Analysis of the Pricing Process in Electricity Market using Multi-Agent Model

NASA Astrophysics Data System (ADS)

Shimomura, Takahiro; Saisho, Yuichi; Fujii, Yasumasa; Yamaji, Kenji

Many electric utilities world-wide have been forced to change their ways of doing business, from vertically integrated mechanisms to open market systems. We are facing urgent issues about how we design the structures of power market systems. In order to settle down these issues, many studies have been made with market models of various characteristics and regulations. The goal of modeling analysis is to enrich our understanding of fundamental process that may appear. However, there are many kinds of modeling methods. Each has drawback and advantage about validity and versatility. This paper presents two kinds of methods to construct multi-agent market models. One is based on game theory and another is based on reinforcement learning. By comparing the results of the two methods, they can advance in validity and help us figure out potential problems in electricity markets which have oligopolistic generators, demand fluctuation and inelastic demand. Moreover, this model based on reinforcement learning enables us to consider characteristics peculiar to electricity markets which have plant unit characteristics, seasonable and hourly demand fluctuation, real-time regulation market and operating reserve market. This model figures out importance of the share of peak-load-plants and the way of designing operating reserve market.

Integrated Agent-Based and Production Cost Modeling Framework for Renewable Energy Studies: Preprint

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

Gallo, Giulia

The agent-based framework for renewable energy studies (ARES) is an integrated approach that adds an agent-based model of industry actors to PLEXOS and combines the strengths of the two to overcome their individual shortcomings. It can examine existing and novel wholesale electricity markets under high penetrations of renewables. ARES is demonstrated by studying how increasing levels of wind will impact the operations and the exercise of market power of generation companies that exploit an economic withholding strategy. The analysis is carried out on a test system that represents the Electric Reliability Council of Texas energy-only market in the year 2020.more » The results more realistically reproduce the operations of an energy market under different and increasing penetrations of wind, and ARES can be extended to address pressing issues in current and future wholesale electricity markets.« less

Integrated Agent-Based and Production Cost Modeling Framework for Renewable Energy Studies

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

Gallo, Giulia

The agent-based framework for renewable energy studies (ARES) is an integrated approach that adds an agent-based model of industry actors to PLEXOS and combines the strengths of the two to overcome their individual shortcomings. It can examine existing and novel wholesale electricity markets under high penetrations of renewables. ARES is demonstrated by studying how increasing levels of wind will impact the operations and the exercise of market power of generation companies that exploit an economic withholding strategy. The analysis is carried out on a test system that represents the Electric Reliability Council of Texas energy-only market in the year 2020.more » The results more realistically reproduce the operations of an energy market under different and increasing penetrations of wind, and ARES can be extended to address pressing issues in current and future wholesale electricity markets.« less

Adapting Price Predictions in TAC SCM

NASA Astrophysics Data System (ADS)

Pardoe, David; Stone, Peter

In agent-based markets, adapting to the behavior of other agents is often necessary for success. When it is not possible to directly model individual competitors, an agent may instead model and adapt to the market conditions that result from competitor behavior. Such an agent could still benefit from reasoning about specific competitor strategies by considering how various combinations of these strategies would impact the conditions being modeled. We present an application of such an approach to a specific prediction problem faced by the agent TacTex-06 in the Trading Agent Competition's Supply Chain Management scenario (TAC SCM).

Estimation of a simple agent-based model of financial markets: An application to Australian stock and foreign exchange data

NASA Astrophysics Data System (ADS)

Alfarano, Simone; Lux, Thomas; Wagner, Friedrich

2006-10-01

Following Alfarano et al. [Estimation of agent-based models: the case of an asymmetric herding model, Comput. Econ. 26 (2005) 19-49; Excess volatility and herding in an artificial financial market: analytical approach and estimation, in: W. Franz, H. Ramser, M. Stadler (Eds.), Funktionsfähigkeit und Stabilität von Finanzmärkten, Mohr Siebeck, Tübingen, 2005, pp. 241-254], we consider a simple agent-based model of a highly stylized financial market. The model takes Kirman's ant process [A. Kirman, Epidemics of opinion and speculative bubbles in financial markets, in: M.P. Taylor (Ed.), Money and Financial Markets, Blackwell, Cambridge, 1991, pp. 354-368; A. Kirman, Ants, rationality, and recruitment, Q. J. Econ. 108 (1993) 137-156] of mimetic contagion as its starting point, but allows for asymmetry in the attractiveness of both groups. Embedding the contagion process into a standard asset-pricing framework, and identifying the abstract groups of the herding model as chartists and fundamentalist traders, a market with periodic bubbles and bursts is obtained. Taking stock of the availability of a closed-form solution for the stationary distribution of returns for this model, we can estimate its parameters via maximum likelihood. Expanding our earlier work, this paper presents pertinent estimates for the Australian dollar/US dollar exchange rate and the Australian stock market index. As it turns out, our model indicates dominance of fundamentalist behavior in both the stock and foreign exchange market.

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.

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.

Agent-based Model for the Coupled Human-Climate System

NASA Astrophysics Data System (ADS)

Zvoleff, A.; Werner, B.

2006-12-01

Integrated assessment models have been used to predict the outcome of coupled economic growth, resource use, greenhouse gas emissions and climate change, both for scientific and policy purposes. These models generally have employed significant simplifications that suppress nonlinearities and the possibility of multiple equilibria in both their economic (DeCanio, 2005) and climate (Schneider and Kuntz-Duriseti, 2002) components. As one step toward exploring general features of the nonlinear dynamics of the coupled system, we have developed a series of variations on the well studied RICE and DICE models, which employ different forms of agent-based market dynamics and "climate surprises." Markets are introduced through the replacement of the production function of the DICE/RICE models with an agent-based market modeling the interactions of producers, policymakers, and consumer agents. Technological change and population growth are treated endogenously. Climate surprises are representations of positive (for example, ice sheet collapse) or negative (for example, increased aerosols from desertification) feedbacks that are turned on with probability depending on warming. Initial results point toward the possibility of large amplitude instabilities in the coupled human-climate system owing to the mismatch between short outlook market dynamics and long term climate responses. Implications for predictability of future climate will be discussed. Supported by the Andrew W Mellon Foundation and the UC Academic Senate.

A threshold model of investor psychology

NASA Astrophysics Data System (ADS)

Cross, Rod; Grinfeld, Michael; Lamba, Harbir; Seaman, Tim

2005-08-01

We introduce a class of agent-based market models founded upon simple descriptions of investor psychology. Agents are subject to various psychological tensions induced by market conditions and endowed with a minimal ‘personality’. This personality consists of a threshold level for each of the tensions being modeled, and the agent reacts whenever a tension threshold is reached. This paper considers an elementary model including just two such tensions. The first is ‘cowardice’, which is the stress caused by remaining in a minority position with respect to overall market sentiment and leads to herding-type behavior. The second is ‘inaction’, which is the increasing desire to act or re-evaluate one's investment position. There is no inductive learning by agents and they are only coupled via the global market price and overall market sentiment. Even incorporating just these two psychological tensions, important stylized facts of real market data, including fat-tails, excess kurtosis, uncorrelated price returns and clustered volatility over the timescale of a few days are reproduced. By then introducing an additional parameter that amplifies the effect of externally generated market noise during times of extreme market sentiment, long-time volatility correlations can also be recovered.

Self-Organization, Resilience and Robustness of Complex Systems Through an Application to Financial Market from an Agent-Based Approach

NASA Astrophysics Data System (ADS)

Lucas, Iris; Cotsaftis, Michel; Bertelle, Cyrille

This paper introduces the implementation of a computational agent-based financial market model in which the system is described on both microscopic and macroscopic levels. This artificial financial market model is used to study the system response when a shock occurs. Indeed, when a market experiences perturbations, financial systems behavior can exhibit two different properties: resilience and robustness. Through simulations and different scenarios of market shocks, these system properties are studied. The results notably show that the emergence of collective herding behavior when market shock occurs leads to a temporary disruption of the system self-organization. Numerical simulations highlight that the market can absorb strong mono-shocks but can also be led to rupture by low but repeated perturbations.

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

Confidence and the stock market: an agent-based approach.

PubMed

Bertella, Mario A; Pires, Felipe R; Feng, Ling; Stanley, Harry Eugene

2014-01-01

Using a behavioral finance approach we study the impact of behavioral bias. We construct an artificial market consisting of fundamentalists and chartists to model the decision-making process of various agents. The agents differ in their strategies for evaluating stock prices, and exhibit differing memory lengths and confidence levels. When we increase the heterogeneity of the strategies used by the agents, in particular the memory lengths, we observe excess volatility and kurtosis, in agreement with real market fluctuations--indicating that agents in real-world financial markets exhibit widely differing memory lengths. We incorporate the behavioral traits of adaptive confidence and observe a positive correlation between average confidence and return rate, indicating that market sentiment is an important driver in price fluctuations. The introduction of market confidence increases price volatility, reflecting the negative effect of irrationality in market behavior.

Confidence and the Stock Market: An Agent-Based Approach

PubMed Central

Bertella, Mario A.; Pires, Felipe R.; Feng, Ling; Stanley, Harry Eugene

2014-01-01

Using a behavioral finance approach we study the impact of behavioral bias. We construct an artificial market consisting of fundamentalists and chartists to model the decision-making process of various agents. The agents differ in their strategies for evaluating stock prices, and exhibit differing memory lengths and confidence levels. When we increase the heterogeneity of the strategies used by the agents, in particular the memory lengths, we observe excess volatility and kurtosis, in agreement with real market fluctuations—indicating that agents in real-world financial markets exhibit widely differing memory lengths. We incorporate the behavioral traits of adaptive confidence and observe a positive correlation between average confidence and return rate, indicating that market sentiment is an important driver in price fluctuations. The introduction of market confidence increases price volatility, reflecting the negative effect of irrationality in market behavior. PMID:24421888

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.

A Financial Market Model Incorporating Herd Behaviour.

PubMed

Wray, Christopher M; Bishop, Steven R

2016-01-01

Herd behaviour in financial markets is a recurring phenomenon that exacerbates asset price volatility, and is considered a possible contributor to market fragility. While numerous studies investigate herd behaviour in financial markets, it is often considered without reference to the pricing of financial instruments or other market dynamics. Here, a trader interaction model based upon informational cascades in the presence of information thresholds is used to construct a new model of asset price returns that allows for both quiescent and herd-like regimes. Agent interaction is modelled using a stochastic pulse-coupled network, parametrised by information thresholds and a network coupling probability. Agents may possess either one or two information thresholds that, in each case, determine the number of distinct states an agent may occupy before trading takes place. In the case where agents possess two thresholds (labelled as the finite state-space model, corresponding to agents' accumulating information over a bounded state-space), and where coupling strength is maximal, an asymptotic expression for the cascade-size probability is derived and shown to follow a power law when a critical value of network coupling probability is attained. For a range of model parameters, a mixture of negative binomial distributions is used to approximate the cascade-size distribution. This approximation is subsequently used to express the volatility of model price returns in terms of the model parameter which controls the network coupling probability. In the case where agents possess a single pulse-coupling threshold (labelled as the semi-infinite state-space model corresponding to agents' accumulating information over an unbounded state-space), numerical evidence is presented that demonstrates volatility clustering and long-memory patterns in the volatility of asset returns. Finally, output from the model is compared to both the distribution of historical stock returns and the market price of an equity index option.

Characteristic time scales of tick quotes on foreign currency markets: an empirical study and agent-based model

NASA Astrophysics Data System (ADS)

Sato, A.-H.

2006-03-01

Power spectrum densities for the number of tick quotes per minute (market activity) on three currency markets (USD/JPY, EUR/USD, and JPY/EUR) for periods from January 1999 to December 2000 are analyzed. We find some peaks on the power spectrum densities at a few minutes. We develop the double-threshold agent model and confirm that stochastic resonance occurs for the market activity of this model. We propose a hypothesis that the periodicities found on the power spectrum densities can be observed due to stochastic resonance.

The predictive power of zero intelligence in financial markets

NASA Astrophysics Data System (ADS)

Farmer, J. Doyne; Patelli, Paolo; Zovko, Ilija I.

2005-02-01

Standard models in economics stress the role of intelligent agents who maximize utility. However, there may be situations where constraints imposed by market institutions dominate strategic agent behavior. We use data from the London Stock Exchange to test a simple model in which minimally intelligent agents place orders to trade at random. The model treats the statistical mechanics of order placement, price formation, and the accumulation of revealed supply and demand within the context of the continuous double auction and yields simple laws relating order-arrival rates to statistical properties of the market. We test the validity of these laws in explaining cross-sectional variation for 11 stocks. The model explains 96% of the variance of the gap between the best buying and selling prices (the spread) and 76% of the variance of the price diffusion rate, with only one free parameter. We also study the market impact function, describing the response of quoted prices to the arrival of new orders. The nondimensional coordinates dictated by the model approximately collapse data from different stocks onto a single curve. This work is important from a practical point of view, because it demonstrates the existence of simple laws relating prices to order flows and, in a broader context, suggests there are circumstances where the strategic behavior of agents may be dominated by other considerations. double auction market | market microstructure | agent-based models

Agent-Based Framework for Personalized Service Provisioning in Converged IP Networks

NASA Astrophysics Data System (ADS)

Podobnik, Vedran; Matijasevic, Maja; Lovrek, Ignac; Skorin-Kapov, Lea; Desic, Sasa

In a global multi-service and multi-provider market, the Internet Service Providers will increasingly need to differentiate in the service quality they offer and base their operation on new, consumer-centric business models. In this paper, we propose an agent-based framework for the Business-to-Consumer (B2C) electronic market, comprising the Consumer Agents, Broker Agents and Content Agents, which enable Internet consumers to select a content provider in an automated manner. We also discuss how to dynamically allocate network resources to provide end-to-end Quality of Service (QoS) for a given consumer and content provider.

The fractional volatility model: An agent-based interpretation

NASA Astrophysics Data System (ADS)

Vilela Mendes, R.

2008-06-01

Based on the criteria of mathematical simplicity and consistency with empirical market data, a model with volatility driven by fractional noise has been constructed which provides a fairly accurate mathematical parametrization of the data. Here, some features of the model are reviewed and extended to account for leverage effects. Using agent-based models, one tries to find which agent strategies and (or) properties of the financial institutions might be responsible for the features of the fractional volatility model.

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.

Minimal agent based model for financial markets I. Origin and self-organization of stylized facts

NASA Astrophysics Data System (ADS)

Alfi, V.; Cristelli, M.; Pietronero, L.; Zaccaria, A.

2009-02-01

We introduce a minimal agent based model for financial markets to understand the nature and self-organization of the stylized facts. The model is minimal in the sense that we try to identify the essential ingredients to reproduce the most important deviations of price time series from a random walk behavior. We focus on four essential ingredients: fundamentalist agents which tend to stabilize the market; chartist agents which induce destabilization; analysis of price behavior for the two strategies; herding behavior which governs the possibility of changing strategy. Bubbles and crashes correspond to situations dominated by chartists, while fundamentalists provide a long time stability (on average). The stylized facts are shown to correspond to an intermittent behavior which occurs only for a finite value of the number of agents N. Therefore they correspond to finite size effects which, however, can occur at different time scales. We propose a new mechanism for the self-organization of this state which is linked to the existence of a threshold for the agents to be active or not active. The feedback between price fluctuations and number of active agents represents a crucial element for this state of self-organized intermittency. The model can be easily generalized to consider more realistic variants.

Word of Mouth : An Agent-based Approach to Predictability of Stock Prices

NASA Astrophysics Data System (ADS)

Shimokawa, Tetsuya; Misawa, Tadanobu; Watanabe, Kyoko

This paper addresses how communication processes among investors affect stock prices formation, especially emerging predictability of stock prices, in financial markets. An agent based model, called the word of mouth model, is introduced for analyzing the problem. This model provides a simple, but sufficiently versatile, description of informational diffusion process and is successful in making lucidly explanation for the predictability of small sized stocks, which is a stylized fact in financial markets but difficult to resolve by traditional models. Our model also provides a rigorous examination of the under reaction hypothesis to informational shocks.

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.

Analyzing the Validity of Relationship Banking through Agent-based Modeling

NASA Astrophysics Data System (ADS)

Nishikido, Yukihito; Takahashi, Hiroshi

This article analyzes the validity of relationship banking through agent-based modeling. In the analysis, we especially focus on the relationship between economic conditions and both lenders' and borrowers' behaviors. As a result of intensive experiments, we made the following interesting findings: (1) Relationship banking contributes to reducing bad loan; (2) relationship banking is more effective in enhancing the market growth compared to transaction banking, when borrowers' sales scale is large; (3) keener competition among lenders may bring inefficiency to the market.

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.

Uncertainty about fundamentals and herding behavior in the FOREX market

NASA Astrophysics Data System (ADS)

Kaltwasser, Pablo Rovira

2010-03-01

It is traditionally assumed in finance models that the fundamental value of assets is known with certainty. Although this is an appealing simplifying assumption it is by no means based on empirical evidence. A simple heterogeneous agent model of the exchange rate is presented. In the model, traders do not observe the true underlying fundamental exchange rate and as a consequence they base their trades on beliefs about this variable. Despite the fact that only fundamentalist traders operate in the market, the model belongs to the heterogeneous agent literature, as traders have different beliefs about the fundamental rate.

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

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.

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

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.

Bankruptcy cascades in interbank markets.

PubMed

Tedeschi, Gabriele; Mazloumian, Amin; Gallegati, Mauro; Helbing, Dirk

2012-01-01

We study a credit network and, in particular, an interbank system with an agent-based model. To understand the relationship between business cycles and cascades of bankruptcies, we model a three-sector economy with goods, credit and interbank market. In the interbank market, the participating banks share the risk of bad debits, which may potentially spread a bank's liquidity problems through the network of banks. Our agent-based model sheds light on the correlation between bankruptcy cascades and the endogenous economic cycle of booms and recessions. It also demonstrates the serious trade-off between, on the one hand, reducing risks of individual banks by sharing them and, on the other hand, creating systemic risks through credit-related interlinkages of banks. As a result of our study, the dynamics underlying the meltdown of financial markets in 2008 becomes much better understandable.

Bankruptcy Cascades in Interbank Markets

PubMed Central

Tedeschi, Gabriele; Mazloumian, Amin; Gallegati, Mauro; Helbing, Dirk

2012-01-01

We study a credit network and, in particular, an interbank system with an agent-based model. To understand the relationship between business cycles and cascades of bankruptcies, we model a three-sector economy with goods, credit and interbank market. In the interbank market, the participating banks share the risk of bad debits, which may potentially spread a bank’s liquidity problems through the network of banks. Our agent-based model sheds light on the correlation between bankruptcy cascades and the endogenous economic cycle of booms and recessions. It also demonstrates the serious trade-off between, on the one hand, reducing risks of individual banks by sharing them and, on the other hand, creating systemic risks through credit-related interlinkages of banks. As a result of our study, the dynamics underlying the meltdown of financial markets in 2008 becomes much better understandable. PMID:23300760

Strategy Space Exploration of a Multi-Agent Model for the Labor Market

NASA Astrophysics Data System (ADS)

de Grande, Pablo; Eguia, Manuel

We present a multi-agent system where typical labor market mechanisms emerge. Based on a few simple rules, our model allows for different interpretative paradigms to be represented and for different scenarios to be tried out. We thoroughly explore the space of possible strategies both for those unemployed and for companies and analyze the trade-off between these strategies regarding global social and economical indicators.

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.

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.

Anti-Obesity Agents and the US Food and Drug Administration.

PubMed

Casey, Martin F; Mechanick, Jeffrey I

2014-09-01

Despite the growing market for obesity care, the US Food and Drug Administration (FDA) has approved only two new pharmaceutical agents-lorcaserin and combination phentermine/topiramate-for weight reduction since 2000, while removing three agents from the market in the same time period. This article explores the FDA's history and role in the approval of anti-obesity medications within the context of a public health model of obesity. Through the review of obesity literature and FDA approval documents, we identified two major barriers preventing fair evaluation of anti-obesity agents including: (1) methodological pitfalls in clinical trials and (2) misaligned values in the assessment of anti-obesity agents. Specific recommendations include the use of adaptive (Bayesian) design protocols, value-based analyses of risks and benefits, and regulatory guidance based on a comprehensive, multi-platform obesity disease model. Positively addressing barriers in the FDA approval process of anti-obesity agents may have many beneficial effects within an obesity disease model.

A heterogeneous artificial stock market model can benefit people against another financial crisis

PubMed Central

2018-01-01

This paper presents results of an artificial stock market and tries to make it more consistent with the statistical features of real stock data. Based on the SFI-ASM, a novel model is proposed to make agents more close to the real world. Agents are divided into four kinds in terms of different learning speeds, strategy-sizes, utility functions, and level of intelligence; and a crucial parameter has been found to ensure system stability. So, some parameters are appended to make the model which contains zero-intelligent and less-intelligent agents run steadily. Moreover, considering real stock markets change violently due to the financial crisis; the real stock markets are divided into two segments, before the financial crisis and after it. The optimal modified model before the financial crisis fails to replicate the statistical features of the real market after the financial crisis. Then, the optimal model after the financial crisis is shown. The experiments indicate that the optimal model after the financial crisis is able to replicate several of real market phenomena, including the first-order autocorrelation, kurtosis, standard deviation of yield series and first-order autocorrelation of yield square. We point out that there is a structural change in stock markets after the financial crisis, which can benefit people forecast the financial crisis. PMID:29912893

A heterogeneous artificial stock market model can benefit people against another financial crisis.

PubMed

Yang, Haijun; Chen, Shuheng

2018-01-01

This paper presents results of an artificial stock market and tries to make it more consistent with the statistical features of real stock data. Based on the SFI-ASM, a novel model is proposed to make agents more close to the real world. Agents are divided into four kinds in terms of different learning speeds, strategy-sizes, utility functions, and level of intelligence; and a crucial parameter has been found to ensure system stability. So, some parameters are appended to make the model which contains zero-intelligent and less-intelligent agents run steadily. Moreover, considering real stock markets change violently due to the financial crisis; the real stock markets are divided into two segments, before the financial crisis and after it. The optimal modified model before the financial crisis fails to replicate the statistical features of the real market after the financial crisis. Then, the optimal model after the financial crisis is shown. The experiments indicate that the optimal model after the financial crisis is able to replicate several of real market phenomena, including the first-order autocorrelation, kurtosis, standard deviation of yield series and first-order autocorrelation of yield square. We point out that there is a structural change in stock markets after the financial crisis, which can benefit people forecast the financial crisis.

Market Model for Resource Allocation in Emerging Sensor Networks with Reinforcement Learning

PubMed Central

Zhang, Yue; Song, Bin; Zhang, Ying; Du, Xiaojiang; Guizani, Mohsen

2016-01-01

Emerging sensor networks (ESNs) are an inevitable trend with the development of the Internet of Things (IoT), and intend to connect almost every intelligent device. Therefore, it is critical to study resource allocation in such an environment, due to the concern of efficiency, especially when resources are limited. By viewing ESNs as multi-agent environments, we model them with an agent-based modelling (ABM) method and deal with resource allocation problems with market models, after describing users’ patterns. Reinforcement learning methods are introduced to estimate users’ patterns and verify the outcomes in our market models. Experimental results show the efficiency of our methods, which are also capable of guiding topology management. PMID:27916841

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

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.

Mechanistic origin of dragon-kings in a population of competing agents

NASA Astrophysics Data System (ADS)

Johnson, N.; Tivnan, B.

2012-05-01

We analyze the mechanistic origins of the extreme behaviors that arise in an idealized model of a population of competing agents, such as traders in a market. These extreme behaviors exhibit the defining characteristics of `dragon-kings'. Our model comprises heterogeneous agents who repeatedly compete for some limited resource, making binary choices based on the strategies that they have in their possession. It generalizes the well-known Minority Game by allowing agents whose strategies have not made accurate recent predictions, to step out of the competition until their strategies improve. This generates a complex dynamical interplay between the number V of active agents (mimicking market volume) and the imbalance D between the decisions made (mimicking excess demand). The wide spectrum of extreme behaviors which emerge, helps to explain why no unique relationship has been identified between the price and volume during real market crashes and rallies.

Stochastic model of financial markets reproducing scaling and memory in volatility return intervals

NASA Astrophysics Data System (ADS)

Gontis, V.; Havlin, S.; Kononovicius, A.; Podobnik, B.; Stanley, H. E.

2016-11-01

We investigate the volatility return intervals in the NYSE and FOREX markets. We explain previous empirical findings using a model based on the interacting agent hypothesis instead of the widely-used efficient market hypothesis. We derive macroscopic equations based on the microscopic herding interactions of agents and find that they are able to reproduce various stylized facts of different markets and different assets with the same set of model parameters. We show that the power-law properties and the scaling of return intervals and other financial variables have a similar origin and could be a result of a general class of non-linear stochastic differential equations derived from a master equation of an agent system that is coupled by herding interactions. Specifically, we find that this approach enables us to recover the volatility return interval statistics as well as volatility probability and spectral densities for the NYSE and FOREX markets, for different assets, and for different time-scales. We find also that the historical S&P500 monthly series exhibits the same volatility return interval properties recovered by our proposed model. Our statistical results suggest that human herding is so strong that it persists even when other evolving fluctuations perturbate the financial system.

Minimal agent based model for financial markets II. Statistical properties of the linear and multiplicative dynamics

NASA Astrophysics Data System (ADS)

Alfi, V.; Cristelli, M.; Pietronero, L.; Zaccaria, A.

2009-02-01

We present a detailed study of the statistical properties of the Agent Based Model introduced in paper I [Eur. Phys. J. B, DOI: 10.1140/epjb/e2009-00028-4] and of its generalization to the multiplicative dynamics. The aim of the model is to consider the minimal elements for the understanding of the origin of the stylized facts and their self-organization. The key elements are fundamentalist agents, chartist agents, herding dynamics and price behavior. The first two elements correspond to the competition between stability and instability tendencies in the market. The herding behavior governs the possibility of the agents to change strategy and it is a crucial element of this class of models. We consider a linear approximation for the price dynamics which permits a simple interpretation of the model dynamics and, for many properties, it is possible to derive analytical results. The generalized non linear dynamics results to be extremely more sensible to the parameter space and much more difficult to analyze and control. The main results for the nature and self-organization of the stylized facts are, however, very similar in the two cases. The main peculiarity of the non linear dynamics is an enhancement of the fluctuations and a more marked evidence of the stylized facts. We will also discuss some modifications of the model to introduce more realistic elements with respect to the real markets.

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

Multi-Agent Market Modeling of Foreign Exchange Rates

NASA Astrophysics Data System (ADS)

Zimmermann, Georg; Neuneier, Ralph; Grothmann, Ralph

A market mechanism is basically driven by a superposition of decisions of many agents optimizing their profit. The oeconomic price dynamic is a consequence of the cumulated excess demand/supply created on this micro level. The behavior analysis of a small number of agents is well understood through the game theory. In case of a large number of agents one may use the limiting case that an individual agent does not have an influence on the market, which allows the aggregation of agents by statistic methods. In contrast to this restriction, we can omit the assumption of an atomic market structure, if we model the market through a multi-agent approach. The contribution of the mathematical theory of neural networks to the market price formation is mostly seen on the econometric side: neural networks allow the fitting of high dimensional nonlinear dynamic models. Furthermore, in our opinion, there is a close relationship between economics and the modeling ability of neural networks because a neuron can be interpreted as a simple model of decision making. With this in mind, a neural network models the interaction of many decisions and, hence, can be interpreted as the price formation mechanism of a market.

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.

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

Emergence of trend trading and its effects in minority game

NASA Astrophysics Data System (ADS)

Liu, Xing-Hua; Liang, Xiao-Bei; Wang, Nai-Jing

2006-09-01

In this paper, we extended Minority Game (MG) by equipping agents with both value and trend strategies. In the new model, agents (we call them strong-adaptation agents) can autonomically select to act as trend trader or value trader when they game and learn in system. So the new model not only can reproduce stylized factors but also has the potential to investigate into the process of some problems of securities market. We investigated the dynamics of trend trading and its impacts on securities market based on the new model. Our research found that trend trading is inevitable when strong-adaptation agents make decisions by inductive reasoning. Trend trading (of strong-adaptation agents) is not irrational behavior but shows agent's strong-adaptation intelligence, because strong-adaptation agents can take advantage of the pure value agents when they game together in hybrid system. We also found that strong-adaptation agents do better in real environment. The results of our research are different with those of behavior finance researches.

Equation-based model for the stock market

NASA Astrophysics Data System (ADS)

Xavier, Paloma O. C.; Atman, A. P. F.; de Magalhães, A. R. Bosco

2017-09-01

We propose a stock market model which is investigated in the forms of difference and differential equations whose variables correspond to the demand or supply of each agent and to the price. In the model, agents are driven by the behavior of their trust contact network as well by fundamental analysis. By means of the deterministic version of the model, the connection between such drive mechanisms and the price is analyzed: imitation behavior promotes market instability, finitude of resources is associated to stock index stability, and high sensitivity to the fair price provokes price oscillations. Long-range correlations in the price temporal series and heavy-tailed distribution of returns are observed for the version of the model which considers different proposals for stochasticity of microeconomic and macroeconomic origins.

Agent Based Model of Livestock Movements

NASA Astrophysics Data System (ADS)

Miron, D. J.; Emelyanova, I. V.; Donald, G. E.; Garner, G. M.

The modelling of livestock movements within Australia is of national importance for the purposes of the management and control of exotic disease spread, infrastructure development and the economic forecasting of livestock markets. In this paper an agent based model for the forecasting of livestock movements is presented. This models livestock movements from farm to farm through a saleyard. The decision of farmers to sell or buy cattle is often complex and involves many factors such as climate forecast, commodity prices, the type of farm enterprise, the number of animals available and associated off-shore effects. In this model the farm agent's intelligence is implemented using a fuzzy decision tree that utilises two of these factors. These two factors are the livestock price fetched at the last sale and the number of stock on the farm. On each iteration of the model farms choose either to buy, sell or abstain from the market thus creating an artificial supply and demand. The buyers and sellers then congregate at the saleyard where livestock are auctioned using a second price sealed bid. The price time series output by the model exhibits properties similar to those found in real livestock markets.

Agent-Based Model Approach to Complex Phenomena in Real Economy

NASA Astrophysics Data System (ADS)

Iyetomi, H.; Aoyama, H.; Fujiwara, Y.; Ikeda, Y.; Souma, W.

An agent-based model for firms' dynamics is developed. The model consists of firm agents with identical characteristic parameters and a bank agent. Dynamics of those agents are described by their balance sheets. Each firm tries to maximize its expected profit with possible risks in market. Infinite growth of a firm directed by the ``profit maximization" principle is suppressed by a concept of ``going concern". Possibility of bankruptcy of firms is also introduced by incorporating a retardation effect of information on firms' decision. The firms, mutually interacting through the monopolistic bank, become heterogeneous in the course of temporal evolution. Statistical properties of firms' dynamics obtained by simulations based on the model are discussed in light of observations in the real economy.

Comparing administered and market-based water allocation systems through a consistent agent-based modeling framework.

PubMed

Zhao, Jianshi; Cai, Ximing; Wang, Zhongjing

2013-07-15

Water allocation can be undertaken through administered systems (AS), market-based systems (MS), or a combination of the two. The debate on the performance of the two systems has lasted for decades but still calls for attention in both research and practice. This paper compares water users' behavior under AS and MS through a consistent agent-based modeling framework for water allocation analysis that incorporates variables particular to both MS (e.g., water trade and trading prices) and AS (water use violations and penalties/subsidies). Analogous to the economic theory of water markets under MS, the theory of rational violation justifies the exchange of entitled water under AS through the use of cross-subsidies. Under water stress conditions, a unique water allocation equilibrium can be achieved by following a simple bargaining rule that does not depend upon initial market prices under MS, or initial economic incentives under AS. The modeling analysis shows that the behavior of water users (agents) depends on transaction, or administrative, costs, as well as their autonomy. Reducing transaction costs under MS or administrative costs under AS will mitigate the effect that equity constraints (originating with primary water allocation) have on the system's total net economic benefits. Moreover, hydrologic uncertainty is shown to increase market prices under MS and penalties/subsidies under AS and, in most cases, also increases transaction, or administrative, costs. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

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.

Green Power Grids: How Energy from Renewable Sources Affects Networks and Markets.

PubMed

Mureddu, Mario; Caldarelli, Guido; Chessa, Alessandro; Scala, Antonio; Damiano, Alfonso

2015-01-01

The increasing attention to environmental issues is forcing the implementation of novel energy models based on renewable sources. This is fundamentally changing the configuration of energy management and is introducing new problems that are only partly understood. In particular, renewable energies introduce fluctuations which cause an increased request for conventional energy sources to balance energy requests at short notice. In order to develop an effective usage of low-carbon sources, such fluctuations must be understood and tamed. In this paper we present a microscopic model for the description and for the forecast of short time fluctuations related to renewable sources in order to estimate their effects on the electricity market. To account for the inter-dependencies in the energy market and the physical power dispatch network, we use a statistical mechanics approach to sample stochastic perturbations in the power system and an agent based approach for the prediction of the market players' behavior. Our model is data-driven; it builds on one-day-ahead real market transactions in order to train agents' behaviour and allows us to deduce the market share of different energy sources. We benchmarked our approach on the Italian market, finding a good accordance with real data.

A Financial Market Model Incorporating Herd Behaviour

PubMed Central

2016-01-01

Herd behaviour in financial markets is a recurring phenomenon that exacerbates asset price volatility, and is considered a possible contributor to market fragility. While numerous studies investigate herd behaviour in financial markets, it is often considered without reference to the pricing of financial instruments or other market dynamics. Here, a trader interaction model based upon informational cascades in the presence of information thresholds is used to construct a new model of asset price returns that allows for both quiescent and herd-like regimes. Agent interaction is modelled using a stochastic pulse-coupled network, parametrised by information thresholds and a network coupling probability. Agents may possess either one or two information thresholds that, in each case, determine the number of distinct states an agent may occupy before trading takes place. In the case where agents possess two thresholds (labelled as the finite state-space model, corresponding to agents’ accumulating information over a bounded state-space), and where coupling strength is maximal, an asymptotic expression for the cascade-size probability is derived and shown to follow a power law when a critical value of network coupling probability is attained. For a range of model parameters, a mixture of negative binomial distributions is used to approximate the cascade-size distribution. This approximation is subsequently used to express the volatility of model price returns in terms of the model parameter which controls the network coupling probability. In the case where agents possess a single pulse-coupling threshold (labelled as the semi-infinite state-space model corresponding to agents’ accumulating information over an unbounded state-space), numerical evidence is presented that demonstrates volatility clustering and long-memory patterns in the volatility of asset returns. Finally, output from the model is compared to both the distribution of historical stock returns and the market price of an equity index option. PMID:27007236

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.

Endogenous Price Bubbles in a Multi-Agent System of the Housing Market

PubMed Central

2015-01-01

Economic history shows a large number of boom-bust cycles, with the U.S. real estate market as one of the latest examples. Classical economic models have not been able to provide a full explanation for this type of market dynamics. Therefore, we analyze home prices in the U.S. using an alternative approach, a multi-agent complex system. Instead of the classical assumptions of agent rationality and market efficiency, agents in the model are heterogeneous, adaptive, and boundedly rational. We estimate the multi-agent system with historical house prices for the U.S. market. The model fits the data well and a deterministic version of the model can endogenously produce boom-and-bust cycles on the basis of the estimated coefficients. This implies that trading between agents themselves can create major price swings in absence of fundamental news. PMID:26107740

Delayed Majority Game with Heterogeneous Learning Speeds for Financial Markets

NASA Astrophysics Data System (ADS)

Yoshimura, Yushi; Yamada, Kenta

There are two famous statistical laws, so-called stylized facts, in financial markets. One is fat tail where the tail of price returns obeys a power law. The other is volatility clustering in which the autocorrelation function of absolute price returns decays with a power law. In order to understand relationships between the stylized facts and dealers' behaviors, we constructed a new agent-based model based on the grand canonical minority game (GCMG) and the Giardina-Bouchaud (GB) model. The recovery of stylized facts by GCMG and GB lacks of robustness. Therefore, based on the GCMG and GB model, we develop a new model that can reproduce stylized facts robustly. Furthermore, we find that heterogeneity of learning speeds of agents is important to reproduce the stylized facts.

Micro-Level Adaptation, Macro-Level Selection, and the Dynamics of Market Partitioning

PubMed Central

García-Díaz, César; van Witteloostuijn, Arjen; Péli, Gábor

2015-01-01

This paper provides a micro-foundation for dual market structure formation through partitioning processes in marketplaces by developing a computational model of interacting economic agents. We propose an agent-based modeling approach, where firms are adaptive and profit-seeking agents entering into and exiting from the market according to their (lack of) profitability. Our firms are characterized by large and small sunk costs, respectively. They locate their offerings along a unimodal demand distribution over a one-dimensional product variety, with the distribution peak constituting the center and the tails standing for the peripheries. We found that large firms may first advance toward the most abundant demand spot, the market center, and release peripheral positions as predicted by extant dual market explanations. However, we also observed that large firms may then move back toward the market fringes to reduce competitive niche overlap in the center, triggering nonlinear resource occupation behavior. Novel results indicate that resource release dynamics depend on firm-level adaptive capabilities, and that a minimum scale of production for low sunk cost firms is key to the formation of the dual structure. PMID:26656107

Micro-Level Adaptation, Macro-Level Selection, and the Dynamics of Market Partitioning.

PubMed

García-Díaz, César; van Witteloostuijn, Arjen; Péli, Gábor

2015-01-01

This paper provides a micro-foundation for dual market structure formation through partitioning processes in marketplaces by developing a computational model of interacting economic agents. We propose an agent-based modeling approach, where firms are adaptive and profit-seeking agents entering into and exiting from the market according to their (lack of) profitability. Our firms are characterized by large and small sunk costs, respectively. They locate their offerings along a unimodal demand distribution over a one-dimensional product variety, with the distribution peak constituting the center and the tails standing for the peripheries. We found that large firms may first advance toward the most abundant demand spot, the market center, and release peripheral positions as predicted by extant dual market explanations. However, we also observed that large firms may then move back toward the market fringes to reduce competitive niche overlap in the center, triggering nonlinear resource occupation behavior. Novel results indicate that resource release dynamics depend on firm-level adaptive capabilities, and that a minimum scale of production for low sunk cost firms is key to the formation of the dual structure.

Racial Labor Market Gaps: The Role of Abilities and Schooling Choices

ERIC Educational Resources Information Center

Urzua, Sergio

2008-01-01

This paper studies the relationship between abilities, schooling choices, and black-white differentials in labor market outcomes. The analysis is based on a model of endogenous schooling choices. Agents' schooling decisions are based on expected future earnings, family background, and unobserved abilities. Earnings are also determined by…

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.

Market behavior and performance of different strategy evaluation schemes.

PubMed

Baek, Yongjoo; Lee, Sang Hoon; Jeong, Hawoong

2010-08-01

Strategy evaluation schemes are a crucial factor in any agent-based market model, as they determine the agents' strategy preferences and consequently their behavioral pattern. This study investigates how the strategy evaluation schemes adopted by agents affect their performance in conjunction with the market circumstances. We observe the performance of three strategy evaluation schemes, the history-dependent wealth game, the trend-opposing minority game, and the trend-following majority game, in a stock market where the price is exogenously determined. The price is either directly adopted from the real stock market indices or generated with a Markov chain of order ≤2 . Each scheme's success is quantified by average wealth accumulated by the traders equipped with the scheme. The wealth game, as it learns from the history, shows relatively good performance unless the market is highly unpredictable. The majority game is successful in a trendy market dominated by long periods of sustained price increase or decrease. On the other hand, the minority game is suitable for a market with persistent zigzag price patterns. We also discuss the consequence of implementing finite memory in the scoring processes of strategies. Our findings suggest under which market circumstances each evaluation scheme is appropriate for modeling the behavior of real market traders.

Exploring Agricultural Livelihood Transitions with an Agent-Based Virtual Laboratory: Global Forces to Local Decision-Making

PubMed Central

Magliocca, Nicholas R.; Brown, Daniel G.; Ellis, Erle C.

2013-01-01

Rural populations are undergoing rapid changes in both their livelihoods and land uses, with associated impacts on ecosystems, global biogeochemistry, and climate change. A primary challenge is, thus, to explain these shifts in terms of the actors and processes operating within a variety of land systems in order to understand how land users might respond locally to future changes in broader-scale environmental and economic conditions. Using ‘induced intensification’ theory as a benchmark, we develop a generalized agent-based model to investigate mechanistic explanations of relationships between agricultural intensity and population density, environmental suitability, and market influence. Land-use and livelihood decisions modeled from basic micro-economic theories generated spatial and temporal patterns of agricultural intensification consistent with predictions of induced intensification theory. Further, agent actions in response to conditions beyond those described by induced intensification theory were explored, revealing that interactions among environmental constraints, population pressure, and market influence may produce transitions to multiple livelihood regimes of varying market integration. The result is new hypotheses that could modify and enrich understanding of the classic relationship between agricultural intensity and population density. The strength of this agent-based model and the experimental results is the generalized form of the decision-making processes underlying land-use and livelihood transitions, creating the prospect of a virtual laboratory for systematically generating hypotheses of how agent decisions and interactions relate to observed land-use and livelihood patterns across diverse land systems. PMID:24039892

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.

Democracy versus dictatorship in self-organized models of financial markets

NASA Astrophysics Data System (ADS)

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

2000-06-01

Models to mimic the transmission of information in financial markets are introduced. As an attempt to generate the demand process, we distinguish between dictatorship associations, where groups of agents rely on one of them to make decision, and democratic associations, where each agent takes part in the group decision. In the dictatorship model, agents segregate into two distinct populations, while the democratic model is driven towards a critical state where groups of agents of all sizes exist. Hence, both models display a level of organization, but only the democratic model is self-organized. We show that the dictatorship model generates less-volatile markets than the democratic model.

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).

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

How Market Structure Drives Commodity Prices

NASA Astrophysics Data System (ADS)

Li, Bin; Wong, K. Y. Michael; Chan, Amos H. M.; So, Tsz Yan; Heimonen, Hermanni; Saad, David

To understand how market structure drives commodity price trends with respect to resource availability we introduce an agent-based model, in which agents set their prices to maximize profit. At steady state the market self-organizes into three groups: excess producers, consumers and balanced agents. When resources are scarce prices rise sharply below a turning point marking the disappearance of excess producers. By introducing an elasticity parameter to mitigate noise and long-term changes in commodities data, we confirm the trend of rising prices, provide evidence for turning points, and indicate yield points for less essential commodities. This work is supported by Research Grants Council of Hong Kong (Grant Numbers 604512, 605813, and 16322616) and the Leverhulme Trust RPG-2013-48.

A market-based optimization approach to sensor and resource management

NASA Astrophysics Data System (ADS)

Schrage, Dan; Farnham, Christopher; Gonsalves, Paul G.

2006-05-01

Dynamic resource allocation for sensor management is a problem that demands solutions beyond traditional approaches to optimization. Market-based optimization applies solutions from economic theory, particularly game theory, to the resource allocation problem by creating an artificial market for sensor information and computational resources. Intelligent agents are the buyers and sellers in this market, and they represent all the elements of the sensor network, from sensors to sensor platforms to computational resources. These agents interact based on a negotiation mechanism that determines their bidding strategies. This negotiation mechanism and the agents' bidding strategies are based on game theory, and they are designed so that the aggregate result of the multi-agent negotiation process is a market in competitive equilibrium, which guarantees an optimal allocation of resources throughout the sensor network. This paper makes two contributions to the field of market-based optimization: First, we develop a market protocol to handle heterogeneous goods in a dynamic setting. Second, we develop arbitrage agents to improve the efficiency in the market in light of its dynamic nature.

Heterogeneity and Self-Organization of Complex Systems Through an Application to Financial Market with Multiagent Systems

NASA Astrophysics Data System (ADS)

Lucas, Iris; Cotsaftis, Michel; Bertelle, Cyrille

2017-12-01

Multiagent systems (MAS) provide a useful tool for exploring the complex dynamics and behavior of financial markets and now MAS approach has been widely implemented and documented in the empirical literature. This paper introduces the implementation of an innovative multi-scale mathematical model for a computational agent-based financial market. The paper develops a method to quantify the degree of self-organization which emerges in the system and shows that the capacity of self-organization is maximized when the agent behaviors are heterogeneous. Numerical results are presented and analyzed, showing how the global market behavior emerges from specific individual behavior interactions.

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.

Comparative advantage between traditional and smart navigation systems

NASA Astrophysics Data System (ADS)

Shin, Jeongkyu; Kim, Pan-Jun; Kim, Seunghwan

2013-03-01

The smart navigation system that refers to real-time traffic data is believed to be superior to traditional navigation systems. To verify this belief, we created an agent-based traffic model and examined the effect of changing market share of the traditional shortest-travel-time algorithm based navigation and the smart navigation system. We tested our model on the grid and actual metropolitan road network structures. The result reveals that the traditional navigation system have better performance than the smart one as the market share of the smart navigation system exceeds a critical value, which is contrary to conventional expectation. We suggest that the superiority inversion between agent groups is strongly related to the traffic weight function form, and is general. We also found that the relationship of market share, traffic flow density and travel time is determined by the combination of congestion avoidance behavior of the smartly navigated agents and the inefficiency of shortest-travel-time based navigated agents. Our results can be interpreted with the minority game and extended to the diverse topics of opinion dynamics. This work was supported by the Original Technology Research Program for Brain Science through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology(No. 2010-0018847).

Calibrating emergent phenomena in stock markets with agent based models

PubMed Central

Sornette, Didier

2018-01-01

Since the 2008 financial crisis, agent-based models (ABMs), which account for out-of-equilibrium dynamics, heterogeneous preferences, time horizons and strategies, have often been envisioned as the new frontier that could revolutionise and displace the more standard models and tools in economics. However, their adoption and generalisation is drastically hindered by the absence of general reliable operational calibration methods. Here, we start with a different calibration angle that qualifies an ABM for its ability to achieve abnormal trading performance with respect to the buy-and-hold strategy when fed with real financial data. Starting from the common definition of standard minority and majority agents with binary strategies, we prove their equivalence to optimal decision trees. This efficient representation allows us to exhaustively test all meaningful single agent models for their potential anomalous investment performance, which we apply to the NASDAQ Composite index over the last 20 years. We uncover large significant predictive power, with anomalous Sharpe ratio and directional accuracy, in particular during the dotcom bubble and crash and the 2008 financial crisis. A principal component analysis reveals transient convergence between the anomalous minority and majority models. A novel combination of the optimal single-agent models of both classes into a two-agents model leads to remarkable superior investment performance, especially during the periods of bubbles and crashes. Our design opens the field of ABMs to construct novel types of advanced warning systems of market crises, based on the emergent collective intelligence of ABMs built on carefully designed optimal decision trees that can be reversed engineered from real financial data. PMID:29499049

Calibrating emergent phenomena in stock markets with agent based models.

PubMed

Fievet, Lucas; Sornette, Didier

2018-01-01

Since the 2008 financial crisis, agent-based models (ABMs), which account for out-of-equilibrium dynamics, heterogeneous preferences, time horizons and strategies, have often been envisioned as the new frontier that could revolutionise and displace the more standard models and tools in economics. However, their adoption and generalisation is drastically hindered by the absence of general reliable operational calibration methods. Here, we start with a different calibration angle that qualifies an ABM for its ability to achieve abnormal trading performance with respect to the buy-and-hold strategy when fed with real financial data. Starting from the common definition of standard minority and majority agents with binary strategies, we prove their equivalence to optimal decision trees. This efficient representation allows us to exhaustively test all meaningful single agent models for their potential anomalous investment performance, which we apply to the NASDAQ Composite index over the last 20 years. We uncover large significant predictive power, with anomalous Sharpe ratio and directional accuracy, in particular during the dotcom bubble and crash and the 2008 financial crisis. A principal component analysis reveals transient convergence between the anomalous minority and majority models. A novel combination of the optimal single-agent models of both classes into a two-agents model leads to remarkable superior investment performance, especially during the periods of bubbles and crashes. Our design opens the field of ABMs to construct novel types of advanced warning systems of market crises, based on the emergent collective intelligence of ABMs built on carefully designed optimal decision trees that can be reversed engineered from real financial data.

A self-adapting herding model: The agent judge-abilities influence the dynamic behaviors

NASA Astrophysics Data System (ADS)

Dong, Linrong

2008-10-01

We propose a self-adapting herding model, in which the financial markets consist of agent clusters with different sizes and market desires. The ratio of successful exchange and merger depends on the volatility of the market and the market desires of the agent clusters. The desires are assigned in term of the wealth of the agent clusters when they merge. After an exchange, the beneficial cluster’s desire keeps on the same, the losing one’s desire is altered which is correlative with the agent judge-ability. A parameter R is given to all agents to denote the judge-ability. The numerical calculation shows that the dynamic behaviors of the market are influenced distinctly by R, which includes the exponential magnitudes of the probability distribution of sizes of the agent clusters and the volatility autocorrelation of the returns, the intensity and frequency of the volatility.

An agent-based model of farmer decision-making and water quality impacts at the watershed scale under markets for carbon allowances and a second-generation biofuel crop

NASA Astrophysics Data System (ADS)

Ng, Tze Ling; Eheart, J. Wayland; Cai, Ximing; Braden, John B.

2011-09-01

An agent-based model of farmers' crop and best management practice (BMP) decisions is developed and linked to a hydrologic-agronomic model of a watershed, to examine farmer behavior, and the attendant effects on stream nitrate load, under the influence of markets for conventional crops, carbon allowances, and a second-generation biofuel crop. The agent-based approach introduces interactions among farmers about new technologies and market opportunities, and includes the updating of forecast expectations and uncertainties using Bayesian inference. The model is applied to a semi-hypothetical example case of farmers in the Salt Creek Watershed in Central Illinois, and a sensitivity analysis is performed to effect a first-order assessment of the plausibility of the results. The results show that the most influential factors affecting farmers' decisions are crop prices, production costs, and yields. The results also show that different farmer behavioral profiles can lead to different predictions of farmer decisions. The farmers who are predicted to be more likely to adopt new practices are those who interact more with other farmers, are less risk averse, quick to adjust their expectations, and slow to reduce their forecast confidence. The decisions of farmers have direct water quality consequences, especially those pertaining to the adoption of the second-generation biofuel crop, which are estimated to lead to reductions in stream nitrate load. The results, though empirically untested, appear plausible and consistent with general farmer behavior. The results demonstrate the usefulness of the coupled agent-based and hydrologic-agronomic models for normative research on watershed management on the water-energy nexus.

Agent-Based Models in Social Physics

NASA Astrophysics Data System (ADS)

Quang, Le Anh; Jung, Nam; Cho, Eun Sung; Choi, Jae Han; Lee, Jae Woo

2018-06-01

We review the agent-based models (ABM) on social physics including econophysics. The ABM consists of agent, system space, and external environment. The agent is autonomous and decides his/her behavior by interacting with the neighbors or the external environment with the rules of behavior. Agents are irrational because they have only limited information when they make decisions. They adapt using learning from past memories. Agents have various attributes and are heterogeneous. ABM is a non-equilibrium complex system that exhibits various emergence phenomena. The social complexity ABM describes human behavioral characteristics. In ABMs of econophysics, we introduce the Sugarscape model and the artificial market models. We review minority games and majority games in ABMs of game theory. Social flow ABM introduces crowding, evacuation, traffic congestion, and pedestrian dynamics. We also review ABM for opinion dynamics and voter model. We discuss features and advantages and disadvantages of Netlogo, Repast, Swarm, and Mason, which are representative platforms for implementing ABM.

Group-Wise Herding Behavior in Financial Markets: An Agent-Based Modeling Approach

PubMed Central

Kim, Minsung; Kim, Minki

2014-01-01

In this paper, we shed light on the dynamic characteristics of rational group behaviors and the relationship between monetary policy and economic units in the financial market by using an agent-based model (ABM), the Hurst exponent, and the Shannon entropy. First, an agent-based model is used to analyze the characteristics of the group behaviors at different levels of irrationality. Second, the Hurst exponent is applied to analyze the characteristics of the trend-following irrationality group. Third, the Shannon entropy is used to analyze the randomness and unpredictability of group behavior. We show that in a system that focuses on macro-monetary policy, steep fluctuations occur, meaning that the medium-level irrationality group has the highest Hurst exponent and Shannon entropy among all of the groups. However, in a system that focuses on micro-monetary policy, all group behaviors follow a stable trend, and the medium irrationality group thus remains stable, too. Likewise, in a system that focuses on both micro- and macro-monetary policies, all groups tend to be stable. Consequently, we find that group behavior varies across economic units at each irrationality level for micro- and macro-monetary policy in the financial market. Together, these findings offer key insights into monetary policy. PMID:24714635

Group-wise herding behavior in financial markets: an agent-based modeling approach.

PubMed

Kim, Minsung; Kim, Minki

2014-01-01

In this paper, we shed light on the dynamic characteristics of rational group behaviors and the relationship between monetary policy and economic units in the financial market by using an agent-based model (ABM), the Hurst exponent, and the Shannon entropy. First, an agent-based model is used to analyze the characteristics of the group behaviors at different levels of irrationality. Second, the Hurst exponent is applied to analyze the characteristics of the trend-following irrationality group. Third, the Shannon entropy is used to analyze the randomness and unpredictability of group behavior. We show that in a system that focuses on macro-monetary policy, steep fluctuations occur, meaning that the medium-level irrationality group has the highest Hurst exponent and Shannon entropy among all of the groups. However, in a system that focuses on micro-monetary policy, all group behaviors follow a stable trend, and the medium irrationality group thus remains stable, too. Likewise, in a system that focuses on both micro- and macro-monetary policies, all groups tend to be stable. Consequently, we find that group behavior varies across economic units at each irrationality level for micro- and macro-monetary policy in the financial market. Together, these findings offer key insights into monetary policy.

Impact of immigrants on a multi-agent economical system

PubMed Central

Razakanirina, Ranaivo; Groen, Derek

2018-01-01

We consider a multi-agent model of a simple economical system and study the impacts of a wave of immigrants on the stability of the system. Our model couples a labor market with a goods market. We first create a stable economy with N agents and study the impact of adding n new workers in the system. The time to reach a new equilibrium market is found to obey a power law in n. The new wages and market prices are observed to decrease as 1/n, whereas the wealth of agents remains unchanged. PMID:29795633

Modeling of the financial market using the two-dimensional anisotropic Ising model

NASA Astrophysics Data System (ADS)

Lima, L. S.

2017-09-01

We have used the two-dimensional classical anisotropic Ising model in an external field and with an ion single anisotropy term as a mathematical model for the price dynamics of the financial market. The model presented allows us to test within the same framework the comparative explanatory power of rational agents versus irrational agents with respect to the facts of financial markets. We have obtained the mean price in terms of the strong of the site anisotropy term Δ which reinforces the sensitivity of the agent's sentiment to external news.

Information-driven trade and price-volume relationship in artificial stock markets

NASA Astrophysics Data System (ADS)

Liu, Xinghua; Liu, Xin; Liang, Xiaobei

2015-07-01

The positive relation between stock price changes and trading volume (price-volume relationship) as a stylized fact has attracted significant interest among finance researchers and investment practitioners. However, until now, consensus has not been reached regarding the causes of the relationship based on real market data because extracting valuable variables (such as information-driven trade volume) from real data is difficult. This lack of general consensus motivates us to develop a simple agent-based computational artificial stock market where extracting the necessary variables is easy. Based on this model and its artificial data, our tests have found that the aggressive trading style of informed agents can produce a price-volume relationship. Therefore, the information spreading process is not a necessary condition for producing price-volume relationship.

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.

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.

Markets, Herding and Response to External Information.

PubMed

Carro, Adrián; Toral, Raúl; San Miguel, Maxi

2015-01-01

We focus on the influence of external sources of information upon financial markets. In particular, we develop a stochastic agent-based market model characterized by a certain herding behavior as well as allowing traders to be influenced by an external dynamic signal of information. This signal can be interpreted as a time-varying advertising, public perception or rumor, in favor or against one of two possible trading behaviors, thus breaking the symmetry of the system and acting as a continuously varying exogenous shock. As an illustration, we use a well-known German Indicator of Economic Sentiment as information input and compare our results with Germany's leading stock market index, the DAX, in order to calibrate some of the model parameters. We study the conditions for the ensemble of agents to more accurately follow the information input signal. The response of the system to the external information is maximal for an intermediate range of values of a market parameter, suggesting the existence of three different market regimes: amplification, precise assimilation and undervaluation of incoming information.

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

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...

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.

Study of market model describing the contrary behaviors of informed and uninformed agents: Being minority and being majority

NASA Astrophysics Data System (ADS)

Zhang, Yu-Xia; Liao, Hao; Medo, Matus; Shang, Ming-Sheng; Yeung, Chi Ho

2016-05-01

In this paper we analyze the contrary behaviors of the informed investors and uniformed investors, and then construct a competition model with two groups of agents, namely agents who intend to stay in minority and those who intend to stay in majority. We find two kinds of competitions, inter- and intra-groups. The model shows periodic fluctuation feature. The average distribution of strategies illustrates a prominent central peak which is relevant to the peak-fat-tail character of price change distribution in stock markets. Furthermore, in the modified model the tolerance time parameter makes the agents diversified. Finally, we compare the strategies distribution with the price change distribution in real stock market, and we conclude that contrary behavior rules and tolerance time parameter are indeed valid in the description of market model.

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.…

Physics and financial economics (1776-2014): puzzles, Ising and agent-based models.

PubMed

Sornette, Didier

2014-06-01

This short review presents a selected history of the mutual fertilization between physics and economics--from Isaac Newton and Adam Smith to the present. The fundamentally different perspectives embraced in theories developed in financial economics compared with physics are dissected with the examples of the volatility smile and of the excess volatility puzzle. The role of the Ising model of phase transitions to model social and financial systems is reviewed, with the concepts of random utilities and the logit model as the analog of the Boltzmann factor in statistical physics. Recent extensions in terms of quantum decision theory are also covered. A wealth of models are discussed briefly that build on the Ising model and generalize it to account for the many stylized facts of financial markets. A summary of the relevance of the Ising model and its extensions is provided to account for financial bubbles and crashes. The review would be incomplete if it did not cover the dynamical field of agent-based models (ABMs), also known as computational economic models, of which the Ising-type models are just special ABM implementations. We formulate the 'Emerging Intelligence Market Hypothesis' to reconcile the pervasive presence of 'noise traders' with the near efficiency of financial markets. Finally, we note that evolutionary biology, more than physics, is now playing a growing role to inspire models of financial markets.

Physics and financial economics (1776-2014): puzzles, Ising and agent-based models

NASA Astrophysics Data System (ADS)

Sornette, Didier

2014-06-01

This short review presents a selected history of the mutual fertilization between physics and economics—from Isaac Newton and Adam Smith to the present. The fundamentally different perspectives embraced in theories developed in financial economics compared with physics are dissected with the examples of the volatility smile and of the excess volatility puzzle. The role of the Ising model of phase transitions to model social and financial systems is reviewed, with the concepts of random utilities and the logit model as the analog of the Boltzmann factor in statistical physics. Recent extensions in terms of quantum decision theory are also covered. A wealth of models are discussed briefly that build on the Ising model and generalize it to account for the many stylized facts of financial markets. A summary of the relevance of the Ising model and its extensions is provided to account for financial bubbles and crashes. The review would be incomplete if it did not cover the dynamical field of agent-based models (ABMs), also known as computational economic models, of which the Ising-type models are just special ABM implementations. We formulate the ‘Emerging Intelligence Market Hypothesis’ to reconcile the pervasive presence of ‘noise traders’ with the near efficiency of financial markets. Finally, we note that evolutionary biology, more than physics, is now playing a growing role to inspire models of financial markets.

A Dealer Model of Foreign Exchange Market with Finite Assets

NASA Astrophysics Data System (ADS)

Hamano, Tomoya; Kanazawa, Kiyoshi; Takayasu, Hideki; Takayasu, Misako

An agent-based model is introduced to study the finite-asset effect in foreign exchange markets. We find that the transacted price asymptotically approaches an equilibrium price, which is determined by the monetary balance between the pair of currencies. We phenomenologically derive a formula to estimate the equilibrium price, and we model its relaxation dynamics around the equilibrium price on the basis of a Langevin-like equation.

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.

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.

Multi-Agent Task Negotiation Among UAVs to Defend Against Swarm Attacks

DTIC Science & Technology

2012-03-01

are based on economic models [39]. Auction methods of task coordination also attempt to deal with agents dealing with noisy, dynamic environments...August 2006. [34] M. Alighanbari, “ Robust and decentralized task assignment algorithms for uavs,” Ph.D. dissertation, Massachusetts Institute of Technology...Implicit Coordination . . . . . . . . . . . . . 12 2.4 Decentralized Algorithm B - Market- Based . . . . . . . . . . . . . . . . 12 2.5 Decentralized

Market-Based Coordination and Auditing Mechanisms for Self-Interested Multi-Robot Systems

ERIC Educational Resources Information Center

Ham, MyungJoo

2009-01-01

We propose market-based coordinated task allocation mechanisms, which allocate complex tasks that require synchronized and collaborated services of multiple robot agents to robot agents, and an auditing mechanism, which ensures proper behaviors of robot agents by verifying inter-agent activities, for self-interested, fully-distributed, and…

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.

Real payoffs and virtual trading in agent based market models

NASA Astrophysics Data System (ADS)

Ferreira, Fernando F.; Marsili, Matteo

2005-01-01

The -Game was recently introduced as an extension of the Minority Game. In this paper we compare this model with the well know Minority Game and the Majority Game models. Due to the inter-temporal nature of the market payoff, we introduce a two step transaction with single and mixed group of interacting traders. When the population is composed of two different group of -traders, they show an anti-imitative behavior. However, when they interact with minority or majority players the $-population imitates the usual behavior of these players. Finally we discuss how these models contribute to clarify the market mechanism.

Financial physics

NASA Astrophysics Data System (ADS)

Feigenbaum, James

2003-10-01

In this introduction to the burgeoning field of econophysics, we review the application of self-organized criticality to economics, the Cont-Bouchaud percolation model, multiple-strategy agent-based models of financial markets, the minority game, and log-periodic precursors to financial crashes.

Evolution and anti-evolution in a minimal stock market model

NASA Astrophysics Data System (ADS)

Rothenstein, R.; Pawelzik, K.

2003-08-01

We present a novel microscopic stock market model consisting of a large number of random agents modeling traders in a market. Each agent is characterized by a set of parameters that serve to make iterated predictions of two successive returns. The future price is determined according to the offer and the demand of all agents. The system evolves by redistributing the capital among the agents in each trading cycle. Without noise the dynamics of this system is nearly regular and thereby fails to reproduce the stochastic return fluctuations observed in real markets. However, when in each cycle a small amount of noise is introduced we find the typical features of real financial time series like fat-tails of the return distribution and large temporal correlations in the volatility without significant correlations in the price returns. Introducing the noise by an evolutionary process leads to different scalings of the return distributions that depend on the definition of fitness. Because our realistic model has only very few parameters, and the results appear to be robust with respect to the noise level and the number of agents we expect that our framework may serve as new paradigm for modeling self-generated return fluctuations in markets.

A self-organising model of market with single commodity

NASA Astrophysics Data System (ADS)

Chakraborti, Anirban; Pradhan, Srutarshi; Chakrabarti, Bikas K.

2001-08-01

We have studied here the self-organising features of the dynamics of a model market, where the agents ‘trade’ for a single commodity with their money. The model market consists of fixed numbers of economic agents, money supply and commodity. We demonstrate that the model, apart from showing a self-organising behaviour, indicates a crucial role for the money supply in the market and also its self-organising behaviour is seen to be significantly affected when the money supply becomes less than the optimum. We also observed that this optimal money supply level of the market depends on the amount of ‘frustration’ or scarcity in the commodity market.

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.

Multi-agent electricity market modeling with EMCAS.

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

North, M.; Macal, C.; Conzelmann, G.

2002-09-05

Electricity systems are a central component of modern economies. Many electricity markets are transitioning from centrally regulated systems to decentralized markets. Furthermore, several electricity markets that have recently undergone this transition have exhibited extremely unsatisfactory results, most notably in California. These high stakes transformations require the introduction of largely untested regulatory structures. Suitable tools that can be used to test these regulatory structures before they are applied to real systems are required. Multi-agent models can provide such tools. To better understand the requirements such as tool, a live electricity market simulation was created. This experience helped to shape the developmentmore » of the multi-agent Electricity Market Complex Adaptive Systems (EMCAS) model. To explore EMCAS' potential, several variations of the live simulation were created. These variations probed the possible effects of changing power plant outages and price setting rules on electricity market prices.« less

Effects of competition and cooperation interaction between agents on networks in the presence of a market capacity

NASA Astrophysics Data System (ADS)

Sonubi, A.; Arcagni, A.; Stefani, S.; Ausloos, M.

2016-08-01

A network effect is introduced taking into account competition, cooperation, and mixed-type interaction among agents along a generalized Verhulst-Lotka-Volterra model. It is also argued that the presence of a market capacity undoubtedly enforces a definite limit on the agent's size growth. The state stability of triadic agents, i.e., the most basic network plaquette, is investigated analytically for possible scenarios, through a fixed-point analysis. It is discovered that: (i) market demand is only satisfied for full competition when one agent monopolizes the market; (ii) growth of agent size is encouraged in full cooperation; (iii) collaboration among agents to compete against one single agent may result in the disappearance of this single agent out of the market; and (iv) cooperating with two rivals may become a growth strategy for an intelligent agent.

Effects of competition and cooperation interaction between agents on networks in the presence of a market capacity.

PubMed

Sonubi, A; Arcagni, A; Stefani, S; Ausloos, M

2016-08-01

A network effect is introduced taking into account competition, cooperation, and mixed-type interaction among agents along a generalized Verhulst-Lotka-Volterra model. It is also argued that the presence of a market capacity undoubtedly enforces a definite limit on the agent's size growth. The state stability of triadic agents, i.e., the most basic network plaquette, is investigated analytically for possible scenarios, through a fixed-point analysis. It is discovered that: (i) market demand is only satisfied for full competition when one agent monopolizes the market; (ii) growth of agent size is encouraged in full cooperation; (iii) collaboration among agents to compete against one single agent may result in the disappearance of this single agent out of the market; and (iv) cooperating with two rivals may become a growth strategy for an intelligent agent.

Modelling financial markets with agents competing on different time scales and with different amount of information

NASA Astrophysics Data System (ADS)

Wohlmuth, Johannes; Andersen, Jørgen Vitting

2006-05-01

We use agent-based models to study the competition among investors who use trading strategies with different amount of information and with different time scales. We find that mixing agents that trade on the same time scale but with different amount of information has a stabilizing impact on the large and extreme fluctuations of the market. Traders with the most information are found to be more likely to arbitrage traders who use less information in the decision making. On the other hand, introducing investors who act on two different time scales has a destabilizing effect on the large and extreme price movements, increasing the volatility of the market. Closeness in time scale used in the decision making is found to facilitate the creation of local trends. The larger the overlap in commonly shared information the more the traders in a mixed system with different time scales are found to profit from the presence of traders acting at another time scale than themselves.

Agent-based approach for generation of a money-centered star network

NASA Astrophysics Data System (ADS)

Yang, Jae-Suk; Kwon, Okyu; Jung, Woo-Sung; Kim, In-mook

2008-09-01

The history of trade is a progression from a pure barter system. A medium of exchange emerges autonomously in the market, a position currently occupied by money. We investigate an agent-based computational economics model consisting of interacting agents considering distinguishable properties of commodities which represent salability. We also analyze the properties of the commodity network using a spanning tree. We find that the “storage fee” is more crucial than “demand” in determining which commodity is used as a medium of exchange.

Speculative and Hedging Interaction Model in Oil and U.S. Dollar Markets—Phase Transition

NASA Astrophysics Data System (ADS)

Campbell, Michael; Carfì, David

2018-01-01

We show that there is a phase transition in the bounded rational Carfì-Musolino model, and the possibility of a market crash. This model has two types of operators: a real economic subject (Air) and one or more investment banks (Bank). It also has two markets: oil spot market and US dollar futures. Bank agents react to Air and equilibrate much more quickly than Air. Thus Air is an acting external agent due to its longer-term investing, whereas the action of the banks equilibrates before Air makes its next transaction. This model constitutes a potential game, and agents crowd their preferences into one of the markets at a critical temperature when air makes no purchases of oil futures.

Assortative Mating and the Reversal of Gender Inequality in Education in Europe: An Agent-Based Model

PubMed Central

Grow, André; Van Bavel, Jan

2015-01-01

While men have always received more education than women in the past, this gender imbalance in education has turned around in large parts of the world. In many countries, women now excel men in terms of participation and success in higher education. This implies that, for the first time in history, there are more highly educated women than men reaching the reproductive ages and looking for a partner. We develop an agent-based computational model that explicates the mechanisms that may have linked the reversal of gender inequality in education with observed changes in educational assortative mating. Our model builds on the notion that individuals search for spouses in a marriage market and evaluate potential candidates based on preferences. Based on insights from earlier research, we assume that men and women prefer partners with similar educational attainment and high earnings prospects, that women tend to prefer men who are somewhat older than themselves, and that men prefer women who are in their mid-twenties. We also incorporate the insight that the educational system structures meeting opportunities on the marriage market. We assess the explanatory power of our model with systematic computational experiments, in which we simulate marriage market dynamics in 12 European countries among individuals born between 1921 and 2012. In these experiments, we make use of realistic agent populations in terms of educational attainment and earnings prospects and validate model outcomes with data from the European Social Survey. We demonstrate that the observed changes in educational assortative mating can be explained without any change in male or female preferences. We argue that our model provides a useful computational laboratory to explore and quantify the implications of scenarios for the future. PMID:26039151

Assortative mating and the reversal of gender inequality in education in europe: an agent-based model.

PubMed

Grow, André; Van Bavel, Jan

2015-01-01

While men have always received more education than women in the past, this gender imbalance in education has turned around in large parts of the world. In many countries, women now excel men in terms of participation and success in higher education. This implies that, for the first time in history, there are more highly educated women than men reaching the reproductive ages and looking for a partner. We develop an agent-based computational model that explicates the mechanisms that may have linked the reversal of gender inequality in education with observed changes in educational assortative mating. Our model builds on the notion that individuals search for spouses in a marriage market and evaluate potential candidates based on preferences. Based on insights from earlier research, we assume that men and women prefer partners with similar educational attainment and high earnings prospects, that women tend to prefer men who are somewhat older than themselves, and that men prefer women who are in their mid-twenties. We also incorporate the insight that the educational system structures meeting opportunities on the marriage market. We assess the explanatory power of our model with systematic computational experiments, in which we simulate marriage market dynamics in 12 European countries among individuals born between 1921 and 2012. In these experiments, we make use of realistic agent populations in terms of educational attainment and earnings prospects and validate model outcomes with data from the European Social Survey. We demonstrate that the observed changes in educational assortative mating can be explained without any change in male or female preferences. We argue that our model provides a useful computational laboratory to explore and quantify the implications of scenarios for the future.

Electric power market agent design

NASA Astrophysics Data System (ADS)

Oh, Hyungseon

The electric power industry in many countries has been restructured in the hope of a more economically efficient system. In the restructured system, traditional operating and planning tools based on true marginal cost do not perform well since information required is strictly confidential. For developing a new tool, it is necessary to understand offer behavior. The main objective of this study is to create a new tool for power system planning. For the purpose, this dissertation develops models for a market and market participants. A new model is developed in this work for explaining a supply-side offer curve, and several variables are introduced to characterize the curve. Demand is estimated using a neural network, and a numerical optimization process is used to determine the values of the variables that maximize the profit of the agent. The amount of data required for the optimization is chosen with the aid of nonlinear dynamics. To suggest an optimal demand-side bidding function, two optimization problems are constructed and solved for maximizing consumer satisfaction based on the properties of two different types of demands: price-based demand and must-be-served demand. Several different simulations are performed to test how an agent reacts in various situations. The offer behavior depends on locational benefit as well as the offer strategies of competitors.

Markets, Herding and Response to External Information

PubMed Central

Carro, Adrián; Toral, Raúl; San Miguel, Maxi

2015-01-01

We focus on the influence of external sources of information upon financial markets. In particular, we develop a stochastic agent-based market model characterized by a certain herding behavior as well as allowing traders to be influenced by an external dynamic signal of information. This signal can be interpreted as a time-varying advertising, public perception or rumor, in favor or against one of two possible trading behaviors, thus breaking the symmetry of the system and acting as a continuously varying exogenous shock. As an illustration, we use a well-known German Indicator of Economic Sentiment as information input and compare our results with Germany’s leading stock market index, the DAX, in order to calibrate some of the model parameters. We study the conditions for the ensemble of agents to more accurately follow the information input signal. The response of the system to the external information is maximal for an intermediate range of values of a market parameter, suggesting the existence of three different market regimes: amplification, precise assimilation and undervaluation of incoming information. PMID:26204451

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

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.

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.

An agent-based approach to financial stylized facts

NASA Astrophysics Data System (ADS)

Shimokawa, Tetsuya; Suzuki, Kyoko; Misawa, Tadanobu

2007-06-01

An important challenge of the financial theory in recent years is to construct more sophisticated models which have consistencies with as many financial stylized facts that cannot be explained by traditional models. Recently, psychological studies on decision making under uncertainty which originate in Kahneman and Tversky's research attract a lot of interest as key factors which figure out the financial stylized facts. These psychological results have been applied to the theory of investor's decision making and financial equilibrium modeling. This paper, following these behavioral financial studies, would like to propose an agent-based equilibrium model with prospect theoretical features of investors. Our goal is to point out a possibility that loss-averse feature of investors explains vast number of financial stylized facts and plays a crucial role in price formations of financial markets. Price process which is endogenously generated through our model has consistencies with, not only the equity premium puzzle and the volatility puzzle, but great kurtosis, asymmetry of return distribution, auto-correlation of return volatility, cross-correlation between return volatility and trading volume. Moreover, by using agent-based simulations, the paper also provides a rigorous explanation from the viewpoint of a lack of market liquidity to the size effect, which means that small-sized stocks enjoy excess returns compared to large-sized stocks.

Agents Play Mix-game

NASA Astrophysics Data System (ADS)

Gou, Chengling

In recent years, economics and finance see the shift of paradigm from representative agent models to heterogeneous agent models [1, 2]. More and more economists and physicists made efforts in research on heterogeneous agent models for financial markets. Minority game (MG) proposed by D. Challet, and Y. C. Zhang [3] is an example among such efforts. Challet and Zhang's MG model, together with the original bar model of Arthur, attracts a lot of following studies [4-6]. Given MG's richness and yet underlying simplicity, MG has also received much attention as a financial market model [4]. MG comprises an odd number of agents choosing repeatedly between the options of buying (1) and selling (0) a quantity of a risky asset. The agents continually try to make the minority decision, i.e. buy assets when the majority of other agents are selling, and sell when the majority of other agents are buying. Neil F. Johnson [4, 5] and coworkers extended MG by allowing a variable number of active traders at each timestep— they called their modified game as the Grand Canonical Minority Game (GCMG). GCMG, and to a lesser extent the basic MG itself, can reproduce the stylized facts of financial markets, such as volatility clustering and fat-tail distributions.

Nonlinear complexity behaviors of agent-based 3D Potts financial dynamics with random environments

NASA Astrophysics Data System (ADS)

Xing, Yani; Wang, Jun

2018-02-01

A new microscopic 3D Potts interaction financial price model is established in this work, to investigate the nonlinear complexity behaviors of stock markets. 3D Potts model, which extends the 2D Potts model to three-dimensional, is a cubic lattice model to explain the interaction behavior among the agents. In order to explore the complexity of real financial markets and the 3D Potts financial model, a new random coarse-grained Lempel-Ziv complexity is proposed to certain series, such as the price returns, the price volatilities, and the random time d-returns. Then the composite multiscale entropy (CMSE) method is applied to the intrinsic mode functions (IMFs) and the corresponding shuffled data to study the complexity behaviors. The empirical results indicate that the 3D financial model is feasible.

Market behavior and performance of different strategy evaluation schemes

NASA Astrophysics Data System (ADS)

Baek, Yongjoo; Lee, Sang Hoon; Jeong, Hawoong

2010-08-01

Strategy evaluation schemes are a crucial factor in any agent-based market model, as they determine the agents’ strategy preferences and consequently their behavioral pattern. This study investigates how the strategy evaluation schemes adopted by agents affect their performance in conjunction with the market circumstances. We observe the performance of three strategy evaluation schemes, the history-dependent wealth game, the trend-opposing minority game, and the trend-following majority game, in a stock market where the price is exogenously determined. The price is either directly adopted from the real stock market indices or generated with a Markov chain of order ≤2 . Each scheme’s success is quantified by average wealth accumulated by the traders equipped with the scheme. The wealth game, as it learns from the history, shows relatively good performance unless the market is highly unpredictable. The majority game is successful in a trendy market dominated by long periods of sustained price increase or decrease. On the other hand, the minority game is suitable for a market with persistent zigzag price patterns. We also discuss the consequence of implementing finite memory in the scoring processes of strategies. Our findings suggest under which market circumstances each evaluation scheme is appropriate for modeling the behavior of real market traders.

Policy design and performance of emissions trading markets: an adaptive agent-based analysis.

PubMed

Bing, Zhang; Qinqin, Yu; Jun, Bi

2010-08-01

Emissions trading is considered to be a cost-effective environmental economic instrument for pollution control. However, the pilot emissions trading programs in China have failed to bring remarkable success in the campaign for pollution control. The policy design of an emissions trading program is found to have a decisive impact on its performance. In this study, an artificial market for sulfur dioxide (SO2) emissions trading applying the agent-based model was constructed. The performance of the Jiangsu SO2 emissions trading market under different policy design scenario was also examined. Results show that the market efficiency of emissions trading is significantly affected by policy design and existing policies. China's coal-electricity price system is the principal factor influencing the performance of the SO2 emissions trading market. Transaction costs would also reduce market efficiency. In addition, current-level emissions discharge fee/tax and banking mechanisms do not distinctly affect policy performance. Thus, applying emissions trading in emission control in China should consider policy design and interaction with other existing policies.

How market structure drives commodity prices

NASA Astrophysics Data System (ADS)

Li, Bin; Wong, K. Y. Michael; Chan, Amos H. M.; So, Tsz Yan; Heimonen, Hermanni; Wei, Junyi; Saad, David

2017-11-01

We introduce an agent-based model, in which agents set their prices to maximize profit. At steady state the market self-organizes into three groups: excess producers, consumers and balanced agents, with prices determined by their own resource level and a couple of macroscopic parameters that emerge naturally from the analysis, akin to mean-field parameters in statistical mechanics. When resources are scarce prices rise sharply below a turning point that marks the disappearance of excess producers. To compare the model with real empirical data, we study the relationship between commodity prices and stock-to-use ratios in a range of commodities such as agricultural products and metals. By introducing an elasticity parameter to mitigate noise and long-term changes in commodities data, we confirm the trend of rising prices, provide evidence for turning points, and indicate yield points for less essential commodities.

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.

Prediction of stock markets by the evolutionary mix-game model

NASA Astrophysics Data System (ADS)

Chen, Fang; Gou, Chengling; Guo, Xiaoqian; Gao, Jieping

2008-06-01

This paper presents the efforts of using the evolutionary mix-game model, which is a modified form of the agent-based mix-game model, to predict financial time series. Here, we have carried out three methods to improve the original mix-game model by adding the abilities of strategy evolution to agents, and then applying the new model referred to as the evolutionary mix-game model to forecast the Shanghai Stock Exchange Composite Index. The results show that these modifications can improve the accuracy of prediction greatly when proper parameters are chosen.

Dendritic growth model of multilevel marketing

NASA Astrophysics Data System (ADS)

Pang, James Christopher S.; Monterola, Christopher P.

2017-02-01

Biologically inspired dendritic network growth is utilized to model the evolving connections of a multilevel marketing (MLM) enterprise. Starting from agents at random spatial locations, a network is formed by minimizing a distance cost function controlled by a parameter, termed the balancing factor bf, that weighs the wiring and the path length costs of connection. The paradigm is compared to an actual MLM membership data and is shown to be successful in statistically capturing the membership distribution, better than the previously reported agent based preferential attachment or analytic branching process models. Moreover, it recovers the known empirical statistics of previously studied MLM, specifically: (i) a membership distribution characterized by the existence of peak levels indicating limited growth, and (ii) an income distribution obeying the 80 - 20 Pareto principle. Extensive types of income distributions from uniform to Pareto to a "winner-take-all" kind are also modeled by varying bf. Finally, the robustness of our dendritic growth paradigm to random agent removals is explored and its implications to MLM income distributions are discussed.

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 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.

Intelligent agents for adaptive security market surveillance

NASA Astrophysics Data System (ADS)

Chen, Kun; Li, Xin; Xu, Baoxun; Yan, Jiaqi; Wang, Huaiqing

2017-05-01

Market surveillance systems have increasingly gained in usage for monitoring trading activities in stock markets to maintain market integrity. Existing systems primarily focus on the numerical analysis of market activity data and generally ignore textual information. To fulfil the requirements of information-based surveillance, a multi-agent-based architecture that uses agent intercommunication and incremental learning mechanisms is proposed to provide a flexible and adaptive inspection process. A prototype system is implemented using the techniques of text mining and rule-based reasoning, among others. Based on experiments in the scalping surveillance scenario, the system can identify target information evidence up to 87.50% of the time and automatically identify 70.59% of cases depending on the constraints on the available information sources. The results of this study indicate that the proposed information surveillance system is effective. This study thus contributes to the market surveillance literature and has significant practical implications.

Poisson-process generalization for the trading waiting-time distribution in a double-auction mechanism

NASA Astrophysics Data System (ADS)

Cincotti, Silvano; Ponta, Linda; Raberto, Marco; Scalas, Enrico

2005-05-01

In this paper, empirical analyses and computational experiments are presented on high-frequency data for a double-auction (book) market. Main objective of the paper is to generalize the order waiting time process in order to properly model such empirical evidences. The empirical study is performed on the best bid and best ask data of 7 U.S. financial markets, for 30-stock time series. In particular, statistical properties of trading waiting times have been analyzed and quality of fits is evaluated by suitable statistical tests, i.e., comparing empirical distributions with theoretical models. Starting from the statistical studies on real data, attention has been focused on the reproducibility of such results in an artificial market. The computational experiments have been performed within the Genoa Artificial Stock Market. In the market model, heterogeneous agents trade one risky asset in exchange for cash. Agents have zero intelligence and issue random limit or market orders depending on their budget constraints. The price is cleared by means of a limit order book. The order generation is modelled with a renewal process. Based on empirical trading estimation, the distribution of waiting times between two consecutive orders is modelled by a mixture of exponential processes. Results show that the empirical waiting-time distribution can be considered as a generalization of a Poisson process. Moreover, the renewal process can approximate real data and implementation on the artificial stocks market can reproduce the trading activity in a realistic way.

Information of Complex Systems and Applications in Agent Based Modeling.

PubMed

Bao, Lei; Fritchman, Joseph C

2018-04-18

Information about a system's internal interactions is important to modeling the system's dynamics. This study examines the finer categories of the information definition and explores the features of a type of local information that describes the internal interactions of a system. Based on the results, a dual-space agent and information modeling framework (AIM) is developed by explicitly distinguishing an information space from the material space. The two spaces can evolve both independently and interactively. The dual-space framework can provide new analytic methods for agent based models (ABMs). Three examples are presented including money distribution, individual's economic evolution, and artificial stock market. The results are analyzed in the dual-space, which more clearly shows the interactions and evolutions within and between the information and material spaces. The outcomes demonstrate the wide-ranging applicability of using the dual-space AIMs to model and analyze a broad range of interactive and intelligent systems.

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.

Fashion, novelty and optimality: an application from Physics

NASA Astrophysics Data System (ADS)

Galam, Serge; Vignes, Annick

2005-06-01

We apply a physical-based model to describe the clothes fashion market. Every time a new outlet appears on the market, it can invade the market under certain specific conditions. Hence, the “old” outlet can be completely dominated and disappears. Each creator competes for a finite population of agents. Fashion phenomena are shown to result from a collective phenomenon produced by local individual imitation effects. We assume that, in each step of the imitation process, agents only interact with a subset rather than with the whole set of agents. People are actually more likely to influence (and be influenced by) their close “neighbors”. Accordingly, we discuss which strategy is best fitted for new producers when people are either simply organized into anonymous reference groups or when they are organized in social groups hierarchically ordered. While counterfeits are shown to reinforce the first strategy, creating social leaders can permit to avoid them.

Integrating adaptive behaviour in large-scale flood risk assessments: an Agent-Based Modelling approach

NASA Astrophysics Data System (ADS)

Haer, Toon; Aerts, Jeroen

2015-04-01

Between 1998 and 2009, Europe suffered over 213 major damaging floods, causing 1126 deaths, displacing around half a million people. In this period, floods caused at least 52 billion euro in insured economic losses making floods the most costly natural hazard faced in Europe. In many low-lying areas, the main strategy to cope with floods is to reduce the risk of the hazard through flood defence structures, like dikes and levees. However, it is suggested that part of the responsibility for flood protection needs to shift to households and businesses in areas at risk, and that governments and insurers can effectively stimulate the implementation of individual protective measures. However, adaptive behaviour towards flood risk reduction and the interaction between the government, insurers, and individuals has hardly been studied in large-scale flood risk assessments. In this study, an European Agent-Based Model is developed including agent representatives for the administrative stakeholders of European Member states, insurers and reinsurers markets, and individuals following complex behaviour models. The Agent-Based Modelling approach allows for an in-depth analysis of the interaction between heterogeneous autonomous agents and the resulting (non-)adaptive behaviour. Existing flood damage models are part of the European Agent-Based Model to allow for a dynamic response of both the agents and the environment to changing flood risk and protective efforts. By following an Agent-Based Modelling approach this study is a first contribution to overcome the limitations of traditional large-scale flood risk models in which the influence of individual adaptive behaviour towards flood risk reduction is often lacking.

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.

A Watershed-Scale Agent-Based Model Incorporating Agent Learning and Interaction of Farmers' Decisions Subject to Carbon and Miscanthus Prices

NASA Astrophysics Data System (ADS)

Ng, T.; Eheart, J.; Cai, X.; Braden, J. B.

2010-12-01

Agricultural watersheds are coupled human-natural systems where the land use decisions of human agents (farmers) affect surface water quality, and in turn, are affected by the weather and yields. The reliable modeling of such systems requires an approach that considers both the human and natural aspects. Agent-based modeling (ABM), representing the human aspect, coupled with hydrologic modeling, representing the natural aspect, is one such approach. ABM is a relatively new modeling paradigm that formulates the system from the perspectives of the individual agents, i.e., each agent is modeled as a discrete autonomous entity with distinct goals and actions. The primary objective of this study is to demonstrate the applicability of this approach to agricultural watershed management. This is done using a semi-hypothetical case study of farmers in the Salt Creek watershed in East-Central Illinois under the influence markets for carbon and second-generation bioenergy crop (specifically, miscanthus). An agent-based model of the system is developed and linked to a hydrologic model of the watershed. The former is based on fundamental economic and mathematical programming principles, while the latter is based on the Soil and Water Assessment Tool (SWAT). Carbon and second-generation bioenergy crop markets are of interest here due to climate change and energy independence concerns. The agent-based model is applied to fifty hypothetical heterogeneous farmers. The farmers' decisions depend on their perceptions of future conditions. Those perceptions are updated, according to a pre-defined algorithm, as the farmers make new observations of prices, costs, yields and the weather with time. The perceptions are also updated as the farmers interact with each other as they share new information on initially unfamiliar activities (e.g., carbon trading, miscanthus cultivation). The updating algorithm is set differently for different farmers such that each is unique in his processing of new information. The results provide insights on how differences in the way farmers learn and adapt affect their forecasts of the future, and hence, decisions. Farmers who are interacting, less risk averse, quick to adjust their expectations with new observations, and slow to reduce their forecast confidence when there are unexpected changes are more likely to practice conservation tillage (farmers may claim carbon credits for sale when practicing conservation tillage), and switch from conventional crops to miscanthus. The results, though empirically untested, appear plausible and consistent with general behavior by farmers. All this demonstrates the ability and potential of ABM to capture, at least partially, the complexities of human decision-making.

From a market of dreamers to economical shocks

NASA Astrophysics Data System (ADS)

Owhadi, Houman

2004-11-01

Over the past years an intense work has been undertaken to understand the origin of the crashes and bubbles of financial markets. The explanations of these crashes have been grounded on the hypothesis of behavioral and social correlations between the agents in interacting particle models or on a feedback of the stock prices on trading behaviors in mean-field models (here bubbles and crashes are seen as collective hysteria). In this paper, we will introduce a market model as a particle system with no other interaction between the agents than the fact that to be able to sell, somebody must be willing to buy and no feedback of the price on their trading behavior. We will show that this model crashes in finite estimable time. Although the age of the market does not appear in the price dynamic the population of traders taken as a whole system is maturing towards collapse. The wealth distribution among the agents follows the second law of thermodynamics and with probability one an agent (or a minority of agents) will accumulate a large portion of the total wealth, at some point this disproportion in the wealth distribution becomes unbearable for the market leading to its collapse. We believe that the origin of the collapse in our model could be of some relevance in understanding long-term economic cycles such as the Kondratiev cycle.

Exact solution of a modified El Farol's bar problem: Efficiency and the role of market impact

NASA Astrophysics Data System (ADS)

Marsili, Matteo; Challet, Damien; Zecchina, Riccardo

2000-06-01

We discuss a model of heterogeneous, inductive rational agents inspired by the El Farol Bar problem and the Minority Game. As in markets, agents interact through a collective aggregate variable - which plays a role similar to price - whose value is fixed by all of them. Agents follow a simple reinforcement-learning dynamics where the reinforcement, for each of their available strategies, is related to the payoff delivered by that strategy. We derive the exact solution of the model in the “thermodynamic” limit of infinitely many agents using tools of statistical physics of disordered systems. Our results show that the impact of agents on the market price plays a key role: even though price has a weak dependence on the behavior of each individual agent, the collective behavior crucially depends on whether agents account for such dependence or not. Remarkably, if the adaptive behavior of agents accounts even “infinitesimally” for this dependence they can, in a whole range of parameters, reduce global fluctuations by a finite amount. Both global efficiency and individual utility improve with respect to a “price taker” behavior if agents account for their market impact.

Modelling of robotic work cells using agent based-approach

NASA Astrophysics Data System (ADS)

Sękala, A.; Banaś, W.; Gwiazda, A.; Monica, Z.; Kost, G.; Hryniewicz, P.

2016-08-01

In the case of modern manufacturing systems the requirements, both according the scope and according characteristics of technical procedures are dynamically changing. This results in production system organization inability to keep up with changes in a market demand. Accordingly, there is a need for new design methods, characterized, on the one hand with a high efficiency and on the other with the adequate level of the generated organizational solutions. One of the tools that could be used for this purpose is the concept of agent systems. These systems are the tools of artificial intelligence. They allow assigning to agents the proper domains of procedures and knowledge so that they represent in a self-organizing system of an agent environment, components of a real system. The agent-based system for modelling robotic work cell should be designed taking into consideration many limitations considered with the characteristic of this production unit. It is possible to distinguish some grouped of structural components that constitute such a system. This confirms the structural complexity of a work cell as a specific production system. So it is necessary to develop agents depicting various aspects of the work cell structure. The main groups of agents that are used to model a robotic work cell should at least include next pattern representatives: machine tool agents, auxiliary equipment agents, robots agents, transport equipment agents, organizational agents as well as data and knowledge bases agents. In this way it is possible to create the holarchy of the agent-based system.

Towards Automated Bargaining in Electronic Markets: A Partially Two-Sided Competition Model

NASA Astrophysics Data System (ADS)

Gatti, Nicola; Lazaric, Alessandro; Restelli, Marcello

This paper focuses on the prominent issue of automating bargaining agents within electronic markets. Models of bargaining in literature deal with settings wherein there are only two agents and no model satisfactorily captures settings in which there is competition among buyers, being they more than one, and analogously among sellers. In this paper, we extend the principal bargaining protocol, i.e. the alternating-offers protocol, to capture bargaining in markets. The model we propose is such that, in presence of a unique buyer and a unique seller, agents' equilibrium strategies are those in the original protocol. Moreover, we game theoretically study the considered game providing the following results: in presence of one-sided competition (more buyers and one seller or vice versa) we provide agents' equilibrium strategies for all the values of the parameters, in presence of two-sided competition (more buyers and more sellers) we provide an algorithm that produce agents' equilibrium strategies for a large set of the parameters and we experimentally evaluate its effectiveness.

Modelling and measuring the irrational behaviour of agents in financial markets: Discovering the psychological soliton

NASA Astrophysics Data System (ADS)

Dhesi, Gurjeet; Ausloos, Marcel

2016-07-01

Following a Geometrical Brownian Motion extension into an Irrational Fractional Brownian Motion model, we re-examine agent behaviour reacting to time dependent news on the log-returns thereby modifying a financial market evolution. We specifically discuss the role of financial news or economic information positive or negative feedback of such irrational (or contrarian) agents upon the price evolution. We observe a kink-like effect reminiscent of soliton behaviour, suggesting how analysts' forecasts errors induce stock prices to adjust accordingly, thereby proposing a measure of the irrational force in a market.

A dynamic network model for interbank market

NASA Astrophysics Data System (ADS)

Xu, Tao; He, Jianmin; Li, Shouwei

2016-12-01

In this paper, a dynamic network model based on agent behavior is introduced to explain the formation mechanism of interbank market network. We investigate the impact of credit lending preference on interbank market network topology, the evolution of interbank market network and stability of interbank market. Experimental results demonstrate that interbank market network is a small-world network and cumulative degree follows the power-law distribution. We find that the interbank network structure keeps dynamic stability in the network evolution process. With the increase of bank credit lending preference, network clustering coefficient increases and average shortest path length decreases monotonously, which improves the stability of the network structure. External shocks are main threats for the interbank market and the reduction of bank external investment yield rate and deposits fluctuations contribute to improve the resilience of the banking system.

A consensus-based dynamics for market volumes

NASA Astrophysics Data System (ADS)

Sabatelli, Lorenzo; Richmond, Peter

2004-12-01

We develop a model of trading orders based on opinion dynamics. The agents may be thought as the share holders of a major mutual fund rather than as direct traders. The balance between their buy and sell orders determines the size of the fund order (volume) and has an impact on prices and indexes. We assume agents interact simultaneously to each other through a Sznajd-like interaction. Their degree of connection is determined by the probability of changing opinion independently of what their neighbours are doing. We assume that such a probability may change randomly, after each transaction, of an amount proportional to the relative difference between the volatility then measured and a benchmark that we assume to be an exponential moving average of the past volume values. We show how this simple model is compatible with some of the main statistical features observed for the asset volumes in financial markets.

Multiscaling Edge Effects in an Agent-based Money Emergence Model

NASA Astrophysics Data System (ADS)

Oświęcimka, P.; Drożdż, S.; Gębarowski, R.; Górski, A. Z.; Kwapień, J.

An agent-based computational economical toy model for the emergence of money from the initial barter trading, inspired by Menger's postulate that money can spontaneously emerge in a commodity exchange economy, is extensively studied. The model considered, while manageable, is significantly complex, however. It is already able to reveal phenomena that can be interpreted as emergence and collapse of money as well as the related competition effects. In particular, it is shown that - as an extra emerging effect - the money lifetimes near the critical threshold value develop multiscaling, which allow one to set parallels to critical phenomena and, thus, to the real financial markets.

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

Economic agents and markets as emergent phenomena

PubMed Central

Tesfatsion, Leigh

2002-01-01

An overview of recent work in agent-based computational economics is provided, with a stress on the research areas highlighted in the National Academy of Sciences Sackler Colloquium session “Economic Agents and Markets as Emergent Phenomena” held in October 2001. PMID:12011395

Modeling financial markets by self-organized criticality

NASA Astrophysics Data System (ADS)

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

2015-10-01

We present a financial market model, characterized by self-organized criticality, that is able to generate endogenously a realistic price dynamics and to reproduce well-known stylized facts. We consider a community of heterogeneous traders, composed by chartists and fundamentalists, and focus on the role of informative pressure on market participants, showing how the spreading of information, based on a realistic imitative behavior, drives contagion and causes market fragility. In this model imitation is not intended as a change in the agent's group of origin, but is referred only to the price formation process. We introduce in the community also a variable number of random traders in order to study their possible beneficial role in stabilizing the market, as found in other studies. Finally, we also suggest some counterintuitive policy strategies able to dampen fluctuations by means of a partial reduction of information.

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.

Temporal asymmetries in Interbank Market: an empirically grounded Agent-Based Model

NASA Astrophysics Data System (ADS)

Zlatic, Vinko; Popovic, Marko; Abraham, Hrvoje; Caldarelli, Guido; Iori, Giulia

2014-03-01

We analyse the changes in the topology of the structure of the E-mid interbank market in the period from September 1st 1999 to September 1st 2009. We uncover a type of temporal irreversibility in the growth of the largest component of the interbank trading network, which is not common to any of the usual network growth models. Such asymmetry, which is also detected on the growth of the clustering and reciprocity coefficient, reveals that the trading mechanism is driven by different dynamics at the beginning and at the end of the day. We are able to recover the complexity of the system by means of a simple Agent Based Model in which the probability of matching between counter parties depends on a time varying vertex fitness (or attractiveness) describing banks liquidity needs. We show that temporal irreversibility is associated with heterogeneity in the banking system and emerges when the distribution of liquidity shocks across banks is broad. We acknowledge support from FET project FOC-II.

An Investment Behavior Analysis using by Brain Computer Interface

NASA Astrophysics Data System (ADS)

Suzuki, Kyoko; Kinoshita, Kanta; Miyagawa, Kazuhiro; Shiomi, Shinichi; Misawa, Tadanobu; Shimokawa, Tetsuya

In this paper, we will construct a new Brain Computer Interface (BCI), for the purpose of analyzing human's investment decision makings. The BCI is made up of three functional parts which take roles of, measuring brain information, determining market price in an artificial market, and specifying investment decision model, respectively. When subjects make decisions, their brain information is conveyed to the part of specifying investment decision model through the part of measuring brain information, whereas, their decisions of investment order are sent to the part of artificial market to form market prices. Both the support vector machine and the 3 layered perceptron are used to assess the investment decision model. In order to evaluate our BCI, we conduct an experiment in which subjects and a computer trader agent trade shares of stock in the artificial market and test how the computer trader agent can forecast market price formation and investment decision makings from the brain information of subjects. The result of the experiment shows that the brain information can improve the accuracy of forecasts, and so the computer trader agent can supply market liquidity to stabilize market volatility without his loss.

A Coupled Economic and Physical Model of Coastal Adaptation and Abandonment: Are human occupied coastlines a bubble waiting to burst?

NASA Astrophysics Data System (ADS)

McNamara, D.; Keeler, A.

2011-12-01

Policy discussions of adaptation by coastal residents to increasing rates of sea level rise and changing frequency of damaging storms have focused on community land use planning processes. This view neglects the role that market dynamics and climate change expectations play in the way coastal communities choose among risk mitigation options and manage land use decisions in an environment of escalating risks. We use a model coupling physical coastal processes with an agent-based model of behavior in real estate and mitigation markets to examine the interplay of climate-driven coastal hazards, collective mitigation decisions, and individual beliefs. The physical component model simulates barrier island processes that respond to both storms and slow scale dynamics associated with sea level rise. The economic component model is an agent-based model of economic behavior where agents are rational economic actors working off different assessments of future climate-driven events. Agents differentially update their beliefs based on a) how much emphasis they give to observed coastal changes and b) how much weight they give to scientific predictions. In essence, agents differ along a spectrum of how much they believe that the past is the best guide to the future and how quickly they react to new information. We use the coupled model to explore three questions of interest to coastal policy. First, how do the interplay of costal processes, beliefs, and mitigation choices affect the level and stability of real estate prices? Second, how does this interplay affect the incentives for community investments in shoreline protection? Third, how do expectations and reactions to observed events, as well as mitigation investments, affect the built environment in circumstances when climate risks reach very high levels? This last question relates to a key aspect of climate change adaptation on the coast - when does mitigation give way to abandonment as an optimal adaptation strategy? Results suggest that subjective expectations about climate risk and about the effectiveness of mitigation in high-risk environments are critical in determining when the market starts to reflect the possibility that property might no longer be inhabitable. Results will be presented that contrast the dynamics of abandonment over a range of sea level rise and storminess scenarios.

Biological trade and markets.

PubMed

Hammerstein, Peter; Noë, Ronald

2016-02-05

Cooperation between organisms can often be understood, like trade between merchants, as a mutually beneficial exchange of services, resources or other 'commodities'. Mutual benefits alone, however, are not sufficient to explain the evolution of trade-based cooperation. First, organisms may reject a particular trade if another partner offers a better deal. Second, while human trade often entails binding contracts, non-human trade requires unwritten 'terms of contract' that 'self-stabilize' trade and prevent cheating even if all traders strive to maximize fitness. Whenever trading partners can be chosen, market-like situations arise in nature that biologists studying cooperation need to account for. The mere possibility of exerting partner choice stabilizes many forms of otherwise cheatable trade, induces competition, facilitates the evolution of specialization and often leads to intricate forms of cooperation. We discuss selected examples to illustrate these general points and review basic conceptual approaches that are important in the theory of biological trade and markets. Comparing these approaches with theory in economics, it turns out that conventional models-often called 'Walrasian' markets-are of limited relevance to biology. In contrast, early approaches to trade and markets, as found in the works of Ricardo and Cournot, contain elements of thought that have inspired useful models in biology. For example, the concept of comparative advantage has biological applications in trade, signalling and ecological competition. We also see convergence between post-Walrasian economics and biological markets. For example, both economists and biologists are studying 'principal-agent' problems with principals offering jobs to agents without being sure that the agents will do a proper job. Finally, we show that mating markets have many peculiarities not shared with conventional economic markets. Ideas from economics are useful for biologists studying cooperation but need to be taken with caution. © 2016 The Authors.

Modeling market mechanism with the minority game

NASA Astrophysics Data System (ADS)

Challet, Damien; Marsili, Matteo; Zhang, Yi-Cheng

2000-01-01

Using the minority game model we study a broad spectrum of problems of market mechanism. We study the role of different types of agents: producers, speculators as well as noise traders. The central issue here is the information flow: producers feed in the information whereas speculators make it away. How well each agent fares in the common game depends on the market conditions, as well as their sophistication. Sometimes there is much to gain with little effort, sometimes great effort virtually brings no more incremental gain. Market impact is also shown to play an important role, a strategy should be judged when it is actually used in play for its quality. Though the minority game is an extremely simplified market model, it allows to ask, analyze and answer many questions which arise in real markets.

Emergent organization in a model market

NASA Astrophysics Data System (ADS)

Yadav, Avinash Chand; Manchanda, Kaustubh; Ramaswamy, Ramakrishna

2017-09-01

We study the collective behaviour of interacting agents in a simple model of market economics that was originally introduced by Nørrelykke and Bak. A general theoretical framework for interacting traders on an arbitrary network is presented, with the interaction consisting of buying (namely consumption) and selling (namely production) of commodities. Extremal dynamics is introduced by having the agent with least profit in the market readjust prices, causing the market to self-organize. In addition to examining this model market on regular lattices in two-dimensions, we also study the cases of random complex networks both with and without community structures. Fluctuations in an activity signal exhibit properties that are characteristic of avalanches observed in models of self-organized criticality, and these can be described by power-law distributions when the system is in the critical state.

Distributed Market-Based Algorithms for Multi-Agent Planning with Shared Resources

DTIC Science & Technology

2013-02-01

1 Introduction 1 2 Distributed Market-Based Multi-Agent Planning 5 2.1 Problem Formulation...over the deterministic planner, on the “test set” of scenarios with changing economies. . . 50 xi xii Chapter 1 Introduction Multi-agent planning is...representation of the objective (4.2.1). For example, for the supply chain mangement problem, we assumed a sequence of Bernoulli coin flips, which seems

a Model for Brand Competition Within a Social Network

NASA Astrophysics Data System (ADS)

Huerta-Quintanilla, R.; Canto-Lugo, E.; Rodríguez-Achach, M.

An agent-based model was built representing an economic environment in which m brands are competing for a product market. These agents represent companies that interact within a social network in which a certain agent persuades others to update or shift their brands; the brands of the products they are using. Decision rules were established that caused each agent to react according to the economic benefits it would receive; they updated/shifted only if it was beneficial. Each agent can have only one of the m possible brands, and she can interact with its two nearest neighbors and another set of agents which are chosen according to a particular set of rules in the network topology. An absorbing state was always reached in which a single brand monopolized the network (known as condensation). The condensation time varied as a function of model parameters is studied including an analysis of brand competition using different networks.

Price dynamics of the financial markets using the stochastic differential equation for a potential double well

NASA Astrophysics Data System (ADS)

Lima, L. S.; Miranda, L. L. B.

2018-01-01

We have used the Itô's stochastic differential equation for the double well with additive white noise as a mathematical model for price dynamics of the financial market. We have presented a model which allows us to test within the same framework the comparative explanatory power of rational agents versus irrational agents, with respect to the facts of financial markets. We have obtained the mean price in terms of the β parameter that represents the force of the randomness term of the model.

Modeling the Structural Dynamic of Industrial Networks

NASA Astrophysics Data System (ADS)

Wilkinson, Ian F.; Wiley, James B.; Lin, Aizhong

Market systems consist of locally interacting agents who continuously pursue advantageous opportunities. Since the time of Adam Smith, a fundamental task of economics has been to understand how market systems develop and to explain their operation. During the intervening years, theory largely has stressed comparative statics analysis. Based on the assumptions of rational, utility or profit-maximizing agents, and negative, diminishing returns) feedback process, traditional economic analysis seeks to describe the, generally) unique state of an economy corresponding to an initial set of assumptions. The analysis is tatic in the sense that it does not describe the process by which an economy might get from one state to another.

Sustainable Society Formed by Unselfish Agents

NASA Astrophysics Data System (ADS)

Kikuchi, Toshiko

It has been pointed out that if the social configuration of the three relations (market, communal and obligatory relations) is not balanced, a market based society as a total system fails. Using multi-agent simulations, this paper shows that a sustainable society is formed when all three relations are integrated and function respectively. When agent trades are based on the market mechanism (i.e., agents act in their own interest and thus only market relations exist), weak agents who cannot perform transactions die. If a compulsory tax is imposed to enable all weak agents to survive (i.e., obligatory relations exist), then the fiscal deficit increases. On the other hand, if agents who have excess income undertake the unselfish action of distributing their surplus to the weak agents (i.e., communal relations exist), then trade volume increases. It is shown that the existence of unselfish agents is necessary for the realization of a sustainable society. However, the survival of all agents is difficult in a communal society. In an artificial society, for all agents survive and fiscal balance to be maintained, all three social relations need to be fully integrated. These results show that adjusting the balance of the three social relations well lead to the realization of a sustainable society.

Emergence of Cooperative Long-Term Market Loyalty in Double Auction Markets.

PubMed

Alorić, Aleksandra; Sollich, Peter; McBurney, Peter; Galla, Tobias

2016-01-01

Loyal buyer-seller relationships can arise by design, e.g. when a seller tailors a product to a specific market niche to accomplish the best possible returns, and buyers respond to the dedicated efforts the seller makes to meet their needs. We ask whether it is possible, instead, for loyalty to arise spontaneously, and in particular as a consequence of repeated interaction and co-adaptation among the agents in a market. We devise a stylized model of double auction markets and adaptive traders that incorporates these features. Traders choose where to trade (which market) and how to trade (to buy or to sell) based on their previous experience. We find that when the typical scale of market returns (or, at fixed scale of returns, the intensity of choice) become higher than some threshold, the preferred state of the system is segregated: both buyers and sellers are segmented into subgroups that are persistently loyal to one market over another. We characterize the segregated state analytically in the limit of large markets: it is stabilized by some agents acting cooperatively to enable trade, and provides higher rewards than its unsegregated counterpart both for individual traders and the population as a whole.

Emergence of Cooperative Long-Term Market Loyalty in Double Auction Markets

PubMed Central

Alorić, Aleksandra; Sollich, Peter; McBurney, Peter; Galla, Tobias

2016-01-01

Loyal buyer-seller relationships can arise by design, e.g. when a seller tailors a product to a specific market niche to accomplish the best possible returns, and buyers respond to the dedicated efforts the seller makes to meet their needs. We ask whether it is possible, instead, for loyalty to arise spontaneously, and in particular as a consequence of repeated interaction and co-adaptation among the agents in a market. We devise a stylized model of double auction markets and adaptive traders that incorporates these features. Traders choose where to trade (which market) and how to trade (to buy or to sell) based on their previous experience. We find that when the typical scale of market returns (or, at fixed scale of returns, the intensity of choice) become higher than some threshold, the preferred state of the system is segregated: both buyers and sellers are segmented into subgroups that are persistently loyal to one market over another. We characterize the segregated state analytically in the limit of large markets: it is stabilized by some agents acting cooperatively to enable trade, and provides higher rewards than its unsegregated counterpart both for individual traders and the population as a whole. PMID:27120473

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).

A Multilateral Negotiation Model for Cloud Service Market

NASA Astrophysics Data System (ADS)

Yoo, Dongjin; Sim, Kwang Mong

Trading cloud services between consumers and providers is a complicated issue of cloud computing. Since a consumer can negotiate with multiple providers to acquire the same service and each provider can receive many requests from multiple consumers, to facilitate the trading of cloud services among multiple consumers and providers, a multilateral negotiation model for cloud market is necessary. The contribution of this work is the proposal of a business model supporting a multilateral price negotiation for trading cloud services. The design of proposed systems for cloud service market includes considering a many-to-many negotiation protocol, and price determining factor from service level feature. Two negotiation strategies are implemented: 1) MDA (Market Driven Agent); and 2) adaptive concession making responding to changes of bargaining position are proposed for cloud service market. Empirical results shows that MDA achieved better performance in some cases that the adaptive concession making strategy, it is noted that unlike the MDA, the adaptive concession making strategy does not assume that an agent has information of the number of competitors (e.g., a consumer agent adopting the adaptive concession making strategy need not know the number of consumer agents competing for the same service).

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.

Intelligent multiagent coordination based on reinforcement hierarchical neuro-fuzzy models.

PubMed

Mendoza, Leonardo Forero; Vellasco, Marley; Figueiredo, Karla

2014-12-01

This paper presents the research and development of two hybrid neuro-fuzzy models for the hierarchical coordination of multiple intelligent agents. The main objective of the models is to have multiple agents interact intelligently with each other in complex systems. We developed two new models of coordination for intelligent multiagent systems, which integrates the Reinforcement Learning Hierarchical Neuro-Fuzzy model with two proposed coordination mechanisms: the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with a market-driven coordination mechanism (MA-RL-HNFP-MD) and the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with graph coordination (MA-RL-HNFP-CG). In order to evaluate the proposed models and verify the contribution of the proposed coordination mechanisms, two multiagent benchmark applications were developed: the pursuit game and the robot soccer simulation. The results obtained demonstrated that the proposed coordination mechanisms greatly improve the performance of the multiagent system when compared with other strategies.

Phase transitions in adaptive competitive environments: Theories and applications of the minority game

NASA Astrophysics Data System (ADS)

Li, Yi

It is of great scientific significance to study the complex systems of agents with adaptive strategies competing for resources. In many of such systems in social and biological environments, agents succeed by making innovative choices. In this thesis, we model this behavior by presenting the results and analysis of a class of games in which heterogeneous agents are rewarded for being in a minority group. Each agent possesses a number of fixed strategies, each of which takes publicly available information as input to predict next group. Commonly known as the minority game, this simple model manifests a maladaptive, informationally efficient phase in which the system performs poorly at generating resources and an inefficient phase in which there is an emergent cooperation among the agents, and the system more effectively generates resources. The best emergent coordination is achieved at the phase transition, which occurs when z, the ratio of the dimension of the strategy space to the number of agents, is about 0.34. This model also has similar properties to a spin glass system thus statistical mechanics methods were employed to provide analytical results. The phase structure persists under variations such as variable payoff schemes and evolutionary mechanisms. Agents in real life are subject to local connectivity and incomplete information. A framework based on bi-graph was proposed to model these factors. In the context of economics, we proposed a stock market model incorporating delayed majority dynamics and agents holding heterogeneous expectations. We found that for a range of parameter settings, minority dynamics are dynamically induced, effectively reducing market volatility. Finally, we introduce a version of the minority game played by human participants. We observed emergent coordination of players' choices leading to increased average reward. Furthermore, players with the simplest strategies reap the most wealth.

Green Power Grids: How Energy from Renewable Sources Affects Networks and Markets

PubMed Central

Mureddu, Mario; Caldarelli, Guido; Chessa, Alessandro; Scala, Antonio; Damiano, Alfonso

2015-01-01

The increasing attention to environmental issues is forcing the implementation of novel energy models based on renewable sources. This is fundamentally changing the configuration of energy management and is introducing new problems that are only partly understood. In particular, renewable energies introduce fluctuations which cause an increased request for conventional energy sources to balance energy requests at short notice. In order to develop an effective usage of low-carbon sources, such fluctuations must be understood and tamed. In this paper we present a microscopic model for the description and for the forecast of short time fluctuations related to renewable sources in order to estimate their effects on the electricity market. To account for the inter-dependencies in the energy market and the physical power dispatch network, we use a statistical mechanics approach to sample stochastic perturbations in the power system and an agent based approach for the prediction of the market players’ behavior. Our model is data-driven; it builds on one-day-ahead real market transactions in order to train agents’ behaviour and allows us to deduce the market share of different energy sources. We benchmarked our approach on the Italian market, finding a good accordance with real data. PMID:26335705

Improving Agent Bidding in Power Stock Markets through a Data Mining Enhanced Agent Platform

NASA Astrophysics Data System (ADS)

Chrysopoulos, Anthony C.; Symeonidis, Andreas L.; Mitkas, Pericles A.

Like in any other auctioning environment, entities participating in Power Stock Markets have to compete against other in order to maximize own revenue. Towards the satisfaction of their goal, these entities (agents - human or software ones) may adopt different types of strategies - from na?ve to extremely complex ones - in order to identify the most profitable goods compilation, the appropriate price to buy or sell etc, always under time pressure and auction environment constraints. Decisions become even more difficult to make in case one takes the vast volumes of historical data available into account: goods’ prices, market fluctuations, bidding habits and buying opportunities. Within the context of this paper we present Cassandra, a multi-agent platform that exploits data mining, in order to extract efficient models for predicting Power Settlement prices and Power Load values in typical Day-ahead Power markets. The functionality of Cassandra is discussed, while focus is given on the bidding mechanism of Cassandra’s agents, and the way data mining analysis is performed in order to generate the optimal forecasting models. Cassandra has been tested in a real-world scenario, with data derived from the Greek Energy Stock market.

Emergent Behavior of Coupled Barrier Island - Resort Systems

NASA Astrophysics Data System (ADS)

McNamara, D. E.; Werner, B. T.

2004-12-01

Barrier islands are attractive sites for resorts. Natural barrier islands experience beach erosion and island overwash during storms, beach accretion and dune building during inter-storm periods, and migration up the continental shelf as sea level rises. Beach replenishment, artificial dune building, seawalls, jetties and groins have been somewhat effective in protecting resorts against erosion and overwash during storms, but it is unknown how the coupled system will respond to long-term sea level rise. We investigate coupled barrier island - resort systems using an agent-based model with three components: natural barrier islands divided into a series of alongshore cells; resorts controlled by markets for tourism and hotel purchases; and coupling via storm damage to resorts and resort protection by government agents. Modeled barrier islands change by beach erosion, island overwash and inlet cutting during storms, and beach accretion, tidal delta growth and dune and vegetation growth between storms. In the resort hotel market, developer agents build hotels and hotel owning agents purchase them using predictions of future revenue and property appreciation, with the goal of maximizing discounted utility. In the tourism market, hotel owning agents set room rental prices to maximize profit and tourist agents choose vacation destinations maximizing a utility based on beach width, price and word-of-mouth. Government agents build seawalls, groins and jetties, and widen the beach and build up dunes by adding sand to protect resorts from storms, enhance beach quality, and maximize resort revenue. Results indicate that barrier islands and resorts evolve in a coupled manner to resort size saturation, with resorts protected against small-to-intermediate-scale storms under fairly stable sea level. Under extended, rapidly rising sea level, protection measures enhance the effect of large storms, leading to emergent behavior in the form of limit cycles or barrier submergence, depending on the relative rates of resort recovery from storms and sea level rise. The model is applied to Ocean City, Maryland and neighboring undeveloped Assateague Island National Seashore. Supported by the National Science Foundation, Geology and Paleontology Program, and the Andrew W. Mellon Foundation

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.

Adaptive Sniping for Volatile and Stable Continuous Double Auction Markets

NASA Astrophysics Data System (ADS)

Toft, I. E.; Bagnall, A. J.

This paper introduces a new adaptive sniping agent for the Continuous Double Auction. We begin by analysing the performance of the well known Kaplan sniper in two extremes of market conditions. We generate volatile and stable market conditions using the well known Zero Intelligence-Constrained agent and a new zero-intelligence agent Small Increment (SI). ZI-C agents submit random but profitable bids/offers and cause high volatility in prices and individual trader performance. Our new zero-intelligence agent, SI, makes small random adjustments to the outstanding bid/offer and hence is more cautious than ZI-C. We present results for SI in self-play and then analyse Kaplan in volatile and stable markets. We demonstrate that the non-adaptive Kaplan sniper can be configured to suit either market conditions, but no single configuration is performs well across both market types. We believe that in a dynamic auction environment where current or future market conditions cannot be predicted a viable sniping strategy should adapt its behaviour to suit prevailing market conditions. To this end, we propose the Adaptive Sniper (AS) agent for the CDA. AS traders classify sniping opportunities using a statistical model of market activity and adjust their classification thresholds using a Widrow-Hoff adapted search. Our AS agent requires little configuration, and outperforms the original Kaplan sniper in volatile and stable markets, and in a mixed trader type scenario that includes adaptive strategies from the literature.

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.

Influence of government controls over the currency exchange rate in the evolution of Hurst's exponent: An autonomous agent-based model

NASA Astrophysics Data System (ADS)

Chávez Muñoz, Pablo; Fernandes da Silva, Marcus; Vivas Miranda, José; Claro, Francisco; Gomez Diniz, Raimundo

2007-12-01

We have studied the performance of the Hurst's index associated with the currency exchange rate in Brazil and Chile. It is shown that this index maps the degree of government control in the exchange rate. A model of supply and demand based in an autonomous agent is proposed, that simulates a virtual market of sale and purchase, where buyer or seller are forced to negotiate through an intermediary. According to this model, the average of the price of daily transactions correspond to the theoretical balance proposed by the law of supply and demand. The influence of an added tendency factor is also analyzed.

Twitter's tweet method modelling and simulation

NASA Astrophysics Data System (ADS)

Sarlis, Apostolos S.; Sakas, Damianos P.; Vlachos, D. S.

2015-02-01

This paper seeks to purpose the concept of Twitter marketing methods. The tools that Twitter provides are modelled and simulated using iThink in the context of a Twitter media-marketing agency. The paper has leveraged the system's dynamic paradigm to conduct Facebook marketing tools and methods modelling, using iThink™ system to implement them. It uses the design science research methodology for the proof of concept of the models and modelling processes. The following models have been developed for a twitter marketing agent/company and tested in real circumstances and with real numbers. These models were finalized through a number of revisions and iterators of the design, develop, simulate, test and evaluate. It also addresses these methods that suit most organized promotion through targeting, to the Twitter social media service. The validity and usefulness of these Twitter marketing methods models for the day-to-day decision making are authenticated by the management of the company organization. It implements system dynamics concepts of Twitter marketing methods modelling and produce models of various Twitter marketing situations. The Tweet method that Twitter provides can be adjusted, depending on the situation, in order to maximize the profit of the company/agent.

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

Effects of introduction of new resources and fragmentation of existing resources on limiting wealth distribution in asset exchange models

NASA Astrophysics Data System (ADS)

Ali Saif, M.; Gade, Prashant M.

2009-03-01

Pareto law, which states that wealth distribution in societies has a power-law tail, has been the subject of intensive investigations in the statistical physics community. Several models have been employed to explain this behavior. However, most of the agent based models assume the conservation of number of agents and wealth. Both these assumptions are unrealistic. In this paper, we study the limiting wealth distribution when one or both of these assumptions are not valid. Given the universality of the law, we have tried to study the wealth distribution from the asset exchange models point of view. We consider models in which (a) new agents enter the market at a constant rate (b) richer agents fragment with higher probability introducing newer agents in the system (c) both fragmentation and entry of new agents is taking place. While models (a) and (c) do not conserve total wealth or number of agents, model (b) conserves total wealth. All these models lead to a power-law tail in the wealth distribution pointing to the possibility that more generalized asset exchange models could help us to explain the emergence of a power-law tail in wealth distribution.

Importance of positive feedbacks and overconfidence in a self-fulfilling Ising model of financial markets

NASA Astrophysics Data System (ADS)

Sornette, Didier; Zhou, Wei-Xing

2006-10-01

Following a long tradition of physicists who have noticed that the Ising model provides a general background to build realistic models of social interactions, we study a model of financial price dynamics resulting from the collective aggregate decisions of agents. This model incorporates imitation, the impact of external news and private information. It has the structure of a dynamical Ising model in which agents have two opinions (buy or sell) with coupling coefficients, which evolve in time with a memory of how past news have explained realized market returns. We study two versions of the model, which differ on how the agents interpret the predictive power of news. We show that the stylized facts of financial markets are reproduced only when agents are overconfident and mis-attribute the success of news to predict return to herding effects, thereby providing positive feedbacks leading to the model functioning close to the critical point. Our model exhibits a rich multifractal structure characterized by a continuous spectrum of exponents of the power law relaxation of endogenous bursts of volatility, in good agreement with previous analytical predictions obtained with the multifractal random walk model and with empirical facts.

Agent-based modeling in ecological economics.

PubMed

Heckbert, Scott; Baynes, Tim; Reeson, Andrew

2010-01-01

Interconnected social and environmental systems are the domain of ecological economics, and models can be used to explore feedbacks and adaptations inherent in these systems. Agent-based modeling (ABM) represents autonomous entities, each with dynamic behavior and heterogeneous characteristics. Agents interact with each other and their environment, resulting in emergent outcomes at the macroscale that can be used to quantitatively analyze complex systems. ABM is contributing to research questions in ecological economics in the areas of natural resource management and land-use change, urban systems modeling, market dynamics, changes in consumer attitudes, innovation, and diffusion of technology and management practices, commons dilemmas and self-governance, and psychological aspects to human decision making and behavior change. Frontiers for ABM research in ecological economics involve advancing the empirical calibration and validation of models through mixed methods, including surveys, interviews, participatory modeling, and, notably, experimental economics to test specific decision-making hypotheses. Linking ABM with other modeling techniques at the level of emergent properties will further advance efforts to understand dynamics of social-environmental systems.

Time-varying economic dominance in financial markets: A bistable dynamics approach

NASA Astrophysics Data System (ADS)

He, Xue-Zhong; Li, Kai; Wang, Chuncheng

2018-05-01

By developing a continuous-time heterogeneous agent financial market model of multi-assets traded by fundamental and momentum investors, we provide a potential mechanism for generating time-varying dominance between fundamental and non-fundamental in financial markets. We show that investment constraints lead to the coexistence of a locally stable fundamental steady state and a locally stable limit cycle around the fundamental, characterized by a Bautin bifurcation. This provides a mechanism for market prices to switch stochastically between the two persistent but very different market states, leading to the coexistence and time-varying dominance of seemingly controversial efficient market and price momentum over different time periods. The model also generates other financial market stylized facts, such as spillover effects in both momentum and volatility, market booms, crashes, and correlation reduction due to cross-sectional momentum trading. Empirical evidence based on the U.S. market supports the main findings. The mechanism developed in this paper can be used to characterize time-varying economic dominance in economics and finance in general.

Time-varying economic dominance in financial markets: A bistable dynamics approach.

PubMed

He, Xue-Zhong; Li, Kai; Wang, Chuncheng

2018-05-01

By developing a continuous-time heterogeneous agent financial market model of multi-assets traded by fundamental and momentum investors, we provide a potential mechanism for generating time-varying dominance between fundamental and non-fundamental in financial markets. We show that investment constraints lead to the coexistence of a locally stable fundamental steady state and a locally stable limit cycle around the fundamental, characterized by a Bautin bifurcation. This provides a mechanism for market prices to switch stochastically between the two persistent but very different market states, leading to the coexistence and time-varying dominance of seemingly controversial efficient market and price momentum over different time periods. The model also generates other financial market stylized facts, such as spillover effects in both momentum and volatility, market booms, crashes, and correlation reduction due to cross-sectional momentum trading. Empirical evidence based on the U.S. market supports the main findings. The mechanism developed in this paper can be used to characterize time-varying economic dominance in economics and finance in general.

Can agent based models effectively reduce fisheries management implementation uncertainty?

NASA Astrophysics Data System (ADS)

Drexler, M.

2016-02-01

Uncertainty is an inherent feature of fisheries management. Implementation uncertainty remains a challenge to quantify often due to unintended responses of users to management interventions. This problem will continue to plague both single species and ecosystem based fisheries management advice unless the mechanisms driving these behaviors are properly understood. Equilibrium models, where each actor in the system is treated as uniform and predictable, are not well suited to forecast the unintended behaviors of individual fishers. Alternatively, agent based models (AMBs) can simulate the behaviors of each individual actor driven by differing incentives and constraints. This study evaluated the feasibility of using AMBs to capture macro scale behaviors of the US West Coast Groundfish fleet. Agent behavior was specified at the vessel level. Agents made daily fishing decisions using knowledge of their own cost structure, catch history, and the histories of catch and quota markets. By adding only a relatively small number of incentives, the model was able to reproduce highly realistic macro patterns of expected outcomes in response to management policies (catch restrictions, MPAs, ITQs) while preserving vessel heterogeneity. These simulations indicate that agent based modeling approaches hold much promise for simulating fisher behaviors and reducing implementation uncertainty. Additional processes affecting behavior, informed by surveys, are continually being added to the fisher behavior model. Further coupling of the fisher behavior model to a spatial ecosystem model will provide a fully integrated social, ecological, and economic model capable of performing management strategy evaluations to properly consider implementation uncertainty in fisheries management.

Price dynamics and market power in an agent-based power exchange

NASA Astrophysics Data System (ADS)

Cincotti, Silvano; Guerci, Eric; Raberto, Marco

2005-05-01

This paper presents an agent-based model of a power exchange. Supply of electric power is provided by competing generating companies, whereas demand is assumed to be inelastic with respect to price and is constant over time. The transmission network topology is assumed to be a fully connected graph and no transmission constraints are taken into account. The price formation process follows a common scheme for real power exchanges: a clearing house mechanism with uniform price, i.e., with price set equal across all matched buyer-seller pairs. A single class of generating companies is considered, characterized by linear cost function for each technology. Generating companies compete for the sale of electricity through repeated rounds of the uniform auction and determine their supply functions according to production costs. However, an individual reinforcement learning algorithm characterizes generating companies behaviors in order to attain the expected maximum possible profit in each auction round. The paper investigates how the market competitive equilibrium is affected by market microstructure and production costs.

Understanding Financial Market States Using an Artificial Double Auction Market

PubMed Central

2016-01-01

The ultimate value of theories describing the fundamental mechanisms behind asset prices in financial systems is reflected in the capacity of such theories to understand these systems. Although the models that explain the various states of financial markets offer substantial evidence from the fields of finance, mathematics, and even physics, previous theories that attempt to address the complexities of financial markets in full have been inadequate. We propose an artificial double auction market as an agent-based model to study the origin of complex states in financial markets by characterizing important parameters with an investment strategy that can cover the dynamics of the financial market. The investment strategies of chartist traders in response to new market information should reduce market stability based on the price fluctuations of risky assets. However, fundamentalist traders strategically submit orders based on fundamental value and, thereby stabilize the market. We construct a continuous double auction market and find that the market is controlled by the proportion of chartists, Pc. We show that mimicking the real state of financial markets, which emerges in real financial systems, is given within the range Pc = 0.40 to Pc = 0.85; however, we show that mimicking the efficient market hypothesis state can be generated with values less than Pc = 0.40. In particular, we observe that mimicking a market collapse state is created with values greater than Pc = 0.85, at which point a liquidity shortage occurs, and the phase transition behavior is described at Pc = 0.85. PMID:27031110

Understanding Financial Market States Using an Artificial Double Auction Market.

PubMed

Yim, Kyubin; Oh, Gabjin; Kim, Seunghwan

2016-01-01

The ultimate value of theories describing the fundamental mechanisms behind asset prices in financial systems is reflected in the capacity of such theories to understand these systems. Although the models that explain the various states of financial markets offer substantial evidence from the fields of finance, mathematics, and even physics, previous theories that attempt to address the complexities of financial markets in full have been inadequate. We propose an artificial double auction market as an agent-based model to study the origin of complex states in financial markets by characterizing important parameters with an investment strategy that can cover the dynamics of the financial market. The investment strategies of chartist traders in response to new market information should reduce market stability based on the price fluctuations of risky assets. However, fundamentalist traders strategically submit orders based on fundamental value and, thereby stabilize the market. We construct a continuous double auction market and find that the market is controlled by the proportion of chartists, Pc. We show that mimicking the real state of financial markets, which emerges in real financial systems, is given within the range Pc = 0.40 to Pc = 0.85; however, we show that mimicking the efficient market hypothesis state can be generated with values less than Pc = 0.40. In particular, we observe that mimicking a market collapse state is created with values greater than Pc = 0.85, at which point a liquidity shortage occurs, and the phase transition behavior is described at Pc = 0.85.

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.

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.

The predictive power of zero intelligence in financial markets.

PubMed

Farmer, J Doyne; Patelli, Paolo; Zovko, Ilija I

2005-02-08

Standard models in economics stress the role of intelligent agents who maximize utility. However, there may be situations where constraints imposed by market institutions dominate strategic agent behavior. We use data from the London Stock Exchange to test a simple model in which minimally intelligent agents place orders to trade at random. The model treats the statistical mechanics of order placement, price formation, and the accumulation of revealed supply and demand within the context of the continuous double auction and yields simple laws relating order-arrival rates to statistical properties of the market. We test the validity of these laws in explaining cross-sectional variation for 11 stocks. The model explains 96% of the variance of the gap between the best buying and selling prices (the spread) and 76% of the variance of the price diffusion rate, with only one free parameter. We also study the market impact function, describing the response of quoted prices to the arrival of new orders. The nondimensional coordinates dictated by the model approximately collapse data from different stocks onto a single curve. This work is important from a practical point of view, because it demonstrates the existence of simple laws relating prices to order flows and, in a broader context, suggests there are circumstances where the strategic behavior of agents may be dominated by other considerations.

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.

Quantitative description of realistic wealth distributions by kinetic trading models

NASA Astrophysics Data System (ADS)

Lammoglia, Nelson; Muñoz, Víctor; Rogan, José; Toledo, Benjamín; Zarama, Roberto; Valdivia, Juan Alejandro

2008-10-01

Data on wealth distributions in trading markets show a power law behavior x-(1+α) at the high end, where, in general, α is greater than 1 (Pareto’s law). Models based on kinetic theory, where a set of interacting agents trade money, yield power law tails if agents are assigned a saving propensity. In this paper we are solving the inverse problem, that is, in finding the saving propensity distribution which yields a given wealth distribution for all wealth ranges. This is done explicitly for two recently published and comprehensive wealth datasets.

From quantum mechanics to finance: Microfoundations for jumps, spikes and high volatility phases in diffusion price processes

NASA Astrophysics Data System (ADS)

Henkel, Christof

2017-03-01

We present an agent behavior based microscopic model that induces jumps, spikes and high volatility phases in the price process of a traded asset. We transfer dynamics of thermally activated jumps of an unexcited/excited two state system discussed in the context of quantum mechanics to agent socio-economic behavior and provide microfoundations. After we link the endogenous agent behavior to price dynamics we establish the circumstances under which the dynamics converge to an Itô-diffusion price processes in the large market limit.

Intelligent agents for e-commerce applications

NASA Astrophysics Data System (ADS)

Vuppala, Krishna

1999-12-01

This thesis focuses on development of intelligent agent solutions for e-commerce applications. E-Commerce has several complexities like: lack of information about the players, learning the nature of one's business partners/competitors, finding the right business partner to do business with, using the right strategy to get best profit out of the negotiations etc. The agent models developed can be used in any agent solution for e-commerce. Concepts and techniques from Game Theory and Artificial Intelligence are used. The developed models have several advantages over the existing ones as: the models assume the non-availability of information about other players in the market, the models of players get updated over the time as and when new information comes about the players, the negotiation model incorporates the patience levels of the players and expectations from other players in the market. Power industry has been chosen as the application area for the demonstration of the capabilities and usage of the developed agent models. Two e-commerce scenarios where sellers and buyers can go through the power exchanges to bid in auctions, or make bilateral deals outside of the exchange are addressed. In the first scenario agent helps market participants in coordinating strategies with other participants, bidding in auctions by analyzing and understanding the behavior of other participants. In the second scenario, called "Power Traders Assistant" agent helps power trader, who buys and sells power through bilateral negotiations, in negotiating deals with his customers.

The effects of behavioral and structural assumptions in artificial stock market

NASA Astrophysics Data System (ADS)

Liu, Xinghua; Gregor, Shirley; Yang, Jianmei

2008-04-01

Recent literature has developed the conjecture that important statistical features of stock price series, such as the fat tails phenomenon, may depend mainly on the market microstructure. This conjecture motivated us to investigate the roles of both the market microstructure and agent behavior with respect to high-frequency returns and daily returns. We developed two simple models to investigate this issue. The first one is a stochastic model with a clearing house microstructure and a population of zero-intelligence agents. The second one has more behavioral assumptions based on Minority Game and also has a clearing house microstructure. With the first model we found that a characteristic of the clearing house microstructure, namely the clearing frequency, can explain fat tail, excess volatility and autocorrelation phenomena of high-frequency returns. However, this feature does not cause the same phenomena in daily returns. So the Stylized Facts of daily returns depend mainly on the agents’ behavior. With the second model we investigated the effects of behavioral assumptions on daily returns. Our study implicates that the aspects which are responsible for generating the stylized facts of high-frequency returns and daily returns are different.

The Interactive Minority Game: a Web-based investigation of human market interactions

NASA Astrophysics Data System (ADS)

Laureti, Paolo; Ruch, Peter; Wakeling, Joseph; Zhang, Yi-Cheng

2004-01-01

The unprecedented access offered by the World Wide Web brings with it the potential to gather huge amounts of data on human activities. Here we exploit this by using a toy model of financial markets, the Minority Game (MG), to investigate human speculative trading behaviour and information capacity. Hundreds of individuals have played a total of tens of thousands of game turns against computer-controlled agents in the Web-based Interactive Minority Game. The analytical understanding of the MG permits fine-tuning of the market situations encountered, allowing for investigation of human behaviour in a variety of controlled environments. In particular, our results indicate a transition in players’ decision-making, as the markets become more difficult, between deductive behaviour making use of short-term trends in the market, and highly repetitive behaviour that ignores entirely the market history, yet outperforms random decision-making.

Multirobot autonomous landmine detection using distributed multisensor information aggregation

NASA Astrophysics Data System (ADS)

Jumadinova, Janyl; Dasgupta, Prithviraj

2012-06-01

We consider the problem of distributed sensor information fusion by multiple autonomous robots within the context of landmine detection. We assume that different landmines can be composed of different types of material and robots are equipped with different types of sensors, while each robot has only one type of landmine detection sensor on it. We introduce a novel technique that uses a market-based information aggregation mechanism called a prediction market. Each robot is provided with a software agent that uses sensory input of the robot and performs calculations of the prediction market technique. The result of the agent's calculations is a 'belief' representing the confidence of the agent in identifying the object as a landmine. The beliefs from different robots are aggregated by the market mechanism and passed on to a decision maker agent. The decision maker agent uses this aggregate belief information about a potential landmine and makes decisions about which other robots should be deployed to its location, so that the landmine can be confirmed rapidly and accurately. Our experimental results show that, for identical data distributions and settings, using our prediction market-based information aggregation technique increases the accuracy of object classification favorably as compared to two other commonly used techniques.

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.

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.

Scaling and criticality in a stochastic multi-agent model of a financial market

NASA Astrophysics Data System (ADS)

Lux, Thomas; Marchesi, Michele

1999-02-01

Financial prices have been found to exhibit some universal characteristics that resemble the scaling laws characterizing physical systems in which large numbers of units interact. This raises the question of whether scaling in finance emerges in a similar way - from the interactions of a large ensemble of market participants. However, such an explanation is in contradiction to the prevalent `efficient market hypothesis' in economics, which assumes that the movements of financial prices are an immediate and unbiased reflection of incoming news about future earning prospects. Within this hypothesis, scaling in price changes would simply reflect similar scaling in the `input' signals that influence them. Here we describe a multi-agent model of financial markets which supports the idea that scaling arises from mutual interactions of participants. Although the `news arrival process' in our model lacks both power-law scaling and any temporal dependence in volatility, we find that it generates such behaviour as a result of interactions between agents.

An Agent-Based Optimization Framework for Engineered Complex Adaptive Systems with Application to Demand Response in Electricity Markets

NASA Astrophysics Data System (ADS)

Haghnevis, Moeed

The main objective of this research is to develop an integrated method to study emergent behavior and consequences of evolution and adaptation in engineered complex adaptive systems (ECASs). A multi-layer conceptual framework and modeling approach including behavioral and structural aspects is provided to describe the structure of a class of engineered complex systems and predict their future adaptive patterns. The approach allows the examination of complexity in the structure and the behavior of components as a result of their connections and in relation to their environment. This research describes and uses the major differences of natural complex adaptive systems (CASs) with artificial/engineered CASs to build a framework and platform for ECAS. While this framework focuses on the critical factors of an engineered system, it also enables one to synthetically employ engineering and mathematical models to analyze and measure complexity in such systems. In this way concepts of complex systems science are adapted to management science and system of systems engineering. In particular an integrated consumer-based optimization and agent-based modeling (ABM) platform is presented that enables managers to predict and partially control patterns of behaviors in ECASs. Demonstrated on the U.S. electricity markets, ABM is integrated with normative and subjective decision behavior recommended by the U.S. Department of Energy (DOE) and Federal Energy Regulatory Commission (FERC). The approach integrates social networks, social science, complexity theory, and diffusion theory. Furthermore, it has unique and significant contribution in exploring and representing concrete managerial insights for ECASs and offering new optimized actions and modeling paradigms in agent-based simulation.

Learning Based Bidding Strategy for HVAC Systems in Double Auction Retail Energy Markets

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

Sun, Yannan; Somani, Abhishek; Carroll, Thomas E.

In this paper, a bidding strategy is proposed using reinforcement learning for HVAC systems in a double auction market. The bidding strategy does not require a specific model-based representation of behavior, i.e., a functional form to translate indoor house temperatures into bid prices. The results from reinforcement learning based approach are compared with the HVAC bidding approach used in the AEP gridSMART® smart grid demonstration project and it is shown that the model-free (learning based) approach tracks well the results from the model-based behavior. Successful use of model-free approaches to represent device-level economic behavior may help develop similar approaches tomore » represent behavior of more complex devices or groups of diverse devices, such as in a building. Distributed control requires an understanding of decision making processes of intelligent agents so that appropriate mechanisms may be developed to control and coordinate their responses, and model-free approaches to represent behavior will be extremely useful in that quest.« less

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.

Phantastic objects and the financial market's sense of reality: a psychoanalytic contribution to the understanding of stock market instability.

PubMed

Tuckett, David; Taffler, Richard

2008-04-01

This paper sets out to explore if standard psychoanalytic thinking based on clinical experience can illuminate instability in financial markets and its widespread human consequences. Buying, holding or selling financial assets in conditions of inherent uncertainty and ambiguity, it is argued, necessarily implies an ambivalent emotional and phantasy relationship to them. Based on the evidence of historical accounts, supplemented by some interviewing, the authors suggest a psychoanalytic approach focusing on unconscious phantasy relationships, states of mind, and unconscious group functioning can explain some outstanding questions about financial bubbles which cannot be explained with mainstream economic theories. The authors also suggest some institutional features of financial markets which may ordinarily increase or decrease the likelihood that financial decisions result from splitting off those thoughts which give rise to painful emotions. Splitting would increase the future risk of financial instability and in this respect the theory with which economic agents in such markets approach their work is important. An interdisciplinary theory recognizing and making possible the integration of emotional experience may be more useful to economic agents than the present mainstream theories which contrast rational and irrational decision-making and model them as making consistent decisions on the basis of reasoning alone.

Market mechanism based on the endogenous changing of game types such as Minority-Majority games

NASA Astrophysics Data System (ADS)

Ahn, Sanghyun; Lim, Gyuchang; Kim, Sooyong; Kim, Kyungsik

2010-03-01

In many social and biological systems agents simultaneously and adaptively compete for limited resources, thereby altering their environment. We propose a evolution function extending Minority-Majority Games that captures the competition between agents to make money. The dynamics changes the ratio of two types of boundedly rational traders, fundamentalists and chartists with the payoff function endogenously. In the previous game theories, the best strategies are not always targeting the minority but are shifting opportunistically between the minority and the majority. And using a mixture of local bifurcation theory and numerical methods, there are possible bifurcation routes to complicated asset price dynamics, chaotic attractors. Hereby we improve the thinking logic of the atoms for attaching the dynamics to the market. This working shows that removing unrealistic features of the game theories leads to models which reproduce a behavior close to what is observed in real markets.

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.

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.

The predictive power of zero intelligence in financial markets

PubMed Central

Farmer, J. Doyne; Patelli, Paolo; Zovko, Ilija I.

2005-01-01

Standard models in economics stress the role of intelligent agents who maximize utility. However, there may be situations where constraints imposed by market institutions dominate strategic agent behavior. We use data from the London Stock Exchange to test a simple model in which minimally intelligent agents place orders to trade at random. The model treats the statistical mechanics of order placement, price formation, and the accumulation of revealed supply and demand within the context of the continuous double auction and yields simple laws relating order-arrival rates to statistical properties of the market. We test the validity of these laws in explaining cross-sectional variation for 11 stocks. The model explains 96% of the variance of the gap between the best buying and selling prices (the spread) and 76% of the variance of the price diffusion rate, with only one free parameter. We also study the market impact function, describing the response of quoted prices to the arrival of new orders. The nondimensional coordinates dictated by the model approximately collapse data from different stocks onto a single curve. This work is important from a practical point of view, because it demonstrates the existence of simple laws relating prices to order flows and, in a broader context, suggests there are circumstances where the strategic behavior of agents may be dominated by other considerations. PMID:15687505

A marketing strategy for a nursing college.

PubMed

Pryde, M; Muller, M

1995-08-01

The objective of this study is to explore and describe a marketing strategy for a nursing college. An explorative and descriptive research design, within the context of a nursing college and affiliated hospitals, was followed. A literature study of marketing models was undertaken and the Delphi-method was utilised to determine the contribution of marketing staff and the possible content of a marketing strategy for a nursing college. The results were utilised to describe guidelines for such a strategy, consisting of marketers/marketing agents, target market, product, price, promotional activities, place and market research. Recommendations include the planning, implementation and evaluation of strategy, inservice training for potential marketing agents, inclusion of marketing as part of the formal education of tutors and nurse managers, as well as an impact study of the scholar as the main consumer.

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.

Elements of decisional dynamics: An agent-based approach applied to artificial financial market

NASA Astrophysics Data System (ADS)

Lucas, Iris; Cotsaftis, Michel; Bertelle, Cyrille

2018-02-01

This paper introduces an original mathematical description for describing agents' decision-making process in the case of problems affected by both individual and collective behaviors in systems characterized by nonlinear, path dependent, and self-organizing interactions. An application to artificial financial markets is proposed by designing a multi-agent system based on the proposed formalization. In this application, agents' decision-making process is based on fuzzy logic rules and the price dynamics is purely deterministic according to the basic matching rules of a central order book. Finally, while putting most parameters under evolutionary control, the computational agent-based system is able to replicate several stylized facts of financial time series (distributions of stock returns showing a heavy tail with positive excess kurtosis, absence of autocorrelations in stock returns, and volatility clustering phenomenon).

Elements of decisional dynamics: An agent-based approach applied to artificial financial market.

PubMed

Lucas, Iris; Cotsaftis, Michel; Bertelle, Cyrille

2018-02-01

This paper introduces an original mathematical description for describing agents' decision-making process in the case of problems affected by both individual and collective behaviors in systems characterized by nonlinear, path dependent, and self-organizing interactions. An application to artificial financial markets is proposed by designing a multi-agent system based on the proposed formalization. In this application, agents' decision-making process is based on fuzzy logic rules and the price dynamics is purely deterministic according to the basic matching rules of a central order book. Finally, while putting most parameters under evolutionary control, the computational agent-based system is able to replicate several stylized facts of financial time series (distributions of stock returns showing a heavy tail with positive excess kurtosis, absence of autocorrelations in stock returns, and volatility clustering phenomenon).

A Sequence Mining Method to Predict the Bidding Strategy of Trading Agents

NASA Astrophysics Data System (ADS)

Nikolaidou, Vivia; Mitkas, Pericles A.

In this work, we describe the process used in order to predict the bidding strategy of trading agents. This was done in the context of the Reverse TAC, or CAT, game of the Trading Agent Competition. In this game, a set of trading agents, buyers or sellers, are provided by the server and they trade their goods in one of the markets operated by the competing agents. Better knowledge of the strategy of the trading agents will allow a market maker to adapt its incentives and attract more agents to its own market. Our prediction was based on the time series of the traders’ past bids, taking into account the variation of each bid compared to its history. The results proved to be of satisfactory accuracy, both in the game’s context and when compared to other existing approaches.

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.

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.

Experimental econophysics: Complexity, self-organization, and emergent properties

NASA Astrophysics Data System (ADS)

Huang, J. P.

2015-03-01

Experimental econophysics is concerned with statistical physics of humans in the laboratory, and it is based on controlled human experiments developed by physicists to study some problems related to economics or finance. It relies on controlled human experiments in the laboratory together with agent-based modeling (for computer simulations and/or analytical theory), with an attempt to reveal the general cause-effect relationship between specific conditions and emergent properties of real economic/financial markets (a kind of complex adaptive systems). Here I review the latest progress in the field, namely, stylized facts, herd behavior, contrarian behavior, spontaneous cooperation, partial information, and risk management. Also, I highlight the connections between such progress and other topics of traditional statistical physics. The main theme of the review is to show diverse emergent properties of the laboratory markets, originating from self-organization due to the nonlinear interactions among heterogeneous humans or agents (complexity).

Dynamics of coupled human-landscape systems

NASA Astrophysics Data System (ADS)

Werner, B. T.; McNamara, D. E.

2007-11-01

A preliminary dynamical analysis of landscapes and humans as hierarchical complex systems suggests that strong coupling between the two that spreads to become regionally or globally pervasive should be focused at multi-year to decadal time scales. At these scales, landscape dynamics is dominated by water, sediment and biological routing mediated by fluvial, oceanic, atmospheric processes and human dynamics is dominated by simplifying, profit-maximizing market forces and political action based on projection of economic effect. Also at these scales, landscapes impact humans through patterns of natural disasters and trends such as sea level rise; humans impact landscapes by the effect of economic activity and changes meant to mitigate natural disasters and longer term trends. Based on this analysis, human-landscape coupled systems can be modeled using heterogeneous agents employing prediction models to determine actions to represent the nonlinear behavior of economic and political systems and rule-based routing algorithms to represent landscape processes. A cellular model for the development of New Orleans illustrates this approach, with routing algorithms for river and hurricane-storm surge determining flood extent, five markets (home, labor, hotel, tourism and port services) connecting seven types of economic agents (home buyers/laborers, home developers, hotel owners/ employers, hotel developers, tourists, port services developer and port services owners/employers), building of levees or a river spillway by political agents and damage to homes, hotels or port services within cells determined by the passage or depth of flood waters. The model reproduces historical aspects of New Orleans economic development and levee construction and the filtering of frequent small-scale floods at the expense of large disasters.

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

Competitive advantage for multiple-memory strategies in an artificial market

NASA Astrophysics Data System (ADS)

Mitman, Kurt E.; Choe, Sehyo C.; Johnson, Neil F.

2005-05-01

We consider a simple binary market model containing N competitive agents. The novel feature of our model is that it incorporates the tendency shown by traders to look for patterns in past price movements over multiple time scales, i.e. multiple memory-lengths. In the regime where these memory-lengths are all small, the average winnings per agent exceed those obtained for either (1) a pure population where all agents have equal memory-length, or (2) a mixed population comprising sub-populations of equal-memory agents with each sub-population having a different memory-length. Agents who consistently play strategies of a given memory-length, are found to win more on average -- switching between strategies with different memory lengths incurs an effective penalty, while switching between strategies of equal memory does not. Agents employing short-memory strategies can outperform agents using long-memory strategies, even in the regime where an equal-memory system would have favored the use of long-memory strategies. Using the many-body 'Crowd-Anticrowd' theory, we obtain analytic expressions which are in good agreement with the observed numerical results. In the context of financial markets, our results suggest that multiple-memory agents have a better chance of identifying price patterns of unknown length and hence will typically have higher winnings.

Effect of Climate Change and Transaction Costs on Performance of a Groundwater Market

NASA Astrophysics Data System (ADS)

Khan, H. F.; Brown, C.

2017-12-01

With surface water resources becoming increasingly stressed, groundwater extraction, much of it unmanaged, has increased globally. Incentive-based policies, such as the cap-and-trade system, have been shown to be useful in the context of groundwater management. Previous research has shown that optimal groundwater markets (i.e. incentives-based policy) outperforms water quotas (command and control policy) with regards to both economic and environmental outcomes. In this work, we investigate whether these advantages of a water market over water quotas hold when assumptions of perfect information are violated due to climate change and hydrogeologic heterogeneity. We also assess whether the benefits of a cap-and-trade system outweigh the costs of implementing it, and how changes in future climate affect the performance a cap-and trade system. We use a sub-basin of the Republican River Basin, overlying the Ogallala aquifer in the High Plains of the United States, as a case study. We develop a multi-agent system model where individual benefits of each self-interested agent are maximized subject to bounds on irrigation requirements and water use permits. This economic model is coupled with a calibrated physically based groundwater model for the study region. Results show that permitting farmers to trade results in increased economic benefits and reduced environmental violations. However, the benefits of trading are dependent on the total allocations and the resulting level of water demand. We quantify third party impacts and environmental externalities for different water allocations, and highlight the unequal distributional effects of uniform water allocations resulting in `winners' and `losers'. The study reveals that high transaction costs can reduce the efficiency of the cap-and-trade system even below that of water quotas. Future changes in climate are shown to significantly influence the dynamics of the water market, and emphasize the need to address climate sensitivity in the setup of water markets.

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

Using Business Process Specification and Agent to Integrate a Scenario Driven Supply Chain

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

Cho, Hyunbo; Kulvatunyou, Boonserm; Jeong, Hanil

2004-07-01

In today's increasingly competitive global market, most enterprises place high priority on reducing order-fulfillment costs, minimizing time-to-market, and maximizing product quality. The desire of businesses to achieve these goals has seen a shift from a make-to-stock paradigm to a make-to-order paradigm. The success of this new paradigm requires robust and efficient supply chain integration and the ability to operate in the business-to-business (B2B) environment. Recent internet-based approaches have enabled instantaneous and secure information sharing among trading partners (i.e., customers, manufacturers, and suppliers). In this paper, we present a framework that enables both integration and B2B operations. This framework uses pre-definedmore » business process specifications (BPS) and agent technologies. The BPS, which specifies a message choreography among the trading partners, is modeled using a modified Unified Modeling Language (UML). The behavior of the enterprise applications within each trading partner -- how they respond to external events specified in the BPS -- is modeled using Petri-nets and implemented as a collection of agents. The concepts and models proposed in this paper should provide the starting point for the formulation of a structured approach to B2B supply chain integration and implementation.« less

An agent-based approach to modelling the effects of extreme events on global food prices

NASA Astrophysics Data System (ADS)

Schewe, Jacob; Otto, Christian; Frieler, Katja

2015-04-01

Extreme climate events such as droughts or heat waves affect agricultural production in major food producing regions and therefore can influence the price of staple foods on the world market. There is evidence that recent dramatic spikes in grain prices were at least partly triggered by actual and/or expected supply shortages. The reaction of the market to supply changes is however highly nonlinear and depends on complex and interlinked processes such as warehousing, speculation, and export restrictions. Here we present for the first time an agent-based modelling framework that accounts, in simplified terms, for these processes and allows to estimate the reaction of world food prices to supply shocks on a short (monthly) timescale. We test the basic model using observed historical supply, demand, and price data of wheat as a major food grain. Further, we illustrate how the model can be used in conjunction with biophysical crop models to assess the effect of future changes in extreme event regimes on the volatility of food prices. In particular, the explicit representation of storage dynamics makes it possible to investigate the potentially nonlinear interaction between simultaneous extreme events in different food producing regions, or between several consecutive events in the same region, which may both occur more frequently under future global warming.

A dynamic agent-based analysis for the environmental impacts of conventional and novel book retailing.

PubMed

Xu, Ming; Allenby, Braden; Kim, Junbeum; Kahhat, Ramzy

2009-04-15

The dynamics of an e-commerce market and the associated environmental impacts from a bottom-up perspective using an agent-based model is explored. A conceptual meta-theory from psychology is adopted to form the behavioral rules of artificial consumers choosing different methods of buying a book, including conventional bookstores, e-commerce, and a proposed self-pick-up option. Given the energy and emissions savings that result from a shift to e-commerce from bookstore purchase, it appears that reductions in environmental impacts are relatively probable. Additionally, our results suggest that the shift to e-commerce is mainly due to the growth of Internet users, which ties energy and emissions savings to Internet penetration. Moreover, under any scenario, the energy and emissions savings will be provided by the introduction of the proposed self-pick-up option. Our model thus provides insights into market behaviors and related environmental impacts of the growing use of e-commerce systems at the retail level, and provides a basis for the development and implementation of more sustainable policies and practices.

Cross-site comparison of land-use decision-making and its consequences across land systems with a generalized agent-based model.

PubMed

Magliocca, Nicholas R; Brown, Daniel G; Ellis, Erle C

2014-01-01

Local changes in land use result from the decisions and actions of land-users within land systems, which are structured by local and global environmental, economic, political, and cultural contexts. Such cross-scale causation presents a major challenge for developing a general understanding of how local decision-making shapes land-use changes at the global scale. This paper implements a generalized agent-based model (ABM) as a virtual laboratory to explore how global and local processes influence the land-use and livelihood decisions of local land-users, operationalized as settlement-level agents, across the landscapes of six real-world test sites. Test sites were chosen in USA, Laos, and China to capture globally-significant variation in population density, market influence, and environmental conditions, with land systems ranging from swidden to commercial agriculture. Publicly available global data were integrated into the ABM to model cross-scale effects of economic globalization on local land-use decisions. A suite of statistics was developed to assess the accuracy of model-predicted land-use outcomes relative to observed and random (i.e. null model) landscapes. At four of six sites, where environmental and demographic forces were important constraints on land-use choices, modeled land-use outcomes were more similar to those observed across sites than the null model. At the two sites in which market forces significantly influenced land-use and livelihood decisions, the model was a poorer predictor of land-use outcomes than the null model. Model successes and failures in simulating real-world land-use patterns enabled the testing of hypotheses on land-use decision-making and yielded insights on the importance of missing mechanisms. The virtual laboratory approach provides a practical framework for systematic improvement of both theory and predictive skill in land change science based on a continual process of experimentation and model enhancement.

Cross-Site Comparison of Land-Use Decision-Making and Its Consequences across Land Systems with a Generalized Agent-Based Model

PubMed Central

Magliocca, Nicholas R.; Brown, Daniel G.; Ellis, Erle C.

2014-01-01

Local changes in land use result from the decisions and actions of land-users within land systems, which are structured by local and global environmental, economic, political, and cultural contexts. Such cross-scale causation presents a major challenge for developing a general understanding of how local decision-making shapes land-use changes at the global scale. This paper implements a generalized agent-based model (ABM) as a virtual laboratory to explore how global and local processes influence the land-use and livelihood decisions of local land-users, operationalized as settlement-level agents, across the landscapes of six real-world test sites. Test sites were chosen in USA, Laos, and China to capture globally-significant variation in population density, market influence, and environmental conditions, with land systems ranging from swidden to commercial agriculture. Publicly available global data were integrated into the ABM to model cross-scale effects of economic globalization on local land-use decisions. A suite of statistics was developed to assess the accuracy of model-predicted land-use outcomes relative to observed and random (i.e. null model) landscapes. At four of six sites, where environmental and demographic forces were important constraints on land-use choices, modeled land-use outcomes were more similar to those observed across sites than the null model. At the two sites in which market forces significantly influenced land-use and livelihood decisions, the model was a poorer predictor of land-use outcomes than the null model. Model successes and failures in simulating real-world land-use patterns enabled the testing of hypotheses on land-use decision-making and yielded insights on the importance of missing mechanisms. The virtual laboratory approach provides a practical framework for systematic improvement of both theory and predictive skill in land change science based on a continual process of experimentation and model enhancement. PMID:24489696

Static and dynamic factors in an information-based multi-asset artificial stock market

NASA Astrophysics Data System (ADS)

Ponta, Linda; Pastore, Stefano; Cincotti, Silvano

2018-02-01

An information-based multi-asset artificial stock market characterized by different types of stocks and populated by heterogeneous agents is presented. In the market, agents trade risky assets in exchange for cash. Beside the amount of cash and of stocks owned, each agent is characterized by sentiments and agents share their sentiments by means of interactions that are determined by sparsely connected networks. A central market maker (clearing house mechanism) determines the price processes for each stock at the intersection of the demand and the supply curves. Single stock price processes exhibit volatility clustering and fat-tailed distribution of returns whereas multivariate price process exhibits both static and dynamic stylized facts, i.e., the presence of static factors and common trends. Static factors are studied making reference to the cross-correlation of returns of different stocks. The common trends are investigated considering the variance-covariance matrix of prices. Results point out that the probability distribution of eigenvalues of the cross-correlation matrix of returns shows the presence of sectors, similar to those observed on real empirical data. As regarding the dynamic factors, the variance-covariance matrix of prices point out a limited number of assets prices series that are independent integrated processes, in close agreement with the empirical evidence of asset price time series of real stock markets. These results remarks the crucial dependence of statistical properties of multi-assets stock market on the agents' interaction structure.

Simulating farmer behaviour under water markets

NASA Astrophysics Data System (ADS)

Padula, SIlvia; Erfani, Tohid; Henriques, Catarina; Maziotis, Alexandros; Garbe, Jennifer; Swinscoe, Thomas; Harou, Julien; Weatherhead, Keith; Beevers, Lindsay; Fleskens, Luuk

2015-04-01

Increasing water scarcity may lead water managers to consider alternative approaches to water allocation including water markets. One concern with markets is how will specific sectors interact with a potential water market, when will they gain or loose water and will they benefit economically - why, when and how? The behaviours of different individual abstractors or institutional actors under water markets is of interest to regulators who seek to design effective market policies which satisfy multiple stakeholder groups. In this study we consider two dozen agricultural water users in eastern England (Nar basin). Using partially synthetic but regionally representative cropping and irrigation data we simulate the buying and selling behaviour of farmers on a weekly basis over multiple years. The impact of on-farm water storage is assessed for farmers who own a reservoir. A river-basin-scale hydro-economic multi-agent model is used that represents individual abstractors and can simulate a spot market under various licensing regimes. Weekly varying economic demand curves for water are calibrated based on historical climate and water use data. The model represents the trade-off between current use value and expected gains from trade to reach weekly decisions. Early results are discussed and model limitations and possible extensions are presented.

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.

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.

Essays in the California electricity reserves markets

NASA Astrophysics Data System (ADS)

Metaxoglou, Konstantinos

This dissertation examines inefficiencies in the California electricity reserves markets. In Chapter 1, I use the information released during the investigation of the state's electricity crisis of 2000 and 2001 by the Federal Energy Regulatory Commission to diagnose allocative inefficiencies. Building upon the work of Wolak (2000), I calculate a lower bound for the sellers' price-cost margins using the inverse elasticities of their residual demand curves. The downward bias in my estimates stems from the fact that I don't account for the hierarchical substitutability of the reserve types. The margins averaged at least 20 percent for the two highest quality types of reserves, regulation and spinning, generating millions of dollars in transfers to a handful of sellers. I provide evidence that the deviations from marginal cost pricing were due to the markets' high concentration and a principal-agent relationship that emerged from their design. In Chapter 2, I document systematic differences between the markets' day- and hour-ahead prices. I use a high-dimensional vector moving average model to estimate the premia and conduct correct inferences. To obtain exact maximum likelihood estimates of the model, I employ the EM algorithm that I develop in Chapter 3. I uncover significant day-ahead premia, which I attribute to market design characteristics too. On the demand side, the market design established a principal-agent relationship between the markets' buyers (principal) and their supervisory authority (agent). The agent had very limited incentives to shift reserve purchases to the lower priced hour-ahead markets. On the supply side, the market design raised substantial entry barriers by precluding purely speculative trading and by introducing a complicated code of conduct that induced uncertainty about which actions were subject to regulatory scrutiny. In Chapter 3, I introduce a state-space representation for vector autoregressive moving average models that enables exact maximum likelihood estimation using the EM algorithm. Moreover, my algorithm uses only analytical expressions; it requires the Kalman filter and a fixed-interval smoother in the E step and least squares-type regression in the M step. In contrast, existing maximum likelihood estimation methods require numerical differentiation, both for univariate and multivariate models.

Transition from Exponential to Power Law Income Distributions in a Chaotic Market

NASA Astrophysics Data System (ADS)

Pellicer-Lostao, Carmen; Lopez-Ruiz, Ricardo

Economy is demanding new models, able to understand and predict the evolution of markets. To this respect, Econophysics offers models of markets as complex systems, that try to comprehend macro-, system-wide states of the economy from the interaction of many agents at micro-level. One of these models is the gas-like model for trading markets. This tries to predict money distributions in closed economies and quite simply, obtains the ones observed in real economies. However, it reveals technical hitches to explain the power law distribution, observed in individuals with high incomes. In this work, nonlinear dynamics is introduced in the gas-like model in an effort to overcomes these flaws. A particular chaotic dynamics is used to break the pairing symmetry of agents (i, j) ⇔ (j, i). The results demonstrate that a "chaotic gas-like model" can reproduce the Exponential and Power law distributions observed in real economies. Moreover, it controls the transition between them. This may give some insight of the micro-level causes that originate unfair distributions of money in a global society. Ultimately, the chaotic model makes obvious the inherent instability of asymmetric scenarios, where sinks of wealth appear and doom the market to extreme inequality.

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.

Stock markets as Minority Games: cognitive heterogeneity and equilibrium emergence

NASA Astrophysics Data System (ADS)

Brandouy, O.

2005-04-01

Standard finance theory generally assumes homogeneous agents relatively to their preferences, heuristics and investment strategies. We propose to study, in an agent-based simulation, the emergence of equilibrium under various heterogeneous conditions. Market interaction is stylized with the Minority Game representation. It is shown that inductive rational equilibrium emerges even though agents do not share the same representations of the value. This may lead to consider again the roots of EMH and REH.

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.

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

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

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

Kinetic market models with single commodity having price fluctuations

NASA Astrophysics Data System (ADS)

Chatterjee, A.; Chakrabarti, B. K.

2006-12-01

We study here numerically the behavior of an ideal gas like model of markets having only one non-consumable commodity. We investigate the behavior of the steady-state distributions of money, commodity and total wealth, as the dynamics of trading or exchange of money and commodity proceeds, with local (in time) fluctuations in the price of the commodity. These distributions are studied in markets with agents having uniform and random saving factors. The self-organizing features in money distribution are similar to the cases without any commodity (or with consumable commodities), while the commodity distribution shows an exponential decay. The wealth distribution shows interesting behavior: gamma like distribution for uniform saving propensity and has the same power-law tail, as that of the money distribution, for a market with agents having random saving propensity.

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.

Illusory versus genuine control in agent-based games

NASA Astrophysics Data System (ADS)

Satinover, J. B.; Sornette, D.

2009-02-01

In the Minority, Majority and Dollar Games (MG, MAJG, G) agents compete for rewards, acting in accord with the previously best-performing of their strategies. Different aspects/kinds of real-world markets are modelled by these games. In the MG, agents compete for scarce resources; in the MAJG agents imitate the group to exploit a trend; in the G agents attempt to predict and benefit both from trends and changes in the direction of a market. It has been previously shown that in the MG for a reasonable number of preliminary time steps preceding equilibrium (Time Horizon MG, THMG), agents’ attempt to optimize their gains by active strategy selection is “illusory”: the hypothetical gains of their strategies is greater on average than agents’ actual average gains. Furthermore, if a small proportion of agents deliberately choose and act in accord with their seemingly worst performing strategy, these outperform all other agents on average, and even attain mean positive gain, otherwise rare for agents in the MG. This latter phenomenon raises the question as to how well the optimization procedure works in the THMAJG and THG. We demonstrate that the illusion of control is absent in THMAJG and THG. This provides further clarification of the kinds of situations subject to genuine control, and those not, in set-ups a priori defined to emphasize the importance of optimization.

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 Markovian model market—Akerlof's lemons and the asymmetry of information

NASA Astrophysics Data System (ADS)

Tilles, Paulo F. C.; Ferreira, Fernando F.; Francisco, Gerson; Pereira, Carlos de B.; Sarti, Flavia M.

2011-07-01

In this work we study an agent based model to investigate the role of asymmetric information degrees for market evolution. This model is quite simple and may be treated analytically since the consumers evaluate the quality of a certain good taking into account only the quality of the last good purchased plus her perceptive capacity β. As a consequence, the system evolves according to a stationary Markov chain. The value of a good offered by the firms increases along with quality according to an exponent α, which is a measure of the technology. It incorporates all the technological capacity of the production systems such as education, scientific development and techniques that change the productivity rates. The technological level plays an important role to explain how the asymmetry of information may affect the market evolution in this model. We observe that, for high technological levels, the market can detect adverse selection. The model allows us to compute the maximum asymmetric information degree before the market collapses. Below this critical point the market evolves during a limited period of time and then dies out completely. When β is closer to 1 (symmetric information), the market becomes more profitable for high quality goods, although high and low quality markets coexist. The maximum asymmetric information level is a consequence of an ergodicity breakdown in the process of quality evaluation.

The use of artificially intelligent agents with bounded rationality in the study of economic markets

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

Rajan, V.; Slagle, J.R.

The concepts of {open_quote}knowledge{close_quote} and {open_quote}rationality{close_quote} are of central importance to fields of science that are interested in human behavior and learning, such as artificial intelligence, economics, and psychology. The similarity between artificial intelligence and economics - both are concerned with intelligent thought, rational behavior, and the use and acquisition of knowledge - has led to the use of economic models as a paradigm for solving problems in distributed artificial intelligence (DAI) and multi agent systems (MAS). What we propose is the opposite; the use of artificial intelligence in the study of economic markets. Over the centuries various theories ofmore » market behavior have been advanced. The prevailing theory holds that an asset`s current price converges to the risk adjusted value of the rationally expected dividend stream. While this rational expectations model holds in equilibrium or near-equilibrium conditions, it does not sufficiently explain conditions of market disequilibrium. An example of market disequilibrium is the phenomenon of a speculative bubble. We present an example of using artificially intelligent agents with bounded rationality in the study of speculative bubbles.« less

Wealth distribution across communities of adaptive financial agents

NASA Astrophysics Data System (ADS)

DeLellis, Pietro; Garofalo, Franco; Lo Iudice, Francesco; Napoletano, Elena

2015-08-01

This paper studies the trading volumes and wealth distribution of a novel agent-based model of an artificial financial market. In this model, heterogeneous agents, behaving according to the Von Neumann and Morgenstern utility theory, may mutually interact. A Tobin-like tax (TT) on successful investments and a flat tax are compared to assess the effects on the agents’ wealth distribution. We carry out extensive numerical simulations in two alternative scenarios: (i) a reference scenario, where the agents keep their utility function fixed, and (ii) a focal scenario, where the agents are adaptive and self-organize in communities, emulating their neighbours by updating their own utility function. Specifically, the interactions among the agents are modelled through a directed scale-free network to account for the presence of community leaders, and the herding-like effect is tested against the reference scenario. We observe that our model is capable of replicating the benefits and drawbacks of the two taxation systems and that the interactions among the agents strongly affect the wealth distribution across the communities. Remarkably, the communities benefit from the presence of leaders with successful trading strategies, and are more likely to increase their average wealth. Moreover, this emulation mechanism mitigates the decrease in trading volumes, which is a typical drawback of TTs.

Study on system dynamics of evolutionary mix-game models

NASA Astrophysics Data System (ADS)

Gou, Chengling; Guo, Xiaoqian; Chen, Fang

2008-11-01

Mix-game model is ameliorated from an agent-based MG model, which is used to simulate the real financial market. Different from MG, there are two groups of agents in Mix-game: Group 1 plays a majority game and Group 2 plays a minority game. These two groups of agents have different bounded abilities to deal with historical information and to count their own performance. In this paper, we modify Mix-game model by assigning the evolution abilities to agents: if the winning rates of agents are smaller than a threshold, they will copy the best strategies the other agent has; and agents will repeat such evolution at certain time intervals. Through simulations this paper finds: (1) the average winning rates of agents in Group 1 and the mean volatilities increase with the increases of the thresholds of Group 1; (2) the average winning rates of both groups decrease but the mean volatilities of system increase with the increase of the thresholds of Group 2; (3) the thresholds of Group 2 have greater impact on system dynamics than the thresholds of Group 1; (4) the characteristics of system dynamics under different time intervals of strategy change are similar to each other qualitatively, but they are different quantitatively; (5) As the time interval of strategy change increases from 1 to 20, the system behaves more and more stable and the performances of agents in both groups become better also.

Using trading strategies to detect phase transitions in financial markets.

PubMed

Forró, Z; Woodard, R; Sornette, D

2015-04-01

We show that the log-periodic power law singularity model (LPPLS), a mathematical embodiment of positive feedbacks between agents and of their hierarchical dynamical organization, has a significant predictive power in financial markets. We find that LPPLS-based strategies significantly outperform the randomized ones and that they are robust with respect to a large selection of assets and time periods. The dynamics of prices thus markedly deviate from randomness in certain pockets of predictability that can be associated with bubble market regimes. Our hybrid approach, marrying finance with the trading strategies, and critical phenomena with LPPLS, demonstrates that targeting information related to phase transitions enables the forecast of financial bubbles and crashes punctuating the dynamics of prices.

Using trading strategies to detect phase transitions in financial markets

NASA Astrophysics Data System (ADS)

Forró, Z.; Woodard, R.; Sornette, D.

2015-04-01

We show that the log-periodic power law singularity model (LPPLS), a mathematical embodiment of positive feedbacks between agents and of their hierarchical dynamical organization, has a significant predictive power in financial markets. We find that LPPLS-based strategies significantly outperform the randomized ones and that they are robust with respect to a large selection of assets and time periods. The dynamics of prices thus markedly deviate from randomness in certain pockets of predictability that can be associated with bubble market regimes. Our hybrid approach, marrying finance with the trading strategies, and critical phenomena with LPPLS, demonstrates that targeting information related to phase transitions enables the forecast of financial bubbles and crashes punctuating the dynamics of prices.

>From naive to sophisticated behavior in multiagents-based financial market models

NASA Astrophysics Data System (ADS)

Mansilla, R.

2000-09-01

The behavior of physical complexity and mutual information function of the outcome of a model of heterogeneous, inductive rational agents inspired by the El Farol Bar problem and the Minority Game is studied. The first magnitude is a measure rooted in the Kolmogorov-Chaitin theory and the second a measure related to Shannon's information entropy. Extensive computer simulations were done, as a result of which, is proposed an ansatz for physical complexity of the type C(l)=lα and the dependence of the exponent α from the parameters of the model is established. The accuracy of our results and the relationship with the behavior of mutual information function as a measure of time correlation of agents choice are discussed.

A Market-Based Approach to Multi-factory Scheduling

NASA Astrophysics Data System (ADS)

Vytelingum, Perukrishnen; Rogers, Alex; MacBeth, Douglas K.; Dutta, Partha; Stranjak, Armin; Jennings, Nicholas R.

In this paper, we report on the design of a novel market-based approach for decentralised scheduling across multiple factories. Specifically, because of the limitations of scheduling in a centralised manner - which requires a center to have complete and perfect information for optimality and the truthful revelation of potentially commercially private preferences to that center - we advocate an informationally decentralised approach that is both agile and dynamic. In particular, this work adopts a market-based approach for decentralised scheduling by considering the different stakeholders representing different factories as self-interested, profit-motivated economic agents that trade resources for the scheduling of jobs. The overall schedule of these jobs is then an emergent behaviour of the strategic interaction of these trading agents bidding for resources in a market based on limited information and their own preferences. Using a simple (zero-intelligence) bidding strategy, we empirically demonstrate that our market-based approach achieves a lower bound efficiency of 84%. This represents a trade-off between a reasonable level of efficiency (compared to a centralised approach) and the desirable benefits of a decentralised solution.

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

An Ss Model with Adverse Selection.

ERIC Educational Resources Information Center

House, Christopher L.; Leahy, John V.

2004-01-01

We present a model of the market for a used durable in which agents face fixed costs of adjustment, the magnitude of which depends on the degree of adverse selection in the secondary market. We find that, unlike typical models, the sS bands in our model contract as the variance of the shock increases. We also analyze a dynamic version of the model…

Combining agent-based modeling and life cycle assessment for the evaluation of mobility policies.

PubMed

Florent, Querini; Enrico, Benetto

2015-02-03

This article presents agent-based modeling (ABM) as a novel approach for consequential life cycle assessment (C-LCA) of large scale policies, more specifically mobility-related policies. The approach is validated at the Luxembourgish level (as a first case study). The agent-based model simulates the car market (sales, use, and dismantling) of the population of users in the period 2013-2020, following the implementation of different mobility policies and available electric vehicles. The resulting changes in the car fleet composition as well as the hourly uses of the vehicles are then used to derive consistent LCA results, representing the consequences of the policies. Policies will have significant environmental consequences: when using ReCiPe2008, we observe a decrease of global warming, fossil depletion, acidification, ozone depletion, and photochemical ozone formation and an increase of metal depletion, ionizing radiations, marine eutrophication, and particulate matter formation. The study clearly shows that the extrapolation of LCA results for the circulating fleet at national scale following the introduction of the policies from the LCAs of single vehicles by simple up-scaling (using hypothetical deployment scenarios) would be flawed. The inventory has to be directly conducted at full scale and to this aim, ABM is indeed a promising approach, as it allows identifying and quantifying emerging effects while modeling the Life Cycle Inventory of vehicles at microscale through the concept of agents.

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.

A Study on Market-based Strategic Procurement Planning in Convergent Supply Networks

NASA Astrophysics Data System (ADS)

Opadiji, Jayeola Femi; Kaihara, Toshiya

We present a market-based decentralized approach which uses a market-oriented programming algorithm to obtain Pareto-optimal allocation of resources traded among agents which represent enterprise units in a supply network. The proposed method divides the network into a series of Walrsian markets in order to obtain procurement budgets for enterprises in the network. An interaction protocol based on market value propagation is constructed to coordinate the flow of resources across the network layers. The method mitigates the effect of product complementarity in convergent network by allowing for enterprises to hold private valuations of resources in the markets.

Modeling of the competition life cycle using the software complex of cellular automata PyCAlab

NASA Astrophysics Data System (ADS)

Berg, D. B.; Beklemishev, K. A.; Medvedev, A. N.; Medvedeva, M. A.

2015-11-01

The aim of the work is to develop a numerical model of the life cycle of competition on the basis of software complex cellular automata PyCAlab. The model is based on the general patterns of growth of various systems in resource-limited settings. At examples it is shown that the period of transition from an unlimited growth of the market agents to the stage of competitive growth takes quite a long time and may be characterized as monotonic. During this period two main strategies of competitive selection coexist: 1) capture of maximum market space with any reasonable costs; 2) saving by reducing costs. The obtained results allow concluding that the competitive strategies of companies must combine two mentioned types of behavior, and this issue needs to be given adequate attention in the academic literature on management. The created numerical model may be used for market research when developing of the strategies for promotion of new goods and services.

Approximating the 0-1 Multiple Knapsack Problem with Agent Decomposition and Market Negotiation

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

Smolinski, B.

The 0-1 multiple knapsack problem appears in many domains from financial portfolio management to cargo ship stowing. Methods for solving it range from approximate algorithms, such as greedy algorithms, to exact algorithms, such as branch and bound. Approximate algorithms have no bounds on how poorly they perform and exact algorithms can suffer from exponential time and space complexities with large data sets. This paper introduces a market model based on agent decomposition and market auctions for approximating the 0-1 multiple knapsack problem, and an algorithm that implements the model (M(x)). M(x) traverses the solution space rather than getting caught inmore » a local maximum, overcoming an inherent problem of many greedy algorithms. The use of agents ensures that infeasible solutions are not considered while traversing the solution space and that traversal of the solution space is not just random, but is also directed. M(x) is compared to a bound and bound algorithm (BB) and a simple greedy algorithm with a random shuffle (G(x)). The results suggest that M(x) is a good algorithm for approximating the 0-1 Multiple Knapsack problem. M(x) almost always found solutions that were close to optimal in a fraction of the time it took BB to run and with much less memory on large test data sets. M(x) usually performed better than G(x) on hard problems with correlated data.« less

Adiabatic theory for the population distribution in the evolutionary minority game

NASA Astrophysics Data System (ADS)

Chen, Kan; Wang, Bing-Hong; Yuan, Baosheng

2004-02-01

We study the evolutionary minority game (EMG) using a statistical mechanics approach. We derive a theory for the steady-state population distribution of the agents. The theory is based on an “adiabatic approximation” in which short time fluctuations in the population distribution are integrated out to obtain an effective equation governing the steady-state distribution. We discover the mechanism for the transition from segregation (into opposing groups) to clustering (towards cautious behaviors). The transition is determined by two generic factors: the market impact (of the agents’ own actions) and the short time market inefficiency (arbitrage opportunities) due to fluctuations in the numbers of agents using opposite strategies. A large market impact favors “extreme” players who choose fixed opposite strategies, while large market inefficiency favors cautious players. The transition depends on the number of agents (N) and the effective rate of strategy switching. When N is small, the market impact is relatively large; this favors the extreme behaviors. Frequent strategy switching, on the other hand, leads to a clustering of the cautious agents.

Agent Based Modeling of Air Carrier Behavior for Evaluation of Technology Equipage and Adoption

NASA Technical Reports Server (NTRS)

Horio, Brant M.; DeCicco, Anthony H.; Stouffer, Virginia L.; Hasan, Shahab; Rosenbaum, Rebecca L.; Smith, Jeremy C.

2014-01-01

As part of ongoing research, the National Aeronautics and Space Administration (NASA) and LMI developed a research framework to assist policymakers in identifying impacts on the U.S. air transportation system (ATS) of potential policies and technology related to the implementation of the Next Generation Air Transportation System (NextGen). This framework, called the Air Transportation System Evolutionary Simulation (ATS-EVOS), integrates multiple models into a single process flow to best simulate responses by U.S. commercial airlines and other ATS stakeholders to NextGen-related policies, and in turn, how those responses impact the ATS. Development of this framework required NASA and LMI to create an agent-based model of airline and passenger behavior. This Airline Evolutionary Simulation (AIRLINE-EVOS) models airline decisions about tactical airfare and schedule adjustments, and strategic decisions related to fleet assignments, market prices, and equipage. AIRLINE-EVOS models its own heterogeneous population of passenger agents that interact with airlines; this interaction allows the model to simulate the cycle of action-reaction as airlines compete with each other and engage passengers. We validated a baseline configuration of AIRLINE-EVOS against Airline Origin and Destination Survey (DB1B) data and subject matter expert opinion, and we verified the ATS-EVOS framework and agent behavior logic through scenario-based experiments. These experiments demonstrated AIRLINE-EVOS's capabilities in responding to an input price shock in fuel prices, and to equipage challenges in a series of analyses based on potential incentive policies for best equipped best served, optimal-wind routing, and traffic management initiative exemption concepts..

Agent-based simulation for human-induced hazard analysis.

PubMed

Bulleit, William M; Drewek, Matthew W

2011-02-01

Terrorism could be treated as a hazard for design purposes. For instance, the terrorist hazard could be analyzed in a manner similar to the way that seismic hazard is handled. No matter how terrorism is dealt with in the design of systems, the need for predictions of the frequency and magnitude of the hazard will be required. And, if the human-induced hazard is to be designed for in a manner analogous to natural hazards, then the predictions should be probabilistic in nature. The model described in this article is a prototype model that used agent-based modeling (ABM) to analyze terrorist attacks. The basic approach in this article of using ABM to model human-induced hazards has been preliminarily validated in the sense that the attack magnitudes seem to be power-law distributed and attacks occur mostly in regions where high levels of wealth pass through, such as transit routes and markets. The model developed in this study indicates that ABM is a viable approach to modeling socioeconomic-based infrastructure systems for engineering design to deal with human-induced hazards. © 2010 Society for Risk Analysis.

Toward Value-Based Pricing to Boost Cancer Research and Innovation.

PubMed

Ocana, Alberto; Amir, Eitan; Tannock, Ian F

2016-06-01

The high market price of new anticancer agents has stimulated debate about the long-term sustainability of healthcare systems and whether these new agents can continue to be supported by public healthcare or by private insurers. In addition, some drugs have been approved with limited clinical benefit, raising concerns about setting a minimum requirement for medical benefit. Options to resolve these problems include raising the bar for approval of new drugs and/or pricing of new agents based on the medical benefit that they offer to patients. In this commentary, we suggest that new agents should be marketed in a two-step process that would include first the approval of the new drug by the regulatory agencies and second the introduction of a market price based on the medical benefit that the new intervention offers to patients. Introduction of value-based pricing would maintain the sustainability of health care systems and would improve drug development, as it would pressure pharmaceutical companies to become more innovative and avoid the development of compounds with limited benefit. Value-based pricing could also stimulate the funding of research directed to development of new anticancer drugs with novel mechanisms of action. Cancer Res; 76(11); 3127-9. ©2016 AACR. ©2016 American Association for Cancer Research.

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

An Agent-Based Model of Private Woodland Owner Management Behavior Using Social Interactions, Information Flow, and Peer-To-Peer Networks

PubMed Central

Huff, Emily Silver; Leahy, Jessica E.; Hiebeler, David; Weiskittel, Aaron R.; Noblet, Caroline L.

2015-01-01

Privately owned woodlands are an important source of timber and ecosystem services in North America and worldwide. Impacts of management on these ecosystems and timber supply from these woodlands are difficult to estimate because complex behavioral theory informs the owner’s management decisions. The decision-making environment consists of exogenous market factors, internal cognitive processes, and social interactions with fellow landowners, foresters, and other rural community members. This study seeks to understand how social interactions, information flow, and peer-to-peer networks influence timber harvesting behavior using an agent-based model. This theoretical model includes forested polygons in various states of ‘harvest readiness’ and three types of agents: forest landowners, foresters, and peer leaders (individuals trained in conservation who use peer-to-peer networking). Agent rules, interactions, and characteristics were parameterized with values from existing literature and an empirical survey of forest landowner attitudes, intentions, and demographics. The model demonstrates that as trust in foresters and peer leaders increases, the percentage of the forest that is harvested sustainably increases. Furthermore, peer leaders can serve to increase landowner trust in foresters. Model output and equations will inform forest policy and extension/outreach efforts. The model also serves as an important testing ground for new theories of landowner decision making and behavior. PMID:26562429

Turnover, account value and diversification of real traders: evidence of collective portfolio optimizing behavior

NASA Astrophysics Data System (ADS)

Morton de Lachapelle, David; Challet, Damien

2010-07-01

Despite the availability of very detailed data on financial markets, agent-based modeling is hindered by the lack of information about real trader behavior. This makes it impossible to validate agent-based models, which are thus reverse-engineering attempts. This work is a contribution towards building a set of stylized facts about the traders themselves. Using the client database of Swissquote Bank SA, the largest online Swiss broker, we find empirical relationships between turnover, account values and the number of assets in which a trader is invested. A theory based on simple mean-variance portfolio optimization that crucially includes variable transaction costs is able to reproduce faithfully the observed behaviors. We finally argue that our results bring to light the collective ability of a population to construct a mean-variance portfolio that takes into account the structure of transaction costs.

Embodied Agents, E-SQ and Stickiness: Improving Existing Cognitive and Affective Models

NASA Astrophysics Data System (ADS)

de Diesbach, Pablo Brice

This paper synthesizes results from two previous studies of embodied virtual agents on commercial websites. We analyze and criticize the proposed models and discuss the limits of the experimental findings. Results from other important research in the literature are integrated. We also integrate concepts from profound, more business-related, analysis that deepens on the mechanisms of rhetoric in marketing and communication, and the possible role of E-SQ in man-agent interaction. We finally suggest a refined model for the impacts of these agents on web site users, and limits of the improved model are commented.

Rationality, irrationality and escalating behavior in lowest unique bid auctions.

PubMed

Radicchi, Filippo; Baronchelli, Andrea; Amaral, Luís A N

2012-01-01

Information technology has revolutionized the traditional structure of markets. The removal of geographical and time constraints has fostered the growth of online auction markets, which now include millions of economic agents worldwide and annual transaction volumes in the billions of dollars. Here, we analyze bid histories of a little studied type of online auctions--lowest unique bid auctions. Similarly to what has been reported for foraging animals searching for scarce food, we find that agents adopt Lévy flight search strategies in their exploration of "bid space". The Lévy regime, which is characterized by a power-law decaying probability distribution of step lengths, holds over nearly three orders of magnitude. We develop a quantitative model for lowest unique bid online auctions that reveals that agents use nearly optimal bidding strategies. However, agents participating in these auctions do not optimize their financial gain. Indeed, as long as there are many auction participants, a rational profit optimizing agent would choose not to participate in these auction markets.

Rationality, Irrationality and Escalating Behavior in Lowest Unique Bid Auctions

PubMed Central

Radicchi, Filippo; Baronchelli, Andrea; Amaral, Luís A. N.

2012-01-01

Information technology has revolutionized the traditional structure of markets. The removal of geographical and time constraints has fostered the growth of online auction markets, which now include millions of economic agents worldwide and annual transaction volumes in the billions of dollars. Here, we analyze bid histories of a little studied type of online auctions – lowest unique bid auctions. Similarly to what has been reported for foraging animals searching for scarce food, we find that agents adopt Lévy flight search strategies in their exploration of “bid space”. The Lévy regime, which is characterized by a power-law decaying probability distribution of step lengths, holds over nearly three orders of magnitude. We develop a quantitative model for lowest unique bid online auctions that reveals that agents use nearly optimal bidding strategies. However, agents participating in these auctions do not optimize their financial gain. Indeed, as long as there are many auction participants, a rational profit optimizing agent would choose not to participate in these auction markets. PMID:22279553

Greed, fear and stock market dynamics

NASA Astrophysics Data System (ADS)

Westerhoff, Frank H.

2004-11-01

We present a behavioral stock market model in which traders are driven by greed and fear. In general, the agents optimistically believe in rising markets and thus buy stocks. But if stock prices change too abruptly, they panic and sell stocks. Our model mimics some stylized facts of stock market dynamics: (1) stock prices increase over time, (2) stock markets sometimes crash, (3) stock prices show little pair correlation between successive daily changes, and (4) periods of low volatility alternate with periods of high volatility. A strong feature of the model is that stock prices completely evolve according to a deterministic low-dimensional nonlinear law of motion.

Burst and inter-burst duration statistics as empirical test of long-range memory in the financial markets

NASA Astrophysics Data System (ADS)

Gontis, V.; Kononovicius, A.

2017-10-01

We address the problem of long-range memory in the financial markets. There are two conceptually different ways to reproduce power-law decay of auto-correlation function: using fractional Brownian motion as well as non-linear stochastic differential equations. In this contribution we address this problem by analyzing empirical return and trading activity time series from the Forex. From the empirical time series we obtain probability density functions of burst and inter-burst duration. Our analysis reveals that the power-law exponents of the obtained probability density functions are close to 3 / 2, which is a characteristic feature of the one-dimensional stochastic processes. This is in a good agreement with earlier proposed model of absolute return based on the non-linear stochastic differential equations derived from the agent-based herding model.

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.

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.

Minority games and stylized facts

NASA Astrophysics Data System (ADS)

Challet, Damien; Marsili, Matteo; Zhang, Yi-Cheng

2001-10-01

The minority game is a generic model of competing adaptive agents, which is often believed to be a model of financial markets. We discuss to which extent this is a reasonable statement, and present minimal modifications that make this model reproduce stylized facts. The resulting model shows that without speculators, prices follow random walks, and that stylized facts disappear if enough speculators take into account their market impact.

Deducing the multi-trader population driving a financial market

NASA Astrophysics Data System (ADS)

Gupta, Nachi; Hauser, Raphael; Johnson, Neil

2005-12-01

We have previously laid out a basic framework for predicting financial movements and pockets of predictability by tracking the distribution of a multi-trader population playing on an artificial financial market model. This work explores extensions to this basic framework. We allow for more intelligent agents with a richer strategy set, and we no longer constrain the distribution over these agents to a probability space. We then introduce a fusion scheme which accounts for multiple runs of randomly chosen sets of possible agent types. We also discuss a mechanism for bias removal on the estimates.

Stock market speculation: Spontaneous symmetry breaking of economic valuation

NASA Astrophysics Data System (ADS)

Sornette, Didier

2000-09-01

Firm foundation theory estimates a security's firm fundamental value based on four determinants: expected growth rate, expected dividend payout, the market interest rate and the degree of risk. In contrast, other views of decision-making in the stock market, using alternatives such as human psychology and behavior, bounded rationality, agent-based modeling and evolutionary game theory, expound that speculative and crowd behavior of investors may play a major role in shaping market prices. Here, we propose that the two views refer to two classes of companies connected through a "phase transition". Our theory is based on (1) the identification of the fundamental parity symmetry of prices (p→-p), which results from the relative direction of payment flux compared to commodity flux and (2) the observation that a company's risk-adjusted growth rate discounted by the market interest rate behaves as a control parameter for the observable price. We find a critical value of this control parameter at which a spontaneous symmetry-breaking of prices occurs, leading to a spontaneous valuation in absence of earnings, similarly to the emergence of a spontaneous magnetization in Ising models in absence of a magnetic field. The low growth rate phase is described by the firm foundation theory while the large growth rate phase is the regime of speculation and crowd behavior. In practice, while large "finite-time horizon" effects round off the predicted singularities, our symmetry-breaking speculation theory accounts for the apparent over-pricing and the high volatility of fast growing companies on the stock markets.

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.

Meeting Rural Demand: A Case for Combining Community-Based Distribution and Social Marketing of Injectable Contraceptives in Tigray, Ethiopia

PubMed Central

Prata, Ndola; Weidert, Karen; Fraser, Ashley; Gessessew, Amanuel

2013-01-01

Background In Sub-Saharan Africa, policy changes have begun to pave the way for community distribution of injectable contraceptives but sustaining such efforts remains challenging. Combining social marketing with community-based distribution provides an opportunity to recover some program costs and compensate workers with proceeds from contraceptive sales. This paper proposes a model for increasing access to injectable contraceptives in rural settings by using community-based distributers as social marketing agents and incorporating financing systems to improve sustainability. Methods This intervention was implemented in three districts of the Central Zone of Tigray, Ethiopia and program data has been collected from November 2011 through October 2012. A total of 137 Community Based Reproductive Health Agents (CBRHAs) were trained to provide injectable contraceptives and were provided with a loan of 25 injectable contraceptives from a drug revolving fund, created with project funds. The price of a single dose credited to a CBRHA was 3 birr ($0.17) and they provide injections to women for 5 birr ($0.29), determined with willingness-to-pay data. Social marketing was used to create awareness and generate demand. Both quantitative and qualitative methods were used to examine important feasibility aspects of the intervention. Results Forty-four percent of CBRHAs were providing family planning methods at the time of the training and 96% believed providing injectable contraceptives would improve their services. By October 2012, 137 CBRHAs had successfully completed training and provided 2541 injections. Of total injections, 47% were provided to new users of injectable contraceptives. Approximately 31% of injections were given for free to the poorest women, including adolescents. Conclusions Insights gained from the first year of implementation of the model provide a framework for further expansion in Tigray, Ethiopia. Our experience highlights how program planners can tailor interventions to match family planning preferences and create more sustainable contraceptive service provision with greater impact. PMID:23874767

Meeting rural demand: a case for combining community-based distribution and social marketing of injectable contraceptives in Tigray, Ethiopia.

PubMed

Prata, Ndola; Weidert, Karen; Fraser, Ashley; Gessessew, Amanuel

2013-01-01

In Sub-Saharan Africa, policy changes have begun to pave the way for community distribution of injectable contraceptives but sustaining such efforts remains challenging. Combining social marketing with community-based distribution provides an opportunity to recover some program costs and compensate workers with proceeds from contraceptive sales. This paper proposes a model for increasing access to injectable contraceptives in rural settings by using community-based distributers as social marketing agents and incorporating financing systems to improve sustainability. This intervention was implemented in three districts of the Central Zone of Tigray, Ethiopia and program data has been collected from November 2011 through October 2012. A total of 137 Community Based Reproductive Health Agents (CBRHAs) were trained to provide injectable contraceptives and were provided with a loan of 25 injectable contraceptives from a drug revolving fund, created with project funds. The price of a single dose credited to a CBRHA was 3 birr ($0.17) and they provide injections to women for 5 birr ($0.29), determined with willingness-to-pay data. Social marketing was used to create awareness and generate demand. Both quantitative and qualitative methods were used to examine important feasibility aspects of the intervention. Forty-four percent of CBRHAs were providing family planning methods at the time of the training and 96% believed providing injectable contraceptives would improve their services. By October 2012, 137 CBRHAs had successfully completed training and provided 2541 injections. Of total injections, 47% were provided to new users of injectable contraceptives. Approximately 31% of injections were given for free to the poorest women, including adolescents. Insights gained from the first year of implementation of the model provide a framework for further expansion in Tigray, Ethiopia. Our experience highlights how program planners can tailor interventions to match family planning preferences and create more sustainable contraceptive service provision with greater impact.

Evaluation of Market Design Agents: The Mertacor Perspective

NASA Astrophysics Data System (ADS)

Stavrogiannis, Lampros C.; Mitkas, Pericles A.

The annual Trading Agent Competition for Market Design, CAT, provides a testbed to study the mechanisms that modern stock exchanges use in their effort to attract potential traders while maximizing their profit. This paper presents an evaluation of the agents that participated in the 2008 competition. The evaluation is based on the analysis of the CAT finals as well as on the results obtained from post-tournament experiments. We present Mertacor, our entrant for 2008, and compare it with the other available agents. In addition, we introduce a simple yet effective way of computing the global competitive equilibrium that Mertacor utilizes and discuss its importance for the game.

The selection of adhesive systems for resin-based luting agents.

PubMed

Carville, Rebecca; Quinn, Frank

2008-01-01

The use of resin-based luting agents is ever expanding with the development of adhesive dentistry. A multitude of different adhesive systems are used with resin-based luting agents, and new products are introduced to the market frequently. Traditional adhesives generally required a multiple step bonding procedure prior to cementing with active resin-based luting materials; however, combined agents offer a simple application procedure. Self-etching 'all-in-one' systems claim that there is no need for the use of a separate adhesive process. The following review addresses the advantages and disadvantages of the available adhesive systems used with resin-based luting agents.

Theory of the evolutionary minority game

NASA Astrophysics Data System (ADS)

Lo, T. S.; Hui, P. M.; Johnson, N. F.

2000-09-01

We present a theory describing a recently introduced model of an evolving, adaptive system in which agents compete to be in the minority. The agents themselves are able to evolve their strategies over time in an attempt to improve their performance. The theory explicitly demonstrates the self-interaction, or market impact, that agents in such systems experience.

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

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.

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.

Epidemics in markets with trade friction and imperfect transactions.

PubMed

Moslonka-Lefebvre, Mathieu; Monod, Hervé; Gilligan, Christopher A; Vergu, Elisabeta; Filipe, João A N

2015-06-07

Market trade-routes can support infectious-disease transmission, impacting biological populations and even disrupting trade that conduces the disease. Epidemiological models increasingly account for reductions in infectious contact, such as risk-aversion behaviour in response to pathogen outbreaks. However, responses in market dynamics clearly differ from simple risk aversion, as are driven by other motivation and conditioned by "friction" constraints (a term we borrow from labour economics). Consequently, the propagation of epidemics in markets of, for example livestock, is frictional due to time and cost limitations in the production and exchange of potentially infectious goods. Here we develop a coupled economic-epidemiological model where transient and long-term market dynamics are determined by trade friction and agent adaptation, and can influence disease transmission. The market model is parameterised from datasets on French cattle and pig exchange networks. We show that, when trade is the dominant route of transmission, market friction can be a significantly stronger determinant of epidemics than risk-aversion behaviour. In particular, there is a critical level of friction above which epidemics do not occur, which suggests some epidemics may not be sustained in highly frictional markets. In addition, friction may allow for greater delay in removal of infected agents that still mitigates the epidemic and its impacts. We suggest that policy for minimising contagion in markets could be adjusted to the level of market friction, by adjusting the urgency of intervention or by increasing friction through incentivisation of larger-volume less-frequent transactions that would have limited effect on overall trade flow. Our results are robust to model specificities and can hold in the presence of non-trade disease-transmission routes. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

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.

Mathematical model of the competition life cycle under limited resources conditions: Problem statement for business community

NASA Astrophysics Data System (ADS)

Shelomentsev, A. G.; Medvedev, M. A.; Berg, D. B.; Lapshina, S. N.; Taubayev, A. A.; Davletbaev, R. H.; Savina, D. V.

2017-12-01

Present study is devoted to the development of competition life cycle mathematical model in the closed business community with limited resources. Growth of each agent is determined by the balance of input and output resource flows: input (cash) flow W is covering the variable V and constant C costs and growth dA/dt of the agent's assets A. Value of V is proportional to assets A that allows us to write down a first order non-stationary differential equation of the agent growth. Model includes the number of such equations due to the number of agents. The amount of resources that is available for agents vary in time. The balances of their input and output flows are changing correspondingly to the different stages of the competition life cycle. According to the theory of systems, the most complete description of any object or process is the model of its life cycle. Such a model describes all stages of its development: from the appearance ("birth") through development ("growth") to extinction ("death"). The model of the evolution of an individual firm, not contradicting the economic meaning of events actually observed in the market, is the desired result from modern AVMs for applied use. With a correct description of the market, rules for participants' actions, restrictions, forecasts can be obtained, which modern mathematics and the economy can not give.

Why only few are so successful?

NASA Astrophysics Data System (ADS)

Mohanty, P. K.

2007-10-01

In many professions employees are rewarded according to their relative performance. Corresponding economy can be modeled by taking N independent agents who gain from the market with a rate which depends on their current gain. We argue that this simple realistic rate generates a scale-free distribution even though intrinsic ability of agents are marginally different from each other. As an evidence we provide distribution of scores for two different systems (a) the global stock game where players invest in real stock market and (b) the international cricket.

Equilibria, prudent compromises, and the "waiting" game.

PubMed

Sim, Kwang Mong

2005-08-01

While evaluation of many e-negotiation agents are carried out through empirical studies, this work supplements and complements existing literature by analyzing the problem of designing market-driven agents (MDAs) in terms of equilibrium points and stable strategies. MDAs are negotiation agents designed to make prudent compromises taking into account factors such as time preference, outside option, and rivalry. This work shows that 1) in a given market situation, an MDA negotiates optimally because it makes minimally sufficient concession, and 2) by modeling negotiation of MDAs as a game gamma of incomplete information, it is shown that the strategies adopted by MDAs are stable. In a bilateral negotiation, it is proven that the strategy pair of two MDAs forms a sequential equilibrium for gamma. In a multilateral negotiation, it is shown that the strategy profile of MDAs forms a market equilibrium for gamma.

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.

76 FR 53882 - Proposed Information Collection; Comment Request; Trade Fair Certification Program Application

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-30

... agents or distributors; market research and exposure; and joint venture and licensing opportunities for...-sector firms. The TFC Program seeks to broaden the base of U.S. firms, particularly new-to-market...

New approach of financial volatility duration dynamics by stochastic finite-range interacting voter system.

PubMed

Wang, Guochao; Wang, Jun

2017-01-01

We make an approach on investigating the fluctuation behaviors of financial volatility duration dynamics. A new concept of volatility two-component range intensity (VTRI) is developed, which constitutes the maximal variation range of volatility intensity and shortest passage time of duration, and can quantify the investment risk in financial markets. In an attempt to study and describe the nonlinear complex properties of VTRI, a random agent-based financial price model is developed by the finite-range interacting biased voter system. The autocorrelation behaviors and the power-law scaling behaviors of return time series and VTRI series are investigated. Then, the complexity of VTRI series of the real markets and the proposed model is analyzed by Fuzzy entropy (FuzzyEn) and Lempel-Ziv complexity. In this process, we apply the cross-Fuzzy entropy (C-FuzzyEn) to study the asynchrony of pairs of VTRI series. The empirical results reveal that the proposed model has the similar complex behaviors with the actual markets and indicate that the proposed stock VTRI series analysis and the financial model are meaningful and feasible to some extent.

New approach of financial volatility duration dynamics by stochastic finite-range interacting voter system

NASA Astrophysics Data System (ADS)

Wang, Guochao; Wang, Jun

2017-01-01

We make an approach on investigating the fluctuation behaviors of financial volatility duration dynamics. A new concept of volatility two-component range intensity (VTRI) is developed, which constitutes the maximal variation range of volatility intensity and shortest passage time of duration, and can quantify the investment risk in financial markets. In an attempt to study and describe the nonlinear complex properties of VTRI, a random agent-based financial price model is developed by the finite-range interacting biased voter system. The autocorrelation behaviors and the power-law scaling behaviors of return time series and VTRI series are investigated. Then, the complexity of VTRI series of the real markets and the proposed model is analyzed by Fuzzy entropy (FuzzyEn) and Lempel-Ziv complexity. In this process, we apply the cross-Fuzzy entropy (C-FuzzyEn) to study the asynchrony of pairs of VTRI series. The empirical results reveal that the proposed model has the similar complex behaviors with the actual markets and indicate that the proposed stock VTRI series analysis and the financial model are meaningful and feasible to some extent.

Acquisition Management for System of Systems: Requirement Evolution and Acquisition Strategy Planning

DTIC Science & Technology

2013-01-29

of modern portfolio and control theory . The reformulation allows for possible changes in estimated quantities (e.g., due to market shifts in... Portfolio Theory (MPT). Final Report: NPS award N00244-11-1-0003 5 Extending CEM and Markov: Agent-Based Modeling Approach Research conducted in the...integration and acquisition from a robust portfolio theory standpoint. Robust portfolio management methodologies have been widely used by financial

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

Hao, He; Lian, Jianming; Kalsi, Karanjit

The HVAC (Heating, Ventilation, and Air- Conditioning) system of commercial buildings is a complex system with a large number of dynamically interacting components. In particular, the thermal dynamics of each zone are coupled with those of the neighboring zones. In this paper, we study a multi-agent based approach to model and control commercial building HVAC system for providing grid services. In the multi-agent system (MAS), individual zones are modeled as agents that can communicate, interact, and negotiate with one another to achieve a common objective. We first propose a distributed characterization method on the aggregated airflow (and thus fan power)more » flexibility that the HVAC system can provide to the ancillary service market. Then, we propose a Nash-bargaining based airflow allocation strategy to track a dispatch signal (that is within the offered flexibility limit) while respecting the preference and flexibility of individual zones. Moreover, we devise a distributed algorithm to obtain the Nash bargaining solution via dual decomposition and average consensus. Numerical simulations illustrate that the proposed distributed protocols are much more scalable than the centralized approaches especially when the system becomes larger and more complex.« less

Policy analysis from first principles

PubMed Central

Moss, Scott

2002-01-01

The argument of this paper is predicated on the view that social science should start with observation and the specification of a problem to be solved. On that basis, the appropriate properties and conditions of application of relevant tools of analysis should be defined. Evidence is adduced from data for sales volumes and values of a disparate range of goods to show that frequency distributions are commonly fat-tailed. This result implies that any stable population distribution will generally have infinite variance and perhaps undefined mean. Models with agents that reason about their behavior and are influenced by, but do not imitate, other agents known to them will typically generate fat-tailed time series data. A simulation model of intermediated exchange is reported that is populated by such agents and yields the same type of fat-tailed time series and cross-sectional data that is found in data for fast moving consumer goods and for retail outlets. This result supports the proposition that adaptive agent models of markets with agents that reason and are socially embedded have the same statistical signatures as real markets. Whereas this statistical signature precludes any conventional hypothesis testing or forecasting, these models do offer unique opportunities for validation on the basis of domain expertise and qualitative data. Perhaps the most striking conclusion is that neither current social theory nor any similar construct will ever support an effective policy analysis. However, adaptive agent modeling is an effective substitute when embedded in a wider policy analysis procedure. PMID:12011405

Self-reinforcing feedback loop in financial markets with coupling of market impact and momentum traders

NASA Astrophysics Data System (ADS)

Zhong, Li-Xin; Xu, Wen-Juan; Chen, Rong-Da; Zhong, Chen-Yang; Qiu, Tian; Ren, Fei; He, Yun-Xing

2018-03-01

By incorporating market impact and momentum traders into an agent-based model, we investigate the conditions for the occurrence of self-reinforcing feedback loops and the coevolutionary mechanism of prices and strategies. For low market impact, the price fluctuations are originally large. The existence of momentum traders has little impact on the change of price fluctuations but destroys the equilibrium between the trend-following and trend-rejecting strategies. The trend-following herd behaviors become dominant. A self-reinforcing feedback loop exists. For high market impact, the existence of momentum traders leads to an increase in price fluctuations. The trend-following strategies of rational individuals are suppressed while the trend-following strategies of momentum traders are promoted. The crowd-anticrowd behaviors become dominant. A negative feedback loop exists. A theoretical analysis indicates that, for low market impact, the majority effect is beneficial for the trend-followers to earn more, which in turn promotes the trend-following strategies. For high market impact, the minority effect causes the trend-followers to suffer great losses, which in turn suppresses the trend-following strategies.

Collective states in social systems with interacting learning agents

NASA Astrophysics Data System (ADS)

Semeshenko, Viktoriya; Gordon, Mirta B.; Nadal, Jean-Pierre

2008-08-01

We study the implications of social interactions and individual learning features on consumer demand in a simple market model. We consider a social system of interacting heterogeneous agents with learning abilities. Given a fixed price, agents repeatedly decide whether or not to buy a unit of a good, so as to maximize their expected utilities. This model is close to Random Field Ising Models, where the random field corresponds to the idiosyncratic willingness to pay. We show that the equilibrium reached depends on the nature of the information agents use to estimate their expected utilities. It may be different from the systems’ Nash equilibria.

The role of independent agents in the success of health insurance market reforms.

PubMed

Hall, M A

2000-01-01

The impact of reforms on the health insurance markets cannot be understood without more information about the role played by insurance agents and a closer analysis of their contribution. An in-depth, qualitative study of insurance-market reforms in seven illustrative states forms the basis for this report on how agents help to shape the efficiency and fairness of insurance markets. Different types of agents relate to insurers in their own ways and are compensated differently. This study shows agents to be almost uniformly enthusiastic about guaranteed-issue requirements and other components of market reforms. Although insurers devise strategies for manipulating agents in order to avoid undesirable business, these opportunities are limited and do not appear to be seriously undermining the effectiveness of market reforms. Despite the layer of cost that agents add to the system, they play an important role in making market reforms work, and they fill essential information and service functions for which many purchasers have no ready substitute.

The Role of Independent Agents in the Success of Health Insurance Market Reforms

PubMed Central

Hall, Mark A.

2000-01-01

The impact of reforms on the health insurance markets cannot be understood without more information about the role played by insurance agents and a closer analysis of their contribution. An in-depth, qualitative study of insurance-market reforms in seven illustrative states forms the basis for this report on how agents help to shape the efficiency and fairness of insurance markets. Different types of agents relate to insurers in their own ways and are compensated differently. This study shows agents to be almost uniformly enthusiastic about guaranteed-issue requirements and other components of market reforms. Although insurers devise strategies for manipulating agents in order to avoid undesirable business, these opportunities are limited and do not appear to be seriously undermining the effectiveness of market reforms. Despite the layer of cost that agents add to the system, they play an important role in making market reforms work, and they fill essential information and service functions for which many purchasers have no ready substitute. PMID:10834080

Black market products confiscated in Norway 2011-2014 compared to analytical findings in urine samples.

PubMed

Hullstein, Ingunn R; Malerod-Fjeld, Helle; Dehnes, Yvette; Hemmersbach, Peter

2015-01-01

Doping agents are widely and illicitly distributed through the Internet. Analysis of these preparations is useful in order to monitor the availability of prohibited substances on the market, and more importantly to predict which substances are expected to be found in urine samples collected from athletes and to aid clinical and forensic investigations. Based on a close collaboration with the Norwegian police and the Norwegian custom authorities, the Norwegian Doping Control Laboratory has performed analyses of confiscated material suspected of containing doping agents. The analyses were performed using gas chromatography (GC) and liquid chromatography (LC) combined with mass spectrometry (MS). The majority (67%) of the analyzed black market products contained anabolic- androgenic steroids (AAS) as expected, whereas peptide- and protein-based doping substances were identified in 28% of the preparations. The Norwegian Doping Control Laboratory receives samples collected from recreational and elite athletes in addition to samples collected in clinical and forensic investigations. The findings in the seized material reflected the findings in the urine samples analyzed regarding the anabolic steroids. Thus, analyzing material seized in Norway may give a good indication of doping agents available on the local market. Copyright © 2015 John Wiley & Sons, Ltd.

Why some market reforms lack legitimacy in health care.

PubMed

Laugesen, Miriam

2005-12-01

Market-oriented health policy reforms in the 1980s and 1990s generally included five kinds of proposals: increased cost sharing for patients through user fees, the separation of purchaser-provider functions, management reforms of hospitals, provider competition, and vouchers for purchasing health insurance. These policies are partly derived from agency theory and a model of managed competition in health insurance. The essay reviews the course of reform in five countries that had a national health service model in place in the late 1980s: Italy, New Zealand, Spain, Sweden, and the United Kingdom. Special consideration is given to New Zealand, where the market model was extensively adopted but short lived. In New Zealand, surveys and polls are compared to archival records of reformers' deliberations. Voters saw health care differently from elites, and voters particularly felt that health care was ill suited to commercialization. There are similarities across all five countries in what has been adopted and rejected. Some market reforms are more legitimate than others. Reforms based on resolving principal-agent problems, including purchaser-provider splits and managerial reforms, have been more successful, although cost sharing has not. Competition-based reforms in financing and to a lesser extent in provision have not gained legitimacy. Most voters in these countries see health care as different from other parts of the economy and view managerial reforms differently from policies that try to make health care more like other sectors.

Random matrix approach to the dynamics of stock inventory variations

NASA Astrophysics Data System (ADS)

Zhou, Wei-Xing; Mu, Guo-Hua; Kertész, János

2012-09-01

It is well accepted that investors can be classified into groups owing to distinct trading strategies, which forms the basic assumption of many agent-based models for financial markets when agents are not zero-intelligent. However, empirical tests of these assumptions are still very rare due to the lack of order flow data. Here we adopt the order flow data of Chinese stocks to tackle this problem by investigating the dynamics of inventory variations for individual and institutional investors that contain rich information about the trading behavior of investors and have a crucial influence on price fluctuations. We find that the distributions of cross-correlation coefficient Cij have power-law forms in the bulk that are followed by exponential tails, and there are more positive coefficients than negative ones. In addition, it is more likely that two individuals or two institutions have a stronger inventory variation correlation than one individual and one institution. We find that the largest and the second largest eigenvalues (λ1 and λ2) of the correlation matrix cannot be explained by random matrix theory and the projections of investors' inventory variations on the first eigenvector u(λ1) are linearly correlated with stock returns, where individual investors play a dominating role. The investors are classified into three categories based on the cross-correlation coefficients CV R between inventory variations and stock returns. A strong Granger causality is unveiled from stock returns to inventory variations, which means that a large proportion of individuals hold the reversing trading strategy and a small part of individuals hold the trending strategy. Our empirical findings have scientific significance in the understanding of investors' trading behavior and in the construction of agent-based models for emerging stock markets.

Predicting the unpredictable.

PubMed

Bonabeau, Eric

2002-03-01

The collective behavior of people in crowds, markets, and organizations has long been a mystery. Why, for instance, do employee bonuses sometimes lead to decreases in productivity? Why do some products generate tremendous buzz, seemingly out of nowhere, while others languish despite multimillion-dollar marketing campaigns? How could a simple clerical error snowball into a catastrophic loss that bankrupts a financial institution? Traditional approaches like spreadsheet and regression analyses have failed to explain such "emergent phenomena," says Eric Bonabeau, because they work from the top down, trying to apply global equations and frameworks to a particular situation. But the behavior of emergent phenomena, contends Bonabeau, is formed from the bottom up--starting with the local interactions of individuals who alter their actions in response to other participants. Together, the myriad interactions result in a group behavior that can easily elude any top-down analysis. But now, thanks to "agent-based modeling," some companies are finding ways to analyze--and even predict--emergent phenomena. Macy's, for instance, has used the technology to investigate better ways to design its department stores. Hewlett-Packard has run agent-based simulations to anticipate how changes in its hiring strategy would affect its corporate culture. And Société Générale has used the technology to determine the operational risk of its asset management group. This article discusses emergent phenomena in detail and explains why they have become more prevalent in recent years. In addition to providing real-world examples of companies that have improved their business practices through agent-based modeling, Bonabeau also examines the future of this technology and points to several fields that may be revolutionized by its use.

A Buyer Behaviour Framework for the Development and Design of Software Agents in E-Commerce.

ERIC Educational Resources Information Center

Sproule, Susan; Archer, Norm

2000-01-01

Software agents are computer programs that run in the background and perform tasks autonomously as delegated by the user. This paper blends models from marketing research and findings from the field of decision support systems to build a framework for the design of software agents to support in e-commerce buying applications. (Contains 35…

Home Energy Management System - VOLTTRON Integration

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

Zandi, Helia

In most Home Energy Management Systems (HEMS) available in the market, different devices running different communication protocols cannot interact with each other and exchange information. As a result of this integration, the information about different devices running different communication protocol can be accessible by other agents and devices running on VOLTTRON platform. The integration process can be used by any HEMS available in the market regardless of the programming language they use. If the existing HEMS provides an Application Programming Interface (API) based on the RESTFul architecture, that API can be used for integration. Our candidate HEMS in this projectmore » is home-assistant (Hass). An agent is implemented which can communicate with the Hass API and receives information about the devices loaded on the API. The agent publishes the information it receives on the VOLTTRON message bus so other agents can have access to this information. On the other side, for each type of devices, an agent is implemented such as Climate Agent, Lock Agent, Switch Agent, Light Agent, etc. Each of these agents is subscribed to the messages published on the message bus about their associated devices. These agents can also change the status of the devices by sending appropriate service calls to the API. Other agents and services on the platform can also access this information and coordinate their decision-making process based on this information.« less

Epoch Lifetimes in the Dynamics of a Competing Population

NASA Astrophysics Data System (ADS)

Yeung, C. H.; Ma, Y. P.; Wong, K. Y. Michael

We propose a dynamical model of a competing population whose agents have a tendency to balance their decisions in time. The model is applicable to financial markets in which the agents trade with finite capital, or other multiagent systems such as routers in communication networks attempting to transmit multiclass traffic in a fair way. We find an oscillatory behavior due to the segregation of agents into two groups. Each group remains winning over epochs. The aggregation of smart agents is able to explain the lifetime distribution of epochs to 8 decades of probability. The existence of the super agents further refines the lifetime distribution of short epochs.

Multi-period equilibrium/near-equilibrium in electricity markets based on locational marginal prices

NASA Astrophysics Data System (ADS)

Garcia Bertrand, Raquel

In this dissertation we propose an equilibrium procedure that coordinates the point of view of every market agent resulting in an equilibrium that simultaneously maximizes the independent objective of every market agent and satisfies network constraints. Therefore, the activities of the generating companies, consumers and an independent system operator are modeled: (1) The generating companies seek to maximize profits by specifying hourly step functions of productions and minimum selling prices, and bounds on productions. (2) The goals of the consumers are to maximize their economic utilities by specifying hourly step functions of demands and maximum buying prices, and bounds on demands. (3) The independent system operator then clears the market taking into account consistency conditions as well as capacity and line losses so as to achieve maximum social welfare. Then, we approach this equilibrium problem using complementarity theory in order to have the capability of imposing constraints on dual variables, i.e., on prices, such as minimum profit conditions for the generating units or maximum cost conditions for the consumers. In this way, given the form of the individual optimization problems, the Karush-Kuhn-Tucker conditions for the generating companies, the consumers and the independent system operator are both necessary and sufficient. The simultaneous solution to all these conditions constitutes a mixed linear complementarity problem. We include minimum profit constraints imposed by the units in the market equilibrium model. These constraints are added as additional constraints to the equivalent quadratic programming problem of the mixed linear complementarity problem previously described. For the sake of clarity, the proposed equilibrium or near-equilibrium is first developed for the particular case considering only one time period. Afterwards, we consider an equilibrium or near-equilibrium applied to a multi-period framework. This model embodies binary decisions, i.e., on/off status for the units, and therefore optimality conditions cannot be directly applied. To avoid limitations provoked by binary variables, while retaining the advantages of using optimality conditions, we define the multi-period market equilibrium using Benders decomposition, which allows computing binary variables through the master problem and continuous variables through the subproblem. Finally, we illustrate these market equilibrium concepts through several case studies.

The application of statistical mechanics on the study of glassy behaviors in transportation networks and dynamics in models of financial markets

NASA Astrophysics Data System (ADS)

Yeung, Chi Ho

In this thesis, we study two interdisciplinary problems in the framework of statistical physics, which show the broad applicability of physics on problems with various origins. The first problem corresponds to an optimization problem in allocating resources on random regular networks. Frustrations arise from competition for resources. When the initial resources are uniform, different regimes with discrete fractions of satisfied nodes are observed, resembling the Devil's staircase. We apply the spin glass theory in analyses and demonstrate how functional recursions are converted to simple recursions of probabilities. Equilibrium properties such as the average energy and the fraction of free nodes are derived. When the initial resources are bimodally distributed, increases in the fraction of rich nodes induce a glassy transition, entering a glassy phase described by the existence of multiple metastable states, in which we employ the replica symmetry breaking ansatz for analysis. The second problem corresponds to the study of multi-agent systems modeling financial markets. Agents in the system trade among themselves, and self-organize to produce macroscopic trading behaviors resembling the real financial markets. These behaviors include the arbitraging activities, the setting up and the following of price trends. A phase diagram of these behaviors is obtained, as a function of the sensitivity of price and the market impact factor. We finally test the applicability of the models with real financial data including the Hang Seng Index, the Nasdaq Composite and the Dow Jones Industrial Average. A substantial fraction of agents gains faster than the inflation rate of the indices, suggesting the possibility of using multi-agent systems as a tool for real trading.

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.

Frontiers of finance: evolution and efficient markets.

PubMed

Farmer, J D; Lo, A W

1999-08-31

In this review article, we explore several recent advances in the quantitative modeling of financial markets. We begin with the Efficient Markets Hypothesis and describe how this controversial idea has stimulated a number of new directions of research, some focusing on more elaborate mathematical models that are capable of rationalizing the empirical facts, others taking a completely different tack in rejecting rationality altogether. One of the most promising directions is to view financial markets from a biological perspective and, specifically, within an evolutionary framework in which markets, instruments, institutions, and investors interact and evolve dynamically according to the "law" of economic selection. Under this view, financial agents compete and adapt, but they do not necessarily do so in an optimal fashion. Evolutionary and ecological models of financial markets is truly a new frontier whose exploration has just begun.

Frontiers of finance: Evolution and efficient markets

PubMed Central

Farmer, J. Doyne; Lo, Andrew W.

1999-01-01

In this review article, we explore several recent advances in the quantitative modeling of financial markets. We begin with the Efficient Markets Hypothesis and describe how this controversial idea has stimulated a number of new directions of research, some focusing on more elaborate mathematical models that are capable of rationalizing the empirical facts, others taking a completely different tack in rejecting rationality altogether. One of the most promising directions is to view financial markets from a biological perspective and, specifically, within an evolutionary framework in which markets, instruments, institutions, and investors interact and evolve dynamically according to the “law” of economic selection. Under this view, financial agents compete and adapt, but they do not necessarily do so in an optimal fashion. Evolutionary and ecological models of financial markets is truly a new frontier whose exploration has just begun. PMID:10468547

Private Information and Insurance Rejections

PubMed Central

Hendren, Nathaniel

2013-01-01

Across a wide set of non-group insurance markets, applicants are rejected based on observable, often high-risk, characteristics. This paper argues that private information, held by the potential applicant pool, explains rejections. I formulate this argument by developing and testing a model in which agents may have private information about their risk. I first derive a new no-trade result that theoretically explains how private information could cause rejections. I then develop a new empirical methodology to test whether this no-trade condition can explain rejections. The methodology uses subjective probability elicitations as noisy measures of agents beliefs. I apply this approach to three non-group markets: long-term care, disability, and life insurance. Consistent with the predictions of the theory, in all three settings I find significant amounts of private information held by those who would be rejected; I find generally more private information for those who would be rejected relative to those who can purchase insurance; and I show it is enough private information to explain a complete absence of trade for those who would be rejected. The results suggest private information prevents the existence of large segments of these three major insurance markets. PMID:24187381

Impact of information cost and switching of trading strategies in an artificial stock market

NASA Astrophysics Data System (ADS)

Liu, Yi-Fang; Zhang, Wei; Xu, Chao; Vitting Andersen, Jørgen; Xu, Hai-Chuan

2014-08-01

This paper studies the switching of trading strategies and its effect on the market volatility in a continuous double auction market. We describe the behavior when some uninformed agents, who we call switchers, decide whether or not to pay for information before they trade. By paying for the information they behave as informed traders. First we verify that our model is able to reproduce some of the stylized facts in real financial markets. Next we consider the relationship between switching and the market volatility under different structures of investors. We find that there exists a positive relationship between the market volatility and the percentage of switchers. We therefore conclude that the switchers are a destabilizing factor in the market. However, for a given fixed percentage of switchers, the proportion of switchers that decide to buy information at a given moment of time is negatively related to the current market volatility. In other words, if more agents pay for information to know the fundamental value at some time, the market volatility will be lower. This is because the market price is closer to the fundamental value due to information diffusion between switchers.

Evaluating Observational Learning in a Competitive Two-Sided Crowdsourcing Market: A Bayesian Inferential Approach

ERIC Educational Resources Information Center

Ayaburi, Emmanuel Wusuhon Yanibo

2017-01-01

This dissertation investigates the effect of observational learning in crowdsourcing markets as a lens to identify appropriate mechanism(s) for sustaining this increasingly popular business model. Observational learning occurs when crowdsourcing participating agents obtain knowledge from signals they observe in the marketplace and incorporate such…

A Multi-Agent Approach to the Simulation of Robotized Manufacturing Systems

NASA Astrophysics Data System (ADS)

Foit, K.; Gwiazda, A.; Banaś, W.

2016-08-01

The recent years of eventful industry development, brought many competing products, addressed to the same market segment. The shortening of a development cycle became a necessity if the company would like to be competitive. Because of switching to the Intelligent Manufacturing model the industry search for new scheduling algorithms, while the traditional ones do not meet the current requirements. The agent-based approach has been considered by many researchers as an important way of evolution of modern manufacturing systems. Due to the properties of the multi-agent systems, this methodology is very helpful during creation of the model of production system, allowing depicting both processing and informational part. The complexity of such approach makes the analysis impossible without the computer assistance. Computer simulation still uses a mathematical model to recreate a real situation, but nowadays the 2D or 3D virtual environments or even virtual reality have been used for realistic illustration of the considered systems. This paper will focus on robotized manufacturing system and will present the one of possible approaches to the simulation of such systems. The selection of multi-agent approach is motivated by the flexibility of this solution that offers the modularity, robustness and autonomy.

Econo-Thermodynamics: The Nature of Economic Interactions

NASA Astrophysics Data System (ADS)

Mimkes, Juergen

2006-03-01

Physicists often model economic interactions like collisions of atoms in gases: by interaction one agent gains, the other loses. This leads to a Boltzmann distribution of capital, which has been observed in wealth distributions of different countries. However, economists object: no economic agent will attend a market in which he gets robbed! This conflict may be resolved by writing basic laws of economics into terms of calculus. In these terms the daily struggle for survival of all economic systems turns out to be a Carnot cycle that is driven by energy: heat pumps and economic production depend on oil, GNP and oil consumption run parallel for all countries. Motors and markets are based on the same laws of calculus (macro-economics) and statistics (micro-economics). Economic interactions mean exploiting a third party (nature) and are indeed close to robbing! A baker sells bread to his customers, but the flour comes from nature. Banks sells loans to investors, but the money comes from savers. Econo-thermodynamics is a thrilling new interdisciplinary field.

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.

Master equation for a kinetic model of a trading market and its analytic solution

NASA Astrophysics Data System (ADS)

Chatterjee, Arnab; Chakrabarti, Bikas K.; Stinchcombe, Robin B.

2005-08-01

We analyze an ideal-gas-like model of a trading market with quenched random saving factors for its agents and show that the steady state income (m) distribution P(m) in the model has a power law tail with Pareto index ν exactly equal to unity, confirming the earlier numerical studies on this model. The analysis starts with the development of a master equation for the time development of P(m) . Precise solutions are then obtained in some special cases.

Master equation for a kinetic model of a trading market and its analytic solution.

PubMed

Chatterjee, Arnab; Chakrabarti, Bikas K; Stinchcombe, Robin B

2005-08-01

We analyze an ideal-gas-like model of a trading market with quenched random saving factors for its agents and show that the steady state income (m) distribution P(m) in the model has a power law tail with Pareto index nu exactly equal to unity, confirming the earlier numerical studies on this model. The analysis starts with the development of a master equation for the time development of P(m) . Precise solutions are then obtained in some special cases.

Trust or robustness? An ecological approach to the study of auction and bilateral markets.

PubMed

Hernández, Laura; Vignes, Annick; Saba, Stéphanie

2018-01-01

Centralized markets are often considered more efficient than bilateral exchanges because information is public and the same for all the agents. On decentralized markets, where the information is private, the influence of trust on the market outcome has been underlined by many authors. We present an empirical study of the distinctive Boulogne-sur-Mer Fish Market (where both buyers and sellers can choose to trade by either bidding or bargaining), focused on the interactions between agents. Our approach is inspired by studies of mutualistic ecosystems, where the agents are of two different types (as in plant-pollinator networks) and the interactions only take place between agents of different kinds, naturally providing benefits to both. In our context, where the two kinds of agents are buyers and sellers, our study shows that not only do their interactions bring economic benefits for the agents directly involved, but they also contribute to the stability of the market. Our results help to explain the surprising coexistence of the two forms of market in the distinctive Boulogne sur Mer Fish Market.

Trust or robustness? An ecological approach to the study of auction and bilateral markets

PubMed Central

Vignes, Annick; Saba, Stéphanie

2018-01-01

Centralized markets are often considered more efficient than bilateral exchanges because information is public and the same for all the agents. On decentralized markets, where the information is private, the influence of trust on the market outcome has been underlined by many authors. We present an empirical study of the distinctive Boulogne-sur-Mer Fish Market (where both buyers and sellers can choose to trade by either bidding or bargaining), focused on the interactions between agents. Our approach is inspired by studies of mutualistic ecosystems, where the agents are of two different types (as in plant-pollinator networks) and the interactions only take place between agents of different kinds, naturally providing benefits to both. In our context, where the two kinds of agents are buyers and sellers, our study shows that not only do their interactions bring economic benefits for the agents directly involved, but they also contribute to the stability of the market. Our results help to explain the surprising coexistence of the two forms of market in the distinctive Boulogne sur Mer Fish Market. PMID:29734331

Space Situational Awareness using Market Based Agents

NASA Astrophysics Data System (ADS)

Sullivan, C.; Pier, E.; Gregory, S.; Bush, M.

2012-09-01

Space surveillance for the DoD is not limited to the Space Surveillance Network (SSN). Other DoD-owned assets have some existing capabilities for tasking but have no systematic way to work collaboratively with the SSN. These are run by diverse organizations including the Services, other defense and intelligence agencies and national laboratories. Beyond these organizations, academic and commercial entities have systems that possess SSA capability. Most all of these assets have some level of connectivity, security, and potential autonomy. Exploiting them in a mutually beneficial structure could provide a more comprehensive, efficient and cost effective solution for SSA. The collection of all potential assets, providers and consumers of SSA data comprises a market which is functionally illiquid. The development of a dynamic marketplace for SSA data could enable would-be providers the opportunity to sell data to SSA consumers for monetary or incentive based compensation. A well-conceived market architecture could drive down SSA data costs through increased supply and improve efficiency through increased competition. Oceanit will investigate market and market agent architectures, protocols, standards, and incentives toward producing high-volume/low-cost SSA.

The Working of Circuit Breakers Within Percolation Models for Financial Markets

NASA Astrophysics Data System (ADS)

Ehrenstein, Gudrun; Westerhoff, Frank

We use a modified Cont-Bouchaud model to explore the effectiveness of trading breaks. The modifications include that the trading activity of the market participants depends positively on historical volatility and that the orders of the agents are conditioned on the observed mispricing. Trading breaks, also called circuit breakers, interrupt the trading process when prices are about to exceed a pre-specified limit. We find that trading breaks are a useful instrument to stabilize financial markets. In particular, trading breaks may reduce price volatility and deviations from fundamentals.

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

Biological trade and markets

PubMed Central

2016-01-01

Cooperation between organisms can often be understood, like trade between merchants, as a mutually beneficial exchange of services, resources or other ‘commodities’. Mutual benefits alone, however, are not sufficient to explain the evolution of trade-based cooperation. First, organisms may reject a particular trade if another partner offers a better deal. Second, while human trade often entails binding contracts, non-human trade requires unwritten ‘terms of contract’ that ‘self-stabilize’ trade and prevent cheating even if all traders strive to maximize fitness. Whenever trading partners can be chosen, market-like situations arise in nature that biologists studying cooperation need to account for. The mere possibility of exerting partner choice stabilizes many forms of otherwise cheatable trade, induces competition, facilitates the evolution of specialization and often leads to intricate forms of cooperation. We discuss selected examples to illustrate these general points and review basic conceptual approaches that are important in the theory of biological trade and markets. Comparing these approaches with theory in economics, it turns out that conventional models—often called ‘Walrasian’ markets—are of limited relevance to biology. In contrast, early approaches to trade and markets, as found in the works of Ricardo and Cournot, contain elements of thought that have inspired useful models in biology. For example, the concept of comparative advantage has biological applications in trade, signalling and ecological competition. We also see convergence between post-Walrasian economics and biological markets. For example, both economists and biologists are studying ‘principal–agent’ problems with principals offering jobs to agents without being sure that the agents will do a proper job. Finally, we show that mating markets have many peculiarities not shared with conventional economic markets. Ideas from economics are useful for biologists studying cooperation but need to be taken with caution. PMID:26729940

Physics of fashion fluctuations

NASA Astrophysics Data System (ADS)

Donangelo, R.; Hansen, A.; Sneppen, K.; Souza, S. R.

2000-12-01

We consider a market where many agents trade different types of products with each other. We model development of collective modes in this market, and quantify these by fluctuations that scale with time with a Hurst exponent of about 0.7. We demonstrate that individual products in the model occasionally become globally accepted means of exchange, and simultaneously become very actively traded. Thus collective features similar to money spontaneously emerge, without any a priori reason.

Equilibrium pricing in an order book environment: Case study for a spin model

NASA Astrophysics Data System (ADS)

Meudt, Frederik; Schmitt, Thilo A.; Schäfer, Rudi; Guhr, Thomas

2016-07-01

When modeling stock market dynamics, the price formation is often based on an equilibrium mechanism. In real stock exchanges, however, the price formation is governed by the order book. It is thus interesting to check if the resulting stylized facts of a model with equilibrium pricing change, remain the same or, more generally, are compatible with the order book environment. We tackle this issue in the framework of a case study by embedding the Bornholdt-Kaizoji-Fujiwara spin model into the order book dynamics. To this end, we use a recently developed agent based model that realistically incorporates the order book. We find realistic stylized facts. We conclude for the studied case that equilibrium pricing is not needed and that the corresponding assumption of a ;fundamental; price may be abandoned.

Statistical ensembles for money and debt

NASA Astrophysics Data System (ADS)

Viaggiu, Stefano; Lionetto, Andrea; Bargigli, Leonardo; Longo, Michele

2012-10-01

We build a statistical ensemble representation of two economic models describing respectively, in simplified terms, a payment system and a credit market. To this purpose we adopt the Boltzmann-Gibbs distribution where the role of the Hamiltonian is taken by the total money supply (i.e. including money created from debt) of a set of interacting economic agents. As a result, we can read the main thermodynamic quantities in terms of monetary ones. In particular, we define for the credit market model a work term which is related to the impact of monetary policy on credit creation. Furthermore, with our formalism we recover and extend some results concerning the temperature of an economic system, previously presented in the literature by considering only the monetary base as a conserved quantity. Finally, we study the statistical ensemble for the Pareto distribution.

Effect of Trader Composition on Stock Market

NASA Astrophysics Data System (ADS)

Wang, Mo-Gei; Wang, Xing-Yuan; Liu, Zhen-Zhen

2011-05-01

In this study, we build a double auction market model, which contains two types of agent traders, i.e., the noise traders and fundamentalists, to investigate the effect of the trader composition on the stock market. It is found that, the non-trivial Hurst exponent and the fat-tailed distribution of transaction prices can be observed at any ratio of the noise traders. Analyses on the price variation properties, including the Hurst exponent and the price variation region, show that these properties are stable when the ratio is moderate. However, the non-price variation properties, including the trading volume and the profitability of the two kinds of agents, do not keep stable untrivially in any interval of the ratio of noise traders.

Multi-agent systems design for aerospace applications

NASA Astrophysics Data System (ADS)

Waslander, Steven L.

2007-12-01

Engineering systems with independent decision makers are becoming increasingly prevalent and present many challenges in coordinating actions to achieve systems goals. In particular, this work investigates the applications of air traffic flow control and autonomous vehicles as motivation to define algorithms that allow agents to agree to safe, efficient and equitable solutions in a distributed manner. To ensure system requirements will be satisfied in practice, each method is evaluated for a specific model of agent behavior, be it cooperative or non-cooperative. The air traffic flow control problem is investigated from the point of view of the airlines, whose costs are directly affected by resource allocation decisions made by the Federal Aviation Administration in order to mitigate traffic disruptions caused by weather. Airlines are first modeled as cooperative, and a distributed algorithm is presented with various global cost metrics which balance efficient and equitable use of resources differently. Next, a competitive airline model is assumed and two market mechanisms are developed for allocating contested airspace resources. The resource market mechanism provides a solution for which convergence to an efficient solution can be guaranteed, and each airline will improve on the solution that would occur without its inclusion in the decision process. A lump-sum market is then introduced as an alternative mechanism, for which efficiency loss bounds exist if airlines attempt to manipulate prices. Initial convergence results for lump-sum markets are presented for simplified problems with a single resource. To validate these algorithms, two air traffic flow models are developed which extend previous techniques, the first a convenient convex model made possible by assuming constant velocity flow, and the second a more complex flow model with full inflow, velocity and rerouting control. Autonomous vehicle teams are envisaged for many applications including mobile sensing and search and rescue. To enable these high-level applications, multi-vehicle collision avoidance is solved using a cooperative, decentralized algorithm. For the development of coordination algorithms for autonomous vehicles, the Stanford Testbed of Autonomous Rotorcraft for Multi-Agent Control (STARMAC) is presented. This testbed provides significant advantages over other aerial testbeds due to its small size and low maintenance requirements.

Scientific and industrial challenges of developing nanoparticle-based theranostics and multiple-modality contrast agents for clinical application

NASA Astrophysics Data System (ADS)

Wáng, Yì Xiáng J.; Idée, Jean-Marc; Corot, Claire

2015-10-01

Designing of theranostics and dual or multi-modality contrast agents are currently two of the hottest topics in biotechnology and biomaterials science. However, for single entity theranostics, a right ratio of their diagnostic component and their therapeutic component may not always be realized in a composite suitable for clinical application. For dual/multiple modality molecular imaging agents, after in vivo administration, there is an optimal time window for imaging, when an agent is imaged by one modality, the pharmacokinetics of this agent may not allow imaging by another modality. Due to reticuloendothelial system clearance, efficient in vivo delivery of nanoparticles to the lesion site is sometimes difficult. The toxicity of these entities also remains poorly understood. While the medical need of theranostics is admitted, the business model remains to be established. There is an urgent need for a global and internationally harmonized re-evaluation of the approval and marketing processes of theranostics. However, a reasonable expectation exists that, in the near future, the current obstacles will be removed, thus allowing the wide use of these very promising agents.

76 FR 70527 - Reporting and Recordkeeping Requirements Under OMB Review

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-14

...: Title: ``25-Model Corp.Resol.or GP Certif.33-Model Letter to Selling Agent. 34-Bank ID, 1065-Appl.Lic...: ``New Markets Venture Capital Program Application Funding and Reporting''. Form No's: 2216, 2185, 2219...

Coevolution in management fashion: an agent-based model of consultant-driven innovation.

PubMed

Strang, David; David, Robert J; Akhlaghpour, Saeed

2014-07-01

The rise of management consultancy has been accompanied by increasingly marked faddish cycles in management techniques, but the mechanisms that underlie this relationship are not well understood. The authors develop a simple agent-based framework that models innovation adoption and abandonment on both the supply and demand sides. In opposition to conceptions of consultants as rhetorical wizards who engineer waves of management fashion, firms and consultants are treated as boundedly rational actors who chase the secrets of success by mimicking their highest-performing peers. Computational experiments demonstrate that consultant-driven versions of this dynamic in which the outcomes of firms are strongly conditioned by their choice of consultant are robustly faddish. The invasion of boom markets by low-quality consultants undercuts popular innovations while simultaneously restarting the fashion cycle by prompting the flight of high-quality consultants into less densely occupied niches. Computational experiments also indicate conditions involving consultant mobility, aspiration levels, mimic probabilities, and client-provider matching that attenuate faddishness.

Lapses, infidelities, and creative adaptations: lessons from evaluation of a participatory market development approach in the Andes.

PubMed

Horton, Douglas; Rotondo, Emma; Paz Ybarnegaray, Rodrigo; Hareau, Guy; Devaux, André; Thiele, Graham

2013-08-01

Participatory approaches are frequently recommended for international development programs, but few have been evaluated. From 2007 to 2010 the Andean Change Alliance evaluated an agricultural research and development approach known as the "Participatory Market Chain Approach" (PMCA). Based on a study of four cases, this paper examines the fidelity of implementation, the factors that influenced implementation and results, and the PMCA change model. We identify three types of deviation from the intervention protocol (lapses, creative adaptations, and true infidelities) and five groups of variables that influenced PMCA implementation and results (attributes of the macro context, the market chain, the key actors, rules in use, and the capacity development strategy). There was insufficient information to test the validity of the PMCA change model, but results were greatest where the PMCA was implemented with highest fidelity. Our analysis suggests that the single most critical component of the PMCA is engagement of market agents - not just farmers - throughout the exercise. We present four lessons for planning and evaluating participatory approaches related to the use of action and change models, the importance of monitoring implementation fidelity, the limits of baseline survey data for outcome evaluation, and the importance of capacity development for implementers. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

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.

Simulating Land-Use Change using an Agent-Based Land Transaction Model

NASA Astrophysics Data System (ADS)

Bakker, M. M.; van Dijk, J.; Alam, S. J.

2013-12-01

In the densely populated cultural landscapes of Europe, the vast majority of all land is owned by private parties, be it farmers (the majority), nature organizations, property developers, or citizens. Therewith, the vast majority of all land-use change arises from land transactions between different owner types: successful farms expand at the expense of less successful farms, and meanwhile property developers, individual citizens, and nature organizations also actively purchase land. These land transactions are driven by specific properties of the land, by governmental policies, and by the (economic) motives of both buyers and sellers. Climate/global change can affect these drivers at various scales: at the local scale changes in hydrology can make certain land less or more desirable; at the global scale the agricultural markets will affect motives of farmers to buy or sell land; while at intermediate (e.g. provincial) scales property developers and nature conservationists may be encouraged or discouraged to purchase land. The cumulative result of all these transactions becomes manifest in changing land-use patterns, and consequent environmental responses. Within the project Climate Adaptation for Rural Areas an agent-based land-use model was developed that explores the future response of individual land users to climate change, within the context of wider global change (i.e. policy and market change). It simulates the exchange of land among farmers and between farmers and nature organizations and property developers, for a specific case study area in the east of the Netherlands. Results show that local impacts of climate change can result in a relative stagnation in the land market in waterlogged areas. Furthermore, the increase in dairying at the expense of arable cultivation - as has been observed in the area in the past - is slowing down as arable produce shows a favourable trend in the agricultural world market. Furthermore, budgets for nature managers are obviously an important driver for nature expansion, but without a strict zoning plan imposed by a government, it is difficult to achieve a continuous, defragmented nature area. Lastly, the model suggests that with time the trend in ever-increasing farm sizes is gradually levelling out. The decision rules that determine the behaviours of the individual agents in the model (selling land, buying land, or none of the two) are calibrated on historical census records, using multi-nominal logistic regression. Because estimating who will sell and who will buy can only be done with a limited certainty, our model reproduces the volatility / uncertainty in who will do what and when. This makes that each specific future scenario can have numerous realizations of reality. Our stakeholders (including, besides policy makers, also local farmers and nature organizations) indicate that this aspect of the model strongly contributes to its credibility. Nevertheless, within different scenarios certain (spatial) trends are distinguishable, so that the model is -besides credible - also useful for exploring future trends.

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.

Facebook's personal page modelling and simulation

NASA Astrophysics Data System (ADS)

Sarlis, Apostolos S.; Sakas, Damianos P.; Vlachos, D. S.

2015-02-01

In this paper we will try to define the utility of Facebook's Personal Page marketing method. This tool that Facebook provides, is modelled and simulated using iThink in the context of a Facebook marketing agency. The paper has leveraged the system's dynamic paradigm to conduct Facebook marketing tools and methods modelling, using iThink™ system to implement them. It uses the design science research methodology for the proof of concept of the models and modelling processes. The following model has been developed for a social media marketing agent/company, Facebook platform oriented and tested in real circumstances. This model is finalized through a number of revisions and iterators of the design, development, simulation, testing and evaluation processes. The validity and usefulness of this Facebook marketing model for the day-to-day decision making are authenticated by the management of the company organization. Facebook's Personal Page method can be adjusted, depending on the situation, in order to maximize the total profit of the company which is to bring new customers, keep the interest of the old customers and deliver traffic to its website.

Conserving analyst attention units: use of multi-agent software and CEP methods to assist information analysis

NASA Astrophysics Data System (ADS)

Rimland, Jeffrey; McNeese, Michael; Hall, David

2013-05-01

Although the capability of computer-based artificial intelligence techniques for decision-making and situational awareness has seen notable improvement over the last several decades, the current state-of-the-art still falls short of creating computer systems capable of autonomously making complex decisions and judgments in many domains where data is nuanced and accountability is high. However, there is a great deal of potential for hybrid systems in which software applications augment human capabilities by focusing the analyst's attention to relevant information elements based on both a priori knowledge of the analyst's goals and the processing/correlation of a series of data streams too numerous and heterogeneous for the analyst to digest without assistance. Researchers at Penn State University are exploring ways in which an information framework influenced by Klein's (Recognition Primed Decision) RPD model, Endsley's model of situational awareness, and the Joint Directors of Laboratories (JDL) data fusion process model can be implemented through a novel combination of Complex Event Processing (CEP) and Multi-Agent Software (MAS). Though originally designed for stock market and financial applications, the high performance data-driven nature of CEP techniques provide a natural compliment to the proven capabilities of MAS systems for modeling naturalistic decision-making, performing process adjudication, and optimizing networked processing and cognition via the use of "mobile agents." This paper addresses the challenges and opportunities of such a framework for augmenting human observational capability as well as enabling the ability to perform collaborative context-aware reasoning in both human teams and hybrid human / software agent teams.

Game theoretic sensor management for target tracking

NASA Astrophysics Data System (ADS)

Shen, Dan; Chen, Genshe; Blasch, Erik; Pham, Khanh; Douville, Philip; Yang, Chun; Kadar, Ivan

2010-04-01

This paper develops and evaluates a game-theoretic approach to distributed sensor-network management for target tracking via sensor-based negotiation. We present a distributed sensor-based negotiation game model for sensor management for multi-sensor multi-target tacking situations. In our negotiation framework, each negotiation agent represents a sensor and each sensor maximizes their utility using a game approach. The greediness of each sensor is limited by the fact that the sensor-to-target assignment efficiency will decrease if too many sensor resources are assigned to a same target. It is similar to the market concept in real world, such as agreements between buyers and sellers in an auction market. Sensors are willing to switch targets so that they can obtain their highest utility and the most efficient way of applying their resources. Our sub-game perfect equilibrium-based negotiation strategies dynamically and distributedly assign sensors to targets. Numerical simulations are performed to demonstrate our sensor-based negotiation approach for distributed sensor management.

A Diversified Investment Strategy Using Autonomous Agents

NASA Astrophysics Data System (ADS)

Barbosa, Rui Pedro; Belo, Orlando

In a previously published article, we presented an architecture for implementing agents with the ability to trade autonomously in the Forex market. At the core of this architecture is an ensemble of classification and regression models that is used to predict the direction of the price of a currency pair. In this paper, we will describe a diversified investment strategy consisting of five agents which were implemented using that architecture. By simulating trades with 18 months of out-of-sample data, we will demonstrate that data mining models can produce profitable predictions, and that the trading risk can be diminished through investment diversification.

Development of an Agent-based Model to Analyze Contemporary Helium Markets

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

Riddle, Matthew E.; Uckun, Canan; Conzelmann, Guenter

Although U.S. helium demand has remained relatively flat since 2009, exports of helium have increased significantly since then, driven primarily by demand for electronic and semiconductor manufacturing in Asia. In the midst of this global demand shift, the Helium Act dictates a new procedure for pricing and distributing the gas through a reserve that historically functioned as a loose “oligarchy.” The new procedure requires prices to be determined by the open market through auctions and a survey of market prices, as opposed to increasing prices according to the consumer price index. Response to these changes has caused temporary shortages, pricemore » increases, and a significant increase in the development of the helium extraction technologies used to produce helium from formerly marginal sources. Technologies are being developed and refined to extract helium from formerly low-yielding natural gas fields containing much lower amounts of helium than the previously considered economic threshold of 0.3%. Combining these transformative policies with the potential for new and significant global supplies from Qatar, Algeria, and Russia could lead to new and unforeseen market behaviors and reactions from global helium markets. The objective of the project is to analyze the global helium markets.« less

Metaphors and the Market: Consequences and Preconditions of Agent and Object Metaphors in Stock Market Commentary

ERIC Educational Resources Information Center

Morris, Michael W.; Sheldon, Oliver J.; Ames, Daniel R.; Young, Maia J.

2007-01-01

We investigated two types of metaphors in stock market commentary. "Agent" metaphors describe price trajectories as volitional actions, whereas "object" metaphors describe them as movements of inanimate objects. Study 1 examined the consequences of commentators' metaphors for their investor audience. Agent metaphors, compared with object metaphors…

Market Imitation and Win-Stay Lose-Shift Strategies Emerge as Unintended Patterns in Market Direction Guesses.

PubMed

Gutiérrez-Roig, Mario; Segura, Carlota; Duch, Jordi; Perelló, Josep

2016-01-01

Decisions made in our everyday lives are based on a wide variety of information so it is generally very difficult to assess what are the strategies that guide us. Stock market provides a rich environment to study how people make decisions since responding to market uncertainty needs a constant update of these strategies. For this purpose, we run a lab-in-the-field experiment where volunteers are given a controlled set of financial information -based on real data from worldwide financial indices- and they are required to guess whether the market price would go "up" or "down" in each situation. From the data collected we explore basic statistical traits, behavioural biases and emerging strategies. In particular, we detect unintended patterns of behavior through consistent actions, which can be interpreted as Market Imitation and Win-Stay Lose-Shift emerging strategies, with Market Imitation being the most dominant. We also observe that these strategies are affected by external factors: the expert advice, the lack of information or an information overload reinforce the use of these intuitive strategies, while the probability to follow them significantly decreases when subjects spends more time to make a decision. The cohort analysis shows that women and children are more prone to use such strategies although their performance is not undermined. Our results are of interest for better handling clients expectations of trading companies, to avoid behavioural anomalies in financial analysts decisions and to improve not only the design of markets but also the trading digital interfaces where information is set down. Strategies and behavioural biases observed can also be translated into new agent based modelling or stochastic price dynamics to better understand financial bubbles or the effects of asymmetric risk perception to price drops.

Market Imitation and Win-Stay Lose-Shift Strategies Emerge as Unintended Patterns in Market Direction Guesses

PubMed Central

Segura, Carlota; Duch, Jordi; Perelló, Josep

2016-01-01

Decisions made in our everyday lives are based on a wide variety of information so it is generally very difficult to assess what are the strategies that guide us. Stock market provides a rich environment to study how people make decisions since responding to market uncertainty needs a constant update of these strategies. For this purpose, we run a lab-in-the-field experiment where volunteers are given a controlled set of financial information -based on real data from worldwide financial indices- and they are required to guess whether the market price would go “up” or “down” in each situation. From the data collected we explore basic statistical traits, behavioural biases and emerging strategies. In particular, we detect unintended patterns of behavior through consistent actions, which can be interpreted as Market Imitation and Win-Stay Lose-Shift emerging strategies, with Market Imitation being the most dominant. We also observe that these strategies are affected by external factors: the expert advice, the lack of information or an information overload reinforce the use of these intuitive strategies, while the probability to follow them significantly decreases when subjects spends more time to make a decision. The cohort analysis shows that women and children are more prone to use such strategies although their performance is not undermined. Our results are of interest for better handling clients expectations of trading companies, to avoid behavioural anomalies in financial analysts decisions and to improve not only the design of markets but also the trading digital interfaces where information is set down. Strategies and behavioural biases observed can also be translated into new agent based modelling or stochastic price dynamics to better understand financial bubbles or the effects of asymmetric risk perception to price drops. PMID:27532219

Information Cost, Memory Length and Market Instability.

PubMed

Diks, Cees; Li, Xindan; Wu, Chengyao

2018-07-01

In this article, we study the instability of a stock market with a modified version of Diks and Dindo's (2008) model where the market is characterized by nonlinear interactions between informed traders and uninformed traders. In the interaction of heterogeneous agents, we replace the replicator dynamics for the fractions by logistic strategy switching. This modification makes the model more suitable for describing realistic price dynamics, as well as more robust with respect to parameter changes. One goal of our paper is to use this model to explore if the arrival of new information (news) and investor behavior have an effect on market instability. A second, related, goal is to study the way markets absorb new information, especially when the market is unstable and the price is far from being fully informative. We find that the dynamics become locally unstable and prices may deviate far from the fundamental price, routing to chaos through bifurcation, with increasing information costs or decreasing memory length of the uninformed traders.

Diffusion of innovations in social interaction systems. An agent-based model for the introduction of new drugs in markets.

PubMed

Pombo-Romero, Julio; Varela, Luis M; Ricoy, Carlos J

2013-06-01

The existence of imitative behavior among consumers is a well-known phenomenon in the field of Economics. This behavior is especially common in markets determined by a high degree of innovation, asymmetric information and/or price-inelastic demand, features that exist in the pharmaceutical market. This paper presents evidence of the existence of imitative behavior among primary care physicians in Galicia (Spain) when choosing treatments for their patients. From this and other evidence, we propose a dynamic model for determining the entry of new drugs into the market. To do this, we introduce the structure of the organization of primary health care centers and the presence of groups of doctors who are specially interrelated, as well as the existence of commercial pressure on doctors. For modeling purposes, physicians are treated as spins connected in an exponentially distributed complex network of the Watts-Strogatz type. The proposed model provides an explanation for the differences observed in the patterns of the introduction of technological innovations in different regions. The main cause of these differences is the different structure of relationships among consumers, where the existence of small groups that show a higher degree of coordination over the average is particularly influential. The evidence presented, together with the proposed model, might be useful for the design of optimal strategies for the introduction of new drugs, as well as for planning policies to manage pharmaceutical expenditure.

Beyond Needs Assessments: Marketing as Change Agent.

ERIC Educational Resources Information Center

Piland, William E.

1984-01-01

Views marketing techniques as agents of change providing valuable assistance to community college decision makers. Discusses the importance of a balance among the four P's of marketing (i.e., promotion, price, place, and product); and seven procedural steps in developing a sound marketing strategy. (DMM)

7 CFR 900.305 - Duties of referendum agent.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Conduct of Referenda To Determine Producer Approval of Milk Marketing Orders To Be Made Effective Pursuant to Agricultural Marketing Agreement Act of 1937, as Amended § 900.305 Duties of referendum agent. The... Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing...

Contagions across networks: colds and markets

NASA Astrophysics Data System (ADS)

Berryman, Matthew J.; Johnson, Neil F.; Abbott, Derek

2005-12-01

We explore a variety of network models describing transmission across a network. In particular we focus on transmission across composite networks, or "networks of networks", in which a finite number of networked objects are then themselves connected together into a network. In a disease context we introduce two interrelated viruses to hosts on a network, to model the infection of hosts in a classroom situation, with high rates of infection within a classroom, and lower rates of infection between classrooms. The hosts can be either susceptible to infection, infected, or recovering from each virus. During the infection stage and recovery stage there is some level of cross-immunity to related viruses. We explore the effects of immunizing sections of the community on transmission through social networks. In a stock market context we introduce memes, or virus-like ideas into a virtual agent-based model of a stock exchange. By varying the parameters of the individual traders and the way in which they are connected we are able to show emergent behaviour, including boom and bust cycles.

Agents' beliefs and economic regimes polarization in interacting markets

NASA Astrophysics Data System (ADS)

Cavalli, F.; Naimzada, A. K.; Pecora, N.; Pireddu, M.

2018-05-01

In the present paper, a model of a market consisting of real and financial interacting sectors is studied. Agents populating the stock market are assumed to be not able to observe the true underlying fundamental, and their beliefs are biased by either optimism or pessimism. Depending on the relevance they give to beliefs, they select the best performing strategy in an evolutionary perspective. The real side of the economy is described within a multiplier-accelerator framework with a nonlinear, bounded investment function. We study the effect of market integration, in particular, of the financialization of the real market. We show that strongly polarized beliefs in an evolutionary framework can introduce multiplicity of steady states, which, consisting in enhanced or depressed levels of income, reflect and reproduce the optimistic or pessimistic nature of the agents' beliefs. The polarization of these steady states, which coexist with an unbiased steady state, positively depends on that of the beliefs and on their relevance. Moreover, with a mixture of analytical and numerical tools, we show that such static characterization is inherited also at the dynamical level, with possibly complex attractors that are characterized by endogenously fluctuating pessimistic and optimistic prices and levels of national income, with the effect of having several coexisting business cycles. This framework, when stochastic perturbations are included, is able to account for stylized facts commonly observed in real financial markets, such as fat tails and excess volatility in the returns distributions, as well as bubbles and crashes for stock prices.

Agents' beliefs and economic regimes polarization in interacting markets.

PubMed

Cavalli, F; Naimzada, A K; Pecora, N; Pireddu, M

2018-05-01

In the present paper, a model of a market consisting of real and financial interacting sectors is studied. Agents populating the stock market are assumed to be not able to observe the true underlying fundamental, and their beliefs are biased by either optimism or pessimism. Depending on the relevance they give to beliefs, they select the best performing strategy in an evolutionary perspective. The real side of the economy is described within a multiplier-accelerator framework with a nonlinear, bounded investment function. We study the effect of market integration, in particular, of the financialization of the real market. We show that strongly polarized beliefs in an evolutionary framework can introduce multiplicity of steady states, which, consisting in enhanced or depressed levels of income, reflect and reproduce the optimistic or pessimistic nature of the agents' beliefs. The polarization of these steady states, which coexist with an unbiased steady state, positively depends on that of the beliefs and on their relevance. Moreover, with a mixture of analytical and numerical tools, we show that such static characterization is inherited also at the dynamical level, with possibly complex attractors that are characterized by endogenously fluctuating pessimistic and optimistic prices and levels of national income, with the effect of having several coexisting business cycles. This framework, when stochastic perturbations are included, is able to account for stylized facts commonly observed in real financial markets, such as fat tails and excess volatility in the returns distributions, as well as bubbles and crashes for stock prices.

Optimal advanced credit releases in ecosystem service markets.

PubMed

BenDor, Todd K; Guo, Tianshu; Yates, Andrew J

2014-03-01

Ecosystem service markets are popular policy tools for ecosystem protection. Advanced credit releases are an important factor affecting the supply side of ecosystem markets. Under an advanced credit release policy, regulators give ecosystem suppliers a fraction of the total ecosystem credits generated by a restoration project before it is verified that the project actually achieves the required ecological thresholds. In spite of their prominent role in ecosystem markets, there is virtually no regulatory or research literature on the proper design of advanced credit release policies. Using U.S. aquatic ecosystem markets as an example, we develop a principal-agent model of the behavior of regulators and wetland/stream mitigation bankers to determine and explore the optimal degree of advance credit release. The model highlights the tension between regulators' desire to induce market participation, while at the same time ensuring that bankers successfully complete ecological restoration. Our findings suggest several simple guidelines for strengthening advanced credit release policy.

Optimal Advanced Credit Releases in Ecosystem Service Markets

NASA Astrophysics Data System (ADS)

BenDor, Todd K.; Guo, Tianshu; Yates, Andrew J.

2014-03-01

Ecosystem service markets are popular policy tools for ecosystem protection. Advanced credit releases are an important factor affecting the supply side of ecosystem markets. Under an advanced credit release policy, regulators give ecosystem suppliers a fraction of the total ecosystem credits generated by a restoration project before it is verified that the project actually achieves the required ecological thresholds. In spite of their prominent role in ecosystem markets, there is virtually no regulatory or research literature on the proper design of advanced credit release policies. Using U.S. aquatic ecosystem markets as an example, we develop a principal-agent model of the behavior of regulators and wetland/stream mitigation bankers to determine and explore the optimal degree of advance credit release. The model highlights the tension between regulators' desire to induce market participation, while at the same time ensuring that bankers successfully complete ecological restoration. Our findings suggest several simple guidelines for strengthening advanced credit release policy.

Robust Reputations for Peer-to-peer Markets

DTIC Science & Technology

2007-05-24

in all the example markets we examined. Of course, this strategy allows the seller to mitigate a great deal of risk: if a buyer does not pay, the...larger values of T relative to R make agents somewhat more willing to try non-cooperative strategies while more a more negative S causes agents to be...allows the market to converge to a cooperative state in the transaction game. The strategies employed by agents in such a cooperative market need not

Market dynamics and stock price volatility

NASA Astrophysics Data System (ADS)

Li, H.; Rosser, J. B., Jr.

2004-06-01

This paper presents a possible explanation for some of the empirical properties of asset returns within a heterogeneous-agents framework. The model turns out, even if we assume the input fundamental value follows an simple Gaussian distribution lacking both fat tails and volatility dependence, these features can show up in the time series of asset returns. In this model, the profit comparison and switching between heterogeneous play key roles, which build a connection between endogenous market and the emergence of stylized facts.

77 FR 55197 - LNG Development Company, LLC; Application for Long-Term Authorization To Export Liquefied Natural...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-07

... LNG both on its own behalf and as agent for other parties who hold title to the LNG at the point of... degree from Rockies supply given that the market modeling commissioned by Oregon LNG demonstrates that... LNG requests authorization to export LNG acting on its own behalf or as agent for others. At present...

Analysis of a decision model in the context of equilibrium pricing and order book pricing

NASA Astrophysics Data System (ADS)

Wagner, D. C.; Schmitt, T. A.; Schäfer, R.; Guhr, T.; Wolf, D. E.

2014-12-01

An agent-based model for financial markets has to incorporate two aspects: decision making and price formation. We introduce a simple decision model and consider its implications in two different pricing schemes. First, we study its parameter dependence within a supply-demand balance setting. We find realistic behavior in a wide parameter range. Second, we embed our decision model in an order book setting. Here, we observe interesting features which are not present in the equilibrium pricing scheme. In particular, we find a nontrivial behavior of the order book volumes which reminds of a trend switching phenomenon. Thus, the decision making model alone does not realistically represent the trading and the stylized facts. The order book mechanism is crucial.

[Research on the marketing status of antimicrobial products and the use of antimicrobial agents indicated on product labels from 1991 through 2005].

PubMed

Nakashima, Harunobu; Miyano, Naoko; Matsunaga, Ichiro; Nakashima, Naomi; Kaniwa, Masa-aki

2007-05-01

To clarify the marketing status of antimicrobial products, descriptions on the labels of commercially available antimicrobial products were investigated from 1991 through 2005, and the results were analyzed using a database system on antimicrobial deodorant agents. A classification table of household antimicrobial products was prepared and revised, based on which target products were reviewed for any changes in the product type. The number of antimicrobial products markedly increased over 3 years starting from 1996, among which there were many products apparently not requiring antimicrobial processing. More recently, in the 2002 and 2004 surveys, while sales of kitchenware and daily necessities decreased, chemical products, baby articles, and articles for pets increased; this poses new problems. To clarify the use of antimicrobial agents in the target products, a 3-step (large, intermediate, small) classification table of antimicrobial agents was also prepared, based on which antimicrobial agents indicated on the product labels were checked. The rate of identifying the agents increased. However, this is because of the increase of chemical products and baby articles, both of which more frequently indicated the ingredient agents on the labels, and the decrease of kitchenware and daily necessities, which less frequently indicated them on the labels. Therefore there has been little change in the actual identification rate. The agents used are characterized by product types: quaternary ammonium salts, metal salts, and organic antimicrobials are commonly used in textiles, plastics, and chemical products, respectively. Since the use of natural organic agents has recently increased, the safety of these agents should be evaluated.

Information visualization of the minority game

NASA Astrophysics Data System (ADS)

Jiang, W.; Herbert, R. D.; Webber, R.

2008-02-01

Many dynamical systems produce large quantities of data. How can the system be understood from the output data? Often people are simply overwhelmed by the data. Traditional tools such as tables and plots are often not adequate, and new techniques are needed to help people to analyze the system. In this paper, we propose the use of two spacefilling visualization tools to examine the output from a complex agent-based financial model. We measure the effectiveness and performance of these tools through usability experiments. Based on the experimental results, we develop two new visualization techniques that combine the advantages and discard the disadvantages of the information visualization tools. The model we use is an evolutionary version of the Minority Game which simulates a financial market.

A novel approach to assess the spontaneous gastrointestinal bleeding risk of antithrombotic agents using Apc(min/+) mice.

PubMed

Wei, Huijun; Shang, Jin; Keohane, CarolAnn; Wang, Min; Li, Qiu; Ni, Weihua; O'Neill, Kim; Chintala, Madhu

2014-06-01

Assessment of the bleeding risk of antithrombotic agents is usually performed in healthy animals with some form of vascular injury to peripheral organs to induce bleeding. However, bleeding observed in patients with currently marketed antithrombotic drugs is typically spontaneous in nature such as intracranial haemorrhage (ICH) and gastrointestinal (GI) bleeding, which happens most frequently on top of preexisting pathologies such as GI ulcerations and polyps. Apc(min/+) mice are reported to develop multiple adenomas through the entire intestinal tract and display progressive anaemia.In this study, we evaluated the potential utility of Apc(min/+) mice as a model for assessing spontaneous GI bleeding with antithrombotic agents. Apc(min/+) mice exhibited progressive blood loss starting at the age of nine weeks. Despite the increase in bleeding, Apc(min/+) mice were in a hypercoagulable state and displayed an age-dependent increase in thrombin generation and circulating fibrinogen as well as a significant decrease in clotting times. We evaluated the effect of warfarin, dabigatran etexilate, apixaban and clopidogrel in this model by administering them in diet or in the drinking water to mice for 1-4 weeks. All of these marketed drugs significantly increased GI bleeding in Apc(min/+) mice, but not in wild-type mice. Although different exposure profiles of these antithrombotic agents make it challenging to compare the bleeding risk of compounds, our results indicate that the Apc(min/+) mouse may be a sensitive preclinical model for assessing the spontaneous GI bleeding risk of novel antithrombotic agents.

Breeds of risk-adjusted fundamentalist strategies in an order-driven market

NASA Astrophysics Data System (ADS)

LiCalzi, Marco; Pellizzari, Paolo

2006-01-01

This paper studies an order-driven stock market where agents have heterogeneous estimates of the fundamental value of the risky asset. The agents are budget-constrained and follow a value-based trading strategy which buys or sells depending on whether the price of the asset is below or above its risk-adjusted fundamental value. This environment generates returns that are remarkably leptokurtic and fat-tailed. By extending the study over a grid of different parameters for the fundamentalist trading strategy, we exhibit the existence of monotone relationships between the bid-ask spread demanded by the agents and several statistics of the returns. We conjecture that this effect, coupled with positive dependence of the risk premium on the volatility, generates positive feedbacks that might explain volatility bursts.

A Multi Agent-Based Framework for Simulating Household PHEV Distribution and Electric Distribution Network Impact

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

Cui, Xiaohui; Liu, Cheng; Kim, Hoe Kyoung

2011-01-01

The variation of household attributes such as income, travel distance, age, household member, and education for different residential areas may generate different market penetration rates for plug-in hybrid electric vehicle (PHEV). Residential areas with higher PHEV ownership could increase peak electric demand locally and require utilities to upgrade the electric distribution infrastructure even though the capacity of the regional power grid is under-utilized. Estimating the future PHEV ownership distribution at the residential household level can help us understand the impact of PHEV fleet on power line congestion, transformer overload and other unforeseen problems at the local residential distribution network level.more » It can also help utilities manage the timing of recharging demand to maximize load factors and utilization of existing distribution resources. This paper presents a multi agent-based simulation framework for 1) modeling spatial distribution of PHEV ownership at local residential household level, 2) discovering PHEV hot zones where PHEV ownership may quickly increase in the near future, and 3) estimating the impacts of the increasing PHEV ownership on the local electric distribution network with different charging strategies. In this paper, we use Knox County, TN as a case study to show the simulation results of the agent-based model (ABM) framework. However, the framework can be easily applied to other local areas in the US.« less

Dynamical behaviors of inter-out-of-equilibrium state intervals in Korean futures exchange markets

NASA Astrophysics Data System (ADS)

Lim, Gyuchang; Kim, SooYong; Kim, Kyungsik; Lee, Dong-In; Scalas, Enrico

2008-05-01

A recently discovered feature of financial markets, the two-phase phenomenon, is utilized to categorize a financial time series into two phases, namely equilibrium and out-of-equilibrium states. For out-of-equilibrium states, we analyze the time intervals at which the state is revisited. The power-law distribution of inter-out-of-equilibrium state intervals is shown and we present an analogy with discrete-time heat bath dynamics, similar to random Ising systems. In the mean-field approximation, this model reduces to a one-dimensional multiplicative process. By varying global and local model parameters, the relevance between volatilities in financial markets and the interaction strengths between agents in the Ising model are investigated and discussed.

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

Poverty index with time-varying consumption and income distributions

NASA Astrophysics Data System (ADS)

Chattopadhyay, Amit K.; Kumar, T. Krishna; Mallick, Sushanta K.

2017-03-01

Starting from a stochastic agent-based model to represent market exchange in a developing economy, we study time variations of the probability density function of income with simultaneous variation of the consumption deprivation (CD), where CD represents the shortfall in consumption from the saturation level of an essential commodity, cereal. Together, these two models combine income-expenditure-based market dynamics with time variations in consumption due to income. In this new unified theoretical structure, exchange of trade in assets is only allowed when the income exceeds consumption-deprivation while CD itself is endogenously obtained from a separate kinetic model. Our results reveal that the nature of time variation of the CD function leads to a downward trend in the threshold level of consumption of basic necessities, suggesting a possible dietary transition in terms of lower saturation level of food-grain consumption, possibly through an improvement in the level of living. The new poverty index, defined as CD, is amenable to approximate probabilistic prediction within a short time horizon. A major achievement of this work is the intrinsic independence of the poverty index from an exogenous poverty line, making it more objective for policy formulation as opposed to existing poverty indices in the literature.

Poverty index with time-varying consumption and income distributions.

PubMed

Chattopadhyay, Amit K; Kumar, T Krishna; Mallick, Sushanta K

2017-03-01

Starting from a stochastic agent-based model to represent market exchange in a developing economy, we study time variations of the probability density function of income with simultaneous variation of the consumption deprivation (CD), where CD represents the shortfall in consumption from the saturation level of an essential commodity, cereal. Together, these two models combine income-expenditure-based market dynamics with time variations in consumption due to income. In this new unified theoretical structure, exchange of trade in assets is only allowed when the income exceeds consumption-deprivation while CD itself is endogenously obtained from a separate kinetic model. Our results reveal that the nature of time variation of the CD function leads to a downward trend in the threshold level of consumption of basic necessities, suggesting a possible dietary transition in terms of lower saturation level of food-grain consumption, possibly through an improvement in the level of living. The new poverty index, defined as CD, is amenable to approximate probabilistic prediction within a short time horizon. A major achievement of this work is the intrinsic independence of the poverty index from an exogenous poverty line, making it more objective for policy formulation as opposed to existing poverty indices in the literature.

Deduction of initial strategy distributions of agents in mix-game models

NASA Astrophysics Data System (ADS)

Gou, Chengling

2006-11-01

This paper reports the effort of deducing the initial strategy distributions (ISDs) of agents in mix-game models that is used to predict a real financial time series generated from a target financial market. Using mix-games to predict Shanghai Index, we find that the time series of prediction accurate rates is sensitive to the ISDs of agents in group 2 who play a minority game, but less sensitive to the ISDs of agents in group 1 who play a majority game. And agents in group 2 tend to cluster in full strategy space (FSS) if the real financial time series has obvious tendency (upward or downward), otherwise they tend to scatter in FSS. We also find that the ISDs and the number of agents in group 1 influence the level of prediction accurate rates. Finally, this paper gives suggestion about further research.

Structure and Connectivity Analysis of Financial Complex System Based on G-Causality Network

NASA Astrophysics Data System (ADS)

Xu, Chuan-Ming; Yan, Yan; Zhu, Xiao-Wu; Li, Xiao-Teng; Chen, Xiao-Song

2013-11-01

The recent financial crisis highlights the inherent weaknesses of the financial market. To explore the mechanism that maintains the financial market as a system, we study the interactions of U.S. financial market from the network perspective. Applied with conditional Granger causality network analysis, network density, in-degree and out-degree rankings are important indicators to analyze the conditional causal relationships among financial agents, and further to assess the stability of U.S. financial systems. It is found that the topological structure of G-causality network in U.S. financial market changed in different stages over the last decade, especially during the recent global financial crisis. Network density of the G-causality model is much higher during the period of 2007-2009 crisis stage, and it reaches the peak value in 2008, the most turbulent time in the crisis. Ranked by in-degrees and out-degrees, insurance companies are listed in the top of 68 financial institutions during the crisis. They act as the hubs which are more easily influenced by other financial institutions and simultaneously influence others during the global financial disturbance.

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.

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.

Analysing Buyers' and Sellers' Strategic Interactions in Marketplaces: An Evolutionary Game Theoretic Approach

NASA Astrophysics Data System (ADS)

Vytelingum, Perukrishnen; Cliff, Dave; Jennings, Nicholas R.

We develop a new model to analyse the strategic behaviour of buyers and sellers in market mechanisms. In particular, we wish to understand how the different strategies they adopt affect their economic efficiency in the market and to understand the impact of these choices on the overall efficiency of the marketplace. To this end, we adopt a two-population evolutionary game theoretic approach, where we consider how the behaviours of both buyers and sellers evolve in marketplaces. In so doing, we address the shortcomings of the previous state-of-the-art analytical model that assumes that buyers and sellers have to adopt the same mixed strategy in the market. Finally, we apply our model in one of the most common market mechanisms, the Continuous Double Auction, and demonstrate how it allows us to provide new insights into the strategic interactions of such trading agents.

Modeling the stylized facts in finance through simple nonlinear adaptive systems

PubMed Central

Hommes, Cars H.

2002-01-01

Recent work on adaptive systems for modeling financial markets is discussed. Financial markets are viewed as evolutionary systems between different, competing trading strategies. Agents are boundedly rational in the sense that they tend to follow strategies that have performed well, according to realized profits or accumulated wealth, in the recent past. Simple technical trading rules may survive evolutionary competition in a heterogeneous world where prices and beliefs co-evolve over time. Evolutionary models can explain important stylized facts, such as fat tails, clustered volatility, and long memory, of real financial series. PMID:12011401

Emergence of power-law in a market with mixed models

NASA Astrophysics Data System (ADS)

Ali Saif, M.; Gade, Prashant M.

2007-10-01

We investigate the problem of wealth distribution from the viewpoint of asset exchange. Robust nature of Pareto's law across economies, ideologies and nations suggests that this could be an outcome of trading strategies. However, the simple asset exchange models fail to reproduce this feature. A Yardsale (YS) model in which amount put on the bet is a fraction of minimum of the two players leads to condensation of wealth in hands of some agent while theft and fraud (TF) model in which the amount to be exchanged is a fraction of loser's wealth leads to an exponential distribution of wealth. We show that if we allow few agents to follow a different model than others, i.e., there are some agents following TF model while rest follow YS model, it leads to distribution with power-law tails. Similar effect is observed when one carries out transactions for a fraction of one's wealth using TF model and for the rest YS model is used. We also observe a power-law tail in wealth distribution if we allow the agents to follow either of the models with some probability.

Evolution of wealth in a non-conservative economy driven by local Nash equilibria.

PubMed

Degond, Pierre; Liu, Jian-Guo; Ringhofer, Christian

2014-11-13

We develop a model for the evolution of wealth in a non-conservative economic environment, extending a theory developed in Degond et al. (2014 J. Stat. Phys. 154, 751-780 (doi:10.1007/s10955-013-0888-4)). The model considers a system of rational agents interacting in a game-theoretical framework. This evolution drives the dynamics of the agents in both wealth and economic configuration variables. The cost function is chosen to represent a risk-averse strategy of each agent. That is, the agent is more likely to interact with the market, the more predictable the market, and therefore the smaller its individual risk. This yields a kinetic equation for an effective single particle agent density with a Nash equilibrium serving as the local thermodynamic equilibrium. We consider a regime of scale separation where the large-scale dynamics is given by a hydrodynamic closure with this local equilibrium. A class of generalized collision invariants is developed to overcome the difficulty of the non-conservative property in the hydrodynamic closure derivation of the large-scale dynamics for the evolution of wealth distribution. The result is a system of gas dynamics-type equations for the density and average wealth of the agents on large scales. We recover the inverse Gamma distribution, which has been previously considered in the literature, as a local equilibrium for particular choices of the cost function. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Electricity market design for the prosumer era

NASA Astrophysics Data System (ADS)

Parag, Yael; Sovacool, Benjamin K.

2016-04-01

Prosumers are agents that both consume and produce energy. With the growth in small and medium-sized agents using solar photovoltaic panels, smart meters, vehicle-to-grid electric automobiles, home batteries and other ‘smart’ devices, prosuming offers the potential for consumers and vehicle owners to re-evaluate their energy practices. As the number of prosumers increases, the electric utility sector of today is likely to undergo significant changes over the coming decades, offering possibilities for greening of the system, but also bringing many unknowns and risks that need to be identified and managed. To develop strategies for the future, policymakers and planners need knowledge of how prosumers could be integrated effectively and efficiently into competitive electricity markets. Here we identify and discuss three promising potential prosumer markets related to prosumer grid integration, peer-to-peer models and prosumer community groups. We also caution against optimism by laying out a series of caveats and complexities.

A complex systems approach to constructing better models for managing financial markets and the economy

NASA Astrophysics Data System (ADS)

Farmer, J. Doyne; Gallegati, M.; Hommes, C.; Kirman, A.; Ormerod, P.; Cincotti, S.; Sanchez, A.; Helbing, D.

2012-11-01

We outline a vision for an ambitious program to understand the economy and financial markets as a complex evolving system of coupled networks of interacting agents. This is a completely different vision from that currently used in most economic models. This view implies new challenges and opportunities for policy and managing economic crises. The dynamics of such models inherently involve sudden and sometimes dramatic changes of state. Further, the tools and approaches we use emphasize the analysis of crises rather than of calm periods. In this they respond directly to the calls of Governors Bernanke and Trichet for new approaches to macroeconomic modelling.

Stochastic Technology Choice Model for Consequential Life Cycle Assessment.

PubMed

Kätelhön, Arne; Bardow, André; Suh, Sangwon

2016-12-06

Discussions on Consequential Life Cycle Assessment (CLCA) have relied largely on partial or general equilibrium models. Such models are useful for integrating market effects into CLCA, but also have well-recognized limitations such as the poor granularity of the sectoral definition and the assumption of perfect oversight by all economic agents. Building on the Rectangular-Choice-of-Technology (RCOT) model, this study proposes a new modeling approach for CLCA, the Technology Choice Model (TCM). In this approach, the RCOT model is adapted for its use in CLCA and extended to incorporate parameter uncertainties and suboptimal decisions due to market imperfections and information asymmetry in a stochastic setting. In a case study on rice production, we demonstrate that the proposed approach allows modeling of complex production technology mixes and their expected environmental outcomes under uncertainty, at a high level of detail. Incorporating the effect of production constraints, uncertainty, and suboptimal decisions by economic agents significantly affects technology mixes and associated greenhouse gas (GHG) emissions of the system under study. The case study also shows the model's ability to determine both the average and marginal environmental impacts of a product in response to changes in the quantity of final demand.

Minority Game of price promotions in fast moving consumer goods markets

NASA Astrophysics Data System (ADS)

Groot, Robert D.; Musters, Pieter A. D.

2005-05-01

A variation of the Minority Game has been applied to study the timing of promotional actions at retailers in the fast moving consumer goods market. The underlying hypotheses for this work are that price promotions are more effective when fewer than average competitors do a promotion, and that a promotion strategy can be based on past sales data. The first assumption has been checked by analysing 1467 promotional actions for three products on the Dutch market (ketchup, mayonnaise and curry sauce) over a 120-week period, both on an aggregated level and on retailer chain level. The second assumption was tested by analysing past sales data with the Minority Game. This revealed that high or low competitor promotional pressure for actual ketchup, mayonnaise, curry sauce and barbecue sauce markets is to some extent predictable up to a forecast of some 10 weeks. Whereas a random guess would be right 50% of the time, a single-agent game can predict the market with a success rate of 56% for a 6-9 week forecast. This number is the same for all four mentioned fast moving consumer markets. For a multi-agent game a larger variability in the success rate is obtained, but predictability can be as high as 65%. Contrary to expectation, the actual market does the opposite of what game theory would predict. This points at a systematic oscillation in the market. Even though this result is not fully understood, merely observing that this trend is present in the data could lead to exploitable trading benefits. As a check, random history strings were generated from which the statistical variation in the game prediction was studied. This shows that the odds are 1:1,000,000 that the observed pattern in the market is based on coincidence.

From General Game Descriptions to a Market Specification Language for General Trading Agents

NASA Astrophysics Data System (ADS)

Thielscher, Michael; Zhang, Dongmo

The idea behind General Game Playing is to build systems that, instead of being programmed for one specific task, are intelligent and flexible enough to negotiate an unknown environment solely on the basis of the rules which govern it. In this paper, we argue that this principle has the great potential to bring to a new level artificially intelligent systems in other application areas as well. Our specific interest lies in General Trading Agents, which are able to understand the rules of unknown markets and then to actively participate in them without human intervention. To this end, we extend the general Game Description Language into a language that allows to formally describe arbitrary markets in such a way that these specifications can be automatically processed by a computer. We present both syntax and a transition-based semantics for this Market Specification Language and illustrate its expressive power by presenting axiomatizations of several well-known auction types.

European Union centralised procedure for marketing authorisation of oncology drugs: an in-depth review of its efficiency.

PubMed

Netzer, Tilo

2006-03-01

In the European Union (EU) 20 anticancer agents have been successfully authorised via the Centralised Procedure since its implementation in 1995. Public information on these 20 agents has been reviewed in order to evaluate the effectiveness of the available regulatory mechanisms to facilitate the marketing authorisation of such drugs in the EU. These mechanisms include orphan drug legislation, exceptional circumstances provision and the accelerated evaluation procedure. Based on the fact that the EU orphan drug legislation was not implemented before the year 2000 no conclusions on its effectiveness to facilitate oncology drug development can be drawn today. Much more data are available on the effects of the exceptional circumstances provision, which was used in 6 out of 10 cases over the past four years. An analysis of the clinical data packages indicates that this provision allows authorisation of innovative oncology drugs based on smaller clinical data sets than required for full approval. The accelerated evaluation procedure was used in only one case and significantly reduced the scientific review time at the EU agencies. However, this mechanism does not influence the administrative time at the authorities, which accounted for almost one-third of the overall duration of the EU marketing authorisation procedures for oncology drugs. Revision of the EU drug legislation brings about some changes to the above-described provisions, with the potential for an improvement in the current situation. Thus, its implementation offers the chance to reduce the time that innovative oncology agents take to reach the market, although -- based on experience with the current procedures -- more effort is likely to be required to achieve this goal.

Retention of gadolinium compounds used in magnetic resonance imaging: a critical review and the recommendations of regulatory agencies.

PubMed

Martí-Bonmatí, L; Martí-Bonmatí, E

The Spanish Agency for Drugs and Healthcare Products (AEMPS), based on the recommendations of the European Committee for Risk Assessment in Pharmacovigilance, established on 13 March 2017 that linear gadolinium-based MR contrast media, such as MultiHance, Omniscan, Magnevist (currently not marketed) and Optimark (no longer marketed in Spain), the clinical benefits do not outweigh the potential risks derived from their use. AEMPS recommends to suspend its marketing for general use based on the retention of these compounds in the brain. On the other hand, the AEMPS justifies the maintenance of Primovist and MultiHance for liver studies, and Magnevist of intra-articular administration (not commercialized in Spain), and justified the almost exclusive use of macrocyclic structure contrasts (Gadovist, ProHance and Dotarem). However, this retention is known to be different for each of the contrast media. All existing gadolinium contrasts agents have a distribution phase with tissue retention, due to a very slow exchange, in the interstitium of bone, skin, kidney, brain and other organs. The existence of histological effects or clinical symptoms associated with the accumulation of these trace amounts of gadolinium has not been demonstrated. The major toxicological concern with these contrast agents is related to nephrogenic systemic fibrosis (NSF). Since the safety profiles are mainly related to the interstitial retention space in the tissues, it does not seem justified to actually exclude contrast media that do not have cases related to the NSF. Based on all of this, we disagree with the latest AEMPS recommendation suggesting the marketing stoppage of linear agents without considering the individual retention profiles. This recommendation is not based neither on the data nor existing knowledge about the retention, relaxivity and clinical efficiency of the Gd compounds. It is therefore necessary to carry out prospective studies on the histological and clinical relevance of these organic Gd deposits. Copyright © 2017 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.

Application of quantum master equation for long-term prognosis of asset-prices

NASA Astrophysics Data System (ADS)

Khrennikova, Polina

2016-05-01

This study combines the disciplines of behavioral finance and an extension of econophysics, namely the concepts and mathematical structure of quantum physics. We apply the formalism of quantum theory to model the dynamics of some correlated financial assets, where the proposed model can be potentially applied for developing a long-term prognosis of asset price formation. At the informational level, the asset price states interact with each other by the means of a ;financial bath;. The latter is composed of agents' expectations about the future developments of asset prices on the finance market, as well as financially important information from mass-media, society, and politicians. One of the essential behavioral factors leading to the quantum-like dynamics of asset prices is the irrationality of agents' expectations operating on the finance market. These expectations lead to a deeper type of uncertainty concerning the future price dynamics of the assets, than given by a classical probability theory, e.g., in the framework of the classical financial mathematics, which is based on the theory of stochastic processes. The quantum dimension of the uncertainty in price dynamics is expressed in the form of the price-states superposition and entanglement between the prices of the different financial assets. In our model, the resolution of this deep quantum uncertainty is mathematically captured with the aid of the quantum master equation (its quantum Markov approximation). We illustrate our model of preparation of a future asset price prognosis by a numerical simulation, involving two correlated assets. Their returns interact more intensively, than understood by a classical statistical correlation. The model predictions can be extended to more complex models to obtain price configuration for multiple assets and portfolios.

A hybrid agent-based approach for modeling microbiological systems.

PubMed

Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

2008-11-21

Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

Biological agents for controlling excessive scarring.

PubMed

Berman, Brian

2010-01-01

The potential of various biological agents to reduce or prevent excessive scar formation has now been evaluated in numerous in-vitro studies, experimental animal models and preliminary clinical trials, in some cases with particularly promising results. Perhaps prominent among this group of biological agents, and, to some degree, possibly representing marketed compounds already being used 'off label' to manage excessive scarring, are the tumor necrosis factor alpha antagonist etanercept, and immune-response modifiers such as IFNalpha2b and imiquimod. Additional assessment of these novel agents is now justified with a view to reducing or preventing hypertrophic scars, keloid scars and the recurrence of post-excision keloid lesions.

The LUE data model for representation of agents and fields

NASA Astrophysics Data System (ADS)

de Jong, Kor; Schmitz, Oliver; Karssenberg, Derek

2017-04-01

Traditionally, agents-based and field-based modelling environments use different data models to represent the state of information they manipulate. In agent-based modelling, involving the representation of phenomena as objects bounded in space and time, agents are often represented by classes, each of which represents a particular kind of agent and all its properties. Such classes can be used to represent entities like people, birds, cars and countries. In field-based modelling, involving the representation of the environment as continuous fields, fields are often represented by a discretization of space, using multidimensional arrays, each storing mostly a single attribute. Such arrays can be used to represent the elevation of the land-surface, the pH of the soil, or the population density in an area, for example. Representing a population of agents by class instances grouped in collections is an intuitive way of organizing information. A drawback, though, is that models in which class instances grouping properties are stored in collections are less efficient (execute slower) than models in which collections of properties are grouped. The field representation, on the other hand, is convenient for the efficient execution of models. Another drawback is that, because the data models used are so different, integrating agent-based and field-based models becomes difficult, since the model builder has to deal with multiple concepts, and often multiple modelling environments. With the development of the LUE data model [1] we aim at representing agents and fields within a single paradigm, by combining the advantages of the data models used in agent-based and field-based data modelling. This removes the barrier for writing integrated agent-based and field-based models. The resulting data model is intuitive to use and allows for efficient execution of models. LUE is both a high-level conceptual data model and a low-level physical data model. The LUE conceptual data model is a generalization of the data models used in agent-based and field-based modelling. The LUE physical data model [2] is an implementation of the LUE conceptual data model in HDF5. In our presentation we will provide details of our approach to organizing information about agents and fields. We will show examples of agent and field data represented by the conceptual and physical data model. References: [1] de Bakker, M.P., de Jong, K., Schmitz, O., Karssenberg, D., 2016. Design and demonstration of a data model to integrate agent-based and field-based modelling. Environmental Modelling and Software. http://dx.doi.org/10.1016/j.envsoft.2016.11.016 [2] de Jong, K., 2017. LUE source code. https://github.com/pcraster/lue

7 CFR 75.15 - Authority of agent.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 3 2010-01-01 2010-01-01 false Authority of agent. 75.15 Section 75.15 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF 1946 AND THE...

7 CFR 75.15 - Authority of agent.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 3 2014-01-01 2014-01-01 false Authority of agent. 75.15 Section 75.15 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF 1946 AND THE...

7 CFR 75.15 - Authority of agent.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 3 2012-01-01 2012-01-01 false Authority of agent. 75.15 Section 75.15 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF 1946 AND THE...

7 CFR 75.15 - Authority of agent.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 3 2011-01-01 2011-01-01 false Authority of agent. 75.15 Section 75.15 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF 1946 AND THE...

7 CFR 75.15 - Authority of agent.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 3 2013-01-01 2013-01-01 false Authority of agent. 75.15 Section 75.15 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF 1946 AND THE...

Natural products for pest control: an analysis of their role, value and future.

PubMed

Gerwick, B Clifford; Sparks, Thomas C

2014-08-01

Natural products (NPs) have long been used as pesticides and have broadly served as a source of inspiration for a great many commercial synthetic organic fungicides, herbicides and insecticides that are in the market today. In light of the continuing need for new tools to address an ever-changing array of fungal, weed and insect pests, NPs continue to be a source of models and templates for the development of new pest control agents. Interestingly, an examination of the literature suggests that NP models exist for many of the pest control agents that were discovered by other means, suggesting that, had circumstances been different, these NPs could have served as inspiration for the discovery of a great many more of today's pest control agents. Here, an attempt is made to answer questions regarding the existence of an NP model for existing classes of pesticides and what is needed for the discovery of new NPs and NP models for pest control agents. © 2014 Society of Chemical Industry.

Investigation of Simulated Trading — A multi agent based trading system for optimization purposes

NASA Astrophysics Data System (ADS)

Schneider, Johannes J.

2010-07-01

Some years ago, Bachem, Hochstättler, and Malich proposed a heuristic algorithm called Simulated Trading for the optimization of vehicle routing problems. Computational agents place buy-orders and sell-orders for customers to be handled at a virtual financial market, the prices of the orders depending on the costs of inserting the customer in the tour or for his removal. According to a proposed rule set, the financial market creates a buy-and-sell graph for the various orders in the order book, intending to optimize the overall system. Here I present a thorough investigation for the application of this algorithm to the traveling salesman problem.

A Multi-Scale Energy Food Systems Modeling Framework For Climate Adaptation

NASA Astrophysics Data System (ADS)

Siddiqui, S.; Bakker, C.; Zaitchik, B. F.; Hobbs, B. F.; Broaddus, E.; Neff, R.; Haskett, J.; Parker, C.

2016-12-01

Our goal is to understand coupled system dynamics across scales in a manner that allows us to quantify the sensitivity of critical human outcomes (nutritional satisfaction, household economic well-being) to development strategies and to climate or market induced shocks in sub-Saharan Africa. We adopt both bottom-up and top-down multi-scale modeling approaches focusing our efforts on food, energy, water (FEW) dynamics to define, parameterize, and evaluate modeled processes nationally as well as across climate zones and communities. Our framework comprises three complementary modeling techniques spanning local, sub-national and national scales to capture interdependencies between sectors, across time scales, and on multiple levels of geographic aggregation. At the center is a multi-player micro-economic (MME) partial equilibrium model for the production, consumption, storage, and transportation of food, energy, and fuels, which is the focus of this presentation. We show why such models can be very useful for linking and integrating across time and spatial scales, as well as a wide variety of models including an agent-based model applied to rural villages and larger population centers, an optimization-based electricity infrastructure model at a regional scale, and a computable general equilibrium model, which is applied to understand FEW resources and economic patterns at national scale. The MME is based on aggregating individual optimization problems for relevant players in an energy, electricity, or food market and captures important food supply chain components of trade and food distribution accounting for infrastructure and geography. Second, our model considers food access and utilization by modeling food waste and disaggregating consumption by income and age. Third, the model is set up to evaluate the effects of seasonality and system shocks on supply, demand, infrastructure, and transportation in both energy and food.

Optimization of space system development resources

NASA Astrophysics Data System (ADS)

Kosmann, William J.; Sarkani, Shahram; Mazzuchi, Thomas

2013-06-01

NASA has had a decades-long problem with cost growth during the development of space science missions. Numerous agency-sponsored studies have produced average mission level cost growths ranging from 23% to 77%. A new study of 26 historical NASA Science instrument set developments using expert judgment to reallocate key development resources has an average cost growth of 73.77%. Twice in history, a barter-based mechanism has been used to reallocate key development resources during instrument development. The mean instrument set development cost growth was -1.55%. Performing a bivariate inference on the means of these two distributions, there is statistical evidence to support the claim that using a barter-based mechanism to reallocate key instrument development resources will result in a lower expected cost growth than using the expert judgment approach. Agent-based discrete event simulation is the natural way to model a trade environment. A NetLogo agent-based barter-based simulation of science instrument development was created. The agent-based model was validated against the Cassini historical example, as the starting and ending instrument development conditions are available. The resulting validated agent-based barter-based science instrument resource reallocation simulation was used to perform 300 instrument development simulations, using barter to reallocate development resources. The mean cost growth was -3.365%. A bivariate inference on the means was performed to determine that additional significant statistical evidence exists to support a claim that using barter-based resource reallocation will result in lower expected cost growth, with respect to the historical expert judgment approach. Barter-based key development resource reallocation should work on spacecraft development as well as it has worked on instrument development. A new study of 28 historical NASA science spacecraft developments has an average cost growth of 46.04%. As barter-based key development resource reallocation has never been tried in a spacecraft development, no historical results exist, and a simulation of using that approach must be developed. The instrument development simulation should be modified to account for spacecraft development market participant differences. The resulting agent-based barter-based spacecraft resource reallocation simulation would then be used to determine if significant statistical evidence exists to prove a claim that using barter-based resource reallocation will result in lower expected cost growth.

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).

Possibilities of fractal analysis of the competitive dynamics: Approaches and procedures

NASA Astrophysics Data System (ADS)

Zagornaya, T. O.; Medvedeva, M. A.; Panova, V. L.; Isaichik, K. F.; Medvedev, A. N.

2017-11-01

The possibilities of the fractal approach are used for the study of non-linear nature of the competitive dynamics of the market of trading intermediaries. Based on a statistical study of the functioning of retail indicators in the region, the approach to the analysis of the characteristics of the competitive behavior of market participants is developed. The authors postulate the principles of studying the dynamics of competition as a result of changes in the characteristics of the vector and the competitive behavior of market agents.

Primary health care lessons from the northeast of Brazil: the Agentes de Saúde Program.

PubMed

Cufino Svitone, E; Garfield, R; Vasconcelos, M I; Araujo Craveiro, V

2000-05-01

Market-led economic reforms are usually viewed as being in conflict with government-stimulated socioeconomic development for disadvantaged groups. Nevertheless, Ceará, a poor state in the Northeast of Brazil, has since 1987 pursued both of those strategies simultaneously. One part of that approach has been a program of nurse-directed auxiliary health workers serving about 5 million people--almost all the persons outside the capital city and half of those in the capital. The system requires that the auxiliaries, called agentes de saúde, live in the local communities that they serve. The health agents visit each home once a month to carry out a small number of priority health activities. While health agent positions are in high demand, the minimum-wage salary that the agents receive makes up only a small portion of the state budget. A key aspect of the system is timely and comprehensive information, which is based on agent visits and is managed by trained nurses. Since the health agents system was launched, there has been a rapid decline in infant mortality, a rapid rise in immunization, identification of bottlenecks limiting the utilization of other medical resources, and timely interventions in times of crisis. The health agents system has combined administrative decentralization with financial centralization during a period of electoral democratization. The system has strengthened Ceará's commitment to primary care even as market-oriented changes have reduced the overall role of government. The Ceará program is being copied throughout the Northeast and other regions of Brazil. The key role that nurses play in the Ceará program in organizing and leading a system of basic primary care in poor neighborhoods and rural areas may provide useful lessons for other countries. In addition, Ceará does not have many of the favorable characteristics of other countries that have successfully invested in primary health care. Ceará thus represents a more achievable model for other countries, where, like Brazil, income, educational levels, and land tenure equity are limited.

A Systematic Review of Agent-Based Modelling and Simulation Applications in the Higher Education Domain

ERIC Educational Resources Information Center

Gu, X.; Blackmore, K. L.

2015-01-01

This paper presents the results of a systematic review of agent-based modelling and simulation (ABMS) applications in the higher education (HE) domain. Agent-based modelling is a "bottom-up" modelling paradigm in which system-level behaviour (macro) is modelled through the behaviour of individual local-level agent interactions (micro).…

Agent autonomy approach to probabilistic physics-of-failure modeling of complex dynamic systems with interacting failure mechanisms

NASA Astrophysics Data System (ADS)

Gromek, Katherine Emily

A novel computational and inference framework of the physics-of-failure (PoF) reliability modeling for complex dynamic systems has been established in this research. The PoF-based reliability models are used to perform a real time simulation of system failure processes, so that the system level reliability modeling would constitute inferences from checking the status of component level reliability at any given time. The "agent autonomy" concept is applied as a solution method for the system-level probabilistic PoF-based (i.e. PPoF-based) modeling. This concept originated from artificial intelligence (AI) as a leading intelligent computational inference in modeling of multi agents systems (MAS). The concept of agent autonomy in the context of reliability modeling was first proposed by M. Azarkhail [1], where a fundamentally new idea of system representation by autonomous intelligent agents for the purpose of reliability modeling was introduced. Contribution of the current work lies in the further development of the agent anatomy concept, particularly the refined agent classification within the scope of the PoF-based system reliability modeling, new approaches to the learning and the autonomy properties of the intelligent agents, and modeling interacting failure mechanisms within the dynamic engineering system. The autonomous property of intelligent agents is defined as agent's ability to self-activate, deactivate or completely redefine their role in the analysis. This property of agents and the ability to model interacting failure mechanisms of the system elements makes the agent autonomy fundamentally different from all existing methods of probabilistic PoF-based reliability modeling. 1. Azarkhail, M., "Agent Autonomy Approach to Physics-Based Reliability Modeling of Structures and Mechanical Systems", PhD thesis, University of Maryland, College Park, 2007.

Agent-Based Modeling of Chronic Diseases: A Narrative Review and Future Research Directions

PubMed Central

Lawley, Mark A.; Siscovick, David S.; Zhang, Donglan; Pagán, José A.

2016-01-01

The United States is experiencing an epidemic of chronic disease. As the US population ages, health care providers and policy makers urgently need decision models that provide systematic, credible prediction regarding the prevention and treatment of chronic diseases to improve population health management and medical decision-making. Agent-based modeling is a promising systems science approach that can model complex interactions and processes related to chronic health conditions, such as adaptive behaviors, feedback loops, and contextual effects. This article introduces agent-based modeling by providing a narrative review of agent-based models of chronic disease and identifying the characteristics of various chronic health conditions that must be taken into account to build effective clinical- and policy-relevant models. We also identify barriers to adopting agent-based models to study chronic diseases. Finally, we discuss future research directions of agent-based modeling applied to problems related to specific chronic health conditions. PMID:27236380

Agent-Based Modeling of Chronic Diseases: A Narrative Review and Future Research Directions.

PubMed

Li, Yan; Lawley, Mark A; Siscovick, David S; Zhang, Donglan; Pagán, José A

2016-05-26

The United States is experiencing an epidemic of chronic disease. As the US population ages, health care providers and policy makers urgently need decision models that provide systematic, credible prediction regarding the prevention and treatment of chronic diseases to improve population health management and medical decision-making. Agent-based modeling is a promising systems science approach that can model complex interactions and processes related to chronic health conditions, such as adaptive behaviors, feedback loops, and contextual effects. This article introduces agent-based modeling by providing a narrative review of agent-based models of chronic disease and identifying the characteristics of various chronic health conditions that must be taken into account to build effective clinical- and policy-relevant models. We also identify barriers to adopting agent-based models to study chronic diseases. Finally, we discuss future research directions of agent-based modeling applied to problems related to specific chronic health conditions.

Maritime Domain Awareness via Agent Learning and Collaboration

DTIC Science & Technology

2010-06-24

available search engines (e.g. Google-like search) are based on popularity or authority scores, which are proven to be useful in marketing and advertising applications...Useful in  marketing   and   advertising  applications  – Not as useful for intelligence applications  – Finding anomalous information can be the goal  • Our

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.

Representing Micro-Macro Linkages by Actor-Based Dynamic Network Models

ERIC Educational Resources Information Center

Snijders, Tom A. B.; Steglich, Christian E. G.

2015-01-01

Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of…

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.

Grid commerce, market-driven G-negotiation, and Grid resource management.

PubMed

Sim, Kwang Mong

2006-12-01

Although the management of resources is essential for realizing a computational grid, providing an efficient resource allocation mechanism is a complex undertaking. Since Grid providers and consumers may be independent bodies, negotiation among them is necessary. The contribution of this paper is showing that market-driven agents (MDAs) are appropriate tools for Grid resource negotiation. MDAs are e-negotiation agents designed with the flexibility of: 1) making adjustable amounts of concession taking into account market rivalry, outside options, and time preferences and 2) relaxing bargaining terms in the face of intense pressure. A heterogeneous testbed consisting of several types of e-negotiation agents to simulate a Grid computing environment was developed. It compares the performance of MDAs against other e-negotiation agents (e.g., Kasbah) in a Grid-commerce environment. Empirical results show that MDAs generally achieve: 1) higher budget efficiencies in many market situations than other e-negotiation agents in the testbed and 2) higher success rates in acquiring Grid resources under high Grid loadings.

AGENT-BASED MODELS IN EMPIRICAL SOCIAL RESEARCH*

PubMed Central

Bruch, Elizabeth; Atwell, Jon

2014-01-01

Agent-based modeling has become increasingly popular in recent years, but there is still no codified set of recommendations or practices for how to use these models within a program of empirical research. This article provides ideas and practical guidelines drawn from sociology, biology, computer science, epidemiology, and statistics. We first discuss the motivations for using agent-based models in both basic science and policy-oriented social research. Next, we provide an overview of methods and strategies for incorporating data on behavior and populations into agent-based models, and review techniques for validating and testing the sensitivity of agent-based models. We close with suggested directions for future research. PMID:25983351

Modeling and Simulation of the Economics of Mining in the Bitcoin Market

PubMed Central

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. PMID:27768691

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.

Smart Grid as Multi-layer Interacting System for Complex Decision Makings

NASA Astrophysics Data System (ADS)

Bompard, Ettore; Han, Bei; Masera, Marcelo; Pons, Enrico

This chapter presents an approach to the analysis of Smart Grids based on a multi-layer representation of their technical, cyber, social and decision-making aspects, as well as the related environmental constraints. In the Smart Grid paradigm, self-interested active customers (prosumers), system operators and market players interact among themselves making use of an extensive cyber infrastructure. In addition, policy decision makers define regulations, incentives and constraints to drive the behavior of the competing operators and prosumers, with the objective of ensuring the global desired performance (e.g. system stability, fair prices). For these reasons, the policy decision making is more complicated than in traditional power systems, and needs proper modeling and simulation tools for assessing "in vitro" and ex-ante the possible impacts of the decisions assumed. In this chapter, we consider the smart grids as multi-layered interacting complex systems. The intricacy of the framework, characterized by several interacting layers, cannot be captured by closed-form mathematical models. Therefore, a new approach using Multi Agent Simulation is described. With case studies we provide some indications about how to develop agent-based simulation tools presenting some preliminary examples.

Modeling marine oily wastewater treatment by a probabilistic agent-based approach.

PubMed

Jing, Liang; Chen, Bing; Zhang, Baiyu; Ye, Xudong

2018-02-01

This study developed a novel probabilistic agent-based approach for modeling of marine oily wastewater treatment processes. It begins first by constructing a probability-based agent simulation model, followed by a global sensitivity analysis and a genetic algorithm-based calibration. The proposed modeling approach was tested through a case study of the removal of naphthalene from marine oily wastewater using UV irradiation. The removal of naphthalene was described by an agent-based simulation model using 8 types of agents and 11 reactions. Each reaction was governed by a probability parameter to determine its occurrence. The modeling results showed that the root mean square errors between modeled and observed removal rates were 8.73 and 11.03% for calibration and validation runs, respectively. Reaction competition was analyzed by comparing agent-based reaction probabilities, while agents' heterogeneity was visualized by plotting their real-time spatial distribution, showing a strong potential for reactor design and process optimization. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effects of diversity on multiagent systems: Minority games

NASA Astrophysics Data System (ADS)

Wong, K. Y. Michael; Lim, S. W.; Gao, Zhuo

2005-06-01

We consider a version of large population games whose agents compete for resources using strategies with adaptable preferences. The games can be used to model economic markets, ecosystems, or distributed control. Diversity of initial preferences of strategies is introduced by randomly assigning biases to the strategies of different agents. We find that diversity among the agents reduces their maladaptive behavior. We find interesting scaling relations with diversity for the variance and other parameters such as the convergence time, the fraction of fickle agents, and the variance of wealth, illustrating their dynamical origin. When diversity increases, the scaling dynamics is modified by kinetic sampling and waiting effects. Analyses yield excellent agreement with simulations.

An Active Learning Exercise for Introducing Agent-Based Modeling

ERIC Educational Resources Information Center

Pinder, Jonathan P.

2013-01-01

Recent developments in agent-based modeling as a method of systems analysis and optimization indicate that students in business analytics need an introduction to the terminology, concepts, and framework of agent-based modeling. This article presents an active learning exercise for MBA students in business analytics that demonstrates agent-based…

Ups and downs of economics and econophysics — Facebook forecast

NASA Astrophysics Data System (ADS)

Gajic, Nenad; Budinski-Petkovic, Ljuba

2013-01-01

What is econophysics and its relationship with economics? What is the state of economics after the global economic crisis, and is there a future for the paradigm of market equilibrium, with imaginary perfect competition and rational agents? Can the next paradigm of economics adopt important assumptions derived from econophysics models: that markets are chaotic systems, striving to extremes as bubbles and crashes show, with psychologically motivated, statistically predictable individual behaviors? Is the future of econophysics, as predicted here, to disappear and become a part of economics? A good test of the current state of econophysics and its methods is the valuation of Facebook immediately after the initial public offering - this forecast indicates that Facebook is highly overvalued, and its IPO valuation of 104 billion dollars is mostly the new financial bubble based on the expectations of unlimited growth, although it’s easy to prove that Facebook is close to the upper limit of its users.

Soy-Based Therapeutic Baby Formulas: Testable Hypotheses Regarding the Pros and Cons.

PubMed

Westmark, Cara J

2016-01-01

Soy-based infant formulas have been consumed in the United States since 1909, and currently constitute a significant portion of the infant formula market. There are efforts underway to generate genetically modified soybeans that produce therapeutic agents of interest with the intent to deliver those agents in a soy-based infant formula platform. The threefold purpose of this review article is to first discuss the pros and cons of soy-based infant formulas, then present testable hypotheses to discern the suitability of a soy platform for drug delivery in babies, and finally start a discussion to inform public policy on this important area of infant nutrition.

Profiting from competition: Financial tools for electric generation companies

NASA Astrophysics Data System (ADS)

Richter, Charles William, Jr.

Regulations governing the operation of electric power systems in North America and many other areas of the world are undergoing major changes designed to promote competition. This process of change is often referred to as deregulation. Participants in deregulated electricity systems may find that their profits will greatly benefit from the implementation of successful bidding strategies. While the goal of the regulators may be to create rules which balance reliable power system operation with maximization of the total benefit to society, the goal of generation companies is to maximize their profit, i.e., return to their shareholders. The majority of the research described here is conducted from the point of view of generation companies (GENCOs) wishing to maximize their expected utility function, which is generally comprised of expected profit and risk. Strategies that help a GENCO to maximize its objective function must consider the impact of (and aid in making) operating decisions that may occur within a few seconds to multiple years. The work described here assumes an environment in which energy service companies (ESCOs) buy and GENCOs sell power via double auctions in regional commodity exchanges. Power is transported on wires owned by transmission companies (TRANSCOs) and distribution companies (DISTCOs). The proposed market framework allows participants to trade electrical energy contracts via the spot, futures, options, planning, and swap markets. An important method of studying these proposed markets and the behavior of participating agents is the field of experimental/computational economics. For much of the research reported here, the market simulator developed by Kumar and Sheble and similar simulators has been adapted to allow computerized agents to trade energy. Creating computerized agents that can react as rationally or irrationally as a human trader is a difficult problem for which we have turned to the field of artificial intelligence. Some of our work uses GP-Automata, a technique which combines genetic programming and finite state machines, to represent adaptive agents. We use a genetic algorithm to evolve these adaptive agents (each with its own bidding strategy) for use in a double auction. The agent's strategies may be judged by the amount of profit they produce and are tested by computerized agents repeatedly buying and selling electricity in an auction simulator. In addition to the obvious profit-maximization strategies, one can also design strategies which exhibit other types of trading behaviors. The resulting strategies can be used directly in on-line trading, or as realistic models of competitors in a trading simulator. In addition to developing double auction bidding strategies, we investigate and discuss methods of an energy trader's risk. This can be done using such financial vehicles as futures and options contracts or through the inclusion of risk while judging strategies used in the market simulations described above. We discuss the role of fuzzy logic in the competitive electric marketplace, including how it can be applied in developing bidding strategies. Since competition promises to drive the power system closer to its operating limits, improvements in measurement and system control will be important. We provide an example of using fuzzy logic to do automatic generation control and discuss extensions that would make it superior to traditional controllers. Since the GENCO's forte is primarily generating electricity, we examine unit commitment and discuss how to update it for the competitive environment. We discuss the role of unit commitment in developing bidding strategies, as well as, the role of bidding strategies in solving the unit commitment problem. Depending on the market structure adopted by a particular location, large amounts of bidding data may be available to regulators or market participants. Ideally, regulators could use this data to verify dig the market is efficient. Market participants with access to this data might gain an advantage over their competitors if they could somehow determine their competitor's bidding strategy. We outline methods of automatically inferring other participants' trading rules based on historical data. Much of the work described here should aid in the design of effective operating procedures, trading strategies and profitable portfolios for energy producers.

Herd behaviour experimental testing in laboratory artificial stock market settings. Behavioural foundations of stylised facts of financial returns

NASA Astrophysics Data System (ADS)

Manahov, Viktor; Hudson, Robert

2013-10-01

Many scholars express concerns that herding behaviour causes excess volatility, destabilises financial markets, and increases the likelihood of systemic risk. We use a special form of the Strongly Typed Genetic Programming (STGP) technique to evolve a stock market divided into two groups-a small subset of artificial agents called ‘Best Agents’ and a main cohort of agents named ‘All Agents’. The ‘Best Agents’ perform best in term of the trailing return of a wealth moving average. We then investigate whether herding behaviour can arise when agents trade Dow Jones, General Electric, and IBM financial instruments in four different artificial stock markets. This paper uses real historical quotes of the three financial instruments to analyse the behavioural foundations of stylised facts such as leptokurtosis, non-IIDness, and volatility clustering. We found evidence of more herding in a group of stocks than in individual stocks, but the magnitude of herding does not contribute to the mispricing of assets in the long run. Our findings suggest that the price formation process caused by the collective behaviour of the entire market exhibit less herding and is more efficient than the segmented market populated by a small subset of agents. Hence, greater genetic diversity leads to greater consistency with fundamental values and market efficiency.

Dynamic Modeling of New Technology Succession: Projecting the Impact of Macro Events and Micro Behaviors On Software Market Cycles

NASA Astrophysics Data System (ADS)

Mertz, Sharon A.; Groothuis, Adam; Fellman, Philip Vos

The subject of technology succession and new technology adoption in a generalized sense has been addressed by numerous authors for over one hundred years. Models which accommodate macro-level events as well as micro-level actions are needed to gain insight to future market outcomes. In the ICT industry, macro-level factors affecting technology adoption include global events and shocks, economic factors, and global regulatory trends. Micro-level elements involve individual agent actions and interactions, such as the behaviors of buyers and suppliers in reaction to each other, and to macro events. Projecting technology adoption and software market composition and growth requires evaluating a special set of technology characteristics, buyer behaviors, and supplier issues and responses which make this effort particularly challenging.

Empirical and theoretical analysis of complex systems

NASA Astrophysics Data System (ADS)

Zhao, Guannan

This thesis is an interdisciplinary work under the heading of complexity science which focuses on an arguably common "hard" problem across physics, finance and biology [1], to quantify and mimic the macroscopic "emergent phenomenon" in large-scale systems consisting of many interacting "particles" governed by microscopic rules. In contrast to traditional statistical physics, we are interested in systems whose dynamics are subject to feedback, evolution, adaption, openness, etc. Global financial markets, like the stock market and currency market, are ideal candidate systems for such a complexity study: there exists a vast amount of accurate data, which is the aggregate output of many autonomous agents continuously competing with each other. We started by examining the ultrafast "mini flash crash (MFC)" events in the US stock market. An abrupt system-wide composition transition from a mixed human machine phase to a new all-machine phase is uncovered, and a novel theory developed to explain this observation. Then in the study of FX market, we found an unexpected variation in the synchronicity of price changes in different market subsections as a function of the overall trading activity. Several survival models have been tested in analyzing the distribution of waiting times to the next price change. In the region of long waiting-times, the distribution for each currency pair exhibits a power law with exponent in the vicinity of 3.5. By contrast, for short waiting times only, the market activity can be mimicked by the fluctuations emerging from a finite resource competition model containing multiple agents with limited rationality (so called El Farol Model). Switching to the biomedical domain, we present a minimal mathematical model built around a co-evolving resource network and cell population, yielding good agreement with primary tumors in mice experiment and with clinical metastasis data. In the quest to understand contagion phenomena in systems where social group structures evolve on a similar timescale to individual level transmission, we investigated the process of transmission through a model population comprising of social groups which follow simple dynamical rules for growth and break-up, and the profiles produced bear a striking resemblance to empirical data obtained from social, financial and biological systems. Finally, for better implementation of a widely accepted power law test algorithm, we have developed a fast testing procedure using parallel computation.

A common mode of origin of power laws in models of market and earthquake

NASA Astrophysics Data System (ADS)

Bhattacharyya, Pratip; Chatterjee, Arnab; Chakrabarti, Bikas K.

2007-07-01

We show that there is a common mode of origin for the power laws observed in two different models: (i) the Pareto law for the distribution of money among the agents with random-saving propensities in an ideal gas-like market model and (ii) the Gutenberg-Richter law for the distribution of overlaps in a fractal-overlap model for earthquakes. We find that the power laws appear as the asymptotic forms of ever-widening log-normal distributions for the agents’ money and the overlap magnitude, respectively. The identification of the generic origin of the power laws helps in better understanding and in developing generalized views of phenomena in such diverse areas as economics and geophysics.

SPARK: A Framework for Multi-Scale Agent-Based Biomedical Modeling.

PubMed

Solovyev, Alexey; Mikheev, Maxim; Zhou, Leming; Dutta-Moscato, Joyeeta; Ziraldo, Cordelia; An, Gary; Vodovotz, Yoram; Mi, Qi

2010-01-01

Multi-scale modeling of complex biological systems remains a central challenge in the systems biology community. A method of dynamic knowledge representation known as agent-based modeling enables the study of higher level behavior emerging from discrete events performed by individual components. With the advancement of computer technology, agent-based modeling has emerged as an innovative technique to model the complexities of systems biology. In this work, the authors describe SPARK (Simple Platform for Agent-based Representation of Knowledge), a framework for agent-based modeling specifically designed for systems-level biomedical model development. SPARK is a stand-alone application written in Java. It provides a user-friendly interface, and a simple programming language for developing Agent-Based Models (ABMs). SPARK has the following features specialized for modeling biomedical systems: 1) continuous space that can simulate real physical space; 2) flexible agent size and shape that can represent the relative proportions of various cell types; 3) multiple spaces that can concurrently simulate and visualize multiple scales in biomedical models; 4) a convenient graphical user interface. Existing ABMs of diabetic foot ulcers and acute inflammation were implemented in SPARK. Models of identical complexity were run in both NetLogo and SPARK; the SPARK-based models ran two to three times faster.

The long road of biopharmaceutical drug development: from inception to marketing.

PubMed

Mundae, M K; Ostör, A J K

2010-01-01

The development of therapeutics is costly, time-consuming and has high attrition rates. Biopharmaceutical medications differ from traditional agents in their discovery, design, structure and formulation. Prior to marketing a drug must show efficacy and acceptable toxicity in both preclinical and clinical trials. Regulatory bodies have a pivotal role in the licensing, naming and marketing of an agent.

The trading rectangle strategy within book models

NASA Astrophysics Data System (ADS)

Matassini, Lorenzo

2001-12-01

We introduce a model of trading where traders interact through the insertion of orders in the book. This matching mechanism is a collection of the activity of agents: They can trade at the market price or place a limit order. The latter is valid until cancelled by the trader; to this end we introduce a threshold in time after which the probability of the order to be removed is strongly increased. There is essentially no source of randomness and all the traders share a common strategy, what we call trading rectangle. Since there are no fundamentalist rules, it is not so important to identify the right moment to enter in the market. Much more effort is required to decide when to sell. The model is able to reproduce many of the complex phenomena manifested in real stock markets, including the positive correlation between bid/ask spreads and volatility.

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

Multi-agent modelling of climate outlooks and food security on a community garden scheme in Limpopo, South Africa.

PubMed

Bharwani, Sukaina; Bithell, Mike; Downing, Thomas E; New, Mark; Washington, Richard; Ziervogel, Gina

2005-11-29

Seasonal climate outlooks provide one tool to help decision-makers allocate resources in anticipation of poor, fair or good seasons. The aim of the 'Climate Outlooks and Agent-Based Simulation of Adaptation in South Africa' project has been to investigate whether individuals, who adapt gradually to annual climate variability, are better equipped to respond to longer-term climate variability and change in a sustainable manner. Seasonal climate outlooks provide information on expected annual rainfall and thus can be used to adjust seasonal agricultural strategies to respond to expected climate conditions. A case study of smallholder farmers in a village in Vhembe district, Limpopo Province, South Africa has been used to examine how such climate outlooks might influence agricultural strategies and how this climate information can be improved to be more useful to farmers. Empirical field data has been collected using surveys, participatory approaches and computer-based knowledge elicitation tools to investigate the drivers of decision-making with a focus on the role of climate, market and livelihood needs. This data is used in an agent-based social simulation which incorporates household agents with varying adaptation options which result in differing impacts on crop yields and thus food security, as a result of using or ignoring the seasonal outlook. Key variables are the skill of the forecast, the social communication of the forecast and the range of available household and community-based risk coping strategies. This research provides a novel approach for exploring adaptation within the context of climate change.

Invisible hand effect in an evolutionary minority game model

NASA Astrophysics Data System (ADS)

Sysi-Aho, Marko; Saramäki, Jari; Kaski, Kimmo

2005-03-01

In this paper, we study the properties of a minority game with evolution realized by using genetic crossover to modify fixed-length decision-making strategies of agents. Although the agents in this evolutionary game act selfishly by trying to maximize their own performances only, it turns out that the whole society will eventually be rewarded optimally. This “invisible hand” effect is what Adam Smith over two centuries ago expected to take place in the context of free market mechanism. However, this behaviour of the society of agents is realized only under idealized conditions, where all agents are utilizing the same efficient evolutionary mechanism. If on the other hand part of the agents are adaptive, but not evolutionary, the system does not reach optimum performance, which is also the case if part of the evolutionary agents form a uniformly acting “cartel”.

Self-organized criticality in a network of economic agents with finite consumption

NASA Astrophysics Data System (ADS)

da Cruz, João P.; Lind, Pedro G.

2012-02-01

We introduce a minimal agent model to explain the emergence of heavy-tailed return distributions as a result of self-organized criticality. The model assumes that agents trade their economic outputs with each other composing a complex network of agents and connections. Further, the incoming degree of an agent is proportional to the demand on its goods, while its outgoing degree is proportional to the supply. The model considers a collection of economic agents which are attracted to establish connections among them to make an exchange at a price formed by supply and demand. With our model we are able to reproduce the evolution of the return of macroscopic quantities (indices) and to correctly retrieve the non-trivial exponent value characterizing the amplitude of drops in several indices in financial markets, relating it to the underlying topology of connections. The distribution of drops in empirical data is obtained by counting the number of successive time-steps for which a decrease in the index value is observed. All eight financial indexes show an exponent m˜5/2. Finally, we present mean-field calculations of the critical exponents, and of the scaling relation m=3/2 γ-1 between the exponent m for the distribution of drops and the topological exponent γ for the degree distribution.

New drugs of 2003.

PubMed

Hussar, Daniel A

2004-01-01

To provide information regarding the most important properties of the new therapeutic agents marketed in 2003. Product labeling supplemented selectively with published studies and drug information reference sources. By the author. By the author. The 28 new therapeutic agents marketed in the United States during 2003 are reviewed in this article: adalimumab, agalsidase beta, alefacept, alfuzosin hydrochloride, aprepitant, atazanavir sulfate, atomoxetine hydrochloride, bortezomib, daptomycin, efalizumab, eletriptan hydrobromide, emtricitabine, enfuvirtide, eplerenone, gefitinib, icodextrin, laronidase, memantine hydrochloride, mequinol/tretinoin, miglustat, nitazoxanide, omalizumab, palonosetron hydrochloride, pegvisomant, rosuvastatin calcium, tadalafil, tositumomab and iodine I 131 tositumomab, and vardenafil hydrochloride. Indications and information on dosage and administration for these agents are reviewed, as are the most important pharmacokinetic properties, adverse events, drug interactions, and other precautions. Practical considerations for the use of the new agents are also discussed. When possible, the properties of the new drugs are compared with those of older drugs marketed for the same indications. A number of the new therapeutic agents marketed in 2003 have important advantages over older medications. An understanding of the properties of these agents is important for the pharmacist to effectively counsel patients about their use and to serve as a valuable source of information for other health professionals regarding these drugs.

7 CFR 920.67 - Agents.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 8 2013-01-01 2013-01-01 false Agents. 920.67 Section 920.67 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (MARKETING AGREEMENTS AND ORDERS; FRUITS, VEGETABLES, NUTS), DEPARTMENT OF AGRICULTURE KIWIFRUIT GROWN IN CALIFORNIA Miscellaneous...

7 CFR 920.67 - Agents.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 8 2012-01-01 2012-01-01 false Agents. 920.67 Section 920.67 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing Agreements and Orders; Fruits, Vegetables, Nuts), DEPARTMENT OF AGRICULTURE KIWIFRUIT GROWN IN CALIFORNIA Miscellaneous...

7 CFR 920.67 - Agents.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 8 2014-01-01 2014-01-01 false Agents. 920.67 Section 920.67 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (MARKETING AGREEMENTS AND ORDERS; FRUITS, VEGETABLES, NUTS), DEPARTMENT OF AGRICULTURE KIWIFRUIT GROWN IN CALIFORNIA Miscellaneous...

7 CFR 920.67 - Agents.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 8 2011-01-01 2011-01-01 false Agents. 920.67 Section 920.67 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing Agreements and Orders; Fruits, Vegetables, Nuts), DEPARTMENT OF AGRICULTURE KIWIFRUIT GROWN IN CALIFORNIA Miscellaneous...

7 CFR 955.83 - Agents.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 8 2014-01-01 2014-01-01 false Agents. 955.83 Section 955.83 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (MARKETING AGREEMENTS AND ORDERS; FRUITS, VEGETABLES, NUTS), DEPARTMENT OF AGRICULTURE VIDALIA ONIONS GROWN IN GEORGIA...

7 CFR 955.83 - Agents.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Agents. 955.83 Section 955.83 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing Agreements and Orders; Fruits, Vegetables, Nuts), DEPARTMENT OF AGRICULTURE VIDALIA ONIONS GROWN IN GEORGIA...

7 CFR 955.83 - Agents.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 8 2013-01-01 2013-01-01 false Agents. 955.83 Section 955.83 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (MARKETING AGREEMENTS AND ORDERS; FRUITS, VEGETABLES, NUTS), DEPARTMENT OF AGRICULTURE VIDALIA ONIONS GROWN IN GEORGIA...

7 CFR 955.83 - Agents.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 8 2011-01-01 2011-01-01 false Agents. 955.83 Section 955.83 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing Agreements and Orders; Fruits, Vegetables, Nuts), DEPARTMENT OF AGRICULTURE VIDALIA ONIONS GROWN IN GEORGIA...

7 CFR 955.83 - Agents.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 8 2012-01-01 2012-01-01 false Agents. 955.83 Section 955.83 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing Agreements and Orders; Fruits, Vegetables, Nuts), DEPARTMENT OF AGRICULTURE VIDALIA ONIONS GROWN IN GEORGIA...

7 CFR 920.67 - Agents.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Agents. 920.67 Section 920.67 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing Agreements and Orders; Fruits, Vegetables, Nuts), DEPARTMENT OF AGRICULTURE KIWIFRUIT GROWN IN CALIFORNIA Miscellaneous...

Rational expectations, psychology and inductive learning via moving thresholds

NASA Astrophysics Data System (ADS)

Lamba, H.; Seaman, T.

2008-06-01

This paper modifies a previously introduced class of heterogeneous agent models in a way that allows for the inclusion of different types of agent motivations and behaviours in a consistent manner. The agents operate within a highly simplified environment where they are only able to be long or short one unit of the asset. The price of the asset is influenced by both an external information stream and the demand of the agents. The current strategy of each agent is defined by a pair of moving thresholds straddling the current price. When the price crosses either of the thresholds for a particular agent, that agent switches position and a new pair of thresholds is generated. The threshold dynamics can mimic different sources of investor motivation, running the gamut from purely rational information-processing, through rational (but often undesirable) behaviour induced by perverse incentives and moral hazards, to purely psychological effects. The simplest model of this kind precisely conforms to the Efficient Market Hypothesis (EMH) and this allows causal relationships to be established between actions at the agent level and violations of EMH price statistics at the global level. In particular, the effects of herding behaviour and perverse incentives are examined.

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.

Information-Constrained Optima with Retrading: An Externality and Its Market-Based Solution☆

PubMed Central

Kilenthong, Weerachart T.; Townsend, Robert M.

2010-01-01

This paper studies the efficiency of competitive equilibria in environments with a moral hazard problem and unobserved states, both with retrading in ex post spot markets. The interaction between private information problems and the possibility of retrade creates an externality, unless preferences have special, restrictive properties. The externality is internalized by allowing agents to contract ex ante on market fundamentals determining the spot price or interest rate, over and above contracting on actions and outputs. Then competitive equilibria are equivalent with the appropriate notion of constrained Pareto optimality. Examples show that it is possible to have multiple market fundamentals or price-islands, created endogenously in equilibrium. PMID:21765540

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.

Generic features of the wealth distribution in ideal-gas-like markets.

PubMed

Mohanty, P K

2006-07-01

We provide an exact solution to the ideal-gas-like models studied in econophysics to understand the microscopic origin of Pareto law. In these classes of models the key ingredient necessary for having a self-organized scale-free steady-state distribution is the trading or collision rule where agents or particles save a definite fraction of their wealth or energy and invest the rest for trading. Using a Gibbs ensemble approach we could obtain the exact distribution of wealth in this model. Moreover we show that in this model (a) good savers are always rich and (b) every agent poor or rich invests the same amount for trading. Nonlinear trading rules could alter the generic scenario observed here.

Cells, Agents, and Support Vectors in Interaction - Modeling Urban Sprawl based on Machine Learning and Artificial Intelligence Techniques in a Post-Industrial Region

NASA Astrophysics Data System (ADS)

Rienow, A.; Menz, G.

2015-12-01

Since the beginning of the millennium, artificial intelligence techniques as cellular automata (CA) and multi-agent systems (MAS) have been incorporated into land-system simulations to address the complex challenges of transitions in urban areas as open, dynamic systems. The study presents a hybrid modeling approach for modeling the two antagonistic processes of urban sprawl and urban decline at once. The simulation power of support vector machines (SVM), cellular automata (CA) and multi-agent systems (MAS) are integrated into one modeling framework and applied to the largest agglomeration of Central Europe: the Ruhr. A modified version of SLEUTH (short for Slope, Land-use, Exclusion, Urban, Transport, and Hillshade) functions as the CA component. SLEUTH makes use of historic urban land-use data sets and growth coefficients for the purpose of modeling physical urban expansion. The machine learning algorithm of SVM is applied in order to enhance SLEUTH. Thus, the stochastic variability of the CA is reduced and information about the human and ecological forces driving the local suitability of urban sprawl is incorporated. Subsequently, the supported CA is coupled with the MAS ReHoSh (Residential Mobility and the Housing Market of Shrinking City Systems). The MAS models population patterns, housing prices, and housing demand in shrinking regions based on interactions between household and city agents. Semi-explicit urban weights are introduced as a possibility of modeling from and to the pixel simultaneously. Three scenarios of changing housing preferences reveal the urban development of the region in terms of quantity and location. They reflect the dissemination of sustainable thinking among stakeholders versus the steady dream of owning a house in sub- and exurban areas. Additionally, the outcomes are transferred into a digital petri dish reflecting a synthetic environment with perfect conditions of growth. Hence, the generic growth elements affecting the future face of post-industrial cities are revealed. Finally, the advantages and limitations of linking pixels and people by combining AI and machine learning techniques in a multi-scale geosimulation approach are to be discussed.

Preliminary investigation of topical nitroglycerin formulations containing natural wound healing agent in diabetes-induced foot ulcer.

PubMed

Hotkar, Mukesh S; Avachat, Amelia M; Bhosale, Sagar S; Oswal, Yogesh M

2015-04-01

Nitroglycerin (NTG) is an organic nitrate rapidly denitrated by enzymes to release free radical nitric oxide and shows improved wound healing and tissue protection from oxidative damage. The purpose of this study was to evaluate whether topical application of NTG in the form of gel/ointment along with a natural wound healing agent, aloe vera, would bring about wound healing by using diabetes-induced foot ulcer model and rat excision wound model. All these formulations were evaluated for pH, viscosity, drug content and ex vivo diffusion studies using rat skin. Based on ex vivo permeation studies, the formulation consisting of carbopol 974p as a gelling agent and aloe vera was found to be suitable. The in vivo study used streptozotocin-induced diabetic foot ulcer and rat excision wound models to analyse wound healing activity. The wound size in animals of all treated groups was significantly reduced compared with that of the diabetic control and marketed treated animals. This study showed that the gel formed with carbopol 974p (1%) and aloe vera promotes significant wound healing and closure in diabetic rats compared with the commercial product and provides a promising product to be used in diabetes-induced foot ulcer. © 2013 The Authors. International Wound Journal © 2013 Medicalhelplines.com Inc and John Wiley & Sons Ltd.

Agents, assemblers, and ANTS: scheduling assembly with market and biological software mechanisms

NASA Astrophysics Data System (ADS)

Toth-Fejel, Tihamer T.

2000-06-01

Nanoscale assemblers will need robust, scalable, flexible, and well-understood mechanisms such as software agents to control them. This paper discusses assemblers and agents, and proposes a taxonomy of their possible interaction. Molecular assembly is seen as a special case of general assembly, subject to many of the same issues, such as the advantages of convergent assembly, and the problem of scheduling. This paper discusses the contract net architecture of ANTS, an agent-based scheduling application under development. It also describes an algorithm for least commitment scheduling, which uses probabilistic committed capacity profiles of resources over time, along with realistic costs, to provide an abstract search space over which the agents can wander to quickly find optimal solutions.

Integration of design and manufacturing in a virtual enterprise using enterprise rules, intelligent agents, STEP, and work flow

NASA Astrophysics Data System (ADS)

Gilman, Charles R.; Aparicio, Manuel; Barry, J.; Durniak, Timothy; Lam, Herman; Ramnath, Rajiv

1997-12-01

An enterprise's ability to deliver new products quickly and efficiently to market is critical for competitive success. While manufactureres recognize the need for speed and flexibility to compete in this market place, companies do not have the time or capital to move to new automation technologies. The National Industrial Information Infrastructure Protocols Consortium's Solutions for MES Adaptable Replicable Technology (NIIIP SMART) subgroup is developing an information infrastructure to enable the integration and interoperation among Manufacturing Execution Systems (MES) and Enterprise Information Systems within an enterprise or among enterprises. The goal of these developments is an adaptable, affordable, reconfigurable, integratable manufacturing system. Key innovative aspects of NIIIP SMART are: (1) Design of an industry standard object model that represents the diverse aspects of MES. (2) Design of a distributed object network to support real-time information sharing. (3) Product data exchange based on STEP and EXPRESS (ISO 10303). (4) Application of workflow and knowledge management technologies to enact manufacturing and business procedures and policy. (5) Application of intelligent agents to support emergent factories. This paper illustrates how these technologies have been incorporated into the NIIIP SMART system architecture to enable the integration and interoperation of existing tools and future MES applications in a 'plug and play' environment.

Smart social adaptation prevents catastrophic ecological regime shifts in networks of myopic harvesters

NASA Astrophysics Data System (ADS)

Donges, Jonathan; Lucht, Wolfgang; Wiedermann, Marc; Heitzig, Jobst; Kurths, Jürgen

2015-04-01

In the anthropocene, the rise of global social and economic networks with ever increasing connectivity and speed of interactions, e.g., the internet or global financial markets, is a key challenge for sustainable development. The spread of opinions, values or technologies on these networks, in conjunction with the coevolution of the network structures themselves, underlies nexuses of current concern such as anthropogenic climate change, biodiversity loss or global land use change. To isolate and quantitatively study the effects and implications of network dynamics for sustainable development, we propose an agent-based model of information flow on adaptive networks between myopic harvesters that exploit private renewable resources. In this conceptual model of a network of socio-ecological systems, information on management practices flows between agents via boundedly rational imitation depending on the state of the resource stocks involved in an interaction. Agents can also adapt the structure of their social network locally by preferentially connecting to culturally similar agents with identical management practices and, at the same time, disconnecting from culturally dissimilar agents. Investigating in detail the statistical mechanics of this model, we find that an increasing rate of information flow through faster imitation dynamics or growing density of network connectivity leads to a marked increase in the likelihood of environmental resource collapse. However, we show that an optimal rate of social network adaptation can mitigate this negative effect without loss of social cohesion through network fragmentation. Our results highlight that seemingly immaterial network dynamics of spreading opinions or values can be of large relevance for the sustainable management of socio-ecological systems and suggest smartly conservative network adaptation as a strategy for mitigating environmental collapse. Hence, facing the great acceleration, these network dynamics should be more routinely incorporated in standard models of economic development or integrated assessment models used for evaluating anthropogenic climate change.

Modeling Framework and Validation of a Smart Grid and Demand Response System for Wind Power Integration

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

Broeer, Torsten; Fuller, Jason C.; Tuffner, Francis K.

2014-01-31

Electricity generation from wind power and other renewable energy sources is increasing, and their variability introduces new challenges to the power system. The emergence of smart grid technologies in recent years has seen a paradigm shift in redefining the electrical system of the future, in which controlled response of the demand side is used to balance fluctuations and intermittencies from the generation side. This paper presents a modeling framework for an integrated electricity system where loads become an additional resource. The agent-based model represents a smart grid power system integrating generators, transmission, distribution, loads and market. The model incorporates generatormore » and load controllers, allowing suppliers and demanders to bid into a Real-Time Pricing (RTP) electricity market. The modeling framework is applied to represent a physical demonstration project conducted on the Olympic Peninsula, Washington, USA, and validation simulations are performed using actual dynamic data. Wind power is then introduced into the power generation mix illustrating the potential of demand response to mitigate the impact of wind power variability, primarily through thermostatically controlled loads. The results also indicate that effective implementation of Demand Response (DR) to assist integration of variable renewable energy resources requires a diversity of loads to ensure functionality of the overall system.« less

Strengthening stakeholder involvement in health workforce governance: why we need to talk about power.

PubMed

Kuhlmann, Ellen; Burau, Viola

2018-01-01

There is now widespread agreement on the benefits of an integrated, people-centred health workforce, but the implementation of new models is difficult. We argue that we need to think about stakeholders and power, if we want to ensure change in the health workforce. We discuss these issues from a governance perspective and suggest a critical approach to stakeholder involvement as an indicator of good governance. Three models of involving stakeholders in health workforce governance can be identified: corporatist professional involvement either in a continental European model of conservative corporatism or in a Nordic model of public corporatism; managerialist and market-centred involvement of professions as organizational agents; and a more inclusive, network-based involvement of plural professional experts at different levels of governance. The power relations embedded in these models of stakeholder involvement have different effects on capacity building for an integrated health workforce.

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

DOE PAGES

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

2015-10-30

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

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

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Marketing for a Web-Based Master's Degree Program in Light of Marketing Mix Model

ERIC Educational Resources Information Center

Pan, Cheng-Chang

2012-01-01

The marketing mix model was applied with a focus on Web media to re-strategize a Web-based Master's program in a southern state university in U.S. The program's existing marketing strategy was examined using the four components of the model: product, price, place, and promotion, in hopes to repackage the program (product) to prospective students…

Oscillations in rational economies.

PubMed

Mishchenko, Yuriy

2014-01-01

Economic (business) cycles are some of the most noted features of market economies, also ranked among the most serious of economic problems. Despite long historical persistence, the nature and the origin of business cycles remain controversial. In this paper we investigate the problem of the nature of business cycles from the positions of the market systems viewed as complex systems of many interacting market agents. We show that the development of cyclic instabilities in these settings can be traced down to just two fundamental factors - the competition of market agents for market shares in the settings of an open market, and the depression of market caused by accumulation of durable overproduced commodities on the market. These findings present the problem of business cycles in a new light as a systemic property of efficient market systems emerging directly from the free market competition itself, and existing in market economies at a very fundamental level.

Oscillations in Rational Economies

PubMed Central

Mishchenko, Yuriy

2014-01-01

Economic (business) cycles are some of the most noted features of market economies, also ranked among the most serious of economic problems. Despite long historical persistence, the nature and the origin of business cycles remain controversial. In this paper we investigate the problem of the nature of business cycles from the positions of the market systems viewed as complex systems of many interacting market agents. We show that the development of cyclic instabilities in these settings can be traced down to just two fundamental factors – the competition of market agents for market shares in the settings of an open market, and the depression of market caused by accumulation of durable overproduced commodities on the market. These findings present the problem of business cycles in a new light as a systemic property of efficient market systems emerging directly from the free market competition itself, and existing in market economies at a very fundamental level. PMID:24505319

7 CFR 981.89 - Agents.

Code of Federal Regulations, 2010 CFR

2010-01-01

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7 CFR 966.88 - Agents.

Code of Federal Regulations, 2010 CFR

2010-01-01

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7 CFR 983.86 - Agents.

Code of Federal Regulations, 2010 CFR

2010-01-01

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7 CFR 929.73 - Agents.

Code of Federal Regulations, 2010 CFR

2010-01-01

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7 CFR 929.73 - Agents.

Code of Federal Regulations, 2011 CFR

2011-01-01

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7 CFR 929.73 - Agents.

Code of Federal Regulations, 2012 CFR

2012-01-01

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7 CFR 929.73 - Agents.

Code of Federal Regulations, 2013 CFR

2013-01-01

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7 CFR 929.73 - Agents.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 8 2014-01-01 2014-01-01 false Agents. 929.73 Section 929.73 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (MARKETING AGREEMENTS AND ORDERS; FRUITS, VEGETABLES, NUTS), DEPARTMENT OF AGRICULTURE CRANBERRIES GROWN IN STATES OF MASSACHUSETTS...

7 CFR 993.88 - Agents.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Agents. 993.88 Section 993.88 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing Agreements and Orders; Fruits, Vegetables, Nuts), DEPARTMENT OF AGRICULTURE DRIED PRUNES PRODUCED IN CALIFORNIA Order...

7 CFR 993.88 - Agents.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 8 2011-01-01 2011-01-01 false Agents. 993.88 Section 993.88 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing Agreements and Orders; Fruits, Vegetables, Nuts), DEPARTMENT OF AGRICULTURE DRIED PRUNES PRODUCED IN CALIFORNIA Order...

7 CFR 993.88 - Agents.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 8 2013-01-01 2013-01-01 false Agents. 993.88 Section 993.88 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (MARKETING AGREEMENTS AND ORDERS; FRUITS, VEGETABLES, NUTS), DEPARTMENT OF AGRICULTURE DRIED PRUNES PRODUCED IN CALIFORNIA Order...