of electricity. However, forecasting electricity prices is a complex task because price series is a non-stationary and highly volatile series. Many factors cause for price spikes such as volatility in load and fuel price as well as power import to and export from outside the market through long term contract. This paper introduces an approach of machine learning algorithm for day ahead electricity price forecasting with Least Square Support Vector Machine (LS-SVM). Previous day data of Hourly Ontario Electricity Price (HOEP), generation's price and demand from Ontario power market are used as the inputs for training data. The simulation is held using LSSVMlab in Matlab with the training and testing data of 2004. SVM that widely used for classification and regression has great generalization ability with structured risk minimization principle rather than empirical risk minimization. Moreover, same parameter settings in trained SVM give same results that absolutely reduce simulation process compared to other techniques such as neural network and time series. The mean absolute percentage error (MAPE) for the proposed model shows that SVM performs well compared to neural network.

Multi-scaling modelling in financial markets

NASA Astrophysics Data System (ADS)

Liu, Ruipeng; Aste, Tomaso; Di Matteo, T.

2007-12-01

In the recent years, a new wave of interest spurred the involvement of complexity in finance which might provide a guideline to understand the mechanism of financial markets, and researchers with different backgrounds have made increasing contributions introducing new techniques and methodologies. In this paper, Markov-switching multifractal models (MSM) are briefly reviewed and the multi-scaling properties of different financial data are analyzed by computing the scaling exponents by means of the generalized Hurst exponent H(q). In particular we have considered H(q) for price data, absolute returns and squared returns of different empirical financial time series. We have computed H(q) for the simulated data based on the MSM models with Binomial and Lognormal distributions of the volatility components. The results demonstrate the capacity of the multifractal (MF) models to capture the stylized facts in finance, and the ability of the generalized Hurst exponents approach to detect the scaling feature of financial time series.

Chemical supply chain modeling for analysis of homeland security events

DOE PAGES

Ehlen, Mark A.; Sun, Amy C.; Pepple, Mark A.; ...

2013-09-06

The potential impacts of man-made and natural disasters on chemical plants, complexes, and supply chains are of great importance to homeland security. To be able to estimate these impacts, we developed an agent-based chemical supply chain model that includes: chemical plants with enterprise operations such as purchasing, production scheduling, and inventories; merchant chemical markets, and multi-modal chemical shipments. Large-scale simulations of chemical-plant activities and supply chain interactions, running on desktop computers, are used to estimate the scope and duration of disruptive-event impacts, and overall system resilience, based on the extent to which individual chemical plants can adjust their internal operationsmore » (e.g., production mixes and levels) versus their external interactions (market sales and purchases, and transportation routes and modes). As a result, to illustrate how the model estimates the impacts of a hurricane disruption, a simple example model centered on 1,4-butanediol is presented.« less

Industrial pollution and the management of river water quality: a model of Kelani River, Sri Lanka.

PubMed

Gunawardena, Asha; Wijeratne, E M S; White, Ben; Hailu, Atakelty; Pandit, Ram

2017-08-19

Water quality of the Kelani River has become a critical issue in Sri Lanka due to the high cost of maintaining drinking water standards and the market and non-market costs of deteriorating river ecosystem services. By integrating a catchment model with a river model of water quality, we developed a method to estimate the effect of pollution sources on ambient water quality. Using integrated model simulations, we estimate (1) the relative contribution from point (industrial and domestic) and non-point sources (river catchment) to river water quality and (2) pollutant transfer coefficients for zones along the lower section of the river. Transfer coefficients provide the basis for policy analyses in relation to the location of new industries and the setting of priorities for industrial pollution control. They also offer valuable information to design socially optimal economic policy to manage industrialized river catchments.

Interdependency Assessment of Coupled Natural Gas and Power Systems in Energy Market

NASA Astrophysics Data System (ADS)

Yang, Hongzhao; Qiu, Jing; Zhang, Sanhua; Lai, Mingyong; Dong, Zhao Yang

2015-12-01

Owing to the technological development of natural gas exploration and the increasing penetration of gas-fired power generation, gas and power systems inevitably interact with each other from both physical and economic points of view. In order to effectively assess the two systems' interdependency, this paper proposes a systematic modeling framework and constructs simulation platforms for coupled gas and power systems in an energy market environment. By applying the proposed approach to the Australian national electricity market (NEM) and gas market, the impacts of six types of market and system factors are quantitatively analyzed, including power transmission limits, gas pipeline contingencies, gas pipeline flow constraints, carbon emission constraints, power load variations, and non-electric gas load variations. The important interdependency and infrastructure weakness for the two systems are well studied and identified. Our work provides a quantitative basis for grid operators and policy makers to support and guide operation and investment decisions for electric power and natural gas industries.

Modeling the Impacts of EU Bioenergy Demand on the Forest Sector of the Southeast U.S.

Treesearch

Rafal Chudy; Robert C. Abt; Frederick W. Cubbage; Ragnar Jonsson; Jeffrey P. Prestemon

2013-01-01

The wood-pellet trade between the U.S. (United States) and the EU (European Union) has increased substantially recently. This research analyzes the effects of EU biomass imports from the Southeast U.S. on Southeast U.S. timber prices, inventories and production and on EU imports of feedstock. The SRTS (sub-regional timber supply model) was used to simulate market...

Building America Case Study: Assessment of a Hybrid Retrofit Gas Water Heater

DOE Office of Scientific and Technical Information (OSTI.GOV)

M. Hoeschele, E. Weitzel, C. Backman

This project completed a modeling evaluation of a hybrid gas water heater that combines a reduced capacity tankless unit with a downsized storage tank. This product would meet a significant market need by providing a higher efficiency gas water heater solution for retrofit applications while maintaining compatibility with the half-inch gas lines and standard B vents found in most homes. The TRNSYS simulation tool was used to model a base case 0.60 EF atmospheric gas storage water, a 0.82 EF non-condensing gas tankless water heater, an existing (high capacity) hybrid unit on the market, and an alternative hybrid unit withmore » lower storage volume and reduced gas input requirements.« less

The economic value of remote sensing of earth resources from space: An ERTS overview and the value of continuity of service. Volume 3: Intensive use of living resources, agriculture. Part 2: Distribution effects

NASA Technical Reports Server (NTRS)

Bradford, D. F.; Kelejian, H. H.

1974-01-01

The results of an investigation of the value of improving information for forecasting future crop harvests are described. A theoretical model is developed to calculate the value of increased speed of availablitiy of that information. The analysis of U.S. domestic wheat consumption was implemented. New estimates of a demand function for wheat and of a cost of storage function were involved, along with a Monte Carlo simulation for the wheat spot and future markets and a model of market determinations of wheat inventories. Results are shown to depend critically on the accuracy of current and proposed measurement techniques.

Financial technical indicator based on chaotic bagging predictors for adaptive stock selection in Japanese and American markets

NASA Astrophysics Data System (ADS)

Suzuki, Tomoya; Ohkura, Yuushi

2016-01-01

In order to examine the predictability and profitability of financial markets, we introduce three ideas to improve the traditional technical analysis to detect investment timings more quickly. Firstly, a nonlinear prediction model is considered as an effective way to enhance this detection power by learning complex behavioral patterns hidden in financial markets. Secondly, the bagging algorithm can be applied to quantify the confidence in predictions and compose new technical indicators. Thirdly, we also introduce how to select more profitable stocks to improve investment performance by the two-step selection: the first step selects more predictable stocks during the learning period, and then the second step adaptively and dynamically selects the most confident stock showing the most significant technical signal in each investment. Finally, some investment simulations based on real financial data show that these ideas are successful in overcoming complex financial markets.

Testing for detailed balance in a financial market

NASA Astrophysics Data System (ADS)

Fiebig, H. R.; Musgrove, D. P.

2015-06-01

We test a historical price-time series in a financial market (the NASDAQ 100 index) for a statistical property known as detailed balance. The presence of detailed balance would imply that the market can be modeled by a stochastic process based on a Markov chain, thus leading to equilibrium. In economic terms, a positive outcome of the test would support the efficient market hypothesis, a cornerstone of neo-classical economic theory. In contrast to the usage in prevalent economic theory the term equilibrium here is tied to the returns, rather than the price-time series. The test is based on an action functional S constructed from the elements of the detailed balance condition and the historical data set, and then analyzing S by means of simulated annealing. Checks are performed to verify the validity of the analysis method. We discuss the outcome of this analysis.

A Dynamic Simulation Model of Organizational Culture and Business Strategy Effects on Performance

NASA Astrophysics Data System (ADS)

Trivellas, Panagiotis; Reklitis, Panagiotis; Konstantopoulos, Nikolaos

2007-12-01

In the past two decades, organizational culture literature has gained tremendous interest for both academic and practitioners. This is based not only on the suggestion that culture is related to performance, but also on the view that it is subject of direct managerial control and manipulation to the desired direction. In the present paper, we adopt Competing Values Framework (CVF) to operationalise organizational culture and Porter's typology to conceptualize business strategy (cost leadership, innovative and marketing differentiation, and focus). Although simulation of social events is a quite difficult task, since there are so many considerations (not all well understood) involved, in the present study we developed a dynamic model to simulate the organizational culture and strategy effects on financial performance. Data obtained from a six-year survey in the banking sector of a European developing economy was used for the proposed dynamic model development.

A game-based decision support methodology for competitive systems design

NASA Astrophysics Data System (ADS)

Briceno, Simon Ignacio

This dissertation describes the development of a game-based methodology that facilitates the exploration and selection of research and development (R&D) projects under uncertain competitive scenarios. The proposed method provides an approach that analyzes competitor positioning and formulates response strategies to forecast the impact of technical design choices on a project's market performance. A critical decision in the conceptual design phase of propulsion systems is the selection of the best architecture, centerline, core size, and technology portfolio. This selection can be challenging when considering evolving requirements from both the airframe manufacturing company and the airlines in the market. Furthermore, the exceedingly high cost of core architecture development and its associated risk makes this strategic architecture decision the most important one for an engine company. Traditional conceptual design processes emphasize performance and affordability as their main objectives. These areas alone however, do not provide decision-makers with enough information as to how successful their engine will be in a competitive market. A key objective of this research is to examine how firm characteristics such as their relative differences in completing R&D projects, differences in the degree of substitutability between different project types, and first/second-mover advantages affect their product development strategies. Several quantitative methods are investigated that analyze business and engineering strategies concurrently. In particular, formulations based on the well-established mathematical field of game theory are introduced to obtain insights into the project selection problem. The use of game theory is explored in this research as a method to assist the selection process of R&D projects in the presence of imperfect market information. The proposed methodology focuses on two influential factors: the schedule uncertainty of project completion times and the uncertainty associated with competitive reactions. A normal-form matrix is created to enumerate players, their moves and payoffs, and to formulate a process by which an optimal decision can be achieved. The non-cooperative model is tested using the concept of a Nash equilibrium to identify potential strategies that are robust to uncertain market fluctuations (e.g: uncertainty in airline demand, airframe requirements and competitor positioning). A first/second-mover advantage parameter is used as a scenario dial to adjust market rewards and firms' payoffs. The methodology is applied to a commercial aircraft engine selection study where engine firms must select an optimal engine project for development. An engine modeling and simulation framework is developed to generate a broad engine project portfolio. The creation of a customer value model enables designers to incorporate airline operation characteristics into the engine modeling and simulation process to improve the accuracy of engine/customer matching. Summary. Several key findings are made that provide recommendations on project selection strategies for firms uncertain as to when they will enter the market. The proposed study demonstrates that within a technical design environment, a rational and analytical means of modeling project development strategies is beneficial in high market risk situations.

Communication Simulations for Power System Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fuller, Jason C.; Ciraci, Selim; Daily, Jeffrey A.

2013-05-29

New smart grid technologies and concepts, such as dynamic pricing, demand response, dynamic state estimation, and wide area monitoring, protection, and control, are expected to require considerable communication resources. As the cost of retrofit can be high, future power grids will require the integration of high-speed, secure connections with legacy communication systems, while still providing adequate system control and security. While considerable work has been performed to create co-simulators for the power domain with load models and market operations, limited work has been performed in integrating communications directly into a power domain solver. The simulation of communication and power systemsmore » will become more important as the two systems become more inter-related. This paper will discuss ongoing work at Pacific Northwest National Laboratory to create a flexible, high-speed power and communication system co-simulator for smart grid applications. The framework for the software will be described, including architecture considerations for modular, high performance computing and large-scale scalability (serialization, load balancing, partitioning, cross-platform support, etc.). The current simulator supports the ns-3 (telecommunications) and GridLAB-D (distribution systems) simulators. Ongoing and future work will be described, including planned future expansions for a traditional transmission solver. A test case using the co-simulator, utilizing a transactive demand response system created for the Olympic Peninsula and AEP gridSMART demonstrations, requiring two-way communication between distributed and centralized market devices, will be used to demonstrate the value and intended purpose of the co-simulation environment.« less

Are stock prices too volatile to be justified by the dividend discount model?

NASA Astrophysics Data System (ADS)

Akdeniz, Levent; Salih, Aslıhan Altay; Ok, Süleyman Tuluğ

2007-03-01

This study investigates excess stock price volatility using the variance bound framework of LeRoy and Porter [The present-value relation: tests based on implied variance bounds, Econometrica 49 (1981) 555-574] and of Shiller [Do stock prices move too much to be justified by subsequent changes in dividends? Am. Econ. Rev. 71 (1981) 421-436.]. The conditional variance bound relationship is examined using cross-sectional data simulated from the general equilibrium asset pricing model of Brock [Asset prices in a production economy, in: J.J. McCall (Ed.), The Economics of Information and Uncertainty, University of Chicago Press, Chicago (for N.B.E.R.), 1982]. Results show that the conditional variance bounds hold, hence, our hypothesis of the validity of the dividend discount model cannot be rejected. Moreover, in our setting, markets are efficient and stock prices are neither affected by herd psychology nor by the outcome of noise trading by naive investors; thus, we are able to control for market efficiency. Consequently, we show that one cannot infer any conclusions about market efficiency from the unconditional variance bounds tests.

Local and global analysis of a speculative housing market with production lag

NASA Astrophysics Data System (ADS)

Campisi, Giovanni; Naimzada, Ahmad K.; Tramontana, Fabio

2018-05-01

We extend the model of Dieci and Westerhoff [J. Evol. Econ. 22(2), 303-329 (2012)], where the authors analyse a speculative housing market populated by heterogeneous interacting agents described by a two dimensional nonlinear discrete time dynamical system. They show the emergence of complicated dynamics through the occurrence of bifurcations for particular parameter combinations. We enlarge their model in several ways. On one hand, we introduce time lag in the supply side and we consider two new scenarios characterised by agents' expectations formation. First, naive expectations instead of perfect foresight are considered, while in the second scenario, we study a mix between the model of Dieci and Westerhoff [J. Evol. Econ. 22(2), 303-329 (2012)] and the one we propose. As a consequence, we, analytically and numerically, explain the appearance of instability in the housing market providing conditions on the parameters that lead to a bifurcation. On the other hand, thanks to further numerical simulations, we conduct a global analysis providing the structure of the basin of attractions of the map showing coexistence of attractors.

Coupled Oscillator Model of the Business Cycle withFluctuating Goods Markets

NASA Astrophysics Data System (ADS)

Ikeda, Y.; Aoyama, H.; Fujiwara, Y.; Iyetomi, H.; Ogimoto, K.; Souma, W.; Yoshikawa, H.

The sectoral synchronization observed for the Japanese business cycle in the Indices of Industrial Production data is an example of synchronization. The stability of this synchronization under a shock, e.g., fluctuation of supply or demand, is a matter of interest in physics and economics. We consider an economic system made up of industry sectors and goods markets in order to analyze the sectoral synchronization observed for the Japanese business cycle. A coupled oscillator model that exhibits synchronization is developed based on the Kuramoto model with inertia by adding goods markets, and analytic solutions of the stationary state and the coupling strength are obtained. We simulate the effects on synchronization of a sectoral shock for systems with different price elasticities and the coupling strengths. Synchronization is reproduced as an equilibrium solution in a nearest neighbor graph. Analysis of the order parameters shows that the synchronization is stable for a finite elasticity, whereas the synchronization is broken and the oscillators behave like a giant oscillator with a certain frequency additional to the common frequency for zero elasticity.

Impacts of renewable fuel regulation and production on agriculture, energy, and welfare

NASA Astrophysics Data System (ADS)

McPhail, Lihong Lu

The purpose of this dissertation is to study the impact of U.S. federal renewable fuel regulations on energy and agriculture commodity markets and welfare. We consider two federal ethanol policies: the Renewable Fuel Standard (RFS) contained in the Energy Security and Independence Act of 2007 and tax credits to ethanol blenders contained in the Food, Conservation, and Energy Act of 2008. My first essay estimates the distribution of short-run impacts of changing federal ethanol policies on U.S. energy prices, agricultural commodity prices, and welfare through a stochastic partial equilibrium model of U.S. corn, ethanol, and gasoline markets. My second essay focuses on studying the price behavior of the renewable fuel credit (RFC) market, which is the mechanism developed by the Environmental Protection Agency (EPA) to meet the RFS. RFCs are a tradable, bankable, and borrowable accounting mechanism to ensure that all obligated parties use a mandated level of renewable fuel. I first develop a conceptual framework to understand how the market works and then apply stochastic dynamic programming to simulate prices for RFCs, examine the sensitivity of prices to relevant shocks, and estimate RFC option premiums. My third essay assesses the impact of policy led U.S. ethanol on the markets of global crude oil and U.S. gasoline using a structural Vector Auto Regression model of global crude oil, U.S. gasoline and ethanol markets.

Complexity study on the Cournot-Bertrand mixed duopoly game model with market share preference

NASA Astrophysics Data System (ADS)

Ma, Junhai; Sun, Lijian; Hou, Shunqi; Zhan, Xueli

2018-02-01

In this paper, a Cournot-Bertrand duopoly model with market share preference is established. Assume that there is a degree of product difference between the two firms, where one firm takes the price as a decision variable and the other takes the quantity. Both firms are bounded rational, with linear cost functions and demand functions. The stability of the equilibrium points is analyzed, and the effects of some parameters (α, β, d and v1) on the model stability are studied. Basins of attraction are investigated and the evolution process is shown with the increase in the output adjustment speed. The simulation results show that instability will lead to the increase in the average utility of the firm that determines the quantity and reduce the average utility of the firm that determines price.

Factors Contributing to Cognitive Absorption and Grounded Learning Effectiveness in a Competitive Business Marketing Simulation

ERIC Educational Resources Information Center

Baker, David Scott; Underwood, James, III; Thakur, Ramendra

2017-01-01

This study aimed to establish a pedagogical positioning of a business marketing simulation as a grounded learning teaching tool and empirically assess the dimensions of cognitive absorption related to grounded learning effectiveness in an iterative business simulation environment. The method/design and sample consisted of a field study survey…

Smart Markets for Water Resources

NASA Astrophysics Data System (ADS)

Raffensperger, John

2017-04-01

Commercial water users often want to trade water, but their trades can hurt other users and the environment. So government has to check every transaction. This checking process is slow and expensive. That's why "free market" water trading doesn't work, especially with trading between a single buyer and a single seller. This talk will describe a water trading mechanism designed to solve these problems. The trading mechanism is called a "smart market". A smart market allows simultaneous many-to-many trades. It can reduce the transaction costs of water trading, while improving environmental outcomes. The smart market depends on a combination of recent technologies: hydrology simulation, computer power, and the Internet. Our smart market design uses standard hydrological models, user bids from a web page, and computer optimization to maximize the economic value of water while meeting all environmental constraints. Before the smart market can be implemented, however, users and the water agency must meet six critical prerequisites. These prerequisites may be viewed as simply good water management that should be done anyway. I will describe these prerequisites, and I will briefly discuss common arguments against water markets. This talk will be an abstract of a forthcoming book, "Smart Markets for Water Resources: A Manual for Implementation," by John F. Raffensperger and Mark W. Milke, from Springer Publishing.

ADOPT: Automotive Deployment Options Projection Tool | Transportation

Science.gov Websites

new model options by combining high-selling powertrains and high-selling vehicle platforms. NREL has . Screenshot of the ADOPT user interface, with two simulation scenario options (low tech and high tech emissions. Biomass Market Dynamics Supporting the Large-Scale Deployment of High-Octane Fuel Production in

Growth Dynamics of Information Search Services.

ERIC Educational Resources Information Center

Lindqvist, Mats

Computer based information search services, ISS's, of the type that provide on-line literature searches are analyzed from a system's viewpoint using a continuous simulation model. The analysis shows that the observed growth and stagnation of a typical ISS can be explained as a natural consequence of market responses to the service together with a…

Remote control circuit breaker evaluation testing. [for space shuttles

NASA Technical Reports Server (NTRS)

Bemko, L. M.

1974-01-01

Engineering evaluation tests were performed on several models/types of remote control circuit breakers marketed in an attempt to gain some insight into their potential suitability for use on the space shuttle vehicle. Tests included the measurement of several electrical and operational performance parameters under laboratory ambient, space simulation, acceleration and vibration environmental conditions.

Financial price dynamics and pedestrian counterflows: A comparison of statistical stylized facts

NASA Astrophysics Data System (ADS)

Parisi, Daniel R.; Sornette, Didier; Helbing, Dirk

2013-01-01

We propose and document the evidence for an analogy between the dynamics of granular counterflows in the presence of bottlenecks or restrictions and financial price formation processes. Using extensive simulations, we find that the counterflows of simulated pedestrians through a door display eight stylized facts observed in financial markets when the density around the door is compared with the logarithm of the price. Finding so many stylized facts is very rare indeed among all agent-based models of financial markets. The stylized properties are present when the agents in the pedestrian model are assumed to display a zero-intelligent behavior. If agents are given decision-making capacity and adapt to partially follow the majority, periods of herding behavior may additionally occur. This generates the very slow decay of the autocorrelation of absolute return due to an intermittent dynamics. Our findings suggest that the stylized facts in the fluctuations of the financial prices result from a competition of two groups with opposite interests in the presence of a constraint funneling the flow of transactions to a narrow band of prices with limited liquidity.

Financial price dynamics and pedestrian counterflows: a comparison of statistical stylized facts.

PubMed

Parisi, Daniel R; Sornette, Didier; Helbing, Dirk

2013-01-01

We propose and document the evidence for an analogy between the dynamics of granular counterflows in the presence of bottlenecks or restrictions and financial price formation processes. Using extensive simulations, we find that the counterflows of simulated pedestrians through a door display eight stylized facts observed in financial markets when the density around the door is compared with the logarithm of the price. Finding so many stylized facts is very rare indeed among all agent-based models of financial markets. The stylized properties are present when the agents in the pedestrian model are assumed to display a zero-intelligent behavior. If agents are given decision-making capacity and adapt to partially follow the majority, periods of herding behavior may additionally occur. This generates the very slow decay of the autocorrelation of absolute return due to an intermittent dynamics. Our findings suggest that the stylized facts in the fluctuations of the financial prices result from a competition of two groups with opposite interests in the presence of a constraint funneling the flow of transactions to a narrow band of prices with limited liquidity.

Portfolio-Scale Optimization of Customer Energy Efficiency Incentive and Marketing: Cooperative Research and Development Final Report, CRADA Number CRD-13-535

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brackney, Larry J.

North East utility National Grid (NGrid) is developing a portfolio-scale application of OpenStudio designed to optimize incentive and marketing expenditures for their energy efficiency (EE) programs. NGrid wishes to leverage a combination of geographic information systems (GIS), public records, customer data, and content from the Building Component Library (BCL) to form a JavaScript Object Notation (JSON) input file that is consumed by an OpenStudio-based expert system for automated model generation. A baseline model for each customer building will be automatically tuned using electricity and gas consumption data, and a set of energy conservation measures (ECMs) associated with each NGrid incentivemore » program will be applied to the model. The simulated energy performance and return on investment (ROI) will be compared with customer hurdle rates and available incentives to A) optimize the incentive required to overcome the customer hurdle rate and B) determine if marketing activity associated with the specific ECM is warranted for that particular customer. Repeated across their portfolio, this process will enable NGrid to substantially optimize their marketing and incentive expenditures, targeting those customers that will likely adopt and benefit from specific EE programs.« less

MASM: a market architecture for sensor management in distributed sensor networks

NASA Astrophysics Data System (ADS)

Viswanath, Avasarala; Mullen, Tracy; Hall, David; Garga, Amulya

2005-03-01

Rapid developments in sensor technology and its applications have energized research efforts towards devising a firm theoretical foundation for sensor management. Ubiquitous sensing, wide bandwidth communications and distributed processing provide both opportunities and challenges for sensor and process control and optimization. Traditional optimization techniques do not have the ability to simultaneously consider the wildly non-commensurate measures involved in sensor management in a single optimization routine. Market-oriented programming provides a valuable and principled paradigm to designing systems to solve this dynamic and distributed resource allocation problem. We have modeled the sensor management scenario as a competitive market, wherein the sensor manager holds a combinatorial auction to sell the various items produced by the sensors and the communication channels. However, standard auction mechanisms have been found not to be directly applicable to the sensor management domain. For this purpose, we have developed a specialized market architecture MASM (Market architecture for Sensor Management). In MASM, the mission manager is responsible for deciding task allocations to the consumers and their corresponding budgets and the sensor manager is responsible for resource allocation to the various consumers. In addition to having a modified combinatorial winner determination algorithm, MASM has specialized sensor network modules that address commensurability issues between consumers and producers in the sensor network domain. A preliminary multi-sensor, multi-target simulation environment has been implemented to test the performance of the proposed system. MASM outperformed the information theoretic sensor manager in meeting the mission objectives in the simulation experiments.

Nonlinear stochastic exclusion financial dynamics modeling and time-dependent intrinsic detrended cross-correlation

NASA Astrophysics Data System (ADS)

Zhang, Wei; Wang, Jun

2017-09-01

In attempt to reproduce price dynamics of financial markets, a stochastic agent-based financial price model is proposed and investigated by stochastic exclusion process. The exclusion process, one of interacting particle systems, is usually thought of as modeling particle motion (with the conserved number of particles) in a continuous time Markov process. In this work, the process is utilized to imitate the trading interactions among the investing agents, in order to explain some stylized facts found in financial time series dynamics. To better understand the correlation behaviors of the proposed model, a new time-dependent intrinsic detrended cross-correlation (TDI-DCC) is introduced and performed, also, the autocorrelation analyses are applied in the empirical research. Furthermore, to verify the rationality of the financial price model, the actual return series are also considered to be comparatively studied with the simulation ones. The comparison results of return behaviors reveal that this financial price dynamics model can reproduce some correlation features of actual stock markets.

An Empirical Model of the Medical Match.

PubMed

Agarwal, Nikhil

2015-07-01

This paper develops a framework for estimating preferences in a many-to-one matching market using only observed matches. I use pairwise stability and a vertical preference restriction on one side to identify preferences on both sides of the market. Counterfactual simulations are used to analyze the antitrust allegation that the centralized medical residency match is responsible for salary depression. Due to residents' willingness to pay for desirable programs and capacity constraints, salaries in any competitive equilibrium would remain, on average, at least $23,000 below the marginal product of labor. Therefore, the match is not the likely cause of low salaries.

Microsimulation of private health insurance and medicaid take-up following the U.S. Supreme court decision upholding the Affordable Care Act.

PubMed

Parente, Stephen T; Feldman, Roger

2013-04-01

To predict take-up of private health insurance and Medicaid following the U.S. Supreme Court decision upholding the Affordable Care Act (ACA). Data came from three large employers and a sampling of premiums from ehealthinsurance.com. We supplemented the employer data with information on state Medicaid eligibility and costs from the Kaiser Family Foundation. National predictions were based on the MEPS Household Component. We estimated a conditional logit model of health plan choice in the large group market. Using the coefficients from the choice model, we predicted take-up in the group and individual health insurance markets. Following ACA implementation, we added choices to the individual market corresponding to plans that will be available in state and federal exchanges. Depending on eligibility for premium subsidies, we reduced the out-of-pocket premiums for those choices. We simulated several possible patterns for states opting out of the Medicaid expansion, as allowed by the Supreme Court. The ACA will increase coverage substantially in the private insurance market and Medicaid. HSAs will remain desirable in both the individual and employer markets. If states opt out of the Medicaid expansion, this could increase the federal cost of health reform, while reducing the number of newly covered lives. © Health Research and Educational Trust.

Agent-based model with multi-level herding for complex financial systems

NASA Astrophysics Data System (ADS)

Chen, Jun-Jie; Tan, Lei; Zheng, Bo

2015-02-01

In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level.

Agent-based model with multi-level herding for complex financial systems

PubMed Central

Chen, Jun-Jie; Tan, Lei; Zheng, Bo

2015-01-01

In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level. PMID:25669427

Agent-based spin model for financial markets on complex networks: Emergence of two-phase phenomena

NASA Astrophysics Data System (ADS)

Kim, Yup; Kim, Hong-Joo; Yook, Soon-Hyung

2008-09-01

We study a microscopic model for financial markets on complex networks, motivated by the dynamics of agents and their structure of interaction. The model consists of interacting agents (spins) with local ferromagnetic coupling and global antiferromagnetic coupling. In order to incorporate more realistic situations, we also introduce an external field which changes in time. From numerical simulations, we find that the model shows two-phase phenomena. When the local ferromagnetic interaction is balanced with the global antiferromagnetic interaction, the resulting return distribution satisfies a power law having a single peak at zero values of return, which corresponds to the market equilibrium phase. On the other hand, if local ferromagnetic interaction is dominant, then the return distribution becomes double peaked at nonzero values of return, which characterizes the out-of-equilibrium phase. On random networks, the crossover between two phases comes from the competition between two different interactions. However, on scale-free networks, not only the competition between the different interactions but also the heterogeneity of underlying topology causes the two-phase phenomena. Possible relationships between the critical phenomena of spin system and the two-phase phenomena are discussed.

Vulnerability of Agriculture to Climate Change as Revealed by Relationships between Simulated Crop Yield and Climate Change Indices

NASA Astrophysics Data System (ADS)

King, A. W.; Absar, S. M.; Nair, S.; Preston, B. L.

2012-12-01

The vulnerability of agriculture is among the leading concerns surrounding climate change. Agricultural production is influenced by drought and other extremes in weather and climate. In regions of subsistence farming, worst case reductions in yield lead to malnutrition and famine. Reduced surplus contributes to poverty in agrarian economies. In more economically diverse and industrialized regions, variations in agricultural yield can influence the regional economy through market mechanisms. The latter grows in importance as agriculture increasingly services the energy market in addition to markets for food and fiber. Agriculture is historically a highly adaptive enterprise and will respond to future changes in climate with a variety of adaptive mechanisms. Nonetheless, the risk, if not expectation, of increases in climate extremes and hazards exceeding historical experience motivates scientifically based anticipatory assessment of the vulnerability of agriculture to climate change. We investigate the sensitivity component of that vulnerability using EPIC, a well established field-scale model of cropping systems that includes the simulation of economic yield. The core of our analysis is the relationship between simulated yield and various indices of climate change, including the CCI/CLIVAR/JCOM ETCCDI indices, calculated from weather inputs to the model. We complement this core with analysis using the DSSAT cropping system model and exploration of relationships between historical yield statistics and climate indices calculated from weather records. Our analyses are for sites in the Southeast/Gulf Coast region of the United States. We do find "tight" monotonic relationships between annual yield and climate for some indices, especially those associated with available water. More commonly, however, we find an increase in the variability of yield as the index value becomes more extreme. Our findings contribute to understanding the sensitivity of crop yield as part of vulnerability analysis. They also contribute to considerations of adaptation, focusing attention on adapting to increased variability in yield rather than just reductions in yield. For example, in the face of increased variability or reduced reliability, hedging and risk spreading strategies may be more important than technological innovations such as drought-resistant crops or other optimization strategies. Our findings also have implications for the choice and application of climate extreme indices, demands on models used to project climate change and the development of next generation integrated assessment models (IAM) that incorporate the agricultural sector, and especially adaption within that sector, in energy and broader more general markets.

Arrhythmic risk biomarkers for the assessment of drug cardiotoxicity: from experiments to computer simulations

PubMed Central

Corrias, A.; Jie, X.; Romero, L.; Bishop, M. J.; Bernabeu, M.; Pueyo, E.; Rodriguez, B.

2010-01-01

In this paper, we illustrate how advanced computational modelling and simulation can be used to investigate drug-induced effects on cardiac electrophysiology and on specific biomarkers of pro-arrhythmic risk. To do so, we first perform a thorough literature review of proposed arrhythmic risk biomarkers from the ionic to the electrocardiogram levels. The review highlights the variety of proposed biomarkers, the complexity of the mechanisms of drug-induced pro-arrhythmia and the existence of significant animal species differences in drug-induced effects on cardiac electrophysiology. Predicting drug-induced pro-arrhythmic risk solely using experiments is challenging both preclinically and clinically, as attested by the rise in the cost of releasing new compounds to the market. Computational modelling and simulation has significantly contributed to the understanding of cardiac electrophysiology and arrhythmias over the last 40 years. In the second part of this paper, we illustrate how state-of-the-art open source computational modelling and simulation tools can be used to simulate multi-scale effects of drug-induced ion channel block in ventricular electrophysiology at the cellular, tissue and whole ventricular levels for different animal species. We believe that the use of computational modelling and simulation in combination with experimental techniques could be a powerful tool for the assessment of drug safety pharmacology. PMID:20478918

Transient dynamics in trial-offer markets with social influence: Trade-offs between appeal and quality

PubMed Central

Altszyler, Edgar; Berbeglia, Franco; Van Hentenryck, Pascal

2017-01-01

We study a trial-offer market where consumers may purchase one of two competing products. Consumer preferences are affected by the products quality, their appeal, and their popularity. While the asymptotic convergence or stationary states of these, and related dynamical systems, has been vastly studied, the literature regarding the transitory dynamics remains surprisingly sparse. To fill this gap, we derive a system of Ordinary Differential Equations, which is solved exactly to gain insight into the roles played by product qualities and appeals in the market behavior. We observe a logarithmic tradeoff between quality and appeal for medium and long-term marketing strategies: The expected market shares remain constant if a decrease in quality is followed by an exponential increase in the product appeal. However, for short time horizons, the trade-off is linear. Finally, we study the variability of the dynamics through Monte Carlo simulations and discover that low appeals may result in high levels of variability. The model results suggest effective marketing strategies for short and long time horizons and emphasize the significance of advertising early in the market life to increase sales and predictability. PMID:28746334

Transient dynamics in trial-offer markets with social influence: Trade-offs between appeal and quality.

PubMed

Altszyler, Edgar; Berbeglia, Franco; Berbeglia, Gerardo; Van Hentenryck, Pascal

2017-01-01

We study a trial-offer market where consumers may purchase one of two competing products. Consumer preferences are affected by the products quality, their appeal, and their popularity. While the asymptotic convergence or stationary states of these, and related dynamical systems, has been vastly studied, the literature regarding the transitory dynamics remains surprisingly sparse. To fill this gap, we derive a system of Ordinary Differential Equations, which is solved exactly to gain insight into the roles played by product qualities and appeals in the market behavior. We observe a logarithmic tradeoff between quality and appeal for medium and long-term marketing strategies: The expected market shares remain constant if a decrease in quality is followed by an exponential increase in the product appeal. However, for short time horizons, the trade-off is linear. Finally, we study the variability of the dynamics through Monte Carlo simulations and discover that low appeals may result in high levels of variability. The model results suggest effective marketing strategies for short and long time horizons and emphasize the significance of advertising early in the market life to increase sales and predictability.

Geosimulation of urban growth and demographic decline in the Ruhr: a case study for 2025 using the artificial intelligence of cells and agents

NASA Astrophysics Data System (ADS)

Rienow, Andreas; Stenger, Dirk

2014-07-01

The Ruhr is an "old acquaintance" in the discourse of urban decline in old industrialized cities. The agglomeration has to struggle with archetypical problems of former monofunctional manufacturing cities. Surprisingly, the image of a shrinking city has to be refuted if you shift the focus from socioeconomic wealth to its morphological extension. Thus, it is the objective of this study to meet the challenge of modeling urban sprawl and demographic decline by combining two artificial intelligent solutions: The popular urban cellular automaton SLEUTH simulates urban growth using four simple but effective growth rules. In order to improve its performance, SLEUTH has been modified among others by combining it with a robust probability map based on support vector machines. Additionally, a complex multi-agent system is developed to simulate residential mobility in a shrinking city agglomeration: residential mobility and the housing market of shrinking city systems focuses on the dynamic of interregional housing markets implying the development of potential dwelling areas. The multi-agent system comprises the simulation of population patterns, housing prices, and housing demand in shrinking city agglomerations. Both models are calibrated and validated regarding their localization and quantification performance. Subsequently, the urban landscape configuration and composition of the Ruhr 2025 are simulated. A simple spatial join is used to combine the results serving as valuable inputs for future regional planning in the context of multifarious demographic change and preceding urban growth.

Timing is everything :

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kobos, Peter Holmes; Walker, La Tonya Nicole; Malczynski, Leonard A.

People save for retirement throughout their career because it is virtually impossible to save all youll need in retirement the year before you retire. Similarly, without installing incremental amounts of clean fossil, renewable or transformative energy technologies throughout the coming decades, a radical and immediate change will be near impossible the year before a policy goal is set to be in place. Therefore, our research question is, To meet our desired technical and policy goals, what are the factors that affect the rate we must install technology to achieve these goals in the coming decades? Existing models do not includemore » full regulatory constraints due to their often complex, and inflexible approaches to solve for optimal engineering instead of robust and multidisciplinary solutions. This project outlines the theory and then develops an applied software tool to model the laboratory-to-market transition using the traditional technology readiness level (TRL) framework, but develops subsequent and a novel regulatory readiness level (RRL) and market readiness level (MRL). This tool uses the ideally-suited system dynamics framework to incorporate feedbacks and time delays. Future energy-economic-environment models, regardless of their programming platform, may adapt this software model component framework or module to further vet the likelihood of new or innovative technology moving through the laboratory, regulatory and market space. The prototype analytical framework and tool, called the Technology, Regulatory and Market Readiness Level simulation model (TRMsim) illustrates the interaction between technology research, application, policy and market dynamics as they relate to a new or innovative technology moving from the theoretical stage to full market deployment. The initial results that illustrate the models capabilities indicate for a hypothetical technology, that increasing the key driver behind each of the TRL, RRL and MRL components individually decreases the time required for the technology to progress through each component by 63, 68 and 64%, respectively. Therefore, under the current working assumptions, to decrease the time it may take for a technology to move from the conceptual stage to full scale market adoption one might consider expending additional effort to secure regulatory approval and reducing the uncertainty of the technologys demand in the marketplace.« less

Evolving dynamics of trading behavior based on coordination game in complex networks

NASA Astrophysics Data System (ADS)

Bian, Yue-tang; Xu, Lu; Li, Jin-sheng

2016-05-01

This work concerns the modeling of evolvement of trading behavior in stock markets. Based on the assumption of the investors' limited rationality, the evolution mechanism of trading behavior is modeled according to the investment strategy of coordination game in network, that investors are prone to imitate their neighbors' activity through comprehensive analysis on the risk dominance degree of certain investment behavior, the network topology of their relationship and its heterogeneity. We investigate by mean-field analysis and extensive simulations the evolution of investors' trading behavior in various typical networks under different risk dominance degree of investment behavior. Our results indicate that the evolution of investors' behavior is affected by the network structure of stock market and the effect of risk dominance degree of investment behavior; the stability of equilibrium states of investors' behavior dynamics is directly related with the risk dominance degree of some behavior; connectivity and heterogeneity of the network plays an important role in the evolution of the investment behavior in stock market.

What will happen to retirement income for 401(k) participants after the market decline?

PubMed

VanDerhei, Jack

2010-04-01

This paper uses administrative data from millions of 401(k) participants dating back to 1996 as well as several simulation models to determine 401(k) plans' susceptibility to several alleged limitations as well as its potential for significant retirement wealth accumulation for employees working for employers who have chosen to sponsor these plans. What will happen to 401(k) participants after the 2008 market decline will be largely determined by the extent to which the features of automatic enrollment, automatic escalation of contributions, and automatic investment are allowed to play out. Simulation results suggest that the first two features will significantly improve retirement wealth for the lowest-income quartiles going forward, and the third feature (primarily target-date funds) suggest that a large percentage of those on the verge of retirement would benefit significantly by a reduction of equity concentrations to a more age-appropriate level.

Teaching Marketing Strategy: Using Resource-Advantage Theory as an Integrative Theoretical Foundation

ERIC Educational Resources Information Center

Hunt, Shelby D.; Madhavaram, Sreedhar

2006-01-01

Knowledge of marketing strategy is essential for marketing majors. To supplement and/or replace the traditional lecture-discussion approach, several pedagogical vehicles have been recommended to teach marketing strategy, including the analytic hierarchy process; career-planning cases; computer-assisted, simulated marketing cases; experiential…

Socioeconophysics:. Opinion Dynamics for Number of Transactions and Price, a Trader Based Model

NASA Astrophysics Data System (ADS)

Tuncay, Çağlar

Involving effects of media, opinion leader and other agents on the opinion of individuals of market society, a trader based model is developed and utilized to simulate price via supply and demand. Pronounced effects are considered with several weights and some personal differences between traders are taken into account. Resulting time series and probabilty distribution function involving a power law for price come out similar to the real ones.

[Effects of pharmacy market deregulation regarding patient-centred drug care in Germany from a health economics perspecitve].

PubMed

Rumm, R; Böcking, W

2013-03-01

This article analyses the impact of a potential deregulation Germany's pharmacy market by allowing foreign ownership of pharmacies and removing the limit of the number pharmacies that can be owned by a pharmacist. Based on a mathematical model and empirical values of foreign countries, scenarios for the German market are calculated and the impact on all participants of the health care system analysed. The key outcomes are:- A deregulation would enables the creation of pharmacy chains- In all simulated scenarios the total number of pharmacies would drastically grow- The increased pharmacy density improves patient centred drug care- The competition among pharmacies increases and leads to the closure of many independently owned and operated pharmacies. © Georg Thieme Verlag KG Stuttgart · New York.

An open data repository and a data processing software toolset of an equivalent Nordic grid model matched to historical electricity market data.

PubMed

Vanfretti, Luigi; Olsen, Svein H; Arava, V S Narasimham; Laera, Giuseppe; Bidadfar, Ali; Rabuzin, Tin; Jakobsen, Sigurd H; Lavenius, Jan; Baudette, Maxime; Gómez-López, Francisco J

2017-04-01

This article presents an open data repository, the methodology to generate it and the associated data processing software developed to consolidate an hourly snapshot historical data set for the year 2015 to an equivalent Nordic power grid model (aka Nordic 44), the consolidation was achieved by matching the model׳s physical response w.r.t historical power flow records in the bidding regions of the Nordic grid that are available from the Nordic electricity market agent, Nord Pool. The model is made available in the form of CIM v14, Modelica and PSS/E (Siemens PTI) files. The Nordic 44 model in Modelica and PSS/E were first presented in the paper titled "iTesla Power Systems Library (iPSL): A Modelica library for phasor time-domain simulations" (Vanfretti et al., 2016) [1] for a single snapshot. In the digital repository being made available with the submission of this paper (SmarTSLab_Nordic44 Repository at Github, 2016) [2], a total of 8760 snapshots (for the year 2015) that can be used to initialize and execute dynamic simulations using tools compatible with CIM v14, the Modelica language and the proprietary PSS/E tool are provided. The Python scripts to generate the snapshots (processed data) are also available with all the data in the GitHub repository (SmarTSLab_Nordic44 Repository at Github, 2016) [2]. This Nordic 44 equivalent model was also used in iTesla project (iTesla) [3] to carry out simulations within a dynamic security assessment toolset (iTesla, 2016) [4], and has been further enhanced during the ITEA3 OpenCPS project (iTEA3) [5]. The raw, processed data and output models utilized within the iTesla platform (iTesla, 2016) [4] are also available in the repository. The CIM and Modelica snapshots of the "Nordic 44" model for the year 2015 are available in a Zenodo repository.

Long-term consequences of selected competitive strategies during deregulation of the United States electric utility industry: System dynamics modeling and simulation

NASA Astrophysics Data System (ADS)

Khalil, Yehia Fahim

Currently, U.S. investor-owned utilities (IOUs) are facing major reforms in their business environment similar to the airlines, telecommunications, banking, and insurance industries. As a result, IOUs are gearing up for fierce price competition in the power generation sector, and are vying for electricity customers outside their franchised service territories. Energy experts predict that some IOUs may suffer fatal financial setbacks (especially those with nuclear plants), while others may thrive under competition. Both federal and state energy regulators anticipate that it may take from five to ten years to complete the transition of America's electric utility industry from a regulated monopoly to a market-driven business. During this transition, utility executives are pursuing aggressive business strategies to confront the upcoming price wars. The most compelling strategies focus on cutting operation and maintenance (O&M) costs of power production, downsizing the work force, and signing bilateral energy agreements with large price-sensitive customers to retain their business. This research assesses the impact of the three pivotal strategies on financial performance of utilities during transition to open market competition. A system-dynamics-based management flight simulator has been developed to predict the dynamic performance of a hypothetical IOU organization preparing for market competition. The simulation results show that while the three business strategies lead to short-lived gains, they also produce unanticipated long-term consequences that adversely impact the organization's operating revenues. Generally, the designed flight simulator serves as a learning laboratory which allows management to test new strategies before implementation.

Medical imaging technology shock and volatility of macro economics: Analysis using a three-sector dynamical stochastic general equilibrium REC model.

PubMed

Han, Shurong; Huang, Yeqing

2017-07-07

The study analysed the medical imaging technology business cycle from 1981 to 2009 and found that the volatility of consumption in Chinese medical imaging business was higher than that of the developed countries. The volatility of gross domestic product (GDP) and the correlation between consumption and GDP is also higher than that of the developed countries. Prior to the early 1990s the volatility of consumption is even higher than GDP. This fact makes it difficult to explain the volatile market using the standard one sector real economic cycle (REC) model. Contrary to the other domestic studies, this study considers a three-sector dynamical stochastic general equilibrium REC model. In this model there are two consumption sectors, whereby one is labour intensive and another is capital intensive. The more capital intensive investment sector only introduces technology shocks in the medical imaging market. Our response functions and Monte-Carlo simulation results show that the model can explain 90% of the volatility of consummation relative to GDP, and explain the correlation between consumption and GDP. The results demonstrated the significant correlation between the technological reform in medical imaging and volatility in the labour market on Chinese macro economy development.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ehlen, Mark A.; Sun, Amy C.; Pepple, Mark A.

The potential impacts of man-made and natural disasters on chemical plants, complexes, and supply chains are of great importance to homeland security. To be able to estimate these impacts, we developed an agent-based chemical supply chain model that includes: chemical plants with enterprise operations such as purchasing, production scheduling, and inventories; merchant chemical markets, and multi-modal chemical shipments. Large-scale simulations of chemical-plant activities and supply chain interactions, running on desktop computers, are used to estimate the scope and duration of disruptive-event impacts, and overall system resilience, based on the extent to which individual chemical plants can adjust their internal operationsmore » (e.g., production mixes and levels) versus their external interactions (market sales and purchases, and transportation routes and modes). As a result, to illustrate how the model estimates the impacts of a hurricane disruption, a simple example model centered on 1,4-butanediol is presented.« less

Modelling diffusion feedbacks between technology performance, cost and consumer behaviour for future energy-transport systems

NASA Astrophysics Data System (ADS)

Tran, Martino; Brand, Christian; Banister, David

2014-04-01

Emerging technologies will have important impacts on sustainability objectives. Yet little is known about the explicit feedbacks between consumer behaviour and technological change, and the potential impact on mass market penetration. We use the UK as a case-study to explore the dynamic interactions between technology supply, performance, cost, and heterogeneous consumer behaviour and the resulting influence on long term market diffusion. Simulations of competing vehicle technologies indicate that petrol hybrids (HEVs) dominate the market over the long-term because they benefit from improved performance and are able to reach the steep part of the diffusion curve by 2025 while competing technologies remain in the early stages of growth and are easier to displace in the market. This is due to the cumulative build-up of stock and slow fleet turnover creating inertia in the technological system. Consequently, it will be difficult to displace incumbent technologies because of system inertia, cumulative growth in stock, long operational life, and consumer risk aversion to new unproven technologies. However, when accounting for both technological and behavioural change, simulations indicate that if investment can reach 30-40% per annum growth in supply, combined with steady technology improvements, and more sophisticated agent decision making such as accounting for full technology lifecycle cost and performance, full battery electric vehicles could displace the incumbent system by 2050.

Modelled female sale options demonstrate improved profitability in northern beef herds.

PubMed

Niethe, G E; Holmes, W E

2008-12-01

To examine the impact of improving the average value of cows sold, the risk of decreasing the number weaned, and total sales on the profitability of northern Australian cattle breeding properties. Gather, model and interpret breeder herd performances and production parameters on properties from six beef-producing regions in northern Australia. Production parameters, prices, costs and herd structure were entered into a herd simulation model for six northern Australian breeding properties that spay females to enhance their marketing options. After the data were validated by management, alternative management strategies were modelled using current market prices and most likely herd outcomes. The model predicted a close relationship between the average sale value of cows, the total herd sales and the gross margin/adult equivalent. Keeping breeders out of the herd to fatten generally improves their sale value, and this can be cost-effective, despite the lower number of progeny produced and the subsequent reduction in total herd sales. Furthermore, if the price of culled cows exceeds the price of culled heifers, provided there are sufficient replacement pregnant heifers available to maintain the breeder herd nucleus, substantial gains in profitability can be obtained by decreasing the age at which cows are culled from the herd. Generalised recommendations on improving reproductive performance are not necessarily the most cost-effective strategy to improve breeder herd profitability. Judicious use of simulation models is essential to help develop the best turnoff strategies for females and to improve station profitability.

Business analysis for a sustainable, multi-stakeholder ecosystem for leveraging the Electronic Health Records for Clinical Research (EHR4CR) platform in Europe.

PubMed

Dupont, Danielle; Beresniak, Ariel; Sundgren, Mats; Schmidt, Andreas; Ainsworth, John; Coorevits, Pascal; Kalra, Dipak; Dewispelaere, Marc; De Moor, Georges

2017-01-01

The Electronic Health Records for Clinical Research (EHR4CR) technological platform has been developed to enable the trustworthy reuse of hospital electronic health records data for clinical research. The EHR4CR platform can enhance and speed up clinical research scenarios: protocol feasibility assessment, patient identification for recruitment in clinical trials, and clinical data exchange, including for reporting serious adverse events. Our objective was to seed a multi-stakeholder ecosystem to enable the scalable exploitation of the EHR4CR platform in Europe, and to assess its economic sustainability. Market analyses were conducted by a multidisciplinary task force to define an EHR4CR emerging ecosystem and multi-stakeholder value chain. This involved mapping stakeholder groups and defining their unmet needs, incentives, potential barriers for adopting innovative solutions, roles and interdependencies. A comprehensive business model, value propositions, and sustainability strategies were developed accordingly. Using simulation modelling (including Monte Carlo simulations) and a 5-year horizon, the potential financial outcomes of the business model were forecasted from the perspective of an EHR4CR service provider. A business ecosystem was defined to leverage the EHR4CR multi-stakeholder value chain. Value propositions were developed describing the expected benefits of EHR4CR solutions for all stakeholders. From an EHR4CR service provider's viewpoint, the business model simulation estimated that a profitability ratio of up to 1.8 could be achieved at year 1, with potential for growth in subsequent years depending on projected market uptake. By enhancing and speeding up existing processes, EHR4CR solutions promise to transform the clinical research landscape. The ecosystem defined provides the organisational framework for optimising the value and benefits for all stakeholders involved, in a sustainable manner. Our study suggests that the exploitation of EHR4CR solutions appears profitable and sustainable in Europe, with a growth potential depending on the rates of market and hospital adoption. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Forecasting fluid milk and cheese demands for the next decade.

PubMed

Schmit, T M; Kaiser, H M

2006-12-01

Predictions of future market demands and farm prices for dairy products are important determinants in developing marketing strategies and farm-production planning decisions. The objective of this report was to use current aggregate forecast data, combined with existing econometric models of demand and supply, to forecast retail demands for fluid milk and cheese and the supply and price of farm milk over the next decade. In doing so, we can investigate whether projections of population and consumer food-spending patterns will extend or alter current consumption trends and examine the implications of future generic advertising strategies for dairy products. To conduct the forecast simulations and appropriately allocate the farm milk supply to various uses, we used a partial equilibrium model of the US domestic dairy sector that segmented the industry into retail, wholesale, and farm markets. Model simulation results indicated that declines in retail per capita demand would persist but at a reduced rate from years past and that retail per capita demand for cheese would continue to grow and strengthen over the next decade. These predictions rely on expected changes in the size of populations of various ages, races, and ethnicities and on existing patterns of spending on food at home and away from home. The combined effect of these forecasted changes in demand levels was reflected in annualized growth in the total farm-milk supply that was similar to growth realized during the past few years. Although we expect nominal farm milk prices to increase over the next decade, we expect real prices (relative to assumed growth in feed costs) to remain relatively stable and show no increase until the end of the forecast period. Supplemental industry model simulations also suggested that net losses in producer revenues would result if only nominal levels of generic advertising spending were maintained in forthcoming years. In fact, if real generic advertising expenditures are increased relative to 2005 levels, returns to the investment in generic advertising can be improved. Specifically, each additional real dollar invested in generic advertising for fluid milk and cheese products over the forecast period would result in an additional 5.61 dollars in producer revenues.

Digital prototyping technique applied for redesigning plastic products

NASA Astrophysics Data System (ADS)

Pop, A.; Andrei, A.

2015-11-01

After products are on the market for some time, they often need to be redesigned to meet new market requirements. New products are generally derived from similar but outdated products. Redesigning a product is an important part of the production and development process. The purpose of this paper is to show that using modern technology, like Digital Prototyping in industry is an effective way to produce new products. This paper tries to demonstrate and highlight the effectiveness of the concept of Digital Prototyping, both to reduce the design time of a new product, but also the costs required for implementing this step. The results of this paper show that using Digital Prototyping techniques in designing a new product from an existing one available on the market mould offers a significantly manufacturing time and cost reduction. The ability to simulate and test a new product with modern CAD-CAM programs in all aspects of production (designing of the 3D model, simulation of the structural resistance, analysis of the injection process and beautification) offers a helpful tool for engineers. The whole process can be realised by one skilled engineer very fast and effective.

Supporting the Development and Adoption of Automatic Lameness Detection Systems in Dairy Cattle: Effect of System Cost and Performance on Potential Market Shares

PubMed Central

Van Weyenberg, Stephanie; Van Nuffel, Annelies; Lauwers, Ludwig; Vangeyte, Jürgen

2017-01-01

Simple Summary Most prototypes of systems to automatically detect lameness in dairy cattle are still not available on the market. Estimating their potential adoption rate could support developers in defining development goals towards commercially viable and well-adopted systems. We simulated the potential market shares of such prototypes to assess the effect of altering the system cost and detection performance on the potential adoption rate. We found that system cost and lameness detection performance indeed substantially influence the potential adoption rate. In order for farmers to prefer automatic detection over current visual detection, the usefulness that farmers attach to a system with specific characteristics should be higher than that of visual detection. As such, we concluded that low system costs and high detection performances are required before automatic lameness detection systems become applicable in practice. Abstract Most automatic lameness detection system prototypes have not yet been commercialized, and are hence not yet adopted in practice. Therefore, the objective of this study was to simulate the effect of detection performance (percentage missed lame cows and percentage false alarms) and system cost on the potential market share of three automatic lameness detection systems relative to visual detection: a system attached to the cow, a walkover system, and a camera system. Simulations were done using a utility model derived from survey responses obtained from dairy farmers in Flanders, Belgium. Overall, systems attached to the cow had the largest market potential, but were still not competitive with visual detection. Increasing the detection performance or lowering the system cost led to higher market shares for automatic systems at the expense of visual detection. The willingness to pay for extra performance was €2.57 per % less missed lame cows, €1.65 per % less false alerts, and €12.7 for lame leg indication, respectively. The presented results could be exploited by system designers to determine the effect of adjustments to the technology on a system’s potential adoption rate. PMID:28991188

Is there any overtrading in stock markets? The moderating role of big five personality traits and gender in a unilateral trend stock market.

PubMed

Zhang, Jian; Wang, Haocheng; Wang, Limin; Liu, Shuyi

2014-01-01

Overtrading is a common anomaly among stock investors. This study examines the relationship between overtrading and investment returns and the impact of the Big Five traits and gender on overtrading in a unilateral trend stock market using a simulated stock investment system. The data were derived from a sample of undergraduates from six universities who performed in a simulated stock investment situation and had their personality traits measured by the Big Five Personality Questionnaire. The results indicate that: (1) Overtrading was significant in rising stock markets, but not significant in falling markets. (2) The degree of female investors who overtraded was significant in rising markets. (3) The degree of overtrading investors who were high in extroversion or agreeableness was significant in rising markets. The implications of these results for more effective investment strategies are discussed.

Is There Any Overtrading in Stock Markets? The Moderating Role of Big Five Personality Traits and Gender in a Unilateral Trend Stock Market

PubMed Central

Zhang, Jian; Wang, Haocheng; Wang, Limin; Liu, Shuyi

2014-01-01

Overtrading is a common anomaly among stock investors. This study examines the relationship between overtrading and investment returns and the impact of the Big Five traits and gender on overtrading in a unilateral trend stock market using a simulated stock investment system. The data were derived from a sample of undergraduates from six universities who performed in a simulated stock investment situation and had their personality traits measured by the Big Five Personality Questionnaire. The results indicate that: (1) Overtrading was significant in rising stock markets, but not significant in falling markets. (2) The degree of female investors who overtraded was significant in rising markets. (3) The degree of overtrading investors who were high in extroversion or agreeableness was significant in rising markets. The implications of these results for more effective investment strategies are discussed. PMID:24475235

Empirical and model study on Travel-entering China

NASA Astrophysics Data System (ADS)

Han, Xue-Fang; Chen, Qi-Juan; Chang, Hui; He, Da-Ren

2006-03-01

We have done an empirical investigation on the travel-entering China from abroad to 31 regions of Chinese Mainland in recent ten years, including the development of the traveler's number, the traveler's number distribution for the traveler's home regions, the traveler's number distribution for the traveler's destination regions in Chinese mainland, and so on. We also suggest a dynamic model for simulating the competition between the 31 regions in the traveling market by considering two main influence factors, the attracting factor of the travel destinations and the distance between the destination and the home regions of the travelers. The simulation results show a good agreement with the empirical data. We expect the model could suggest some advice and thoughts to the travel-entering management departments in China and may be also for other countries.

Effects of Participation in a Simulation Game on Marketing Students' Numeracy and Financial Skills

ERIC Educational Resources Information Center

Brennan, Ross; Vos, Lynn

2013-01-01

The need to endow marketing graduates with skills relevant to employability grows ever more important. Marketing math and elementary financial understanding are essential employability skills, particularly given the contemporary emphasis on marketing metrics, but the evidence is that marketing graduates are often relatively weak in such skills.…

New parsimonious simulation methods and tools to assess future food and environmental security of farm populations

PubMed Central

Antle, John M.; Stoorvogel, Jetse J.; Valdivia, Roberto O.

2014-01-01

This article presents conceptual and empirical foundations for new parsimonious simulation models that are being used to assess future food and environmental security of farm populations. The conceptual framework integrates key features of the biophysical and economic processes on which the farming systems are based. The approach represents a methodological advance by coupling important behavioural processes, for example, self-selection in adaptive responses to technological and environmental change, with aggregate processes, such as changes in market supply and demand conditions or environmental conditions as climate. Suitable biophysical and economic data are a critical limiting factor in modelling these complex systems, particularly for the characterization of out-of-sample counterfactuals in ex ante analyses. Parsimonious, population-based simulation methods are described that exploit available observational, experimental, modelled and expert data. The analysis makes use of a new scenario design concept called representative agricultural pathways. A case study illustrates how these methods can be used to assess food and environmental security. The concluding section addresses generalizations of parametric forms and linkages of regional models to global models. PMID:24535388

New parsimonious simulation methods and tools to assess future food and environmental security of farm populations.

PubMed

Antle, John M; Stoorvogel, Jetse J; Valdivia, Roberto O

2014-04-05

This article presents conceptual and empirical foundations for new parsimonious simulation models that are being used to assess future food and environmental security of farm populations. The conceptual framework integrates key features of the biophysical and economic processes on which the farming systems are based. The approach represents a methodological advance by coupling important behavioural processes, for example, self-selection in adaptive responses to technological and environmental change, with aggregate processes, such as changes in market supply and demand conditions or environmental conditions as climate. Suitable biophysical and economic data are a critical limiting factor in modelling these complex systems, particularly for the characterization of out-of-sample counterfactuals in ex ante analyses. Parsimonious, population-based simulation methods are described that exploit available observational, experimental, modelled and expert data. The analysis makes use of a new scenario design concept called representative agricultural pathways. A case study illustrates how these methods can be used to assess food and environmental security. The concluding section addresses generalizations of parametric forms and linkages of regional models to global models.

Dynamics of market structure driven by the degree of consumer’s rationality

NASA Astrophysics Data System (ADS)

Yanagita, Tatsuo; Onozaki, Tamotsu

2010-03-01

We study a simple model of market share dynamics with boundedly rational consumers and firms interacting with each other. As the number of consumers is large, we employ a statistical description to represent firms’ distribution of consumer share, which is characterized by a single parameter representing how rationally the mass of consumers pursue higher utility. As the boundedly rational firm does not know the shape of demand function it faces, it revises production and price so as to raise its profit with the aid of a simple reinforcement learning rule. Simulation results show that (1) three phases of market structure, i.e. the uniform share phase, the oligopolistic phase, and the monopolistic phase, appear depending upon how rational consumers are, and (2) in an oligopolistic phase, the market share distribution of firms follows Zipf’s law and the growth-rate distribution of firms follows Gibrat’s law, and (3) an oligopolistic phase is the best state of market in terms of consumers’ utility but brings the minimum profit to the firms because of severe competition based on the moderate rationality of consumers.

A review of virtual reality based training simulators for orthopaedic surgery.

PubMed

Vaughan, Neil; Dubey, Venketesh N; Wainwright, Thomas W; Middleton, Robert G

2016-02-01

This review presents current virtual reality based training simulators for hip, knee and other orthopaedic surgery, including elective and trauma surgical procedures. There have not been any reviews focussing on hip and knee orthopaedic simulators. A comparison of existing simulator features is provided to identify what is missing and what is required to improve upon current simulators. In total 11 hip replacements pre-operative planning tools were analysed, plus 9 hip trauma fracture training simulators. Additionally 9 knee arthroscopy simulators and 8 other orthopaedic simulators were included for comparison. The findings are that for orthopaedic surgery simulators in general, there is increasing use of patient-specific virtual models which reduce the learning curve. Modelling is also being used for patient-specific implant design and manufacture. Simulators are being increasingly validated for assessment as well as training. There are very few training simulators available for hip replacement, yet more advanced virtual reality is being used for other procedures such as hip trauma and drilling. Training simulators for hip replacement and orthopaedic surgery in general lag behind other surgical procedures for which virtual reality has become more common. Further developments are required to bring hip replacement training simulation up to date with other procedures. This suggests there is a gap in the market for a new high fidelity hip replacement and resurfacing training simulator. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

Cystic echinococcosis in marketed offal of sheep in Basrah, Iraq: Abattoir-based survey and a probabilistic model estimation of the direct economic losses due to hydatid cyst.

PubMed

Abdulhameed, Mohanad F; Habib, Ihab; Al-Azizz, Suzan A; Robertson, Ian

2018-02-01

Cystic echinococcosis (CE) is a highly endemic parasitic zoonosis in Iraq with substantial impacts on livestock productivity and human health. The objectives of this study were to study the abattoir-based occurrence of CE in marketed offal of sheep in Basrah province, Iraq, and to estimate, using a probabilistic modelling approach, the direct economic losses due to hydatid cysts. Based on detailed visual meat inspection, results from an active abattoir survey in this study revealed detection of hydatid cysts in 7.3% (95% CI: 5.4; 9.6) of 631 examined sheep carcasses. Post-mortem lesions of hydatid cyst were concurrently present in livers and lungs of more than half (54.3% (25/46)) of the positive sheep. Direct economic losses due to hydatid cysts in marketed offal were estimated using data from government reports, the one abattoir survey completed in this study, and expert opinions of local veterinarians and butchers. A Monte-Carlo simulation model was developed in a spreadsheet utilizing Latin Hypercube sampling to account for uncertainty in the input parameters. The model estimated that the average annual economic losses associated with hydatid cysts in the liver and lungs of sheep marketed for human consumption in Basrah to be US$72,470 (90% Confidence Interval (CI); ±11,302). The mean proportion of annual losses in meat products value (carcasses and offal) due to hydatid cysts in the liver and lungs of sheep marketed in Basrah province was estimated as 0.42% (90% CI; ±0.21). These estimates suggest that CE is responsible for considerable livestock-associated monetary losses in the south of Iraq. These findings can be used to inform different regional CE control program options in Iraq.

Exploring International Investment through a Classroom Portfolio Simulation Project

ERIC Educational Resources Information Center

Chen, Xiaoying; Yur-Austin, Jasmine

2013-01-01

A rapid integration of financial markets has prevailed during the last three decades. Investors are able to diversify investment beyond national markets to mitigate return volatility of a "pure domestic portfolio." This article discusses a simulation project through which students learn the role of international investment by managing…

Market-driven automotive industry compliance with fuel economy and greenhouse gas standards: Analysis based on consumer choice

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xie, Fei; Lin, Zhenhong

This paper explored factors that affect market-driven compliance with both Corporate Average Fuel Economy (CAFE) and greenhouse gas (GHG) standards (together called the National Program) in the United States for phase I 2012–2016 and phase II 2017–2025. We considered a consumer-choice-based simulation approach, using the MA3T model, to estimate the market acceptance of fuel efficiency (FE) technologies and alternative fuel technologies as reflected by new sales of light-duty vehicle (LDV). Because both full and extremely low FE valuations are common in the literature, we use a moderate assumption of a 10-year perceived vehicle lifetime at a 7% annual discount ratemore » in the baseline and include both extreme views (5 years and 15 years) in the sensitivity analysis. The study focuses on market-driven compliance and therefore excludes manufacturers’ cross-subsidization. The model results suggest that the LDV industry is able to comply with both standards even without cross-subsidization and with projected high technology cost, mainly thanks to the multiple credit programs and technology advancements. The compliance robustness, while encouraging, however is based on moderate market assumptions, such as Annual Energy Outlook 2016 Reference oil price projection and moderate FE consumer valuation. Finally, sensitivity analysis results reveal two significant risk factors for compliance: low oil prices and consumers’ FE undervaluation.« less

Microsimulation of Private Health Insurance and Medicaid Take-Up Following the U.S. Supreme Court Decision Upholding the Affordable Care Act

PubMed Central

Parente, Stephen T; Feldman, Roger

2013-01-01

Objective To predict take-up of private health insurance and Medicaid following the U.S. Supreme Court decision upholding the Affordable Care Act (ACA). Data Sources Data came from three large employers and a sampling of premiums from http://ehealthinsurance.com. We supplemented the employer data with information on state Medicaid eligibility and costs from the Kaiser Family Foundation. National predictions were based on the MEPS Household Component. Study Design We estimated a conditional logit model of health plan choice in the large group market. Using the coefficients from the choice model, we predicted take-up in the group and individual health insurance markets. Following ACA implementation, we added choices to the individual market corresponding to plans that will be available in state and federal exchanges. Depending on eligibility for premium subsidies, we reduced the out-of-pocket premiums for those choices. We simulated several possible patterns for states opting out of the Medicaid expansion, as allowed by the Supreme Court. Principal Findings The ACA will increase coverage substantially in the private insurance market and Medicaid. HSAs will remain desirable in both the individual and employer markets. Conclusions If states opt out of the Medicaid expansion, this could increase the federal cost of health reform, while reducing the number of newly covered lives. PMID:23398372

Market-driven automotive industry compliance with fuel economy and greenhouse gas standards: Analysis based on consumer choice

DOE PAGES

Xie, Fei; Lin, Zhenhong

2017-06-09

This paper explored factors that affect market-driven compliance with both Corporate Average Fuel Economy (CAFE) and greenhouse gas (GHG) standards (together called the National Program) in the United States for phase I 2012–2016 and phase II 2017–2025. We considered a consumer-choice-based simulation approach, using the MA3T model, to estimate the market acceptance of fuel efficiency (FE) technologies and alternative fuel technologies as reflected by new sales of light-duty vehicle (LDV). Because both full and extremely low FE valuations are common in the literature, we use a moderate assumption of a 10-year perceived vehicle lifetime at a 7% annual discount ratemore » in the baseline and include both extreme views (5 years and 15 years) in the sensitivity analysis. The study focuses on market-driven compliance and therefore excludes manufacturers’ cross-subsidization. The model results suggest that the LDV industry is able to comply with both standards even without cross-subsidization and with projected high technology cost, mainly thanks to the multiple credit programs and technology advancements. The compliance robustness, while encouraging, however is based on moderate market assumptions, such as Annual Energy Outlook 2016 Reference oil price projection and moderate FE consumer valuation. Finally, sensitivity analysis results reveal two significant risk factors for compliance: low oil prices and consumers’ FE undervaluation.« less

The evolving cobweb of relations among partially rational investors

PubMed Central

DiMeglio, Anna; Garofalo, Franco; Lo Iudice, Francesco

2017-01-01

To overcome the limitations of neoclassical economics, researchers have leveraged tools of statistical physics to build novel theories. The idea was to elucidate the macroscopic features of financial markets from the interaction of its microscopic constituents, the investors. In this framework, the model of the financial agents has been kept separate from that of their interaction. Here, instead, we explore the possibility of letting the interaction topology emerge from the model of the agents’ behavior. Then, we investigate how the emerging cobweb of relationship affects the overall market dynamics. To this aim, we leverage tools from complex systems analysis and nonlinear dynamics, and model the network of mutual influence as the output of a dynamical system describing the edge evolution. In this work, the driver of the link evolution is the relative reputation between possibly coupled agents. The reputation is built differently depending on the extent of rationality of the investors. The continuous edge activation or deactivation induces the emergence of leaders and of peculiar network structures, typical of real influence networks. The subsequent impact on the market dynamics is investigated through extensive numerical simulations in selected scenarios populated by partially rational investors. PMID:28196144

Forecasting the portuguese stock market time series by using artificial neural networks

NASA Astrophysics Data System (ADS)

Isfan, Monica; Menezes, Rui; Mendes, Diana A.

2010-04-01

In this paper, we show that neural networks can be used to uncover the non-linearity that exists in the financial data. First, we follow a traditional approach by analysing the deterministic/stochastic characteristics of the Portuguese stock market data and some typical features are studied, like the Hurst exponents, among others. We also simulate a BDS test to investigate nonlinearities and the results are as expected: the financial time series do not exhibit linear dependence. Secondly, we trained four types of neural networks for the stock markets and used the models to make forecasts. The artificial neural networks were obtained using a three-layer feed-forward topology and the back-propagation learning algorithm. The quite large number of parameters that must be selected to develop a neural network forecasting model involves some trial and as a consequence the error is not small enough. In order to improve this we use a nonlinear optimization algorithm to minimize the error. Finally, the output of the 4 models is quite similar, leading to a qualitative forecast that we compare with the results of the application of k-nearest-neighbor for the same time series.

The evolving cobweb of relations among partially rational investors.

PubMed

DeLellis, Pietro; DiMeglio, Anna; Garofalo, Franco; Lo Iudice, Francesco

2017-01-01

To overcome the limitations of neoclassical economics, researchers have leveraged tools of statistical physics to build novel theories. The idea was to elucidate the macroscopic features of financial markets from the interaction of its microscopic constituents, the investors. In this framework, the model of the financial agents has been kept separate from that of their interaction. Here, instead, we explore the possibility of letting the interaction topology emerge from the model of the agents' behavior. Then, we investigate how the emerging cobweb of relationship affects the overall market dynamics. To this aim, we leverage tools from complex systems analysis and nonlinear dynamics, and model the network of mutual influence as the output of a dynamical system describing the edge evolution. In this work, the driver of the link evolution is the relative reputation between possibly coupled agents. The reputation is built differently depending on the extent of rationality of the investors. The continuous edge activation or deactivation induces the emergence of leaders and of peculiar network structures, typical of real influence networks. The subsequent impact on the market dynamics is investigated through extensive numerical simulations in selected scenarios populated by partially rational investors.

Analysis of the French insurance market exposure to floods: a stochastic model combining river overflow and surface runoff

NASA Astrophysics Data System (ADS)

Moncoulon, D.; Labat, D.; Ardon, J.; Onfroy, T.; Leblois, E.; Poulard, C.; Aji, S.; Rémy, A.; Quantin, A.

2013-07-01

The analysis of flood exposure at a national scale for the French insurance market must combine the generation of a probabilistic event set of all possible but not yet occurred flood situations with hazard and damage modeling. In this study, hazard and damage models are calibrated on a 1995-2012 historical event set, both for hazard results (river flow, flooded areas) and loss estimations. Thus, uncertainties in the deterministic estimation of a single event loss are known before simulating a probabilistic event set. To take into account at least 90% of the insured flood losses, the probabilistic event set must combine the river overflow (small and large catchments) with the surface runoff due to heavy rainfall, on the slopes of the watershed. Indeed, internal studies of CCR claim database has shown that approximately 45% of the insured flood losses are located inside the floodplains and 45% outside. 10% other percent are due to seasurge floods and groundwater rise. In this approach, two independent probabilistic methods are combined to create a single flood loss distribution: generation of fictive river flows based on the historical records of the river gauge network and generation of fictive rain fields on small catchments, calibrated on the 1958-2010 Météo-France rain database SAFRAN. All the events in the probabilistic event sets are simulated with the deterministic model. This hazard and damage distribution is used to simulate the flood losses at the national scale for an insurance company (MACIF) and to generate flood areas associated with hazard return periods. The flood maps concern river overflow and surface water runoff. Validation of these maps is conducted by comparison with the address located claim data on a small catchment (downstream Argens).

Design and application of a technologically explicit hybrid energy-economy policy model with micro and macro economic dynamics

NASA Astrophysics Data System (ADS)

Bataille, Christopher G. F.

2005-11-01

Are further energy efficiency gains, or more recently greenhouse gas reductions, expensive or cheap? Analysts provide conflicting advice to policy makers based on divergent modelling perspectives, a 'top-down/bottom-up debate' in which economists use equation based models that equilibrate markets by maximizing consumer welfare, and technologists use technology simulation models that minimize the financial cost of providing energy services. This thesis summarizes a long term research project to find a middle ground between these two positions that is more useful to policy makers. Starting with the individual components of a behaviourally realistic and technologically explicit simulation model (ISTUM---Inter Sectoral Technology Use Model), or "hybrid", the individual sectors of the economy are linked using a framework of micro and macro economic feedbacks. These feedbacks are taken from the economic theory that informs the computable general equilibrium (CGE) family of models. Speaking in the languages of both economists and engineers, the resulting "physical" equilibrium model of Canada (CIMS---Canadian Integrated Modeling System), equilibrates energy and end-product markets, including imports and exports, for seven regions and 15 economic sectors, including primary industry, manufacturing, transportation, commerce, residences, governmental infrastructure and the energy supply sectors. Several different policy experiments demonstrate the value-added of the model and how its results compare to top-down and bottom-up practice. In general, the results show that technical adjustments make up about half the response to simulated energy policy, and macroeconomic demand adjustments the other half. Induced technical adjustments predominate with minor policies, while the importance of macroeconomic demand adjustment increases with the strength of the policy. Results are also shown for an experiment to derive estimates of future elasticity of substitution (ESUB) and autonomous energy efficiency indices (AEEI) from the model, parameters that could be used in long-run computable general equilibrium (CGE) analysis. The thesis concludes with a summary of the strengths and weakness of the new model as a policy tool, a work plan for its further improvement, and a discussion of the general potential for technologically explicit general equilibrium modelling.

Social capital and transaction costs in millet markets.

PubMed

Jacques, Damien Christophe; Marinho, Eduardo; d'Andrimont, Raphaël; Waldner, François; Radoux, Julien; Gaspart, Frédéric; Defourny, Pierre

2018-01-01

In sub-Saharan Africa, transaction costs are believed to be the most significant barrier that prevents smallholders and farmers from gaining access to markets and productive assets. In this study, we explore the impact of social capital on millet prices for three contrasted years in Senegal. Social capital is approximated using a unique data set on mobile phone communications between 9 million people allowing to simulate the business network between economic agents. Our approach is a spatial equilibrium model that integrates a diversified set of data. Local supply and demand were respectively derived from remotely sensed imagery and population density maps. The road network was used to establish market catchment areas, and transportation costs were derived from distances between markets. Results demonstrate that accounting for the social capital in the transaction costs explained 1-9% of the price variance depending on the year. The year-specific effect remains challenging to assess but could be related to a strengthening of risk aversion following a poor harvest.

Data mining techniques for scientific computing: Application to asymptotic paraxial approximations to model ultrarelativistic particles

NASA Astrophysics Data System (ADS)

Assous, Franck; Chaskalovic, Joël

2011-06-01

We propose a new approach that consists in using data mining techniques for scientific computing. Indeed, data mining has proved to be efficient in other contexts which deal with huge data like in biology, medicine, marketing, advertising and communications. Our aim, here, is to deal with the important problem of the exploitation of the results produced by any numerical method. Indeed, more and more data are created today by numerical simulations. Thus, it seems necessary to look at efficient tools to analyze them. In this work, we focus our presentation to a test case dedicated to an asymptotic paraxial approximation to model ultrarelativistic particles. Our method directly deals with numerical results of simulations and try to understand what each order of the asymptotic expansion brings to the simulation results over what could be obtained by other lower-order or less accurate means. This new heuristic approach offers new potential applications to treat numerical solutions to mathematical models.

Impact of alternative harvesting technologies on thinning entry and optimal rotation age for eastern hardwoods

Treesearch

Chris B. LeDoux

2007-01-01

A complete system simulation model is used to integrate alternative logging technologies, stand data, market prices, transportation costs, and economic concerns in a longterm continuous manner to evaluate thinning entry timing and optimal rotation age. Forest Inventory and Analysis (FIA) stand data for the oak/hickory forest type and time and motion study data for 70,...

Global critical materials markets: An agent-based modeling approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Riddle, Matthew; Macal, Charles M.; Conzelmann, Guenter

As part of efforts to position the United States as a leader in clean energy technology production, the U. S. Department of Energy (DOE) issued two Critical Materials Strategy reports, which assessed 16 materials on the basis of their importance to clean energy development and their supply risk ( U.S. Department of Energy (DOE), 2010 and DOE, 2011). To understand the implications for clean energy of disruptions in supplies of critical materials, it is important to understand supply chain dynamics from mining to final product production. As a case study of critical material supply chains, we focus on the supplymore » of two rare earth metals, neodymium (Nd) and dysprosium (Dy), for permanent magnets used in wind turbines, electric vehicles and other applications. We introduce GCMat, a dynamic agent-based model that includes interacting agents at five supply chain stages consisting of mining, metal refining, magnet production, final product production and demand. Agents throughout the supply chain make pricing, production and inventory management decisions. Deposit developers choose which deposits to develop based on market conditions and detailed data on 57 rare earth deposits. Wind turbine and electric vehicle producers choose from a set of possible production technologies that require different amounts of rare earths. We ran the model under a baseline scenario and four alternative scenarios with different demand and production technology inputs. Model results from 2010 to 2013 fit well with historical data. Projections through 2025 show a number of possible future price, demand, and supply trajectories. For each scenario, we highlight reasons for turning points under market conditions, for differences between Nd and Dy markets, and for differences between scenarios. Because GCMat can model causal dynamics and provide fine-grain representation of agents and their decisions, it provides explanations for turning points under market conditions that are not otherwise available from other modeling approaches. Our baseline projections show very different behaviors for Nd and Dy prices. Nd prices continue to drop and remain low even at the end of our simulation period as new capacity comes online and leads to a market in which production capacity outpaces demand. Dy price movements, on the other hand, change directions several times with several key turning points related to inventory behaviors of particular agents in the supply chain and asymmetric supply and demand trends. Scenario analyses show the impact of stronger demand growth for rare earths, and in particular finds that Nd price impacts are significantly delayed as compared to Dy. This is explained by the substantial excess production capacity for Nd in the early simulation years that keeps prices down. Scenarios that explore the impact of reducing the Dy content of magnets show the intricate interdependencies of these two markets as price trends for both rare earths reverse directions – reducing the Dy content of magnets reduces Dy demand, which drives down Dy prices and translates into lower magnet prices. This in turn raises the demand for magnets and therefore the demand for Nd and eventually drives up the Nd price.« less

China's Rare Earth Supply Chain: Illegal Production, and Response to new Cerium Demand

NASA Astrophysics Data System (ADS)

Nguyen, Ruby Thuy; Imholte, D. Devin

2016-07-01

As the demand for personal electronic devices, wind turbines, and electric vehicles increases, the world becomes more dependent on rare earth elements. Given the volatile, Chinese-concentrated supply chain, global attempts have been made to diversify supply of these materials. However, the overall effect of supply diversification on the entire supply chain, including increasing low-value rare earth demand, is not fully understood. This paper is the first attempt to shed some light on China's supply chain from both demand and supply perspectives, taking into account different Chinese policies such as mining quotas, separation quotas, export quotas, and resource taxes. We constructed a simulation model using Powersim Studio that analyzes production (both legal and illegal), production costs, Chinese and rest-of-world demand, and market dynamics. We also simulated new demand of an automotive aluminum-cerium alloy in the US market starting from 2018. Results showed that market share of the illegal sector has grown since 2007-2015, ranging between 22% and 25% of China's rare earth supply, translating into 59-65% illegal heavy rare earths and 14-16% illegal light rare earths. There will be a shortage in certain light and heavy rare earths given three production quota scenarios and constant demand growth rate from 2015 to 2030. The new simulated Ce demand would require supply beyond that produced in China. Finally, we illustrate revenue streams for different ore compositions in China in 2015.

China’s rare earth supply chain: Illegal production, and response to new cerium demand

DOE PAGES

Nguyen, Ruby Thuy; Imholte, D. Devin

2016-03-29

As the demand for personal electronic devices, wind turbines, and electric vehicles increases, the world becomes more dependent on rare earth elements. Given the volatile, Chinese-concentrated supply chain, global attempts have been made to diversify supply of these materials. However, the overall effect of supply diversification on the entire supply chain, including increasing low-value rare earth demand, is not fully understood. This paper is the first attempt to shed some light on China’s supply chain from both demand and supply perspectives, taking into account different Chinese policies such as mining quotas, separation quotas, export quotas, and resource taxes. We constructedmore » a simulation model using Powersim Studio that analyzes production (both legal and illegal), production costs, Chinese and rest-of-world demand, and market dynamics. We also simulated new demand of an automotive aluminum-cerium alloy in the U.S. market starting from 2018. Results showed that market share of the illegal sector has grown since 2007 to 2015, ranging between 22% and 25% of China’s rare earth supply, translating into 59–65% illegal heavy rare earths and 14–16% illegal light rare earths. There would be a shortage in certain light and heavy rare earths given three production quota scenarios and constant demand growth rate from 2015 to 2030. The new simulated Ce demand would require supply beyond that produced in China. Lastly, we illustrated revenue streams for different ore compositions in China in 2015.« less

China’s rare earth supply chain: Illegal production, and response to new cerium demand

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nguyen, Ruby Thuy; Imholte, D. Devin

As the demand for personal electronic devices, wind turbines, and electric vehicles increases, the world becomes more dependent on rare earth elements. Given the volatile, Chinese-concentrated supply chain, global attempts have been made to diversify supply of these materials. However, the overall effect of supply diversification on the entire supply chain, including increasing low-value rare earth demand, is not fully understood. This paper is the first attempt to shed some light on China’s supply chain from both demand and supply perspectives, taking into account different Chinese policies such as mining quotas, separation quotas, export quotas, and resource taxes. We constructedmore » a simulation model using Powersim Studio that analyzes production (both legal and illegal), production costs, Chinese and rest-of-world demand, and market dynamics. We also simulated new demand of an automotive aluminum-cerium alloy in the U.S. market starting from 2018. Results showed that market share of the illegal sector has grown since 2007 to 2015, ranging between 22% and 25% of China’s rare earth supply, translating into 59–65% illegal heavy rare earths and 14–16% illegal light rare earths. There would be a shortage in certain light and heavy rare earths given three production quota scenarios and constant demand growth rate from 2015 to 2030. The new simulated Ce demand would require supply beyond that produced in China. Lastly, we illustrated revenue streams for different ore compositions in China in 2015.« less

Energy Storage Applications in Power Systems with Renewable Energy Generation

NASA Astrophysics Data System (ADS)

Ghofrani, Mahmoud

In this dissertation, we propose new operational and planning methodologies for power systems with renewable energy sources. A probabilistic optimal power flow (POPF) is developed to model wind power variations and evaluate the power system operation with intermittent renewable energy generation. The methodology is used to calculate the operating and ramping reserves that are required to compensate for power system uncertainties. Distributed wind generation is introduced as an operational scheme to take advantage of the spatial diversity of renewable energy resources and reduce wind power fluctuations using low or uncorrelated wind farms. The POPF is demonstrated using the IEEE 24-bus system where the proposed operational scheme reduces the operating and ramping reserve requirements and operation and congestion cost of the system as compared to operational practices available in the literature. A stochastic operational-planning framework is also proposed to adequately size, optimally place and schedule storage units within power systems with high wind penetrations. The method is used for different applications of energy storage systems for renewable energy integration. These applications include market-based opportunities such as renewable energy time-shift, renewable capacity firming, and transmission and distribution upgrade deferral in the form of revenue or reduced cost and storage-related societal benefits such as integration of more renewables, reduced emissions and improved utilization of grid assets. A power-pool model which incorporates the one-sided auction market into POPF is developed. The model considers storage units as market participants submitting hourly price bids in the form of marginal costs. This provides an accurate market-clearing process as compared to the 'price-taker' analysis available in the literature where the effects of large-scale storage units on the market-clearing prices are neglected. Different case studies are provided to demonstrate our operational-planning framework and economic justification for different storage applications. A new reliability model is proposed for security and adequacy assessment of power networks containing renewable resources and energy storage systems. The proposed model is used in combination with the operational-planning framework to enhance the reliability and operability of wind integration. The proposed framework optimally utilizes the storage capacity for reliability applications of wind integration. This is essential for justification of storage deployment within regulated utilities where the absence of market opportunities limits the economic advantage of storage technologies over gas-fired generators. A control strategy is also proposed to achieve the maximum reliability using energy storage systems. A cost-benefit analysis compares storage technologies and conventional alternatives to reliably and efficiently integrate different wind penetrations and determines the most economical design. Our simulation results demonstrate the necessity of optimal storage placement for different wind applications. This dissertation also proposes a new stochastic framework to optimally charge and discharge electric vehicles (EVs) to mitigate the effects of wind power uncertainties. Vehicle-to-grid (V2G) service for hedging against wind power imbalances is introduced as a novel application for EVs. This application enhances the predictability of wind power and reduces the power imbalances between the scheduled output and actual power. An Auto Regressive Moving Average (ARMA) wind speed model is developed to forecast the wind power output. Driving patterns of EVs are stochastically modeled and the EVs are clustered in the fleets of similar daily driving patterns. Monte Carlo Simulation (MCS) simulates the system behavior by generating samples of system states using the wind ARMA model and EVs driving patterns. A Genetic Algorithm (GA) is used in combination with MCS to optimally coordinate the EV fleets for their V2G services and minimize the penalty cost associated with wind power imbalances. The economic characteristics of automotive battery technologies and costs of V2G service are incorporated into a cost-benefit analysis which evaluates the economic justification of the proposed V2G application. Simulation results demonstrate that the developed algorithm enhances wind power utilization and reduces the penalty cost for wind power under-/over-production. This offers potential revenues for the wind producer. Our cost-benefit analysis also demonstrates that the proposed algorithm will provide the EV owners with economic incentives to participate in V2G services. The proposed smart scheduling strategy develops a sustainable integrated electricity and transportation infrastructure.

Forecasting VaR and ES of stock index portfolio: A Vine copula method

NASA Astrophysics Data System (ADS)

Zhang, Bangzheng; Wei, Yu; Yu, Jiang; Lai, Xiaodong; Peng, Zhenfeng

2014-12-01

Risk measurement has both theoretical and practical significance in risk management. Using daily sample of 10 international stock indices, firstly this paper models the internal structures among different stock markets with C-Vine, D-Vine and R-Vine copula models. Secondly, the Value-at-Risk (VaR) and Expected Shortfall (ES) of the international stock markets portfolio are forecasted using Monte Carlo method based on the estimated dependence of different Vine copulas. Finally, the accuracy of VaR and ES measurements obtained from different statistical models are evaluated by UC, IND, CC and Posterior analysis. The empirical results show that the VaR forecasts at the quantile levels of 0.9, 0.95, 0.975 and 0.99 with three kinds of Vine copula models are sufficiently accurate. Several traditional methods, such as historical simulation, mean-variance and DCC-GARCH models, fail to pass the CC backtesting. The Vine copula methods can accurately forecast the ES of the portfolio on the base of VaR measurement, and D-Vine copula model is superior to other Vine copulas.

Adaptive hidden Markov model with anomaly States for price manipulation detection.

PubMed

Cao, Yi; Li, Yuhua; Coleman, Sonya; Belatreche, Ammar; McGinnity, Thomas Martin

2015-02-01

Price manipulation refers to the activities of those traders who use carefully designed trading behaviors to manually push up or down the underlying equity prices for making profits. With increasing volumes and frequency of trading, price manipulation can be extremely damaging to the proper functioning and integrity of capital markets. The existing literature focuses on either empirical studies of market abuse cases or analysis of particular manipulation types based on certain assumptions. Effective approaches for analyzing and detecting price manipulation in real time are yet to be developed. This paper proposes a novel approach, called adaptive hidden Markov model with anomaly states (AHMMAS) for modeling and detecting price manipulation activities. Together with wavelet transformations and gradients as the feature extraction methods, the AHMMAS model caters to price manipulation detection and basic manipulation type recognition. The evaluation experiments conducted on seven stock tick data from NASDAQ and the London Stock Exchange and 10 simulated stock prices by stochastic differential equation show that the proposed AHMMAS model can effectively detect price manipulation patterns and outperforms the selected benchmark models.

Development of a Gas Dynamic and Thermodynamic Simulation Model of the Lontra Blade Compressor™

NASA Astrophysics Data System (ADS)

Karlovsky, Jerome

2015-08-01

The Lontra Blade Compressor™ is a patented double acting, internally compressing, positive displacement rotary compressor of innovative design. The Blade Compressor is in production for waste-water treatment, and will soon be launched for a range of applications at higher pressure ratios. In order to aid the design and development process, a thermodynamic and gas dynamic simulation program has been written in house. The software has been successfully used to optimise geometries and running conditions of current designs, and is also being used to evaluate future designs for different applications and markets. The simulation code has three main elements. A positive displacement chamber model, a leakage model and a gas dynamic model to simulate gas flow through ports and to track pressure waves in the inlet and outlet pipes. All three of these models are interlinked in order to track mass and energy flows within the system. A correlation study has been carried out to verify the software. The main correlation markers used were mass flow, chamber pressure, pressure wave tracking in the outlet pipe, and volumetric efficiency. It will be shown that excellent correlation has been achieved between measured and simulated data. Mass flow predictions were to within 2% of measured data, and the timings and magnitudes of all major gas dynamic effects were well replicated. The simulation will be further developed in the near future to help with the optimisation of exhaust and inlet silencers.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krishnamurthy, Dheepak

This paper is an overview of Power System Simulation Toolbox (psst). psst is an open-source Python application for the simulation and analysis of power system models. psst simulates the wholesale market operation by solving a DC Optimal Power Flow (DCOPF), Security Constrained Unit Commitment (SCUC) and a Security Constrained Economic Dispatch (SCED). psst also includes models for the various entities in a power system such as Generator Companies (GenCos), Load Serving Entities (LSEs) and an Independent System Operator (ISO). psst features an open modular object oriented architecture that will make it useful for researchers to customize, expand, experiment beyond solvingmore » traditional problems. psst also includes a web based Graphical User Interface (GUI) that allows for user friendly interaction and for implementation on remote High Performance Computing (HPCs) clusters for parallelized operations. This paper also provides an illustrative application of psst and benchmarks with standard IEEE test cases to show the advanced features and the performance of toolbox.« less

Time interval between successive trading in foreign currency market: from microscopic to macroscopic

NASA Astrophysics Data System (ADS)

Sato, Aki-Hiro

2004-12-01

Recently, it has been shown that inter-transaction interval (ITI) distribution of foreign currency rates has a fat tail. In order to understand the statistical property of the ITI dealer model with N interactive agents is proposed. From numerical simulations it is confirmed that the ITI distribution of the dealer model has a power law tail. The random multiplicative process (RMP) can be approximately derived from the ITI of the dealer model. Consequently, we conclude that the power law tail of the ITI distribution of the dealer model is a result of the RMP.

Online Stock Market Games for High Schools.

ERIC Educational Resources Information Center

Lopus, Jane; Placone, Dennis

2002-01-01

Identifies a Web site providing information about stock market simulations for high school economics courses. Divides the information into two tables: (1) the structure of online stock market games; and (2) the determination of portfolio values of online stock market games. States that changes and updates are available at Web sites. (JEH)

Using an Integrated Hydrologic-Economic Model to Develop Minimum Cost Water Supply Portfolios and Manage Supply Risk

NASA Astrophysics Data System (ADS)

Characklis, G. W.; Ramsey, J.

2004-12-01

Water scarcity has become a reality in many areas as a result of population growth, fewer available sources, and reduced tolerance for the environmental impacts of developing the new supplies that do exist. As a result, successfully managing future water supply risk will become more dependent on coordinating the use of existing resources. Toward that end, flexible supply strategies that can rapidly respond to hydrologic variability will provide communities with increasing economic advantages, particularly if the frequency of more extreme events (e.g., drought) increases due to global climate change. Markets for established commodities (e.g., oil, gas) often provide a framework for efficiently responding to changes in supply and demand. Water markets, however, have remained relatively crude, with most transactions involving permanent transfers and long regulatory processes. Recently, interest in the use of flexible short-term transfers (e.g., leases, options) has begun to motivate consideration of more sophisticated strategies for managing supply risk, strategies similar to those used in more mature markets. In this case, communities can benefit from some of the advantages that water enjoys over other commodities, in particular, the ability to accurately characterize the stochastic nature of supply and demand through hydrologic modeling. Hydrologic-economic models are developed for two different water scarce regions supporting active water markets: Edward Aquifer and Lower Rio Grande Valley. These models are used to construct portfolios of water supply transfers (e.g., permanent transfers, options, and spot leases) that minimize the cost of meeting a probabilistic reliability constraint. Real and simulated spot price distributions allow each type of transfer to be priced in a manner consistent with financial theory (e.g., Black-Scholes). Market simulations are integrated with hydrologic models such that variability in supply and demand are linked with price behavior. Decisions on when and how much water to lease (or exercise, in the case of options) are made on the basis of anticipatory rules based on the ratio of expected supply to expected demand, and are used to evaluate the economic consequences of a utilityAƒAøAøâ_sA¬Aøâ_zAøs attitude toward risk. The marginal cost of supply reliability is also explored by varying the water supply reliability constraint, an important consideration as the rising expense of new source development may encourage some communities to accept a nominal number of supply shortfalls. Results demonstrate how changes in the distribution of various transfer types within a portfolio can affect its cost and reliability. Results also suggest that substantial savings can be obtained through the use of market-based risk management strategies, with optimal portfolio costs averaging as much as 35 percent less than the costs of meeting reliability targets through the maintenance of firm capacity. Both the conceptual and modeling approach described in this work are likely to have increasing application as water scarcity continues to drive the search for more efficient approaches to water resource management.

Micro and macro benefits of random investments in financial markets

NASA Astrophysics Data System (ADS)

Biondo, A. E.; Pluchino, A.; Rapisarda, A.

2014-10-01

In this paper, making use of recent statistical physics techniques and models, we address the specific role of randomness in financial markets, both at the micro and the macro level. In particular, we review some recent results obtained about the effectiveness of random strategies of investment, compared with some of the most used trading strategies for forecasting the behaviour of real financial indexes. We also push forward our analysis by means of a self-organised criticality model, able to simulate financial avalanches in trading communities with different network topologies, where a Pareto-like power law behaviour of wealth spontaneously emerges. In this context, we present new findings and suggestions for policies based on the effects that random strategies can have in terms of reduction of dangerous financial extreme events, i.e. bubbles and crashes.

Does the U.S. exercise contagion on Italy? A theoretical model and empirical evidence

NASA Astrophysics Data System (ADS)

Cerqueti, Roy; Fenga, Livio; Ventura, Marco

2018-06-01

This paper deals with the theme of contagion in financial markets. At this aim, we develop a model based on Mixed Poisson Processes to describe the abnormal returns of financial markets of two considered countries. In so doing, the article defines the theoretical conditions to be satisfied in order to state that one of them - the so-called leader - exercises contagion on the others - the followers. Specifically, we employ an invariant probabilistic result stating that a suitable transformation of a Mixed Poisson Process is still a Mixed Poisson Process. The theoretical claim is validated by implementing an extensive simulation analysis grounded on empirical data. The countries considered are the U.S. (as the leader) and Italy (as the follower) and the period under scrutiny is very large, ranging from 1970 to 2014.

Emergence of Opinion Leaders Based on Agent Model and Its Impact to Stock Prices

NASA Astrophysics Data System (ADS)

Misawa, Tadanobu; Suzuki, Kyoko; Okano, Yoshitaka; Shimokawa, Tetsuya

Recently, we can be able to get a lot of information easily because information technology has been developed. Therefore, it is thought that the impact to a society by communication of information such as word of mouth has been growing. In this paper, we propose a model of emergence of opinion leader based on word of mouth in artificial stock market. Moreover, the process of emergence of opinion leader and impact to stock prices by opinion leader are verified by simulation.

Multifractal Value at Risk model

NASA Astrophysics Data System (ADS)

Lee, Hojin; Song, Jae Wook; Chang, Woojin

2016-06-01

In this paper new Value at Risk (VaR) model is proposed and investigated. We consider the multifractal property of financial time series and develop a multifractal Value at Risk (MFVaR). MFVaR introduced in this paper is analytically tractable and not based on simulation. Empirical study showed that MFVaR can provide the more stable and accurate forecasting performance in volatile financial markets where large loss can be incurred. This implies that our multifractal VaR works well for the risk measurement of extreme credit events.

Gauge invariant lattice quantum field theory: Implications for statistical properties of high frequency financial markets

NASA Astrophysics Data System (ADS)

Dupoyet, B.; Fiebig, H. R.; Musgrove, D. P.

2010-01-01

We report on initial studies of a quantum field theory defined on a lattice with multi-ladder geometry and the dilation group as a local gauge symmetry. The model is relevant in the cross-disciplinary area of econophysics. A corresponding proposal by Ilinski aimed at gauge modeling in non-equilibrium pricing is implemented in a numerical simulation. We arrive at a probability distribution of relative gains which matches the high frequency historical data of the NASDAQ stock exchange index.

Incorporating Customer Lifetime Value into Marketing Simulation Games

ERIC Educational Resources Information Center

Cannon, Hugh M.; Cannon, James N.; Schwaiger, Manfred

2010-01-01

Notwithstanding the emerging prominence of customer lifetime value (CLV) and customer equity (CE) in the marketing literature during the past decade, virtually nothing has been done to address these concepts in the literature on simulation and gaming. This article addresses the failing, discussing the nature of CLV and CE and demonstrating how…

The Paper Airplane Challenge: A Market Economy Simulation. Lesson Plan.

ERIC Educational Resources Information Center

Owens, Kimberly

This lesson plan features a classroom simulation that helps students understand the characteristics of a market economic system. The lesson plan states a purpose; cites student objectives; suggests a time duration; lists materials needed; and details a step-by-step teaching procedure. The "Paper Airplane Challenge" handout is attached. (BT)

The co-evolutionary dynamics of directed network of spin market agents

NASA Astrophysics Data System (ADS)

Horváth, Denis; Kuscsik, Zoltán; Gmitra, Martin

2006-09-01

The spin market model [S. Bornholdt, Int. J. Mod. Phys. C 12 (2001) 667] is generalized by employing co-evolutionary principles, where strategies of the interacting and competitive traders are represented by local and global couplings between the nodes of dynamic directed stochastic network. The co-evolutionary principles are applied in the frame of Bak-Sneppen self-organized dynamics [P. Bak, K. Sneppen, Phys. Rev. Lett. 71 (1993) 4083] that includes the processes of selection and extinction actuated by the local (node) fitness. The local fitness is related to orientation of spin agent with respect to the instant magnetization. The stationary regime is formed due to the interplay of self-organization and adaptivity effects. The fat tailed distributions of log-price returns are identified numerically. The non-trivial model consequence is the evidence of the long time market memory indicated by the power-law range of the autocorrelation function of volatility with exponent smaller than one. The simulations yield network topology with broad-scale node degree distribution characterized by the range of exponents 1.3<γin<3 coinciding with social networks.

Education and the Market: A Response to "Imagined Evidence and False Imperatives"

ERIC Educational Resources Information Center

Holmes, Mark

2009-01-01

While Merrifield is correct in his basic argument that so-called "market reforms" in el/sec schooling are far from being pure market, he is incorrect to suggest that purer market projects are needed together with simulations of pure market reforms. There are two fundamental problems in that thesis. First, it is not clear that school choice in…

Further results on the macroeconomic effects of AIDS: the dualistic, labor-surplus economy.

PubMed

Cuddington, J T

1993-09-01

Analyses by Cuddington in 1993 and forthcoming work from Cuddington and Hancock model the macroeconomic effects of the AIDS epidemic using a modified Solow growth model. This single-sector framework rests upon the assumption that labor and capital are always efficiently allocated throughout the economy with neither market failures nor policy-induced distortions resulting in resource misallocation. Economies in low-income developing countries in sub-Saharan Africa, however, are not operating at capacity. Impact models based upon the potential growth path of economies will therefore significantly overstate the effect of an AIDS epidemic. The author thus incorporates the presence of underemployment and dual labor markets to redress the limitations of these earlier impact models. The dual-economy simulations of the economic impact of AIDS using Tanzanian data suggest that the macroeconomic consequences of the epidemic are of the same order of magnitude as those obtained using a single-sector, full-employment model: gross domestic product (GDP) is 15-25% smaller by 2010 than it would have been without AIDS, and per capita GDP is 0-10% smaller. Output lost from AIDS in the dual-economy framework is approximately the same as the output gain achievable through policies designed to increase labor market flexibility. Findings suggest that serious economic reform in economies fraught with AIDS may lessen the negative economic effects of the epidemic.

Coordination and decision making of regulation, operation, and market activities in power systems

NASA Astrophysics Data System (ADS)

Nakashima, Tomoaki

Electric power has been traditionally supplied to customers at regulated rates by vertically integrated utilities (VIUs), which own generation, transmission, and distribution systems. However, the regulatory authorities of VIUs are promoting competition in their businesses to lower the price of electric energy. Consequently, in new deregulated circumstances, many suppliers and marketers compete in the generation market, and conflict of interest may often occur over transmission. Therefore, a neutral entity, called an independent system operator (ISO), which operates the power system independently, has been established to give market participants nondiscriminatory access to transmission sectors with a natural monopoly, and to facilitate competition in generation sectors. Several types of ISOs are established at present, with their respective regions and authorities. The ISO receives many requests from market participants to transfer power, and must evaluate the feasibility of their requests under the system's condition. In the near future, regulatory authorities may impose various objectives on the ISOs. Then, based on the regulators' policies, the ISO must determine the optimal schedules from feasible solutions, or change the market participants' requests. In a newly developed power market, market participants will conduct their transactions in order to maximize their profit. The most crucial information in conducting power transactions is price and demand. A direct transaction between suppliers and consumers may become attractive because of its stability of price, while in a power exchange market, gaming and speculation of participants may push up electricity prices considerably. To assist the consumers in making effective decisions, suitable methods for forecasting volatile market price are necessary. This research has been approached from three viewpoints: Firstly, from the system operator's point of view, desirable system operation and power market structure are explored. Two typical ISO models, centralized and decentralized, have been identified and compared. These ISO models have been simulated to observe the advantages and disadvantages of the different systems. If no powerful players exist, the centralized system would achieve the maximum market efficiency. However, in decentralized systems, freedom of trade protects market participants from strategic bidding caused by powerful players. Reduced market efficiency is the price markets have to pay to prevent strategic bidding. Secondly, from the regulator's point of view, the effects of different policies imposed by regulators on power transactions are examined. The optimal schedule could be affected greatly by the ideal goals and their allowable values. Therefore, when the ISO defines its objectives and their allowable ranges, an agreeable conclusion among market participants is required. Fuzzy multiobjective optimization methods can be suitably applied to the scheduling of the ISO, reflecting its objectives and their allowable ranges properly. Thirdly, from market participants' point of view, models to represent and forecast the price and demand of power are developed. Electricity consumption and price are forecasted based on possibility theory and fuzzy autoregression. The fuzzy model can represent highly volatile demand-price relations as a range, and gives the possibility distribution of prices. Based on the proposed model, a procedure to help consumers decide whether to accept a bilateral transaction contract or market-based purchases of electricity has been developed. The same procedure can also be used by an electricity supplier or broker to determine an offering price.

Scheduling and Pricing for Expected Ramp Capability in Real-Time Power Markets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ela, Erik; O'Malley, Mark

2016-05-01

Higher variable renewable generation penetrations are occurring throughout the world on different power systems. These resources increase the variability and uncertainty on the system which must be accommodated by an increase in the flexibility of the system resources in order to maintain reliability. Many scheduling strategies have been discussed and introduced to ensure that this flexibility is available at multiple timescales. To meet variability, that is, the expected changes in system conditions, two recent strategies have been introduced: time-coupled multi-period market clearing models and the incorporation of ramp capability constraints. To appropriately evaluate these methods, it is important to assessmore » both efficiency and reliability. But it is also important to assess the incentive structure to ensure that resources asked to perform in different ways have the proper incentives to follow these directions, which is a step often ignored in simulation studies. We find that there are advantages and disadvantages to both approaches. We also find that look-ahead horizon length in multi-period market models can impact incentives. This paper proposes scheduling and pricing methods that ensure expected ramps are met reliably, efficiently, and with associated prices based on true marginal costs that incentivize resources to do as directed by the market. Case studies show improvements of the new method.« less

Optimal GENCO bidding strategy

NASA Astrophysics Data System (ADS)

Gao, Feng

Electricity industries worldwide are undergoing a period of profound upheaval. The conventional vertically integrated mechanism is being replaced by a competitive market environment. Generation companies have incentives to apply novel technologies to lower production costs, for example: Combined Cycle units. Economic dispatch with Combined Cycle units becomes a non-convex optimization problem, which is difficult if not impossible to solve by conventional methods. Several techniques are proposed here: Mixed Integer Linear Programming, a hybrid method, as well as Evolutionary Algorithms. Evolutionary Algorithms share a common mechanism, stochastic searching per generation. The stochastic property makes evolutionary algorithms robust and adaptive enough to solve a non-convex optimization problem. This research implements GA, EP, and PS algorithms for economic dispatch with Combined Cycle units, and makes a comparison with classical Mixed Integer Linear Programming. The electricity market equilibrium model not only helps Independent System Operator/Regulator analyze market performance and market power, but also provides Market Participants the ability to build optimal bidding strategies based on Microeconomics analysis. Supply Function Equilibrium (SFE) is attractive compared to traditional models. This research identifies a proper SFE model, which can be applied to a multiple period situation. The equilibrium condition using discrete time optimal control is then developed for fuel resource constraints. Finally, the research discusses the issues of multiple equilibria and mixed strategies, which are caused by the transmission network. Additionally, an advantage of the proposed model for merchant transmission planning is discussed. A market simulator is a valuable training and evaluation tool to assist sellers, buyers, and regulators to understand market performance and make better decisions. A traditional optimization model may not be enough to consider the distributed, large-scale, and complex energy market. This research compares the performance and searching paths of different artificial life techniques such as Genetic Algorithm (GA), Evolutionary Programming (EP), and Particle Swarm (PS), and look for a proper method to emulate Generation Companies' (GENCOs) bidding strategies. After deregulation, GENCOs face risk and uncertainty associated with the fast-changing market environment. A profit-based bidding decision support system is critical for GENCOs to keep a competitive position in the new environment. Most past research do not pay special attention to the piecewise staircase characteristic of generator offer curves. This research proposes an optimal bidding strategy based on Parametric Linear Programming. The proposed algorithm is able to handle actual piecewise staircase energy offer curves. The proposed method is then extended to incorporate incomplete information based on Decision Analysis. Finally, the author develops an optimal bidding tool (GenBidding) and applies it to the RTS96 test system.

Hotspot detection using image pattern recognition based on higher-order local auto-correlation

NASA Astrophysics Data System (ADS)

Maeda, Shimon; Matsunawa, Tetsuaki; Ogawa, Ryuji; Ichikawa, Hirotaka; Takahata, Kazuhiro; Miyairi, Masahiro; Kotani, Toshiya; Nojima, Shigeki; Tanaka, Satoshi; Nakagawa, Kei; Saito, Tamaki; Mimotogi, Shoji; Inoue, Soichi; Nosato, Hirokazu; Sakanashi, Hidenori; Kobayashi, Takumi; Murakawa, Masahiro; Higuchi, Tetsuya; Takahashi, Eiichi; Otsu, Nobuyuki

2011-04-01

Below 40nm design node, systematic variation due to lithography must be taken into consideration during the early stage of design. So far, litho-aware design using lithography simulation models has been widely applied to assure that designs are printed on silicon without any error. However, the lithography simulation approach is very time consuming, and under time-to-market pressure, repetitive redesign by this approach may result in the missing of the market window. This paper proposes a fast hotspot detection support method by flexible and intelligent vision system image pattern recognition based on Higher-Order Local Autocorrelation. Our method learns the geometrical properties of the given design data without any defects as normal patterns, and automatically detects the design patterns with hotspots from the test data as abnormal patterns. The Higher-Order Local Autocorrelation method can extract features from the graphic image of design pattern, and computational cost of the extraction is constant regardless of the number of design pattern polygons. This approach can reduce turnaround time (TAT) dramatically only on 1CPU, compared with the conventional simulation-based approach, and by distributed processing, this has proven to deliver linear scalability with each additional CPU.

Parallel computing in enterprise modeling.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goldsby, Michael E.; Armstrong, Robert C.; Shneider, Max S.

2008-08-01

This report presents the results of our efforts to apply high-performance computing to entity-based simulations with a multi-use plugin for parallel computing. We use the term 'Entity-based simulation' to describe a class of simulation which includes both discrete event simulation and agent based simulation. What simulations of this class share, and what differs from more traditional models, is that the result sought is emergent from a large number of contributing entities. Logistic, economic and social simulations are members of this class where things or people are organized or self-organize to produce a solution. Entity-based problems never have an a priorimore » ergodic principle that will greatly simplify calculations. Because the results of entity-based simulations can only be realized at scale, scalable computing is de rigueur for large problems. Having said that, the absence of a spatial organizing principal makes the decomposition of the problem onto processors problematic. In addition, practitioners in this domain commonly use the Java programming language which presents its own problems in a high-performance setting. The plugin we have developed, called the Parallel Particle Data Model, overcomes both of these obstacles and is now being used by two Sandia frameworks: the Decision Analysis Center, and the Seldon social simulation facility. While the ability to engage U.S.-sized problems is now available to the Decision Analysis Center, this plugin is central to the success of Seldon. Because Seldon relies on computationally intensive cognitive sub-models, this work is necessary to achieve the scale necessary for realistic results. With the recent upheavals in the financial markets, and the inscrutability of terrorist activity, this simulation domain will likely need a capability with ever greater fidelity. High-performance computing will play an important part in enabling that greater fidelity.« less

Information diffusion in structured online social networks

NASA Astrophysics Data System (ADS)

Li, Pei; Zhang, Yini; Qiao, Fengcai; Wang, Hui

2015-05-01

Nowadays, due to the word-of-mouth effect, online social networks have been considered to be efficient approaches to conduct viral marketing, which makes it of great importance to understand the diffusion dynamics in online social networks. However, most research on diffusion dynamics in epidemiology and existing social networks cannot be applied directly to characterize online social networks. In this paper, we propose models to characterize the information diffusion in structured online social networks with push-based forwarding mechanism. We introduce the term user influence to characterize the average number of times that messages are browsed which is incurred by a given type user generating a message, and study the diffusion threshold, above which the user influence of generating a message will approach infinity. We conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly. These results are of use in understanding the diffusion dynamics in online social networks and also critical for advertisers in viral marketing who want to estimate the user influence before posting an advertisement.

An Agent-Based Model of New Venture Creation: Conceptual Design for Simulating Entrepreneurship

NASA Technical Reports Server (NTRS)

Provance, Mike; Collins, Andrew; Carayannis, Elias

2012-01-01

There is a growing debate over the means by which regions can foster the growth of entrepreneurial activity in order to stimulate recovery and growth of their economies. On one side, agglomeration theory suggests the regions grow because of strong clusters that foster knowledge spillover locally; on the other side, the entrepreneurial action camp argues that innovative business models are generated by entrepreneurs with unique market perspectives who draw on knowledge from more distant domains. We will show you the design for a novel agent-based model of new venture creation that will demonstrate the relationship between agglomeration and action. The primary focus of this model is information exchange as the medium for these agent interactions. Our modeling and simulation study proposes to reveal interesting relationships in these perspectives, offer a foundation on which these disparate theories from economics and sociology can find common ground, and expand the use of agent-based modeling into entrepreneurship research.

Finite Element Modeling, Simulation, Tools, and Capabilities at Superform

NASA Astrophysics Data System (ADS)

Raman, Hari; Barnes, A. J.

2010-06-01

Over the past thirty years Superform has been a pioneer in the SPF arena, having developed a keen understanding of the process and a range of unique forming techniques to meet varying market needs. Superform’s high-profile list of customers includes Boeing, Airbus, Aston Martin, Ford, and Rolls Royce. One of the more recent additions to Superform’s technical know-how is finite element modeling and simulation. Finite element modeling is a powerful numerical technique which when applied to SPF provides a host of benefits including accurate prediction of strain levels in a part, presence of wrinkles and predicting pressure cycles optimized for time and part thickness. This paper outlines a brief history of finite element modeling applied to SPF and then reviews some of the modeling tools and techniques that Superform have applied and continue to do so to successfully superplastically form complex-shaped parts. The advantages of employing modeling at the design stage are discussed and illustrated with real-world examples.

True and apparent scaling: The proximity of the Markov-switching multifractal model to long-range dependence

NASA Astrophysics Data System (ADS)

Liu, Ruipeng; Di Matteo, T.; Lux, Thomas

2007-09-01

In this paper, we consider daily financial data of a collection of different stock market indices, exchange rates, and interest rates, and we analyze their multi-scaling properties by estimating a simple specification of the Markov-switching multifractal (MSM) model. In order to see how well the estimated model captures the temporal dependence of the data, we estimate and compare the scaling exponents H(q) (for q=1,2) for both empirical data and simulated data of the MSM model. In most cases the multifractal model appears to generate ‘apparent’ long memory in agreement with the empirical scaling laws.

Stochastic simulation of power systems with integrated renewable and utility-scale storage resources

NASA Astrophysics Data System (ADS)

Degeilh, Yannick

The push for a more sustainable electric supply has led various countries to adopt policies advocating the integration of renewable yet variable energy resources, such as wind and solar, into the grid. The challenges of integrating such time-varying, intermittent resources has in turn sparked a growing interest in the implementation of utility-scale energy storage resources ( ESRs), with MWweek storage capability. Indeed, storage devices provide flexibility to facilitate the management of power system operations in the presence of uncertain, highly time-varying and intermittent renewable resources. The ability to exploit the potential synergies between renewable and ESRs hinges on developing appropriate models, methodologies, tools and policy initiatives. We report on the development of a comprehensive simulation methodology that provides the capability to quantify the impacts of integrated renewable and ESRs on the economics, reliability and emission variable effects of power systems operating in a market environment. We model the uncertainty in the demands, the available capacity of conventional generation resources and the time-varying, intermittent renewable resources, with their temporal and spatial correlations, as discrete-time random processes. We deploy models of the ESRs to emulate their scheduling and operations in the transmission-constrained hourly day-ahead markets. To this end, we formulate a scheduling optimization problem (SOP) whose solutions determine the operational schedule of the controllable ESRs in coordination with the demands and the conventional/renewable resources. As such, the SOP serves the dual purpose of emulating the clearing of the transmission-constrained day-ahead markets (DAMs ) and scheduling the energy storage resource operations. We also represent the need for system operators to impose stricter ramping requirements on the conventional generating units so as to maintain the system capability to perform "load following'', i.e., respond to quick variations in the loads and renewable resource outputs in a manner that maintains the power balance, by incorporating appropriate ramping requirement constraints in the formulation of the SOP. The simulation approach makes use of Monte Carlo simulation techniques to represent the impacts of the sources of uncertainty on the side-by-side power system and market operations. As such, we systematically sample the "input'' random processes -- namely the buyer demands, renewable resource outputs and conventional generation resource available capacities -- to generate the realizations, or sample paths, that we use in the emulation of the transmission-constrained day-ahead markets via SOP . As a result, we obtain realizations of the market outcomes and storage resource operations that we can use to approximate their statistics. The approach not only has the capability to emulate the side-by-side power system and energy market operations with the explicit representation of the chronology of time-dependent phenomena -- including storage cycles of charge/discharge -- and constraints imposed by the transmission network in terms of deliverability of the energy, but also to provide the figures of merit for all metrics to assess the economics, reliability and the environmental impacts of the performance of those operations. Our efforts to address the implementational aspects of the methodology so as to ensure computational tractability for large-scale systems over longer periods include relaxing the SOP, the use of a "warm-start'' technique as well as representative simulation periods, parallelization and variance reduction techniques. Our simulation approach is useful in power system planning, operations and investment analysis. There is a broad range of applications of the simulation methodology to resource planning studies, production costing issues, investment analysis, transmission utilization, reliability analysis, environmental assessments, policy formulation and to answer quantitatively various what-if questions. We demonstrate the capabilities of the simulation approach by carrying out various studies on modified IEEE 118- and WECC 240-bus systems. The results of our representative case studies effectively illustrate the synergies among wind and ESRs. Our investigations clearly indicate that energy storage and wind resources tend to complement each other in the reduction of wholesale purchase payments in the DAMs and the improvement of system reliability. In addition, we observe that CO2 emission impacts with energy storage depend on the resource mix characteristics. An important finding is that storage seems to attenuate the "diminishing returns'' associated with increased penetration of wind generation. Our studies also evidence the limited ability of integrated ESRs to enhance the wind resource capability to replace conventional resources from purely a system reliability perspective. Some useful insights into the siting of ESRs are obtained and they indicate the potentially significant impacts of such decisions on the network congestion patterns and, consequently, on the LMPs. Simulation results further indicate that the explicit representation of ramping requirements on the conventional units at the DAM level causes the expected total wholesale purchase payments to increase, thereby mitigating the benefits of wind integration. The stricter ramping requirements are also shown to impact the revenues of generators that do not even provide any ramp capability services.

A Generalized Formulation of Demand Response under Market Environments

NASA Astrophysics Data System (ADS)

Nguyen, Minh Y.; Nguyen, Duc M.

2015-06-01

This paper presents a generalized formulation of Demand Response (DR) under deregulated electricity markets. The problem is scheduling and controls the consumption of electrical loads according to the market price to minimize the energy cost over a day. Taking into account the modeling of customers' comfort (i.e., preference), the formulation can be applied to various types of loads including what was traditionally classified as critical loads (e.g., air conditioning, lights). The proposed DR scheme is based on Dynamic Programming (DP) framework and solved by DP backward algorithm in which the stochastic optimization is used to treat the uncertainty, if any occurred in the problem. The proposed formulation is examined with the DR problem of different loads, including Heat Ventilation and Air Conditioning (HVAC), Electric Vehicles (EVs) and a newly DR on the water supply systems of commercial buildings. The result of simulation shows significant saving can be achieved in comparison with their traditional (On/Off) scheme.

Bootstrap simulation, Markov decision process models, and role of discounting in the valuation of ecological criteria in uneven-aged forest management

Treesearch

Mo Zhou; Joseph Buongiorno; Jingjing Liang

2012-01-01

Besides the market value of timber, forests provide substantial nonmarket benefits, especially with continuous-cover silviculture, which have long been acknowledged by forest managers. They include wildlife habitat (e.g. Bevers and Hof 1999), carbon sequestration (e.g. Dewar and Cannell 1992), biodiversity (e.g. Kangas and Kuusipalo 1993; Austin and Meyers 1999),...

Timber Supply Projections for Northern New England and New York: Integrating a Market Perspective

Treesearch

Paul E. Sendak; Robert C. Abt; Robert J. Turner

2003-01-01

The North East State Foresters Association (NEFA) commissioned a study that resulted in the publication of a report titled, "A Forest Resource Model of the States of New York, Vermont, New Hampshire, and Maine." In this article we used the integrated NEFA computer simulation framework to go beyond the reported results and further explore the effects on the...

Redundancy of Supply in the International Nuclear Fuel Fabrication Market: Are Fabrication Services Assured?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seward, Amy M.; Toomey, Christopher; Ford, Benjamin E.

2011-11-14

For several years, Pacific Northwest National Laboratory (PNNL) has been assessing the reliability of nuclear fuel supply in support of the U.S. Department of Energy/National Nuclear Security Administration. Three international low enriched uranium reserves, which are intended back up the existing and well-functioning nuclear fuel market, are currently moving toward implementation. These backup reserves are intended to provide countries credible assurance that of the uninterrupted supply of nuclear fuel to operate their nuclear power reactors in the event that their primary fuel supply is disrupted, whether for political or other reasons. The efficacy of these backup reserves, however, may bemore » constrained without redundant fabrication services. This report presents the findings of a recent PNNL study that simulated outages of varying durations at specific nuclear fuel fabrication plants. The modeling specifically enabled prediction and visualization of the reactors affected and the degree of fuel delivery delay. The results thus provide insight on the extent of vulnerability to nuclear fuel supply disruption at the level of individual fabrication plants, reactors, and countries. The simulation studies demonstrate that, when a reasonable set of qualification criteria are applied, existing fabrication plants are technically qualified to provide backup fabrication services to the majority of the world's power reactors. The report concludes with an assessment of the redundancy of fuel supply in the nuclear fuel market, and a description of potential extra-market mechanisms to enhance the security of fuel supply in cases where it may be warranted. This report is an assessment of the ability of the existing market to respond to supply disruptions that occur for technical reasons. A forthcoming report will address political disruption scenarios.« less

WORKING AND CARING: THE SIMULTANEOUS DECISION OF LABOR FORCE PARTICIPATION AND INFORMAL ELDERLY AND CHILD SUPPORT ACT IVITIES IN MEXICO*

PubMed Central

van Gameren, Edwin; Velandia Naranjo, Durfari

2016-01-01

We analyze factors determining women’s decisions to participate in the labor market and provide elderly care and nonfinancial support to their (grand)children. We use data from the Mexican Health and Aging Study, a survey of people aged 50 and over, applying a three-equation, reduced-form SUR model. Results suggest that care needs are the driving force behind caregiving activities. Traditional roles also appear to be relevant in the labor force participation decision: women with a closer labor market connection when they were young are more likely to work. Simulations of demographic changes illustrate potential effects for future caregiving and participation rates. PMID:26924883

Nonisothermal glass molding for the cost-efficient production of precision freeform optics

NASA Astrophysics Data System (ADS)

Vu, Anh-Tuan; Kreilkamp, Holger; Dambon, Olaf; Klocke, Fritz

2016-07-01

Glass molding has become a key replication-based technology to satisfy intensively growing demands of complex precision optics in the today's photonic market. However, the state-of-the-art replicative technologies are still limited, mainly due to their insufficiency to meet the requirements of mass production. This paper introduces a newly developed nonisothermal glass molding in which a complex-shaped optic is produced in a very short process cycle. The innovative molding technology promises a cost-efficient production because of increased mold lifetime, less energy consumption, and high throughput from a fast process chain. At the early stage of the process development, the research focuses on an integration of finite element simulation into the process chain to reduce time and labor-intensive cost. By virtue of numerical modeling, defects including chill ripples and glass sticking in the nonisothermal molding process can be predicted and the consequent effects are avoided. In addition, the influences of process parameters and glass preforms on the surface quality, form accuracy, and residual stress are discussed. A series of experiments was carried out to validate the simulation results. The successful modeling, therefore, provides a systematic strategy for glass preform design, mold compensation, and optimization of the process parameters. In conclusion, the integration of simulation into the entire nonisothermal glass molding process chain will significantly increase the manufacturing efficiency as well as reduce the time-to-market for the mass production of complex precision yet low-cost glass optics.

Design and application of a CA-BDI model to determine farmers' land-use behavior.

PubMed

Liang, Xiaoying; Chen, Hai; Wang, Yanni; Song, Shixiong

2016-01-01

The belief-desire-intention (BDI) model has been widely used to construct reasoning systems for complex tasks in dynamic environments. We have designed a capabilities and abilities (CA)-BDI farmer decision-making model, which is an extension of the BDI architecture and includes internal representations for farmer household Capabilities and Abilities. This model is used to explore farmer learning mechanisms and to simulate the bounded rational decisions made by farmer households. Our case study focuses on the Gaoqu Commune of Mizhi County, Shaanxi Province, China, where scallion is one of the main cash crops. After comparing the differences between actual land-use changes from 2007 to 2009 and the simulation results, we analyze the validity of the model and discuss the potential and limitations of the farmer land-use decision-making model under three scenarios. Based on the design and implementation of the model, the following conclusions can be drawn: (1) the CA-BDI framework is an appropriate model for exploring learning mechanisms and simulating bounded rational decisions; and (2) local governments should encourage scallion planting by assisting scallion farmer cooperatives and farmers to understand the market risk, standardize the rules of their cooperation, and supervise the contracts made between scallion cooperatives and farmers.

A dual theory of price and value in a meso-scale economic model with stochastic profit rate

NASA Astrophysics Data System (ADS)

Greenblatt, R. E.

2014-12-01

The problem of commodity price determination in a market-based, capitalist economy has a long and contentious history. Neoclassical microeconomic theories are based typically on marginal utility assumptions, while classical macroeconomic theories tend to be value-based. In the current work, I study a simplified meso-scale model of a commodity capitalist economy. The production/exchange model is represented by a network whose nodes are firms, workers, capitalists, and markets, and whose directed edges represent physical or monetary flows. A pair of multivariate linear equations with stochastic input parameters represent physical (supply/demand) and monetary (income/expense) balance. The input parameters yield a non-degenerate profit rate distribution across firms. Labor time and price are found to be eigenvector solutions to the respective balance equations. A simple relation is derived relating the expected value of commodity price to commodity labor content. Results of Monte Carlo simulations are consistent with the stochastic price/labor content relation.

Covered California: The Impact of Provider and Health Plan Market Power on Premiums.

PubMed

Scheffler, Richard M; Kessell, Eric; Brandt, Margareta

2015-12-01

We explain the establishment of Covered California, California's health insurance marketplace. The marketplace uses an active purchaser model, which means that Covered California can selectively contract with some health plans and exclude others. During the 2014 open-enrollment period, it enrolled 1.3 million people, who are covered by eleven health plans. We describe the market shares of health plans in California and in each of the nineteen rating regions. We examine the empirical relationship between measures of provider market concentration--spanning health plans, hospitals, and medical groups--and rating region premiums. To do this, we analyze premiums for silver and bronze plans for specific age groups. We find both medical group concentration and hospital concentration to be positively associated with premiums, while health plan concentration is not statistically significant. We simulate the impact of reducing hospital concentration to levels that would exist in moderately competitive markets. This produces a predicted overall premium reduction of more than 2 percent. However, in three of the nineteen rating regions, the predicted premium reduction was more than 10 percent. These results suggest the importance of provider market concentration on premiums. Copyright © 2016 by Duke University Press.

Testing the feasibility of a hypothetical whaling-conservation permit market in Norway.

PubMed

Huang, Biao; Abbott, Joshua K; Fenichel, Eli P; Muneepeerakul, Rachata; Perrings, Charles; Gerber, Leah R

2017-08-01

A cap-and-trade system for managing whale harvests represents a potentially useful approach to resolve the current gridlock in international whale management. The establishment of whale permit markets, open to both whalers and conservationists, could reveal the strength of conservation demand, about which little is known. This lack of knowledge makes it difficult to predict the outcome of a hypothetical whale permit market. We developed a bioeconomic model to evaluate the influence of economic uncertainty about demand for whale conservation or harvest. We used simulations over a wide range of parameterizations of whaling and conservation demands to examine the potential ecological consequences of the establishment of a whale permit market in Norwegian waters under bounded (but substantial) economic uncertainty. Uncertainty variables were slope of whaling and conservation demand, participation level of conservationists and their willingness to pay for whale conservation, and functional forms of demand, including linear, quadratic, and log-linear forms. A whale-conservation market had the potential to yield a wide range of conservation and harvest outcomes, the most likely outcomes were those in which conservationists bought all whale permits. © 2017 Society for Conservation Biology.

Implementing "Marketing Me": A Simulation Enhanced Variant for a Student Self-Marketing Exercise

ERIC Educational Resources Information Center

Flostrand, Andrew; Ho, Jason Y. C.; Krider, Robert E.

2016-01-01

The use of student self-branding exercises in introductory marketing courses for undergraduate business programs has been growing in popularity due to a number of advantages for students. This article introduces implementation of the "Marketing Me" variant developed and used since 2013 by the authors, wherein alumni are brought in to…

Reputations in Markets with Asymmetric Information: A Classroom Game

ERIC Educational Resources Information Center

Wolf, James R.; Myerscough, Mark A.

2007-01-01

The authors describe a classroom game used to teach students about the impact of reputations in markets with asymmetric information. The game is an extension of Holt and Sherman's lemons market game and simulates a market under three information conditions. In the full information setting, all participants know both the quality and the price of…

Structural model for fluctuations in financial markets

NASA Astrophysics Data System (ADS)

Anand, Kartik; Khedair, Jonathan; Kühn, Reimer

2018-05-01

In this paper we provide a comprehensive analysis of a structural model for the dynamics of prices of assets traded in a market which takes the form of an interacting generalization of the geometric Brownian motion model. It is formally equivalent to a model describing the stochastic dynamics of a system of analog neurons, which is expected to exhibit glassy properties and thus many metastable states in a large portion of its parameter space. We perform a generating functional analysis, introducing a slow driving of the dynamics to mimic the effect of slowly varying macroeconomic conditions. Distributions of asset returns over various time separations are evaluated analytically and are found to be fat-tailed in a manner broadly in line with empirical observations. Our model also allows us to identify collective, interaction-mediated properties of pricing distributions and it predicts pricing distributions which are significantly broader than their noninteracting counterparts, if interactions between prices in the model contain a ferromagnetic bias. Using simulations, we are able to substantiate one of the main hypotheses underlying the original modeling, viz., that the phenomenon of volatility clustering can be rationalized in terms of an interplay between the dynamics within metastable states and the dynamics of occasional transitions between them.

Simulation of Electrical Characteristics of a Solar Panel

NASA Astrophysics Data System (ADS)

Obukhov, S.; Plotnikov, I.; Kryuchkova, M.

2016-06-01

The fast-growing photovoltaic system market leads to the necessity of the informed choice of major energy components and optimization of operating conditions in order to improve energy efficiency. Development of mathematical models of the main components of photovoltaic systems to ensure their comprehensive study is an urgent problem of improving and practical using of the technology of electrical energy production. The paper presents a mathematical model of the solar module implemented in the popular software MATLAB/Simulink. Equivalent circuit of the solar cell with a diode parallel without derived resistance is used for modelling. The serie8s resistance of the solar module is calculated by Newton's iterative method using the data of its technical specifications. It ensures high precision of simulation. Model validity was evaluated by the well-known technical characteristics of the module Solarex MSX 60. The calculation results of the experiment showed that the obtained current-voltage and current-watt characteristics of the model are compatible with those of the manufacturer.

The evaluation of simulation market in nursing education and the determination of learning style of students

PubMed Central

Çelik, Yasemin; Ceylantekin, Yeşim; Kiliç, İbrahim

2017-01-01

Objective: The aim of this study is to detect the overall evaluation of nursing students toward simulation markets throughout the practice education and to reveal their learning styles in relation to certain individual features. Materials and Methods: The data were collected via questionnaires including students’ evaluation toward simulation markets and “Kolb learning styles inventory.” Participants included 103 male and female nursing students in Turkey. For the analysis, percentage, means, standard deviation, t-test, and ANOVA were utilized. Results: 71% of the students stated that the laboratory was suitable for the skill education but 53.4% uttered the duration of the practice was not enough. Students were found to have different learning styles (28.2% assimilating, 27.2% convergent, 26.2% accommodating, and 18.4% divergent). Conclusion: The results demonstrated that the duration of the laboratory practice and the number of the markets should be increased during the education of students with different learning styles. PMID:28293150

The Effectiveness of Web-Based Foreign Exchange Trading Simulation in an International Finance Course

ERIC Educational Resources Information Center

Chou, Chen-Huei; Liu, Hao-Chen

2013-01-01

The purpose of this article is to study if trading simulation is an effective tool to increase students' knowledge of the foreign exchange market. We developed a real-time multiuser web-based trading system that replicates an electronic brokerage foreign exchange market. To assess the effectiveness of the program, we conducted surveys in three…

MainXchange in the Classroom: The New Internet Stock Market Game. Teacher's Guide and Student Activities.

ERIC Educational Resources Information Center

1998

This teaching guide/student activities booklet, for grades 6-9 and 7-11, outlines an Internet-based stock exchange simulation that allows students to learn about the stock market in a fun format. The simulation (the "MainXchange") described in the booklet offers students the opportunity to engage in "real-life" investing, while…

Forest-stressing climate factors on the US West Coast as simulated by CMIP5

NASA Astrophysics Data System (ADS)

Rupp, D. E.; Buotte, P.; Hicke, J. A.; Law, B. E.; Mote, P.; Sharp, D.; Zhenlin, Y.

2013-12-01

The rate of forest mortality has increased significantly in western North America since the 1970s. Causes include insect attacks, fire, and soil water deficit, all of which are interdependent. We first identify climate factors that stress forests by reducing photosynthesis and hydraulic conductance, and by promoting bark beetle infestation and wildfire. Examples of such factors may be two consecutive years of extreme summer precipitation deficit, or prolonged vapor pressure deficit exceeding some threshold. Second, we quantify the frequency and magnitude of these climate factors in 20th and 21st century climates, as simulated by global climate models (GCMs) in Coupled Model Intercomparison Project phase 5 (CMIP5), of Washington, Oregon, and California in the western US. Both ';raw' (i.e., original spatial resolution) and statistically downscaled simulations are considered, the latter generated using the Multivariate Adaptive Constructed Analogs (MACA) method. CMIP5 models that most faithfully reproduce the observed historical statistics of these climate factors are identified. Furthermore, significant changes in the statistics between the 20th and 21st centuries are reported. A subsequent task will be to use a selected subset of MACA-downscaled CMIP5 simulations to force the Community Land Model, version 4.5 (CLM 4.5). CLM 4.5 will be modified to better simulate forest mortality and to couple CLM with an economic model. The ultimate goal of this study is to understand the interactions and the feedbacks by which the market and the forest ecosystem influence each other.

Structural Health Monitoring challenges on the 10-MW offshore wind turbine model

NASA Astrophysics Data System (ADS)

Di Lorenzo, E.; Kosova, G.; Musella, U.; Manzato, S.; Peeters, B.; Marulo, F.; Desmet, W.

2015-07-01

The real-time structural damage detection on large slender structures has one of its main application on offshore Horizontal Axis Wind Turbines (HAWT). The renewable energy market is continuously pushing the wind turbine sizes and performances. This is the reason why nowadays offshore wind turbines concepts are going toward a 10 MW reference wind turbine model. The aim of the work is to perform operational analyses on the 10-MW reference wind turbine finite element model using an aeroelastic code in order to obtain long-time-low- cost simulations. The aeroelastic code allows simulating the damages in several ways: by reducing the edgewise/flapwise blades stiffness, by adding lumped masses or considering a progressive mass addiction (i.e. ice on the blades). The damage detection is then performed by means of Operational Modal Analysis (OMA) techniques. Virtual accelerometers are placed in order to simulate real measurements and to estimate the modal parameters. The feasibility of a robust damage detection on the model has been performed on the HAWT model in parked conditions. The situation is much more complicated in case of operating wind turbines because the time periodicity of the structure need to be taken into account. Several algorithms have been implemented and tested in the simulation environment. They are needed in order to carry on a damage detection simulation campaign and develop a feasible real-time damage detection method. In addition to these algorithms, harmonic removal tools are needed in order to dispose of the harmonics due to the rotation.

Pattern-oriented modeling of agent-based complex systems: Lessons from ecology

USGS Publications Warehouse

Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

2005-01-01

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology

NASA Astrophysics Data System (ADS)

Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

2005-11-01

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

On financial markets trading

NASA Astrophysics Data System (ADS)

Matassini, Lorenzo; Franci, Fabio

2001-01-01

Starting from the observation of the real trading activity, we propose a model of a stockmarket simulating all the typical phases taking place in a stock exchange. We show that there is no need of several classes of agents once one has introduced realistic constraints in order to confine money, time, gain and loss within an appropriate range. The main ingredients are local and global coupling, randomness, Zipf distribution of resources and price formation when inserting an order. The simulation starts with the initial public offer and comprises the broadcasting of news/advertisements and the building of the book, where all the selling and buying orders are stored. The model is able to reproduce fat tails and clustered volatility, the two most significant characteristics of a real stockmarket, being driven by very intuitive parameters.

Design optimization of a prescribed vibration system using conjoint value analysis

NASA Astrophysics Data System (ADS)

Malinga, Bongani; Buckner, Gregory D.

2016-12-01

This article details a novel design optimization strategy for a prescribed vibration system (PVS) used to mechanically filter solids from fluids in oil and gas drilling operations. A dynamic model of the PVS is developed, and the effects of disturbance torques are detailed. This model is used to predict the effects of design parameters on system performance and efficiency, as quantified by system attributes. Conjoint value analysis, a statistical technique commonly used in marketing science, is utilized to incorporate designer preferences. This approach effectively quantifies and optimizes preference-based trade-offs in the design process. The effects of designer preferences on system performance and efficiency are simulated. This novel optimization strategy yields improvements in all system attributes across all simulated vibration profiles, and is applicable to other industrial electromechanical systems.

Dynamically Hedging Oil and Currency Futures Using Receding Horizontal Control and Stochastic Programming

NASA Astrophysics Data System (ADS)

Cottrell, Paul Edward

There is a lack of research in the area of hedging future contracts, especially in illiquid or very volatile market conditions. It is important to understand the volatility of the oil and currency markets because reduced fluctuations in these markets could lead to better hedging performance. This study compared different hedging methods by using a hedging error metric, supplementing the Receding Horizontal Control and Stochastic Programming (RHCSP) method by utilizing the London Interbank Offered Rate with the Levy process. The RHCSP hedging method was investigated to determine if improved hedging error was accomplished compared to the Black-Scholes, Leland, and Whalley and Wilmott methods when applied on simulated, oil, and currency futures markets. A modified RHCSP method was also investigated to determine if this method could significantly reduce hedging error under extreme market illiquidity conditions when applied on simulated, oil, and currency futures markets. This quantitative study used chaos theory and emergence for its theoretical foundation. An experimental research method was utilized for this study with a sample size of 506 hedging errors pertaining to historical and simulation data. The historical data were from January 1, 2005 through December 31, 2012. The modified RHCSP method was found to significantly reduce hedging error for the oil and currency market futures by the use of a 2-way ANOVA with a t test and post hoc Tukey test. This study promotes positive social change by identifying better risk controls for investment portfolios and illustrating how to benefit from high volatility in markets. Economists, professional investment managers, and independent investors could benefit from the findings of this study.

Game Theoretic Modeling of Water Resources Allocation Under Hydro-Climatic Uncertainty

NASA Astrophysics Data System (ADS)

Brown, C.; Lall, U.; Siegfried, T.

2005-12-01

Typical hydrologic and economic modeling approaches rely on assumptions of climate stationarity and economic conditions of ideal markets and rational decision-makers. In this study, we incorporate hydroclimatic variability with a game theoretic approach to simulate and evaluate common water allocation paradigms. Game Theory may be particularly appropriate for modeling water allocation decisions. First, a game theoretic approach allows economic analysis in situations where price theory doesn't apply, which is typically the case in water resources where markets are thin, players are few, and rules of exchange are highly constrained by legal or cultural traditions. Previous studies confirm that game theory is applicable to water resources decision problems, yet applications and modeling based on these principles is only rarely observed in the literature. Second, there are numerous existing theoretical and empirical studies of specific games and human behavior that may be applied in the development of predictive water allocation models. With this framework, one can evaluate alternative orderings and rules regarding the fraction of available water that one is allowed to appropriate. Specific attributes of the players involved in water resources management complicate the determination of solutions to game theory models. While an analytical approach will be useful for providing general insights, the variety of preference structures of individual players in a realistic water scenario will likely require a simulation approach. We propose a simulation approach incorporating the rationality, self-interest and equilibrium concepts of game theory with an agent-based modeling framework that allows the distinct properties of each player to be expressed and allows the performance of the system to manifest the integrative effect of these factors. Underlying this framework, we apply a realistic representation of spatio-temporal hydrologic variability and incorporate the impact of decision-making a priori to hydrologic realizations and those made a posteriori on alternative allocation mechanisms. Outcomes are evaluated in terms of water productivity, net social benefit and equity. The performance of hydro-climate prediction modeling in each allocation mechanism will be assessed. Finally, year-to-year system performance and feedback pathways are explored. In this way, the system can be adaptively managed toward equitable and efficient water use.

Strategy and gaps for modeling, simulation, and control of hybrid systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rabiti, Cristian; Garcia, Humberto E.; Hovsapian, Rob

2015-04-01

The purpose of this report is to establish a strategy for modeling and simulation of candidate hybrid energy systems. Modeling and simulation is necessary to design, evaluate, and optimize the system technical and economic performance. Accordingly, this report first establishes the simulation requirements to analysis candidate hybrid systems. Simulation fidelity levels are established based on the temporal scale, real and synthetic data availability or needs, solution accuracy, and output parameters needed to evaluate case-specific figures of merit. Accordingly, the associated computational and co-simulation resources needed are established; including physical models when needed, code assembly and integrated solutions platforms, mathematical solvers,more » and data processing. This report first attempts to describe the figures of merit, systems requirements, and constraints that are necessary and sufficient to characterize the grid and hybrid systems behavior and market interactions. Loss of Load Probability (LOLP) and effective cost of Effective Cost of Energy (ECE), as opposed to the standard Levelized Cost of Electricty (LCOE), are introduced as technical and economical indices for integrated energy system evaluations. Financial assessment methods are subsequently introduced for evaluation of non-traditional, hybrid energy systems. Algorithms for coupled and iterative evaluation of the technical and economic performance are subsequently discussed. This report further defines modeling objectives, computational tools, solution approaches, and real-time data collection and processing (in some cases using real test units) that will be required to model, co-simulate, and optimize; (a) an energy system components (e.g., power generation unit, chemical process, electricity management unit), (b) system domains (e.g., thermal, electrical or chemical energy generation, conversion, and transport), and (c) systems control modules. Co-simulation of complex, tightly coupled, dynamic energy systems requires multiple simulation tools, potentially developed in several programming languages and resolved on separate time scales. Whereas further investigation and development of hybrid concepts will provide a more complete understanding of the joint computational and physical modeling needs, this report highlights areas in which co-simulation capabilities are warranted. The current development status, quality assurance, availability and maintainability of simulation tools that are currently available for hybrid systems modeling is presented. Existing gaps in the modeling and simulation toolsets and development needs are subsequently discussed. This effort will feed into a broader Roadmap activity for designing, developing, and demonstrating hybrid energy systems.« less

Temperature Effects on Olive Fruit Fly Infestation in the FlySim Cellular Automata Model

NASA Astrophysics Data System (ADS)

Bruno, Vincenzo; Baldacchini, Valerio; di Gregorio, Salvatore

FlySim is a Cellular Automata model developed for simulating infestation of olive fruit flies (Bactrocera Oleae) on olive (Olea europaea) groves. The flies move into the groves looking for mature olives where eggs are spawn. This serious agricultural problem is mainly tackled by using chemical agents at the first signs of the infestation, but organic productions with no or few chemicals are strongly requested by the market. Oil made with infested olives is poor in quality, nor olives are suitable for selling in stores. The FlySim model simulates the diffusion of flies looking for mature olives and the growing of flies due to atmospheric conditions. Foreseeing an infestation is the best way to prevent it and to reduce the need of chemicals in agriculture. In this work we investigated the effects of temperature on olive fruit flies and resulting infestation during late spring and summer.

Adaptive Portfolio Optimization for Multiple Electricity Markets Participation.

PubMed

Pinto, Tiago; Morais, Hugo; Sousa, Tiago M; Sousa, Tiago; Vale, Zita; Praca, Isabel; Faia, Ricardo; Pires, Eduardo Jose Solteiro

2016-08-01

The increase of distributed energy resources, mainly based on renewable sources, requires new solutions that are able to deal with this type of resources' particular characteristics (namely, the renewable energy sources intermittent nature). The smart grid concept is increasing its consensus as the most suitable solution to facilitate the small players' participation in electric power negotiations while improving energy efficiency. The opportunity for players' participation in multiple energy negotiation environments (smart grid negotiation in addition to the already implemented market types, such as day-ahead spot markets, balancing markets, intraday negotiations, bilateral contracts, forward and futures negotiations, and among other) requires players to take suitable decisions on whether to, and how to participate in each market type. This paper proposes a portfolio optimization methodology, which provides the best investment profile for a market player, considering different market opportunities. The amount of power that each supported player should negotiate in each available market type in order to maximize its profits, considers the prices that are expected to be achieved in each market, in different contexts. The price forecasts are performed using artificial neural networks, providing a specific database with the expected prices in the different market types, at each time. This database is then used as input by an evolutionary particle swarm optimization process, which originates the most advantage participation portfolio for the market player. The proposed approach is tested and validated with simulations performed in multiagent simulator of competitive electricity markets, using real electricity markets data from the Iberian operator-MIBEL.

Simulation of sovereign CDS market based on interaction between market participant

NASA Astrophysics Data System (ADS)

Ko, Bonggyun; Kim, Kyungwon

2017-08-01

A research for distributional property of financial asset is the subject of intense interest not only for financial theory but also for practitioner. Such respect is no exception to CDS market. The CDS market, which began to receive attention since the global financial debacle, is not well researched despite of the importance of research necessity. This research introduces creation of CDS market and use Ising system utilizing occurrence characteristics (to shift risk) as an important factor. Therefore the results of this paper would be of great assistance to both financial theory and practice. From this study, not only distributional property of the CDS market but also various statistics like multifractal characteristics could promote understanding about the market. A salient point in this study is that countries are mainly clustering into 2 groups and it might be because of market situation and geographical characteristics of each country. This paper suggested 2 simulation parameters representing this market based on understanding such CDS market situation. The estimated parameters are suitable for high and low risk event of CDS market respectively and these two parameters are complementary and can cover not only basic statistics but also multifractal properties of most countries. Therefore these estimated parameters can be used in researches preparing for a certain event (high or low risk). Finally this research will serve as a momentum double-checking indirectly the performance of Ising system based on these results.

Modelling volatility recurrence intervals in the Chinese commodity futures market

NASA Astrophysics Data System (ADS)

Zhou, Weijie; Wang, Zhengxin; Guo, Haiming

2016-09-01

The law of extreme event occurrence attracts much research. The volatility recurrence intervals of Chinese commodity futures market prices are studied: the results show that the probability distributions of the scaled volatility recurrence intervals have a uniform scaling curve for different thresholds q. So we can deduce the probability distribution of extreme events from normal events. The tail of a scaling curve can be well fitted by a Weibull form, which is significance-tested by KS measures. Both short-term and long-term memories are present in the recurrence intervals with different thresholds q, which denotes that the recurrence intervals can be predicted. In addition, similar to volatility, volatility recurrence intervals also have clustering features. Through Monte Carlo simulation, we artificially synthesise ARMA, GARCH-class sequences similar to the original data, and find out the reason behind the clustering. The larger the parameter d of the FIGARCH model, the stronger the clustering effect is. Finally, we use the Fractionally Integrated Autoregressive Conditional Duration model (FIACD) to analyse the recurrence interval characteristics. The results indicated that the FIACD model may provide a method to analyse volatility recurrence intervals.

Modeling and Simulation of the Economics of Mining in the Bitcoin Market.

PubMed

Cocco, Luisanna; Marchesi, Michele

2016-01-01

In January 3, 2009, Satoshi Nakamoto gave rise to the "Bitcoin Blockchain", creating the first block of the chain hashing on his computer's central processing unit (CPU). Since then, the hash calculations to mine Bitcoin have been getting more and more complex, and consequently the mining hardware evolved to adapt to this increasing difficulty. Three generations of mining hardware have followed the CPU's generation. They are GPU's, FPGA's and ASIC's generations. This work presents an agent-based artificial market model of the Bitcoin mining process and of the Bitcoin transactions. The goal of this work is to model the economy of the mining process, starting from GPU's generation, the first with economic significance. The model reproduces some "stylized facts" found in real-time price series and some core aspects of the mining business. In particular, the computational experiments performed can reproduce the unit root property, the fat tail phenomenon and the volatility clustering of Bitcoin price series. In addition, under proper assumptions, they can reproduce the generation of Bitcoins, the hashing capability, the power consumption, and the mining hardware and electrical energy expenditures of the Bitcoin network.

Measuring Training ROI: Silver Bullet or Urban Legend

DTIC Science & Technology

2008-06-01

unlimited 13. SUPPLEMENTARY NOTES See also ADM202527. Military Operations Research Society Symposium (76th) Held in New London, Connecticut on June... new markets and innovation) than the bottom line (the accounting fiction of profits).” Jay Cross, CEO of Internet Time Group, “A Fresh Look at ROI...AFAMS. Return on Investment oF Modeling and Simulation (M&S) Workshop Briefing, April 2008 ALTERNATIVES? MATERIAL NEW SYSTEMS SOFTWARE COURSWARE

Profit-based conventional resource scheduling with renewable energy penetration

NASA Astrophysics Data System (ADS)

Reddy, K. Srikanth; Panwar, Lokesh Kumar; Kumar, Rajesh; Panigrahi, B. K.

2017-08-01

Technological breakthroughs in renewable energy technologies (RETs) enabled them to attain grid parity thereby making them potential contenders for existing conventional resources. To examine the market participation of RETs, this paper formulates a scheduling problem accommodating energy market participation of wind- and solar-independent power producers (IPPs) treating both conventional and RETs as identical entities. Furthermore, constraints pertaining to penetration and curtailments of RETs are restructured. Additionally, an appropriate objective function for profit incurred by conventional resource IPPs through reserve market participation as a function of renewable energy curtailment is also proposed. The proposed concept is simulated with a test system comprising 10 conventional generation units in conjunction with solar photovoltaic (SPV) and wind energy generators (WEG). The simulation results indicate that renewable energy integration and its curtailment limits influence the market participation or scheduling strategies of conventional resources in both energy and reserve markets. Furthermore, load and reliability parameters are also affected.

A User’s Manual for the ARL Mathematical Model of the Sea King Mk-50 Helicopter: Part 1. Basic Use

DTIC Science & Technology

1988-10-01

responsibility of the Director Publishing and Marketing, AGPS. Inquiries should be directed to the Manager, AGPS Press, Australian Government...a Royal Australian Navy (RAN) task requirement. This model, which was developed originally on a DEC System 10 computer using the simulation language...f /nSAIG/CablePlot/SONRJWX /piloyt.o /b1ladn.f /CablePlot/SCNIMo /ptivre. f /bladin.o /ch~mpr. f /Ptine.o /Wv/ch~or.o /READThPE / BMe ’.L1B.0 /cm-pa.f

Time- and temperature-dependent migration studies of Irganox 1076 from plastics into foods and food simulants.

PubMed

Beldì, G; Pastorelli, S; Franchini, F; Simoneau, C

2012-01-01

The study provides an exhaustive set of migration data for octadecyl 3-(3,5-di-tert-butyl-4-hydroxyphenyl)propionate (Irganox 1076) from low-density polyethylene (LDPE) in several food matrices. Irganox 1076 was used as a model migrant because it represents one of the typical substances used as an antioxidant in food packaging polymers. Kinetic (time-dependent) migration studies of Irganox 1076 were performed for selected foodstuffs chosen with different physical-chemical properties and in relation to the actual European food consumption market. The effect of fat content and of the temperature of storage on the migration from plastic packaging was evaluated. The results show that migration increased with fat content and storage temperature. All data obtained from real foods were also compared with data obtained from simulants tested in the same conditions. In all studied cases, the kinetics in simulants were higher than those in foodstuffs. The work provides data valuable for the extension of the validation of migration model developed on simulants to foodstuffs themselves.

New Methodology for Evaluating Optimal Pricing for Primary Regulation of Deregulated Power Systems under Steady State Condition

NASA Astrophysics Data System (ADS)

Satyaramesh, P. V.; RadhaKrishna, C.

2013-06-01

A generalized pricing structure for procurement of power under frequency ancillary service is developed in this paper. It is a frequency linked-price model and suitable for deregulation market environment. This model takes into consideration: governor characteristics and frequency characteristics of generator as additional parameters in load flow method. The main objective of the new approach proposed in this paper is to establish bidding price structure for frequency regulation services in competitive ancillary electrical markets under steady state condition. Lot of literatures are available for calculating the frequency deviations with respect to load changes by using dynamic simulation methods. But in this paper, the model computes the frequency deviations for additional requirements of power under steady state with considering power system network topology. An attempt is also made in this paper to develop optimal bidding price structure for the frequency-regulated systems. It gives a signal to traders or bidders that the power demand can be assessed more accurately much closer to real time and helps participants bid more accurate quantities on day-ahead market. The recent trends of frequency linked-price model existing in Indian power systems issues required for attention are also dealt in this paper. Test calculations have been performed on 30-bus system. The paper also explains adoptability of 33 this model to practical Indian power system. The results presented are analyzed and useful conclusions are drawn.

Learning in innovation networks: Some simulation experiments

NASA Astrophysics Data System (ADS)

Gilbert, Nigel; Ahrweiler, Petra; Pyka, Andreas

2007-05-01

According to the organizational learning literature, the greatest competitive advantage a firm has is its ability to learn. In this paper, a framework for modeling learning competence in firms is presented to improve the understanding of managing innovation. Firms with different knowledge stocks attempt to improve their economic performance by engaging in radical or incremental innovation activities and through partnerships and networking with other firms. In trying to vary and/or to stabilize their knowledge stocks by organizational learning, they attempt to adapt to environmental requirements while the market strongly selects on the results. The simulation experiments show the impact of different learning activities, underlining the importance of innovation and learning.

Valuation of exotic options in the framework of Levy processes

NASA Astrophysics Data System (ADS)

Milev, Mariyan; Georgieva, Svetla; Markovska, Veneta

2013-12-01

In this paper we explore a straightforward procedure to price derivatives by using the Monte Carlo approach when the underlying process is a jump-diffusion. We have compared the Black-Scholes model with one of its extensions that is the Merton model. The latter model is better in capturing the market's phenomena and is comparative to stochastic volatility models in terms of pricing accuracy. We have presented simulations of asset paths and pricing of barrier options for both Geometric Brownian motion and exponential Levy processes as it is the concrete case of the Merton model. A desired level of accuracy is obtained with simple computer operations in MATLAB for efficient computational time.

FDTD-based optical simulations methodology for CMOS image sensors pixels architecture and process optimization

NASA Astrophysics Data System (ADS)

Hirigoyen, Flavien; Crocherie, Axel; Vaillant, Jérôme M.; Cazaux, Yvon

2008-02-01

This paper presents a new FDTD-based optical simulation model dedicated to describe the optical performances of CMOS image sensors taking into account diffraction effects. Following market trend and industrialization constraints, CMOS image sensors must be easily embedded into even smaller packages, which are now equipped with auto-focus and short-term coming zoom system. Due to miniaturization, the ray-tracing models used to evaluate pixels optical performances are not accurate anymore to describe the light propagation inside the sensor, because of diffraction effects. Thus we adopt a more fundamental description to take into account these diffraction effects: we chose to use Maxwell-Boltzmann based modeling to compute the propagation of light, and to use a software with an FDTD-based (Finite Difference Time Domain) engine to solve this propagation. We present in this article the complete methodology of this modeling: on one hand incoherent plane waves are propagated to approximate a product-use diffuse-like source, on the other hand we use periodic conditions to limit the size of the simulated model and both memory and computation time. After having presented the correlation of the model with measurements we will illustrate its use in the case of the optimization of a 1.75μm pixel.

Robust Approach to Verifying the Weak Form of the Efficient Market Hypothesis

NASA Astrophysics Data System (ADS)

Střelec, Luboš

2011-09-01

The weak form of the efficient markets hypothesis states that prices incorporate only past information about the asset. An implication of this form of the efficient markets hypothesis is that one cannot detect mispriced assets and consistently outperform the market through technical analysis of past prices. One of possible formulations of the efficient market hypothesis used for weak form tests is that share prices follow a random walk. It means that returns are realizations of IID sequence of random variables. Consequently, for verifying the weak form of the efficient market hypothesis, we can use distribution tests, among others, i.e. some tests of normality and/or some graphical methods. Many procedures for testing the normality of univariate samples have been proposed in the literature [7]. Today the most popular omnibus test of normality for a general use is the Shapiro-Wilk test. The Jarque-Bera test is the most widely adopted omnibus test of normality in econometrics and related fields. In particular, the Jarque-Bera test (i.e. test based on the classical measures of skewness and kurtosis) is frequently used when one is more concerned about heavy-tailed alternatives. As these measures are based on moments of the data, this test has a zero breakdown value [2]. In other words, a single outlier can make the test worthless. The reason so many classical procedures are nonrobust to outliers is that the parameters of the model are expressed in terms of moments, and their classical estimators are expressed in terms of sample moments, which are very sensitive to outliers. Another approach to robustness is to concentrate on the parameters of interest suggested by the problem under this study. Consequently, novel robust testing procedures of testing normality are presented in this paper to overcome shortcomings of classical normality tests in the field of financial data, which are typical with occurrence of remote data points and additional types of deviations from normality. This study also discusses some results of simulation power studies of these tests for normality against selected alternatives. Based on outcome of the power simulation study, selected normality tests were consequently used to verify weak form of efficiency in Central Europe stock markets.

The Future of Hydropower: Assessing the Impacts of Climate Change, Energy Prices and New Storage Technologies

NASA Astrophysics Data System (ADS)

Gaudard, Ludovic; Madani, Kaveh; Romerio, Franco

2016-04-01

The future of hydropower depends on various drivers, and in particular on climate change, electricity market evolution and innovation in new storage technologies. Their impacts on the power plants' profitability can widely differ in regards of scale, timing, and probability of occurrence. In this respect, the risk should not be expressed only in terms of expected revenue, but also of uncertainty. These two aspects must be considered to assess the future of hydropower. This presentation discusses the impacts of climate change, electricity market volatility and competing energy storage's technologies and quantifies them in terms of annual revenue. Our simulations integrate a glacio-hydrological model (GERM) with various electricity market data and models (mean reversion and jump diffusion). The medium (2020-50) and long-term (2070-2100) are considered thanks to various greenhouse gas scenarios (A1B, A2 and RCP3PD) and the stochastic approach for the electricity prices. An algorithm named "threshold acceptance" is used to optimize the reservoir operations. The impacts' scale, and the related uncertainties are presented for Mauvoisin, which is a storage-hydropower plant situated in the Swiss Alps, and two generic pure pumped-storage installations, which are assessed with the prices of 17 European electricity markets. The discussion will highlight the key differences between the impacts brought about by the drivers.

Market assessment overview

NASA Technical Reports Server (NTRS)

Habib-Agahi, H.

1981-01-01

Market assessment, refined with analysis disaggregated from a national level to the regional level and to specific market applications, resulted in more accurate and detailed market estimates. The development of an integrated set of computer simulations, coupled with refined market data, allowed progress in the ability to evaluate the worth of solar thermal parabolic dish systems. In-depth analyses of both electric and thermal market applications of these systems are described. The following market assessment studies were undertaken: (1) regional analysis of the near term market for parabolic dish systems; (2) potential early market estimate for electric applications; (3) potential early market estimate for industrial process heat/cogeneration applications; and (4) selection of thermal and electric application case studies for fiscal year 1981.

Using genetic algorithm to solve a new multi-period stochastic optimization model

NASA Astrophysics Data System (ADS)

Zhang, Xin-Li; Zhang, Ke-Cun

2009-09-01

This paper presents a new asset allocation model based on the CVaR risk measure and transaction costs. Institutional investors manage their strategic asset mix over time to achieve favorable returns subject to various uncertainties, policy and legal constraints, and other requirements. One may use a multi-period portfolio optimization model in order to determine an optimal asset mix. Recently, an alternative stochastic programming model with simulated paths was proposed by Hibiki [N. Hibiki, A hybrid simulation/tree multi-period stochastic programming model for optimal asset allocation, in: H. Takahashi, (Ed.) The Japanese Association of Financial Econometrics and Engineering, JAFFE Journal (2001) 89-119 (in Japanese); N. Hibiki A hybrid simulation/tree stochastic optimization model for dynamic asset allocation, in: B. Scherer (Ed.), Asset and Liability Management Tools: A Handbook for Best Practice, Risk Books, 2003, pp. 269-294], which was called a hybrid model. However, the transaction costs weren't considered in that paper. In this paper, we improve Hibiki's model in the following aspects: (1) The risk measure CVaR is introduced to control the wealth loss risk while maximizing the expected utility; (2) Typical market imperfections such as short sale constraints, proportional transaction costs are considered simultaneously. (3) Applying a genetic algorithm to solve the resulting model is discussed in detail. Numerical results show the suitability and feasibility of our methodology.

Estimating the production, consumption and export of cannabis: The Dutch case.

PubMed

van der Giessen, Mark; van Ooyen-Houben, Marianne M J; Moolenaar, Debora E G

2016-05-01

Quantifying an illegal phenomenon like a drug market is inherently complex due to its hidden nature and the limited availability of reliable information. This article presents findings from a recent estimate of the production, consumption and export of Dutch cannabis and discusses the opportunities provided by, and limitations of, mathematical models for estimating the illegal cannabis market. The data collection consisted of a comprehensive literature study, secondary analyses on data from available registrations (2012-2014) and previous studies, and expert opinion. The cannabis market was quantified with several mathematical models. The data analysis included a Monte Carlo simulation to come to a 95% interval estimate (IE) and a sensitivity analysis to identify the most influential indicators. The annual production of Dutch cannabis was estimated to be between 171 and 965tons (95% IE of 271-613tons). The consumption was estimated to be between 28 and 119tons, depending on the inclusion or exclusion of non-residents (95% IE of 51-78tons or 32-49tons respectively). The export was estimated to be between 53 and 937tons (95% IE of 206-549tons or 231-573tons, respectively). Mathematical models are valuable tools for the systematic assessment of the size of illegal markets and determining the uncertainty inherent in the estimates. The estimates required the use of many assumptions and the availability of reliable indicators was limited. This uncertainty is reflected in the wide ranges of the estimates. The estimates are sensitive to 10 of the 45 indicators. These 10 account for 86-93% of the variation found. Further research should focus on improving the variables and the independence of the mathematical models. Copyright © 2016 Elsevier B.V. All rights reserved.

Coevolution of Epidemics, Social Networks, and Individual Behavior: A Case Study

NASA Astrophysics Data System (ADS)

Chen, Jiangzhuo; Marathe, Achla; Marathe, Madhav

This research shows how a limited supply of antivirals can be distributed optimally between the hospitals and the market so that the attack rate is minimized and enough revenue is generated to recover the cost of the antivirals. Results using an individual based model find that prevalence elastic demand behavior delays the epidemic and change in the social contact network induced by isolation reduces the peak of the epidemic significantly. A microeconomic analysis methodology combining behavioral economics and agent-based simulation is a major contribution of this work. In this paper we apply this methodology to analyze the fairness of the stockpile distribution, and the response of human behavior to disease prevalence level and its interaction with the market.

Sensitivity Analysis for an Assignment Incentive Pay in the U.S. Navy Enlisted Personnel Assignment Process in a Simulation Environment

DTIC Science & Technology

2004-03-01

Assignment Sub-Process.........................................................................................12 2. Possible Improvements By A Market ...COMPENSATION STARTEGY .............................................17 A. THE RIGHT COMPENSATION SYSTEM ...............................................17 B. AN...5. Market -Based Labor Markets (From: Gates, 2001).........................................13 Figure 6. What should a compensation system do? (From

An analysis of the diffusion of new antidepressants: variety, quality, and marketing efforts.

PubMed

Berndt, Ernst R; Bhattacharjya, Ashoke; Mishol, David N; Arcelus, Almudena; Lasky, Thomas

2002-03-01

We are not aware of any published research that quantifies and compares the importance of effectiveness and side effects for pharmaceutical sales, and that simultaneously incorporates the impacts of marketing efforts on the diffusion of new pharmaceutical agents in the U.S. The overall level and market share success of the various selective serotonin reuptake inhibitors ( SSRIs ) relative to a representative older generation tricyclic (such as amitriptyline) provides a useful focus for studying such issues. To model jointly the marketing and sales relationships of the SSRIs in the U.S., to quantify the extent to which marketing efforts are responsive to the availability of new scientific information accompanying changes in quality and increases in product variety, and in turn to assess how the new FDA indication approvals and the enhanced marketing initiatives involving product quality and variety affect sales of the SSRI and other novel antidepressants. Quarterly US sales, price, quantity and marketing data 1988Q1-1997Q4 are taken from IMS Health for the eight new antidepressants introduced into the US during this time period. Measures of physician-perceived quality attributes of the antidepressants are drawn from Market Measures, Inc., a medical survey research firm. These data are used to construct measures of product quality (effectiveness and side effect profile), and attribute variety across all antidepressants. Multivariate regression methods are used in estimating parameters of a marketing efforts model, a sales demand model encompassing the aggregate of the newer antidepressants, and a product share model. Simulation methods are employed to quantify elasticities. Since 1988, and relative to amitriptyline, there has been only a rather modest increase in the perceived average effectiveness of the SSRIs and related products, but the side effect profiles have improved substantially. Variety measures for effectiveness show greater increases over time than do those for side effects. Marketing efforts respond to science-based events, such as new FDA indication approvals, and to effectiveness and side-effect quality improvements. Total antidepressant sales are positively and significantly related to price reductions, increased marketing efforts, and the level and variety of side effect profiles involving antidepressants. The level and variety of effectiveness does not significantly affect total antidepressant sales. Order of entry effects are important in affecting product market shares, while marketing efforts and relative quality attributes (particularly a more favorable side effect profile) have positive and significant impacts on relative market shares. Since patient response to SSRIs and related products is idiosyncratic, greater product variety facilitates better matching of antidepressant with patient. Much of the growth of the SSRIs and related antidepressants since 1988 can be attributed to increased product attribute variety, to improved changes in side effect quality relative to that of the tricyclics, and to the marketing of those improvements. Marketing efforts play an important role in diffusing product information. Marketing efforts increase considerably following FDA approval for indications other than depression, and also increase with the average effectiveness and the average side effect rating of the products. Whether the relatively minor role that perceived effectiveness has in affecting sales relative to perceived side effect profile is unique to antidepressants, or generalizes to other therapeutic classes, merits further examination.

High-fidelity simulation of transcutaneous cardiac pacing: characteristics and limitations of available high-fidelity simulators, and description of an alternative two-mannequin model.

PubMed

Robitaille, Arnaud; Perron, Roger; Germain, Jean-François; Tanoubi, Issam; Georgescu, Mihai

2015-04-01

Transcutaneous cardiac pacing (TCP) is a potentially lifesaving technique that is part of the recommended treatment for symptomatic bradycardia. Transcutaneous cardiac pacing however is used uncommonly, and its successful application is not straightforward. Simulation could, therefore, play an important role in the teaching and assessment of TCP competence. However, even the highest-fidelity mannequins available on the market have important shortcomings, which limit the potential of simulation. Six criteria defining clinical competency in TCP were established and used as a starting point in the creation of an improved TCP simulator. The goal was a model that could be used to assess experienced clinicians, an objective that justifies the additional effort required by the increased fidelity. The proposed 2-mannequin model (TMM) combines a highly modified Human Patient Simulator with a SimMan 3G, the latter being used solely to provide the electrocardiography (ECG) tracing. The TMM improves the potential of simulation to assess experienced clinicians (1) by reproducing key features of TCP, like using the same multifunctional pacing electrodes used clinically, allowing dual ECG monitoring, and responding with upper body twitching when stimulated, but equally importantly (2) by reproducing key pitfalls of the technique, like allowing pacing electrode misplacement and reproducing false signs of ventricular capture, commonly, but erroneously, used clinically to establish that effective pacing has been achieved (like body twitching, electrical artifact on the ECG, and electrical capture without ventricular capture). The proposed TMM uses a novel combination of 2 high-fidelity mannequins to improve TCP simulation until upgraded mannequins become commercially available.

A chaotic model for advertising diffusion problem with competition

NASA Astrophysics Data System (ADS)

Ip, W. H.; Yung, K. L.; Wang, Dingwei

2012-08-01

In this article, the author extends Dawid and Feichtinger's chaotic advertising diffusion model into the duopoly case. A computer simulation system is used to test this enhanced model. Based on the analysis of simulation results, it is found that the best advertising strategy in duopoly is to increase the advertising investment to reach the best Win-Win situation where the oscillation of market portion will not occur. In order to effectively arrive at the best situation, we define a synthetic index and two thresholds. An estimation method for the parameters of the index and thresholds is proposed in this research. We can reach the Win-Win situation by simply selecting the control parameters to make the synthetic index close to the threshold of min-oscillation state. The numerical example and computational results indicated that the proposed chaotic model is useful to describe and analyse advertising diffusion process in duopoly, it is an efficient tool for the selection and optimisation of advertising strategy.

Volatility Behaviors of Financial Time Series by Percolation System on Sierpinski Carpet Lattice

NASA Astrophysics Data System (ADS)

Pei, Anqi; Wang, Jun

2015-01-01

The financial time series is simulated and investigated by the percolation system on the Sierpinski carpet lattice, where percolation is usually employed to describe the behavior of connected clusters in a random graph, and the Sierpinski carpet lattice is a graph which corresponds the fractal — Sierpinski carpet. To study the fluctuation behavior of returns for the financial model and the Shanghai Composite Index, we establish a daily volatility measure — multifractal volatility (MFV) measure to obtain MFV series, which have long-range cross-correlations with squared daily return series. The autoregressive fractionally integrated moving average (ARFIMA) model is used to analyze the MFV series, which performs better when compared to other volatility series. By a comparative study of the multifractality and volatility analysis of the data, the simulation data of the proposed model exhibits very similar behaviors to those of the real stock index, which indicates somewhat rationality of the model to the market application.

Proposal of Classification Method of Time Series Data in International Emissions Trading Market Using Agent-based Simulation

NASA Astrophysics Data System (ADS)

Nakada, Tomohiro; Takadama, Keiki; Watanabe, Shigeyoshi

This paper proposes the classification method using Bayesian analytical method to classify the time series data in the international emissions trading market depend on the agent-based simulation and compares the case with Discrete Fourier transform analytical method. The purpose demonstrates the analytical methods mapping time series data such as market price. These analytical methods have revealed the following results: (1) the classification methods indicate the distance of mapping from the time series data, it is easier the understanding and inference than time series data; (2) these methods can analyze the uncertain time series data using the distance via agent-based simulation including stationary process and non-stationary process; and (3) Bayesian analytical method can show the 1% difference description of the emission reduction targets of agent.

Ontological simulation for educational process organisation in a higher educational institution

NASA Astrophysics Data System (ADS)

Berestneva, O. G.; Marukhina, O. V.; Bahvalov, S. V.; Fisochenko, O. N.; Berestneva, E. V.

2017-01-01

Following the new-generation standards is needed to form a task list connected with planning and organizing of an academic process, structure and content formation of degree programmes. Even when planning the structure and content of an academic process, one meets some problems concerning the necessity to assess the correlation between degree programmes and demands of educational and professional standards and to consider today’s job-market and students demands. The paper presents examples of ontological simulations for solutions of organizing educational process problems in a higher educational institution and gives descriptions of model development. The article presents two examples: ontological simulation when planning an educational process in a higher educational institution and ontological simulation for describing competences of an IT-specialist. The paper sets a conclusion about ontology application perceptiveness for formalization of educational process organization in a higher educational institution.

Measuring market performance in restructured electricity markets: An empirical analysis of the PJM energy market

NASA Astrophysics Data System (ADS)

Tucker, Russell Jay

2002-09-01

Today the electric industry in the U.S. is transitioning to competitive markets for wholesale electricity. Independent system operators (ISOs) now manage broad regional markets for electrical energy in several areas of the U.S. A recent rulemaking by the Federal Energy Regulatory Commission (FERC) encourages the development of regional transmission organizations (RTOs) and restructured competitive wholesale electricity markets nationwide. To date, the transition to competitive wholesale markets has not been easy. The increased reliance on market forces coupled with unusually high electricity demand for some periods have created conditions amenable to market power abuse in many regions throughout the U.S. In the summer of 1999, hot and humid summer conditions in Pennsylvania, New Jersey, Maryland, Delaware, and the District of Columbia pushed peak demand in the PJM Interconnection to record levels. These demand conditions coincided with the introduction of market-based pricing in the wholesale electricity market. Prices for electricity increased on average by 55 percent, and reached the $1,000/MWh range. This study examines the extent to which generator market power raised prices above competitive levels in the PJM Interconnection during the summer of 1999. It simulates hourly market-clearing prices assuming competitive market behavior and compares these prices with observed market prices in computing price markups over the April 1-August 31, 1999 period. The results of the simulation analysis are supported with an examination of actual generator bid data of incumbent generators. Price markups averaged 14.7 percent above expected marginal cost over the 5-month period for all non-transmission-constrained hours. The evidence presented suggests that the June and July monthly markups were strongly influenced by generator market power as price inelastic peak demand approached the electricity generation capacity constraint of the market. While this analysis of the performance of the PJM market finds evidence of market power, the measured markups are markedly less than estimates from prior analysis of the PJM market.

Analysis of the French insurance market exposure to floods: a stochastic model combining river overflow and surface runoff

NASA Astrophysics Data System (ADS)

Moncoulon, D.; Labat, D.; Ardon, J.; Leblois, E.; Onfroy, T.; Poulard, C.; Aji, S.; Rémy, A.; Quantin, A.

2014-09-01

The analysis of flood exposure at a national scale for the French insurance market must combine the generation of a probabilistic event set of all possible (but which have not yet occurred) flood situations with hazard and damage modeling. In this study, hazard and damage models are calibrated on a 1995-2010 historical event set, both for hazard results (river flow, flooded areas) and loss estimations. Thus, uncertainties in the deterministic estimation of a single event loss are known before simulating a probabilistic event set. To take into account at least 90 % of the insured flood losses, the probabilistic event set must combine the river overflow (small and large catchments) with the surface runoff, due to heavy rainfall, on the slopes of the watershed. Indeed, internal studies of the CCR (Caisse Centrale de Reassurance) claim database have shown that approximately 45 % of the insured flood losses are located inside the floodplains and 45 % outside. Another 10 % is due to sea surge floods and groundwater rise. In this approach, two independent probabilistic methods are combined to create a single flood loss distribution: a generation of fictive river flows based on the historical records of the river gauge network and a generation of fictive rain fields on small catchments, calibrated on the 1958-2010 Météo-France rain database SAFRAN. All the events in the probabilistic event sets are simulated with the deterministic model. This hazard and damage distribution is used to simulate the flood losses at the national scale for an insurance company (Macif) and to generate flood areas associated with hazard return periods. The flood maps concern river overflow and surface water runoff. Validation of these maps is conducted by comparison with the address located claim data on a small catchment (downstream Argens).

Pre-layout AC decoupling analysis with Mentor Graphics HyperLynx

NASA Astrophysics Data System (ADS)

Hnatiuc, Mihaela; Iov, Cǎtǎlin J.

2015-02-01

Considerable resources have been used since the humans got interested to discover the world around. Any discovery and science advance was taken tremendously amount of time, money, sometimes lives. All of these define the cost of a discovery, developing process. Getting back to electronics, this field faced in the last 20-30 years, a big boom in terms of technologies and opportunities. Thousands of equipment were developed and placed on the market. The big difference between various competitors is made at the moment by that we call the time to market. A mobile, for instance, has a time to market of around 6 months and the tendency is to have it smaller than that. That means between the concept and the first model sale, no more than 6 months should be passing. That is why new approaches are needed. The one extensively used now is the simulation. We call the simulation virtual prototyping. The virtual prototyping takes into account more than the components only. It takes into account some other project parameters that would affect the final product. Certified tools can handle such analysis. In our paper we present the case of HyperLynx, a concept developed by Mentor Graphics Company, assisting the hardware designer throughout the designing process, from thermal point of view. A test case board was analyzed at the pre-layout stage and the results presented.

Appraisal of artificial neural network for forecasting of economic parameters

NASA Astrophysics Data System (ADS)

Kordanuli, Bojana; Barjaktarović, Lidija; Jeremić, Ljiljana; Alizamir, Meysam

2017-01-01

The main aim of this research is to develop and apply artificial neural network (ANN) with extreme learning machine (ELM) and back propagation (BP) to forecast gross domestic product (GDP) and Hirschman-Herfindahl Index (HHI). GDP could be developed based on combination of different factors. In this investigation GDP forecasting based on the agriculture and industry added value in gross domestic product (GDP) was analysed separately. Other inputs are final consumption expenditure of general government, gross fixed capital formation (investments) and fertility rate. The relation between product market competition and corporate investment is contentious. On one hand, the relation can be positive, but on the other hand, the relation can be negative. Several methods have been proposed to monitor market power for the purpose of developing procedures to mitigate or eliminate the effects. The most widely used methods are based on indices such as the Hirschman-Herfindahl Index (HHI). The reliability of the ANN models were accessed based on simulation results and using several statistical indicators. Based upon simulation results, it was presented that ELM shows better performances than BP learning algorithm in applications of GDP and HHI forecasting.

Tick size and stock returns

NASA Astrophysics Data System (ADS)

Onnela, Jukka-Pekka; Töyli, Juuso; Kaski, Kimmo

2009-02-01

Tick size is an important aspect of the micro-structural level organization of financial markets. It is the smallest institutionally allowed price increment, has a direct bearing on the bid-ask spread, influences the strategy of trading order placement in electronic markets, affects the price formation mechanism, and appears to be related to the long-term memory of volatility clustering. In this paper we investigate the impact of tick size on stock returns. We start with a simple simulation to demonstrate how continuous returns become distorted after confining the price to a discrete grid governed by the tick size. We then move on to a novel experimental set-up that combines decimalization pilot programs and cross-listed stocks in New York and Toronto. This allows us to observe a set of stocks traded simultaneously under two different ticks while holding all security-specific characteristics fixed. We then study the normality of the return distributions and carry out fits to the chosen distribution models. Our empirical findings are somewhat mixed and in some cases appear to challenge the simulation results.

Social percolation models

NASA Astrophysics Data System (ADS)

Solomon, Sorin; Weisbuch, Gerard; de Arcangelis, Lucilla; Jan, Naeem; Stauffer, Dietrich

2000-03-01

We here relate the occurrence of extreme market shares, close to either 0 or 100%, in the media industry to a percolation phenomenon across the social network of customers. We further discuss the possibility of observing self-organized criticality when customers and cinema producers adjust their preferences and the quality of the produced films according to previous experience. Comprehensive computer simulations on square lattices do indeed exhibit self-organized criticality towards the usual percolation threshold and related scaling behaviour.

Monte Carlo Simulation of Effective Coordination Mechanisms for e-Commerce

NASA Astrophysics Data System (ADS)

Sakas, D. P.; Vlachos, D. S.; Simos, T. E.

2008-11-01

Making decisions in a dynamic environment is considered extremely important in today's market. Decision trees which can be used to model these systems, are not easily constructed and solved, especially in the case of infinite sets of consequences (for example, consider the case where only the mean and the variance of an outcome is known). In this work, discrete approximation and Monte Carlo techniques are used to overcome the aforementioned difficulties.

Demand Response Availability Profiles for California in the Year 2020

DOE Office of Scientific and Technical Information (OSTI.GOV)

Olsen, Daniel; Sohn, Michael; Piette, Mary Ann

2014-11-01

Demand response (DR) is being considered as a valuable resource for keeping the electrical grid stable and efficient, and deferring upgrades to generation, transmission, and distribution systems. However, simulations to determine how much infrastructure upgrades can be deferred are necessary in order to plan optimally. Production cost modeling is a technique, which simulates the dispatch of generators to meet demand and reserves in each hour of the year, at minimal cost. By integrating demand response resources into a production cost model (PCM), their value to the grid can be estimated and used to inform operations and infrastructure planning. DR availabilitymore » profiles and constraints for 13 end-uses in California for the year 2020 were developed by Lawrence Berkeley National Laboratory (LBNL), and integrated into a production cost model by Lawrence Livermore National Laboratory (LLNL), for the California Energy Commission’s Value of Energy Storage and Demand Response for Renewable Integration in California Study. This report summarizes the process for developing the DR availability profiles for California, and their aggregate capabilities. While LBNL provided potential DR hourly profiles for regulation product in the ancillary services market and five-minute load following product in the energy market for LLNL’s study, additional results in contingency reserves and an assumed flexible product are also defined. These additional products are included in the analysis for managing high ramps associated with renewable generation and capacity products and they are also presented in this report.« less

Strategic marketing applications of conjoint analysis: an HMO perspective.

PubMed

Rosko, M D; DeVita, M; McKenna, W F; Walker, L R

1985-01-01

The purpose of this article is to demonstrate how data from a conjoint analysis study can be used to help determine the most appropriate marketing mix for an operational HMO which is entering a new market--the geriatric population. Included are two features which are absent in previous articles on health care applications of conjoint analysis: external validation of results, and a demonstration of how conjoint analysis can be used to simulate market responses to changes in the provider's marketing mix.

Common Pool Water Markets and their Role in Facilitating Land Use Change in Drying Climates

NASA Astrophysics Data System (ADS)

Teasley, R. L.; Milke, M.; Raffensperger, J. F.; Zargar, M.

2010-12-01

Concern is growing worldwide that climate change will lead to drier climates in many regions and in turn diminish water resources. To protect these limited resources, users may need to shift water use to more economically productive areas. However, changing the land use associated with water permits can be quite difficult, because water is not easily traded. Water markets have been well researched as a method for trading water between users, but these markets can often be difficult and costly requiring one-to-one trades between buyers and sellers. In contrast to a one-to-one market, a common pool market can reduce the transaction costs associated with trading water. In this research, a common pool market is applied to an example groundwater system set up in GWM2000 with ten users and various environmental constraints. The users represent three types of the largest groundwater users in the Canterbury region of New Zealand: agricultural, dairy and livestock. The response matrix from GWM2000 is used to develop constraints in the market model along with user bids. Bids are calculated from economic and water use data for Canterbury, New Zealand. Varying spatial distributions of water users by type are evaluated for the effect on the market under drying conditions. These conditions are simulated from climate change scenarios produced by the National Institute of Water and Atmospheric Research in New Zealand. The results demonstrate potential land use changes falls under drying conditions. As water availability falls, the price for additional water increases, particularly near environmental constraints, driving the land and water towards more efficient uses.

Target-mediated drug disposition model and its approximations for antibody-drug conjugates.

PubMed

Gibiansky, Leonid; Gibiansky, Ekaterina

2014-02-01

Antibody-drug conjugate (ADC) is a complex structure composed of an antibody linked to several molecules of a biologically active cytotoxic drug. The number of ADC compounds in clinical development now exceeds 30, with two of them already on the market. However, there is no rigorous mechanistic model that describes pharmacokinetic (PK) properties of these compounds. PK modeling of ADCs is even more complicated than that of other biologics as the model should describe distribution, binding, and elimination of antibodies with different toxin load, and also the deconjugation process and PK of the released toxin. This work extends the target-mediated drug disposition (TMDD) model to describe ADCs, derives the rapid binding (quasi-equilibrium), quasi-steady-state, and Michaelis-Menten approximations of the TMDD model as applied to ADCs, derives the TMDD model and its approximations for ADCs with load-independent properties, and discusses further simplifications of the system under various assumptions. The developed models are shown to describe data simulated from the available clinical population PK models of trastuzumab emtansine (T-DM1), one of the two currently approved ADCs. Identifiability of model parameters is also discussed and illustrated on the simulated T-DM1 examples.

Standardisation of digital human models.

PubMed

Paul, Gunther; Wischniewski, Sascha

2012-01-01

Digital human models (DHM) have evolved as useful tools for ergonomic workplace design and product development, and found in various industries and education. DHM systems which dominate the market were developed for specific purposes and differ significantly, which is not only reflected in non-compatible results of DHM simulations, but also provoking misunderstanding of how DHM simulations relate to real world problems. While DHM developers are restricted by uncertainty about the user need and lack of model data related standards, users are confined to one specific product and cannot exchange results, or upgrade to another DHM system, as their previous results would be rendered worthless. Furthermore, origin and validity of anthropometric and biomechanical data is not transparent to the user. The lack of standardisation in DHM systems has become a major roadblock in further system development, affecting all stakeholders in the DHM industry. Evidently, a framework for standardising digital human models is necessary to overcome current obstructions. Practitioner Summary: This short communication addresses a standardisation issue for digital human models, which has been addressed at the International Ergonomics Association Technical Committee for Human Simulation and Virtual Environments. It is the outcome of a workshop at the DHM 2011 symposium in Lyon, which concluded steps towards DHM standardisation that need to be taken.

A numerical model to simulate foams during devolatilization of polymers

NASA Astrophysics Data System (ADS)

Khan, Irfan; Dixit, Ravindra

2014-11-01

Customers often demand that the polymers sold in the market have low levels of volatile organic compounds (VOC). Some of the processes for making polymers involve the removal of volatiles to the levels of parts per million (devolatilization). During this step the volatiles are phase separated out of the polymer through a combination of heating and applying lower pressure, creating foam with the pure polymer in liquid phase and the volatiles in the gas phase. The efficiency of the devolatilization process depends on predicting the onset of solvent phase change in the polymer and volatiles mixture accurately based on the processing conditions. However due to the complex relationship between the polymer properties and the processing conditions this is not trivial. In this work, a bubble scale model is coupled with a bulk scale transport model to simulate the processing conditions of polymer devolatilization. The bubble scale model simulates the nucleation and bubble growth based on the classical nucleation theory and the popular ``influence volume approach.'' As such it provides the information of bubble size distribution and number density inside the polymer at any given time and position. This information is used to predict the bulk properties of the polymer and its behavior under the applied processing conditions. Initial results of this modeling approach will be presented.

Engaging Marketing Students: Student Operated Businesses in a Simulated World

ERIC Educational Resources Information Center

Russell-Bennett, Rebekah; Rundle-Thiele, Sharyn R.; Kuhn, Kerri-Ann

2010-01-01

Engaged students are committed and more likely to continue their university studies. Subsequently, they are less resource intensive from a university's perspective. This article details an experiential second-year marketing course that requires students to develop real products and services to sell on two organized market days. In the course,…

Games for the Foreign Language Classroom.

ERIC Educational Resources Information Center

McMillan, Nancy; Madaras, Susan W.

Two marketing games are described, "Le Marche Francais" and "El Mercado: The Mexican Market Comes to Life in the Spanish Classroom." Both are patterned after a published game entitled "Market: A Simulation Game." The adaptation in each instance relied on simplifying the original game and presenting it in a form understandable to middle school…