Enhanced index tracking modelling in portfolio optimization

NASA Astrophysics Data System (ADS)

Lam, W. S.; Hj. Jaaman, Saiful Hafizah; Ismail, Hamizun bin

2013-09-01

Enhanced index tracking is a popular form of passive fund management in stock market. It is a dual-objective optimization problem, a trade-off between maximizing the mean return and minimizing the risk. Enhanced index tracking aims to generate excess return over the return achieved by the index without purchasing all of the stocks that make up the index by establishing an optimal portfolio. The objective of this study is to determine the optimal portfolio composition and performance by using weighted model in enhanced index tracking. Weighted model focuses on the trade-off between the excess return and the risk. The results of this study show that the optimal portfolio for the weighted model is able to outperform the Malaysia market index which is Kuala Lumpur Composite Index because of higher mean return and lower risk without purchasing all the stocks in the market index.

A mathematical model for maximizing the value of phase 3 drug development portfolios incorporating budget constraints and risk.

PubMed

Patel, Nitin R; Ankolekar, Suresh; Antonijevic, Zoran; Rajicic, Natasa

2013-05-10

We describe a value-driven approach to optimizing pharmaceutical portfolios. Our approach incorporates inputs from research and development and commercial functions by simultaneously addressing internal and external factors. This approach differentiates itself from current practices in that it recognizes the impact of study design parameters, sample size in particular, on the portfolio value. We develop an integer programming (IP) model as the basis for Bayesian decision analysis to optimize phase 3 development portfolios using expected net present value as the criterion. We show how this framework can be used to determine optimal sample sizes and trial schedules to maximize the value of a portfolio under budget constraints. We then illustrate the remarkable flexibility of the IP model to answer a variety of 'what-if' questions that reflect situations that arise in practice. We extend the IP model to a stochastic IP model to incorporate uncertainty in the availability of drugs from earlier development phases for phase 3 development in the future. We show how to use stochastic IP to re-optimize the portfolio development strategy over time as new information accumulates and budget changes occur. Copyright © 2013 John Wiley & Sons, Ltd.

Mean-variance model for portfolio optimization with background risk based on uncertainty theory

NASA Astrophysics Data System (ADS)

Zhai, Jia; Bai, Manying

2018-04-01

The aim of this paper is to develop a mean-variance model for portfolio optimization considering the background risk, liquidity and transaction cost based on uncertainty theory. In portfolio selection problem, returns of securities and assets liquidity are assumed as uncertain variables because of incidents or lacking of historical data, which are common in economic and social environment. We provide crisp forms of the model and a hybrid intelligent algorithm to solve it. Under a mean-variance framework, we analyze the portfolio frontier characteristic considering independently additive background risk. In addition, we discuss some effects of background risk and liquidity constraint on the portfolio selection. Finally, we demonstrate the proposed models by numerical simulations.

Portfolio Optimization of Nanomaterial Use in Clean Energy Technologies.

PubMed

Moore, Elizabeth A; Babbitt, Callie W; Gaustad, Gabrielle; Moore, Sean T

2018-04-03

While engineered nanomaterials (ENMs) are increasingly incorporated in diverse applications, risks of ENM adoption remain difficult to predict and mitigate proactively. Current decision-making tools do not adequately account for ENM uncertainties including varying functional forms, unique environmental behavior, economic costs, unknown supply and demand, and upstream emissions. The complexity of the ENM system necessitates a novel approach: in this study, the adaptation of an investment portfolio optimization model is demonstrated for optimization of ENM use in renewable energy technologies. Where a traditional investment portfolio optimization model maximizes return on investment through optimal selection of stock, ENM portfolio optimization maximizes the performance of energy technology systems by optimizing selective use of ENMs. Cumulative impacts of multiple ENM material portfolios are evaluated in two case studies: organic photovoltaic cells (OPVs) for renewable energy and lithium-ion batteries (LIBs) for electric vehicles. Results indicate ENM adoption is dependent on overall performance and variance of the material, resource use, environmental impact, and economic trade-offs. From a sustainability perspective, improved clean energy applications can help extend product lifespans, reduce fossil energy consumption, and substitute ENMs for scarce incumbent materials.

Robust Portfolio Optimization Using Pseudodistances.

PubMed

Toma, Aida; Leoni-Aubin, Samuela

2015-01-01

The presence of outliers in financial asset returns is a frequently occurring phenomenon which may lead to unreliable mean-variance optimized portfolios. This fact is due to the unbounded influence that outliers can have on the mean returns and covariance estimators that are inputs in the optimization procedure. In this paper we present robust estimators of mean and covariance matrix obtained by minimizing an empirical version of a pseudodistance between the assumed model and the true model underlying the data. We prove and discuss theoretical properties of these estimators, such as affine equivariance, B-robustness, asymptotic normality and asymptotic relative efficiency. These estimators can be easily used in place of the classical estimators, thereby providing robust optimized portfolios. A Monte Carlo simulation study and applications to real data show the advantages of the proposed approach. We study both in-sample and out-of-sample performance of the proposed robust portfolios comparing them with some other portfolios known in literature.

Robust Portfolio Optimization Using Pseudodistances

PubMed Central

2015-01-01

The presence of outliers in financial asset returns is a frequently occurring phenomenon which may lead to unreliable mean-variance optimized portfolios. This fact is due to the unbounded influence that outliers can have on the mean returns and covariance estimators that are inputs in the optimization procedure. In this paper we present robust estimators of mean and covariance matrix obtained by minimizing an empirical version of a pseudodistance between the assumed model and the true model underlying the data. We prove and discuss theoretical properties of these estimators, such as affine equivariance, B-robustness, asymptotic normality and asymptotic relative efficiency. These estimators can be easily used in place of the classical estimators, thereby providing robust optimized portfolios. A Monte Carlo simulation study and applications to real data show the advantages of the proposed approach. We study both in-sample and out-of-sample performance of the proposed robust portfolios comparing them with some other portfolios known in literature. PMID:26468948

Mean-variance portfolio optimization by using time series approaches based on logarithmic utility function

NASA Astrophysics Data System (ADS)

Soeryana, E.; Fadhlina, N.; Sukono; Rusyaman, E.; Supian, S.

2017-01-01

Investments in stocks investors are also faced with the issue of risk, due to daily price of stock also fluctuate. For minimize the level of risk, investors usually forming an investment portfolio. Establishment of a portfolio consisting of several stocks are intended to get the optimal composition of the investment portfolio. This paper discussed about optimizing investment portfolio of Mean-Variance to stocks by using mean and volatility is not constant based on logarithmic utility function. Non constant mean analysed using models Autoregressive Moving Average (ARMA), while non constant volatility models are analysed using the Generalized Autoregressive Conditional heteroscedastic (GARCH). Optimization process is performed by using the Lagrangian multiplier technique. As a numerical illustration, the method is used to analyse some Islamic stocks in Indonesia. The expected result is to get the proportion of investment in each Islamic stock analysed.

Mean-Variance portfolio optimization by using non constant mean and volatility based on the negative exponential utility function

NASA Astrophysics Data System (ADS)

Soeryana, Endang; Halim, Nurfadhlina Bt Abdul; Sukono, Rusyaman, Endang; Supian, Sudradjat

2017-03-01

Investments in stocks investors are also faced with the issue of risk, due to daily price of stock also fluctuate. For minimize the level of risk, investors usually forming an investment portfolio. Establishment of a portfolio consisting of several stocks are intended to get the optimal composition of the investment portfolio. This paper discussed about optimizing investment portfolio of Mean-Variance to stocks by using mean and volatility is not constant based on the Negative Exponential Utility Function. Non constant mean analyzed using models Autoregressive Moving Average (ARMA), while non constant volatility models are analyzed using the Generalized Autoregressive Conditional heteroscedastic (GARCH). Optimization process is performed by using the Lagrangian multiplier technique. As a numerical illustration, the method is used to analyze some stocks in Indonesia. The expected result is to get the proportion of investment in each stock analyzed

Optimal portfolio strategy with cross-correlation matrix composed by DCCA coefficients: Evidence from the Chinese stock market

NASA Astrophysics Data System (ADS)

Sun, Xuelian; Liu, Zixian

2016-02-01

In this paper, a new estimator of correlation matrix is proposed, which is composed of the detrended cross-correlation coefficients (DCCA coefficients), to improve portfolio optimization. In contrast to Pearson's correlation coefficients (PCC), DCCA coefficients acquired by the detrended cross-correlation analysis (DCCA) method can describe the nonlinear correlation between assets, and can be decomposed in different time scales. These properties of DCCA make it possible to improve the investment effect and more valuable to investigate the scale behaviors of portfolios. The minimum variance portfolio (MVP) model and the Mean-Variance (MV) model are used to evaluate the effectiveness of this improvement. Stability analysis shows the effect of two kinds of correlation matrices on the estimation error of portfolio weights. The observed scale behaviors are significant to risk management and could be used to optimize the portfolio selection.

Risk-Based Sampling: I Don't Want to Weight in Vain.

PubMed

Powell, Mark R

2015-12-01

Recently, there has been considerable interest in developing risk-based sampling for food safety and animal and plant health for efficient allocation of inspection and surveillance resources. The problem of risk-based sampling allocation presents a challenge similar to financial portfolio analysis. Markowitz (1952) laid the foundation for modern portfolio theory based on mean-variance optimization. However, a persistent challenge in implementing portfolio optimization is the problem of estimation error, leading to false "optimal" portfolios and unstable asset weights. In some cases, portfolio diversification based on simple heuristics (e.g., equal allocation) has better out-of-sample performance than complex portfolio optimization methods due to estimation uncertainty. Even for portfolios with a modest number of assets, the estimation window required for true optimization may imply an implausibly long stationary period. The implications for risk-based sampling are illustrated by a simple simulation model of lot inspection for a small, heterogeneous group of producers. © 2015 Society for Risk Analysis.

Portfolio Optimization with Stochastic Dividends and Stochastic Volatility

ERIC Educational Resources Information Center

Varga, Katherine Yvonne

2015-01-01

We consider an optimal investment-consumption portfolio optimization model in which an investor receives stochastic dividends. As a first problem, we allow the drift of stock price to be a bounded function. Next, we consider a stochastic volatility model. In each problem, we use the dynamic programming method to derive the Hamilton-Jacobi-Bellman…

Replica Approach for Minimal Investment Risk with Cost

NASA Astrophysics Data System (ADS)

Shinzato, Takashi

2018-06-01

In the present work, the optimal portfolio minimizing the investment risk with cost is discussed analytically, where an objective function is constructed in terms of two negative aspects of investment, the risk and cost. We note the mathematical similarity between the Hamiltonian in the mean-variance model and the Hamiltonians in the Hopfield model and the Sherrington-Kirkpatrick model, show that we can analyze this portfolio optimization problem by using replica analysis, and derive the minimal investment risk with cost and the investment concentration of the optimal portfolio. Furthermore, we validate our proposed method through numerical simulations.

Multi-objective possibilistic model for portfolio selection with transaction cost

NASA Astrophysics Data System (ADS)

Jana, P.; Roy, T. K.; Mazumder, S. K.

2009-06-01

In this paper, we introduce the possibilistic mean value and variance of continuous distribution, rather than probability distributions. We propose a multi-objective Portfolio based model and added another entropy objective function to generate a well diversified asset portfolio within optimal asset allocation. For quantifying any potential return and risk, portfolio liquidity is taken into account and a multi-objective non-linear programming model for portfolio rebalancing with transaction cost is proposed. The models are illustrated with numerical examples.

Black-Litterman model on non-normal stock return (Case study four banks at LQ-45 stock index)

NASA Astrophysics Data System (ADS)

Mahrivandi, Rizki; Noviyanti, Lienda; Setyanto, Gatot Riwi

2017-03-01

The formation of the optimal portfolio is a method that can help investors to minimize risks and optimize profitability. One model for the optimal portfolio is a Black-Litterman (BL) model. BL model can incorporate an element of historical data and the views of investors to form a new prediction about the return of the portfolio as a basis for preparing the asset weighting models. BL model has two fundamental problems, the assumption of normality and estimation parameters on the market Bayesian prior framework that does not from a normal distribution. This study provides an alternative solution where the modelling of the BL model stock returns and investor views from non-normal distribution.

Optimization of the bank's operating portfolio

NASA Astrophysics Data System (ADS)

Borodachev, S. M.; Medvedev, M. A.

2016-06-01

The theory of efficient portfolios developed by Markowitz is used to optimize the structure of the types of financial operations of a bank (bank portfolio) in order to increase the profit and reduce the risk. The focus of this paper is to check the stability of the model to errors in the original data.

The Role of Nuclear Power in Reducing Risk of the Fossil Fuel Prices and Diversity of Electricity Generation in Tunisia: A Portfolio Approach

NASA Astrophysics Data System (ADS)

Abdelhamid, Mohamed Ben; Aloui, Chaker; Chaton, Corinne; Souissi, Jomâa

2010-04-01

This paper applies real options and mean-variance portfolio theories to analyze the electricity generation planning into presence of nuclear power plant for the Tunisian case. First, we analyze the choice between fossil fuel and nuclear production. A dynamic model is presented to illustrate the impact of fossil fuel cost uncertainty on the optimal timing to switch from gas to nuclear. Next, we use the portfolio theory to manage risk of the electricity generation portfolio and to determine the optimal fuel mix with the nuclear alternative. Based on portfolio theory, the results show that there is other optimal mix than the mix fixed for the Tunisian mix for the horizon 2010-2020, with lower cost for the same risk degree. In the presence of nuclear technology, we found that the optimal generating portfolio must include 13% of nuclear power technology share.

A comparison of portfolio selection models via application on ISE 100 index data

NASA Astrophysics Data System (ADS)

Altun, Emrah; Tatlidil, Hüseyin

2013-10-01

Markowitz Model, a classical approach to portfolio optimization problem, relies on two important assumptions: the expected return is multivariate normally distributed and the investor is risk averter. But this model has not been extensively used in finance. Empirical results show that it is very hard to solve large scale portfolio optimization problems with Mean-Variance (M-V)model. Alternative model, Mean Absolute Deviation (MAD) model which is proposed by Konno and Yamazaki [7] has been used to remove most of difficulties of Markowitz Mean-Variance model. MAD model don't need to assume that the probability of the rates of return is normally distributed and based on Linear Programming. Another alternative portfolio model is Mean-Lower Semi Absolute Deviation (M-LSAD), which is proposed by Speranza [3]. We will compare these models to determine which model gives more appropriate solution to investors.

The admissible portfolio selection problem with transaction costs and an improved PSO algorithm

NASA Astrophysics Data System (ADS)

Chen, Wei; Zhang, Wei-Guo

2010-05-01

In this paper, we discuss the portfolio selection problem with transaction costs under the assumption that there exist admissible errors on expected returns and risks of assets. We propose a new admissible efficient portfolio selection model and design an improved particle swarm optimization (PSO) algorithm because traditional optimization algorithms fail to work efficiently for our proposed problem. Finally, we offer a numerical example to illustrate the proposed effective approaches and compare the admissible portfolio efficient frontiers under different constraints.

Power Grid Construction Project Portfolio Optimization Based on Bi-level programming model

NASA Astrophysics Data System (ADS)

Zhao, Erdong; Li, Shangqi

2017-08-01

As the main body of power grid operation, county-level power supply enterprises undertake an important emission to guarantee the security of power grid operation and safeguard social power using order. The optimization of grid construction projects has been a key issue of power supply capacity and service level of grid enterprises. According to the actual situation of power grid construction project optimization of county-level power enterprises, on the basis of qualitative analysis of the projects, this paper builds a Bi-level programming model based on quantitative analysis. The upper layer of the model is the target restriction of the optimal portfolio; the lower layer of the model is enterprises’ financial restrictions on the size of the enterprise project portfolio. Finally, using a real example to illustrate operation proceeding and the optimization result of the model. Through qualitative analysis and quantitative analysis, the bi-level programming model improves the accuracy and normative standardization of power grid enterprises projects.

Flow of Funds Modeling for Localized Financial Markets: An Application of Spatial Price and Allocation Activity Analysis Models.

DTIC Science & Technology

1981-01-01

on modeling the managerial aspects of the firm. The second has been the application to economic theory led by ...individual portfolio optimization problems which were embedded in a larger global optimization problem. In the global problem, portfolios were linked by market ...demand quantities or be given by linear demand relationships. As in~ the source markets , the model

Portfolio optimization using fuzzy linear programming

NASA Astrophysics Data System (ADS)

Pandit, Purnima K.

2013-09-01

Portfolio Optimization (PO) is a problem in Finance, in which investor tries to maximize return and minimize risk by carefully choosing different assets. Expected return and risk are the most important parameters with regard to optimal portfolios. In the simple form PO can be modeled as quadratic programming problem which can be put into equivalent linear form. PO problems with the fuzzy parameters can be solved as multi-objective fuzzy linear programming problem. In this paper we give the solution to such problems with an illustrative example.

Optimal Decision-making Model of Integrated Water Resources Management - A Case of Hsinchu Water Resources Management

NASA Astrophysics Data System (ADS)

Wang, S. Y.; Ho, C. C.; Chang, L. C.

2017-12-01

The public use water in Hsinchu are mainly supplied from Baoshan Reservoir, Second Baoshan Reservoir, Yongheshan Reservoir and Longen Weir. However, the increasing water demand, caused by development of the Hsinchu Science and Industrial Park, results in supply stable water getting more difficult. For stabilize water supply in Hsinchu, the study applies long-term and short-term plans to fulfill the water shortage. Developing an efficient methodology to define a cost-effective action portfolio is an important task. Hence, the study develops a novel decision model, the Stochastic Programming with Recourse Decision Model (SPRDM), to estimate a cost-effective action portfolio. The first-stage of SPRDM determine the long-term action portfolio and the portfolio accompany recourse information (the probability for water shortage event). The second-stage of SPRDM optimize the cost-effective action portfolio in response to the recourse information. In order to consider the uncertainty of reservoir sediment and demand growth, the study set 9 scenarios comprise optimistic, most likely, and pessimistic reservoir sediment and demand growth. The results show the optimal action portfolio consist of FengTain Lake and Panlon Weir, Hsinchu Desalination Plant, Domestic and Industrial Water long-term plans, and Emergency Backup Well, Irrigation Water Transference, Preliminary Water Rationing, Advanced Water Rationing and Water Transport from Other Districts short-term plans. The minimum expected cost of optimal action portfolio is NT$1.1002 billion. The results can be used as a reference for decision making because the results have considered the uncertainty of varied hydrology, reservoir sediment, and water demand growth.

A method for minimum risk portfolio optimization under hybrid uncertainty

NASA Astrophysics Data System (ADS)

Egorova, Yu E.; Yazenin, A. V.

2018-03-01

In this paper, we investigate a minimum risk portfolio model under hybrid uncertainty when the profitability of financial assets is described by fuzzy random variables. According to Feng, the variance of a portfolio is defined as a crisp value. To aggregate fuzzy information the weakest (drastic) t-norm is used. We construct an equivalent stochastic problem of the minimum risk portfolio model and specify the stochastic penalty method for solving it.

Ant Colony Optimization for Markowitz Mean-Variance Portfolio Model

NASA Astrophysics Data System (ADS)

Deng, Guang-Feng; Lin, Woo-Tsong

This work presents Ant Colony Optimization (ACO), which was initially developed to be a meta-heuristic for combinatorial optimization, for solving the cardinality constraints Markowitz mean-variance portfolio model (nonlinear mixed quadratic programming problem). To our knowledge, an efficient algorithmic solution for this problem has not been proposed until now. Using heuristic algorithms in this case is imperative. Numerical solutions are obtained for five analyses of weekly price data for the following indices for the period March, 1992 to September, 1997: Hang Seng 31 in Hong Kong, DAX 100 in Germany, FTSE 100 in UK, S&P 100 in USA and Nikkei 225 in Japan. The test results indicate that the ACO is much more robust and effective than Particle swarm optimization (PSO), especially for low-risk investment portfolios.

Firefly algorithm for cardinality constrained mean-variance portfolio optimization problem with entropy diversity constraint.

PubMed

Bacanin, Nebojsa; Tuba, Milan

2014-01-01

Portfolio optimization (selection) problem is an important and hard optimization problem that, with the addition of necessary realistic constraints, becomes computationally intractable. Nature-inspired metaheuristics are appropriate for solving such problems; however, literature review shows that there are very few applications of nature-inspired metaheuristics to portfolio optimization problem. This is especially true for swarm intelligence algorithms which represent the newer branch of nature-inspired algorithms. No application of any swarm intelligence metaheuristics to cardinality constrained mean-variance (CCMV) portfolio problem with entropy constraint was found in the literature. This paper introduces modified firefly algorithm (FA) for the CCMV portfolio model with entropy constraint. Firefly algorithm is one of the latest, very successful swarm intelligence algorithm; however, it exhibits some deficiencies when applied to constrained problems. To overcome lack of exploration power during early iterations, we modified the algorithm and tested it on standard portfolio benchmark data sets used in the literature. Our proposed modified firefly algorithm proved to be better than other state-of-the-art algorithms, while introduction of entropy diversity constraint further improved results.

Firefly Algorithm for Cardinality Constrained Mean-Variance Portfolio Optimization Problem with Entropy Diversity Constraint

PubMed Central

2014-01-01

Portfolio optimization (selection) problem is an important and hard optimization problem that, with the addition of necessary realistic constraints, becomes computationally intractable. Nature-inspired metaheuristics are appropriate for solving such problems; however, literature review shows that there are very few applications of nature-inspired metaheuristics to portfolio optimization problem. This is especially true for swarm intelligence algorithms which represent the newer branch of nature-inspired algorithms. No application of any swarm intelligence metaheuristics to cardinality constrained mean-variance (CCMV) portfolio problem with entropy constraint was found in the literature. This paper introduces modified firefly algorithm (FA) for the CCMV portfolio model with entropy constraint. Firefly algorithm is one of the latest, very successful swarm intelligence algorithm; however, it exhibits some deficiencies when applied to constrained problems. To overcome lack of exploration power during early iterations, we modified the algorithm and tested it on standard portfolio benchmark data sets used in the literature. Our proposed modified firefly algorithm proved to be better than other state-of-the-art algorithms, while introduction of entropy diversity constraint further improved results. PMID:24991645

Modelling on optimal portfolio with exchange rate based on discontinuous stochastic process

NASA Astrophysics Data System (ADS)

Yan, Wei; Chang, Yuwen

2016-12-01

Considering the stochastic exchange rate, this paper is concerned with the dynamic portfolio selection in financial market. The optimal investment problem is formulated as a continuous-time mathematical model under mean-variance criterion. These processes follow jump-diffusion processes (Weiner process and Poisson process). Then the corresponding Hamilton-Jacobi-Bellman(HJB) equation of the problem is presented and its efferent frontier is obtained. Moreover, the optimal strategy is also derived under safety-first criterion.

Artificial bee colony algorithm for constrained possibilistic portfolio optimization problem

NASA Astrophysics Data System (ADS)

Chen, Wei

2015-07-01

In this paper, we discuss the portfolio optimization problem with real-world constraints under the assumption that the returns of risky assets are fuzzy numbers. A new possibilistic mean-semiabsolute deviation model is proposed, in which transaction costs, cardinality and quantity constraints are considered. Due to such constraints the proposed model becomes a mixed integer nonlinear programming problem and traditional optimization methods fail to find the optimal solution efficiently. Thus, a modified artificial bee colony (MABC) algorithm is developed to solve the corresponding optimization problem. Finally, a numerical example is given to illustrate the effectiveness of the proposed model and the corresponding algorithm.

Noise sensitivity of portfolio selection in constant conditional correlation GARCH models

NASA Astrophysics Data System (ADS)

Varga-Haszonits, I.; Kondor, I.

2007-11-01

This paper investigates the efficiency of minimum variance portfolio optimization for stock price movements following the Constant Conditional Correlation GARCH process proposed by Bollerslev. Simulations show that the quality of portfolio selection can be improved substantially by computing optimal portfolio weights from conditional covariances instead of unconditional ones. Measurement noise can be further reduced by applying some filtering method on the conditional correlation matrix (such as Random Matrix Theory based filtering). As an empirical support for the simulation results, the analysis is also carried out for a time series of S&P500 stock prices.

Divergent estimation error in portfolio optimization and in linear regression

NASA Astrophysics Data System (ADS)

Kondor, I.; Varga-Haszonits, I.

2008-08-01

The problem of estimation error in portfolio optimization is discussed, in the limit where the portfolio size N and the sample size T go to infinity such that their ratio is fixed. The estimation error strongly depends on the ratio N/T and diverges for a critical value of this parameter. This divergence is the manifestation of an algorithmic phase transition, it is accompanied by a number of critical phenomena, and displays universality. As the structure of a large number of multidimensional regression and modelling problems is very similar to portfolio optimization, the scope of the above observations extends far beyond finance, and covers a large number of problems in operations research, machine learning, bioinformatics, medical science, economics, and technology.

More efficient optimization of long-term water supply portfolios

NASA Astrophysics Data System (ADS)

Kirsch, Brian R.; Characklis, Gregory W.; Dillard, Karen E. M.; Kelley, C. T.

2009-03-01

The use of temporary transfers, such as options and leases, has grown as utilities attempt to meet increases in demand while reducing dependence on the expansion of costly infrastructure capacity (e.g., reservoirs). Earlier work has been done to construct optimal portfolios comprising firm capacity and transfers, using decision rules that determine the timing and volume of transfers. However, such work has only focused on the short-term (e.g., 1-year scenarios), which limits the utility of these planning efforts. Developing multiyear portfolios can lead to the exploration of a wider range of alternatives but also increases the computational burden. This work utilizes a coupled hydrologic-economic model to simulate the long-term performance of a city's water supply portfolio. This stochastic model is linked with an optimization search algorithm that is designed to handle the high-frequency, low-amplitude noise inherent in many simulations, particularly those involving expected values. This noise is detrimental to the accuracy and precision of the optimized solution and has traditionally been controlled by investing greater computational effort in the simulation. However, the increased computational effort can be substantial. This work describes the integration of a variance reduction technique (control variate method) within the simulation/optimization as a means of more efficiently identifying minimum cost portfolios. Random variation in model output (i.e., noise) is moderated using knowledge of random variations in stochastic input variables (e.g., reservoir inflows, demand), thereby reducing the computing time by 50% or more. Using these efficiency gains, water supply portfolios are evaluated over a 10-year period in order to assess their ability to reduce costs and adapt to demand growth, while still meeting reliability goals. As a part of the evaluation, several multiyear option contract structures are explored and compared.

Credibilistic multi-period portfolio optimization based on scenario tree

NASA Astrophysics Data System (ADS)

Mohebbi, Negin; Najafi, Amir Abbas

2018-02-01

In this paper, we consider a multi-period fuzzy portfolio optimization model with considering transaction costs and the possibility of risk-free investment. We formulate a bi-objective mean-VaR portfolio selection model based on the integration of fuzzy credibility theory and scenario tree in order to dealing with the markets uncertainty. The scenario tree is also a proper method for modeling multi-period portfolio problems since the length and continuity of their horizon. We take the return and risk as well cardinality, threshold, class, and liquidity constraints into consideration for further compliance of the model with reality. Then, an interactive dynamic programming method, which is based on a two-phase fuzzy interactive approach, is employed to solve the proposed model. In order to verify the proposed model, we present an empirical application in NYSE under different circumstances. The results show that the consideration of data uncertainty and other real-world assumptions lead to more practical and efficient solutions.

Fuzzy Random λ-Mean SAD Portfolio Selection Problem: An Ant Colony Optimization Approach

NASA Astrophysics Data System (ADS)

Thakur, Gour Sundar Mitra; Bhattacharyya, Rupak; Mitra, Swapan Kumar

2010-10-01

To reach the investment goal, one has to select a combination of securities among different portfolios containing large number of securities. Only the past records of each security do not guarantee the future return. As there are many uncertain factors which directly or indirectly influence the stock market and there are also some newer stock markets which do not have enough historical data, experts' expectation and experience must be combined with the past records to generate an effective portfolio selection model. In this paper the return of security is assumed to be Fuzzy Random Variable Set (FRVS), where returns are set of random numbers which are in turn fuzzy numbers. A new λ-Mean Semi Absolute Deviation (λ-MSAD) portfolio selection model is developed. The subjective opinions of the investors to the rate of returns of each security are taken into consideration by introducing a pessimistic-optimistic parameter vector λ. λ-Mean Semi Absolute Deviation (λ-MSAD) model is preferred as it follows absolute deviation of the rate of returns of a portfolio instead of the variance as the measure of the risk. As this model can be reduced to Linear Programming Problem (LPP) it can be solved much faster than quadratic programming problems. Ant Colony Optimization (ACO) is used for solving the portfolio selection problem. ACO is a paradigm for designing meta-heuristic algorithms for combinatorial optimization problem. Data from BSE is used for illustration.

Estimating risk of foreign exchange portfolio: Using VaR and CVaR based on GARCH-EVT-Copula model

NASA Astrophysics Data System (ADS)

Wang, Zong-Run; Chen, Xiao-Hong; Jin, Yan-Bo; Zhou, Yan-Ju

2010-11-01

This paper introduces GARCH-EVT-Copula model and applies it to study the risk of foreign exchange portfolio. Multivariate Copulas, including Gaussian, t and Clayton ones, were used to describe a portfolio risk structure, and to extend the analysis from a bivariate to an n-dimensional asset allocation problem. We apply this methodology to study the returns of a portfolio of four major foreign currencies in China, including USD, EUR, JPY and HKD. Our results suggest that the optimal investment allocations are similar across different Copulas and confidence levels. In addition, we find that the optimal investment concentrates on the USD investment. Generally speaking, t Copula and Clayton Copula better portray the correlation structure of multiple assets than Normal Copula.

Inverse Optimization: A New Perspective on the Black-Litterman Model.

PubMed

Bertsimas, Dimitris; Gupta, Vishal; Paschalidis, Ioannis Ch

2012-12-11

The Black-Litterman (BL) model is a widely used asset allocation model in the financial industry. In this paper, we provide a new perspective. The key insight is to replace the statistical framework in the original approach with ideas from inverse optimization. This insight allows us to significantly expand the scope and applicability of the BL model. We provide a richer formulation that, unlike the original model, is flexible enough to incorporate investor information on volatility and market dynamics. Equally importantly, our approach allows us to move beyond the traditional mean-variance paradigm of the original model and construct "BL"-type estimators for more general notions of risk such as coherent risk measures. Computationally, we introduce and study two new "BL"-type estimators and their corresponding portfolios: a Mean Variance Inverse Optimization (MV-IO) portfolio and a Robust Mean Variance Inverse Optimization (RMV-IO) portfolio. These two approaches are motivated by ideas from arbitrage pricing theory and volatility uncertainty. Using numerical simulation and historical backtesting, we show that both methods often demonstrate a better risk-reward tradeoff than their BL counterparts and are more robust to incorrect investor views.

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

NASA Astrophysics Data System (ADS)

Pavlak, Gregory S.

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

Mean-variance portfolio analysis data for optimizing community-based photovoltaic investment.

PubMed

Shakouri, Mahmoud; Lee, Hyun Woo

2016-03-01

The amount of electricity generated by Photovoltaic (PV) systems is affected by factors such as shading, building orientation and roof slope. To increase electricity generation and reduce volatility in generation of PV systems, a portfolio of PV systems can be made which takes advantages of the potential synergy among neighboring buildings. This paper contains data supporting the research article entitled: PACPIM: new decision-support model of optimized portfolio analysis for community-based photovoltaic investment [1]. We present a set of data relating to physical properties of 24 houses in Oregon, USA, along with simulated hourly electricity data for the installed PV systems. The developed Matlab code to construct optimized portfolios is also provided in . The application of these files can be generalized to variety of communities interested in investing on PV systems.

Getting the most out of your IP--patent management along its life cycle.

PubMed

Bader, Martin A; Gassmann, Oliver; Ziegler, Nicole; Ruether, Frauke

2012-04-01

Effectively managing and optimizing the value of the patent portfolio is a major challenge for many firms, especially those in knowledge intensive industries, such as the pharmaceutical, biotechnological and chemical industry. However, insights on effective patent portfolio strategies are rare. Therefore, in this article we investigate in detail how firms successfully manage and optimize their patent portfolios to increase their overall competitiveness. We discover that successful patent portfolio management is rooted in managing the patents along their life cycles. Based on the findings of ten case studies, we develop a holistic patent life cycle management model reflecting five distinctive phases of patent management: explore, generate, protect, optimize and decline. We conclude with how our findings can be used in practice. Copyright © 2011 Elsevier Ltd. All rights reserved.

Estimating Risk of Natural Gas Portfolios by Using GARCH-EVT-Copula Model.

PubMed

Tang, Jiechen; Zhou, Chao; Yuan, Xinyu; Sriboonchitta, Songsak

2015-01-01

This paper concentrates on estimating the risk of Title Transfer Facility (TTF) Hub natural gas portfolios by using the GARCH-EVT-copula model. We first use the univariate ARMA-GARCH model to model each natural gas return series. Second, the extreme value distribution (EVT) is fitted to the tails of the residuals to model marginal residual distributions. Third, multivariate Gaussian copula and Student t-copula are employed to describe the natural gas portfolio risk dependence structure. Finally, we simulate N portfolios and estimate value at risk (VaR) and conditional value at risk (CVaR). Our empirical results show that, for an equally weighted portfolio of five natural gases, the VaR and CVaR values obtained from the Student t-copula are larger than those obtained from the Gaussian copula. Moreover, when minimizing the portfolio risk, the optimal natural gas portfolio weights are found to be similar across the multivariate Gaussian copula and Student t-copula and different confidence levels.

Estimating Risk of Natural Gas Portfolios by Using GARCH-EVT-Copula Model

PubMed Central

Tang, Jiechen; Zhou, Chao; Yuan, Xinyu; Sriboonchitta, Songsak

2015-01-01

This paper concentrates on estimating the risk of Title Transfer Facility (TTF) Hub natural gas portfolios by using the GARCH-EVT-copula model. We first use the univariate ARMA-GARCH model to model each natural gas return series. Second, the extreme value distribution (EVT) is fitted to the tails of the residuals to model marginal residual distributions. Third, multivariate Gaussian copula and Student t-copula are employed to describe the natural gas portfolio risk dependence structure. Finally, we simulate N portfolios and estimate value at risk (VaR) and conditional value at risk (CVaR). Our empirical results show that, for an equally weighted portfolio of five natural gases, the VaR and CVaR values obtained from the Student t-copula are larger than those obtained from the Gaussian copula. Moreover, when minimizing the portfolio risk, the optimal natural gas portfolio weights are found to be similar across the multivariate Gaussian copula and Student t-copula and different confidence levels. PMID:26351652

An efficient heuristic method for dynamic portfolio selection problem under transaction costs and uncertain conditions

NASA Astrophysics Data System (ADS)

Najafi, Amir Abbas; Pourahmadi, Zahra

2016-04-01

Selecting the optimal combination of assets in a portfolio is one of the most important decisions in investment management. As investment is a long term concept, looking into a portfolio optimization problem just in a single period may cause loss of some opportunities that could be exploited in a long term view. Hence, it is tried to extend the problem from single to multi-period model. We include trading costs and uncertain conditions to this model which made it more realistic and complex. Hence, we propose an efficient heuristic method to tackle this problem. The efficiency of the method is examined and compared with the results of the rolling single-period optimization and the buy and hold method which shows the superiority of the proposed method.

Markowitz portfolio optimization model employing fuzzy measure

NASA Astrophysics Data System (ADS)

Ramli, Suhailywati; Jaaman, Saiful Hafizah

2017-04-01

Markowitz in 1952 introduced the mean-variance methodology for the portfolio selection problems. His pioneering research has shaped the portfolio risk-return model and become one of the most important research fields in modern finance. This paper extends the classical Markowitz's mean-variance portfolio selection model applying the fuzzy measure to determine the risk and return. In this paper, we apply the original mean-variance model as a benchmark, fuzzy mean-variance model with fuzzy return and the model with return are modeled by specific types of fuzzy number for comparison. The model with fuzzy approach gives better performance as compared to the mean-variance approach. The numerical examples are included to illustrate these models by employing Malaysian share market data.

Optimization of investment portfolio weight of stocks affected by market index

NASA Astrophysics Data System (ADS)

Azizah, E.; Rusyaman, E.; Supian, S.

2017-01-01

Stock price assessment, selection of optimum combination, and measure the risk of a portfolio investment is one important issue for investors. In this paper single index model used for the assessment of the stock price, and formulation optimization model developed using Lagrange multiplier technique to determine the proportion of assets to be invested. The level of risk is estimated by using variance. These models are used to analyse the stock price data Lippo Bank and Bumi Putera.

Big Data Challenges of High-Dimensional Continuous-Time Mean-Variance Portfolio Selection and a Remedy.

PubMed

Chiu, Mei Choi; Pun, Chi Seng; Wong, Hoi Ying

2017-08-01

Investors interested in the global financial market must analyze financial securities internationally. Making an optimal global investment decision involves processing a huge amount of data for a high-dimensional portfolio. This article investigates the big data challenges of two mean-variance optimal portfolios: continuous-time precommitment and constant-rebalancing strategies. We show that both optimized portfolios implemented with the traditional sample estimates converge to the worst performing portfolio when the portfolio size becomes large. The crux of the problem is the estimation error accumulated from the huge dimension of stock data. We then propose a linear programming optimal (LPO) portfolio framework, which applies a constrained ℓ 1 minimization to the theoretical optimal control to mitigate the risk associated with the dimensionality issue. The resulting portfolio becomes a sparse portfolio that selects stocks with a data-driven procedure and hence offers a stable mean-variance portfolio in practice. When the number of observations becomes large, the LPO portfolio converges to the oracle optimal portfolio, which is free of estimation error, even though the number of stocks grows faster than the number of observations. Our numerical and empirical studies demonstrate the superiority of the proposed approach. © 2017 Society for Risk Analysis.

Asset Allocation and Optimal Contract for Delegated Portfolio Management

NASA Astrophysics Data System (ADS)

Liu, Jingjun; Liang, Jianfeng

This article studies the portfolio selection and the contracting problems between an individual investor and a professional portfolio manager in a discrete-time principal-agent framework. Portfolio selection and optimal contracts are obtained in closed form. The optimal contract was composed with the fixed fee, the cost, and the fraction of excess expected return. The optimal portfolio is similar to the classical two-fund separation theorem.

A stochastic model for optimizing composite predictors based on gene expression profiles.

PubMed

Ramanathan, Murali

2003-07-01

This project was done to develop a mathematical model for optimizing composite predictors based on gene expression profiles from DNA arrays and proteomics. The problem was amenable to a formulation and solution analogous to the portfolio optimization problem in mathematical finance: it requires the optimization of a quadratic function subject to linear constraints. The performance of the approach was compared to that of neighborhood analysis using a data set containing cDNA array-derived gene expression profiles from 14 multiple sclerosis patients receiving intramuscular inteferon-beta1a. The Markowitz portfolio model predicts that the covariance between genes can be exploited to construct an efficient composite. The model predicts that a composite is not needed for maximizing the mean value of a treatment effect: only a single gene is needed, but the usefulness of the effect measure may be compromised by high variability. The model optimized the composite to yield the highest mean for a given level of variability or the least variability for a given mean level. The choices that meet this optimization criteria lie on a curve of composite mean vs. composite variability plot referred to as the "efficient frontier." When a composite is constructed using the model, it outperforms the composite constructed using the neighborhood analysis method. The Markowitz portfolio model may find potential applications in constructing composite biomarkers and in the pharmacogenomic modeling of treatment effects derived from gene expression endpoints.

Mean-variance portfolio analysis data for optimizing community-based photovoltaic investment

PubMed Central

Shakouri, Mahmoud; Lee, Hyun Woo

2016-01-01

The amount of electricity generated by Photovoltaic (PV) systems is affected by factors such as shading, building orientation and roof slope. To increase electricity generation and reduce volatility in generation of PV systems, a portfolio of PV systems can be made which takes advantages of the potential synergy among neighboring buildings. This paper contains data supporting the research article entitled: PACPIM: new decision-support model of optimized portfolio analysis for community-based photovoltaic investment [1]. We present a set of data relating to physical properties of 24 houses in Oregon, USA, along with simulated hourly electricity data for the installed PV systems. The developed Matlab code to construct optimized portfolios is also provided in Supplementary materials. The application of these files can be generalized to variety of communities interested in investing on PV systems. PMID:26937458

Portfolio optimization using median-variance approach

NASA Astrophysics Data System (ADS)

Wan Mohd, Wan Rosanisah; Mohamad, Daud; Mohamed, Zulkifli

2013-04-01

Optimization models have been applied in many decision-making problems particularly in portfolio selection. Since the introduction of Markowitz's theory of portfolio selection, various approaches based on mathematical programming have been introduced such as mean-variance, mean-absolute deviation, mean-variance-skewness and conditional value-at-risk (CVaR) mainly to maximize return and minimize risk. However most of the approaches assume that the distribution of data is normal and this is not generally true. As an alternative, in this paper, we employ the median-variance approach to improve the portfolio optimization. This approach has successfully catered both types of normal and non-normal distribution of data. With this actual representation, we analyze and compare the rate of return and risk between the mean-variance and the median-variance based portfolio which consist of 30 stocks from Bursa Malaysia. The results in this study show that the median-variance approach is capable to produce a lower risk for each return earning as compared to the mean-variance approach.

Inverse Optimization: A New Perspective on the Black-Litterman Model

PubMed Central

Bertsimas, Dimitris; Gupta, Vishal; Paschalidis, Ioannis Ch.

2014-01-01

The Black-Litterman (BL) model is a widely used asset allocation model in the financial industry. In this paper, we provide a new perspective. The key insight is to replace the statistical framework in the original approach with ideas from inverse optimization. This insight allows us to significantly expand the scope and applicability of the BL model. We provide a richer formulation that, unlike the original model, is flexible enough to incorporate investor information on volatility and market dynamics. Equally importantly, our approach allows us to move beyond the traditional mean-variance paradigm of the original model and construct “BL”-type estimators for more general notions of risk such as coherent risk measures. Computationally, we introduce and study two new “BL”-type estimators and their corresponding portfolios: a Mean Variance Inverse Optimization (MV-IO) portfolio and a Robust Mean Variance Inverse Optimization (RMV-IO) portfolio. These two approaches are motivated by ideas from arbitrage pricing theory and volatility uncertainty. Using numerical simulation and historical backtesting, we show that both methods often demonstrate a better risk-reward tradeoff than their BL counterparts and are more robust to incorrect investor views. PMID:25382873

Fireworks algorithm for mean-VaR/CVaR models

NASA Astrophysics Data System (ADS)

Zhang, Tingting; Liu, Zhifeng

2017-10-01

Intelligent algorithms have been widely applied to portfolio optimization problems. In this paper, we introduce a novel intelligent algorithm, named fireworks algorithm, to solve the mean-VaR/CVaR model for the first time. The results show that, compared with the classical genetic algorithm, fireworks algorithm not only improves the optimization accuracy and the optimization speed, but also makes the optimal solution more stable. We repeat our experiments at different confidence levels and different degrees of risk aversion, and the results are robust. It suggests that fireworks algorithm has more advantages than genetic algorithm in solving the portfolio optimization problem, and it is feasible and promising to apply it into this field.

Airline Maintenance Manpower Optimization from the De Novo Perspective

NASA Astrophysics Data System (ADS)

Liou, James J. H.; Tzeng, Gwo-Hshiung

Human resource management (HRM) is an important issue for today’s competitive airline marketing. In this paper, we discuss a multi-objective model designed from the De Novo perspective to help airlines optimize their maintenance manpower portfolio. The effectiveness of the model and solution algorithm is demonstrated in an empirical study of the optimization of the human resources needed for airline line maintenance. Both De Novo and traditional multiple objective programming (MOP) methods are analyzed. A comparison of the results with those of traditional MOP indicates that the proposed model and solution algorithm does provide better performance and an improved human resource portfolio.

A hybrid intelligent algorithm for portfolio selection problem with fuzzy returns

NASA Astrophysics Data System (ADS)

Li, Xiang; Zhang, Yang; Wong, Hau-San; Qin, Zhongfeng

2009-11-01

Portfolio selection theory with fuzzy returns has been well developed and widely applied. Within the framework of credibility theory, several fuzzy portfolio selection models have been proposed such as mean-variance model, entropy optimization model, chance constrained programming model and so on. In order to solve these nonlinear optimization models, a hybrid intelligent algorithm is designed by integrating simulated annealing algorithm, neural network and fuzzy simulation techniques, where the neural network is used to approximate the expected value and variance for fuzzy returns and the fuzzy simulation is used to generate the training data for neural network. Since these models are used to be solved by genetic algorithm, some comparisons between the hybrid intelligent algorithm and genetic algorithm are given in terms of numerical examples, which imply that the hybrid intelligent algorithm is robust and more effective. In particular, it reduces the running time significantly for large size problems.

Development of Solution Algorithm and Sensitivity Analysis for Random Fuzzy Portfolio Selection Model

NASA Astrophysics Data System (ADS)

Hasuike, Takashi; Katagiri, Hideki

2010-10-01

This paper focuses on the proposition of a portfolio selection problem considering an investor's subjectivity and the sensitivity analysis for the change of subjectivity. Since this proposed problem is formulated as a random fuzzy programming problem due to both randomness and subjectivity presented by fuzzy numbers, it is not well-defined. Therefore, introducing Sharpe ratio which is one of important performance measures of portfolio models, the main problem is transformed into the standard fuzzy programming problem. Furthermore, using the sensitivity analysis for fuzziness, the analytical optimal portfolio with the sensitivity factor is obtained.

Stochastic optimal control of ultradiffusion processes with application to dynamic portfolio management

NASA Astrophysics Data System (ADS)

Marcozzi, Michael D.

2008-12-01

We consider theoretical and approximation aspects of the stochastic optimal control of ultradiffusion processes in the context of a prototype model for the selling price of a European call option. Within a continuous-time framework, the dynamic management of a portfolio of assets is effected through continuous or point control, activation costs, and phase delay. The performance index is derived from the unique weak variational solution to the ultraparabolic Hamilton-Jacobi equation; the value function is the optimal realization of the performance index relative to all feasible portfolios. An approximation procedure based upon a temporal box scheme/finite element method is analyzed; numerical examples are presented in order to demonstrate the viability of the approach.

Planning a Target Renewable Portfolio using Atmospheric Modeling and Stochastic Optimization

NASA Astrophysics Data System (ADS)

Hart, E.; Jacobson, M. Z.

2009-12-01

A number of organizations have suggested that an 80% reduction in carbon emissions by 2050 is a necessary step to mitigate climate change and that decarbonization of the electricity sector is a crucial component of any strategy to meet this target. Integration of large renewable and intermittent generators poses many new problems in power system planning. In this study, we attempt to determine an optimal portfolio of renewable resources to meet best the fluctuating California load while also meeting an 80% carbon emissions reduction requirement. A stochastic optimization scheme is proposed that is based on a simplified model of the California electricity grid. In this single-busbar power system model, the load is met with generation from wind, solar thermal, photovoltaic, hydroelectric, geothermal, and natural gas plants. Wind speeds and insolation are calculated using GATOR-GCMOM, a global-through-urban climate-weather-air pollution model. Fields were produced for California and Nevada at 21km SN by 14 km WE spatial resolution every 15 minutes for the year 2006. Load data for 2006 were obtained from the California ISO OASIS database. Maximum installed capacities for wind and solar thermal generation were determined using a GIS analysis of potential development sites throughout the state. The stochastic optimization scheme requires that power balance be achieved in a number of meteorological and load scenarios that deviate from the forecasted (or modeled) data. By adjusting the error distributions of the forecasts, the model describes how improvements in wind speed and insolation forecasting may affect the optimal renewable portfolio. Using a simple model, we describe the diversity, size, and sensitivities of a renewable portfolio that is best suited to the resources and needs of California and that contributes significantly to reduction of the state’s carbon emissions.

Dynamic Portfolio Strategy Using Clustering Approach

PubMed Central

Lu, Ya-Nan; Li, Sai-Ping; Jiang, Xiong-Fei; Zhong, Li-Xin; Qiu, Tian

2017-01-01

The problem of portfolio optimization is one of the most important issues in asset management. We here propose a new dynamic portfolio strategy based on the time-varying structures of MST networks in Chinese stock markets, where the market condition is further considered when using the optimal portfolios for investment. A portfolio strategy comprises two stages: First, select the portfolios by choosing central and peripheral stocks in the selection horizon using five topological parameters, namely degree, betweenness centrality, distance on degree criterion, distance on correlation criterion and distance on distance criterion. Second, use the portfolios for investment in the investment horizon. The optimal portfolio is chosen by comparing central and peripheral portfolios under different combinations of market conditions in the selection and investment horizons. Market conditions in our paper are identified by the ratios of the number of trading days with rising index to the total number of trading days, or the sum of the amplitudes of the trading days with rising index to the sum of the amplitudes of the total trading days. We find that central portfolios outperform peripheral portfolios when the market is under a drawup condition, or when the market is stable or drawup in the selection horizon and is under a stable condition in the investment horizon. We also find that peripheral portfolios gain more than central portfolios when the market is stable in the selection horizon and is drawdown in the investment horizon. Empirical tests are carried out based on the optimal portfolio strategy. Among all possible optimal portfolio strategies based on different parameters to select portfolios and different criteria to identify market conditions, 65% of our optimal portfolio strategies outperform the random strategy for the Shanghai A-Share market while the proportion is 70% for the Shenzhen A-Share market. PMID:28129333

Dynamic Portfolio Strategy Using Clustering Approach.

PubMed

Ren, Fei; Lu, Ya-Nan; Li, Sai-Ping; Jiang, Xiong-Fei; Zhong, Li-Xin; Qiu, Tian

2017-01-01

The problem of portfolio optimization is one of the most important issues in asset management. We here propose a new dynamic portfolio strategy based on the time-varying structures of MST networks in Chinese stock markets, where the market condition is further considered when using the optimal portfolios for investment. A portfolio strategy comprises two stages: First, select the portfolios by choosing central and peripheral stocks in the selection horizon using five topological parameters, namely degree, betweenness centrality, distance on degree criterion, distance on correlation criterion and distance on distance criterion. Second, use the portfolios for investment in the investment horizon. The optimal portfolio is chosen by comparing central and peripheral portfolios under different combinations of market conditions in the selection and investment horizons. Market conditions in our paper are identified by the ratios of the number of trading days with rising index to the total number of trading days, or the sum of the amplitudes of the trading days with rising index to the sum of the amplitudes of the total trading days. We find that central portfolios outperform peripheral portfolios when the market is under a drawup condition, or when the market is stable or drawup in the selection horizon and is under a stable condition in the investment horizon. We also find that peripheral portfolios gain more than central portfolios when the market is stable in the selection horizon and is drawdown in the investment horizon. Empirical tests are carried out based on the optimal portfolio strategy. Among all possible optimal portfolio strategies based on different parameters to select portfolios and different criteria to identify market conditions, 65% of our optimal portfolio strategies outperform the random strategy for the Shanghai A-Share market while the proportion is 70% for the Shenzhen A-Share market.

The returns and risks of investment portfolio in stock market crashes

NASA Astrophysics Data System (ADS)

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

2015-06-01

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

Replica Analysis for Portfolio Optimization with Single-Factor Model

NASA Astrophysics Data System (ADS)

Shinzato, Takashi

2017-06-01

In this paper, we use replica analysis to investigate the influence of correlation among the return rates of assets on the solution of the portfolio optimization problem. We consider the behavior of an optimal solution for the case where the return rate is described with a single-factor model and compare the findings obtained from our proposed methods with correlated return rates with those obtained with independent return rates. We then analytically assess the increase in the investment risk when correlation is included. Furthermore, we also compare our approach with analytical procedures for minimizing the investment risk from operations research.

A diversified portfolio model of adaptability.

PubMed

Chandra, Siddharth; Leong, Frederick T L

2016-12-01

A new model of adaptability, the diversified portfolio model (DPM) of adaptability, is introduced. In the 1950s, Markowitz developed the financial portfolio model by demonstrating that investors could optimize the ratio of risk and return on their portfolios through risk diversification. The DPM integrates attractive features of a variety of models of adaptability, including Linville's self-complexity model, the risk and resilience model, and Bandura's social cognitive theory. The DPM draws on the concept of portfolio diversification, positing that diversified investment in multiple life experiences, life roles, and relationships promotes positive adaptation to life's challenges. The DPM provides a new integrative model of adaptability across the biopsychosocial levels of functioning. More importantly, the DPM addresses a gap in the literature by illuminating the antecedents of adaptive processes studied in a broad array of psychological models. The DPM is described in relation to the biopsychosocial model and propositions are offered regarding its utility in increasing adaptiveness. Recommendations for future research are also offered. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Extended Information Ratio for Portfolio Optimization Using Simulated Annealing with Constrained Neighborhood

NASA Astrophysics Data System (ADS)

Orito, Yukiko; Yamamoto, Hisashi; Tsujimura, Yasuhiro; Kambayashi, Yasushi

The portfolio optimizations are to determine the proportion-weighted combination in the portfolio in order to achieve investment targets. This optimization is one of the multi-dimensional combinatorial optimizations and it is difficult for the portfolio constructed in the past period to keep its performance in the future period. In order to keep the good performances of portfolios, we propose the extended information ratio as an objective function, using the information ratio, beta, prime beta, or correlation coefficient in this paper. We apply the simulated annealing (SA) to optimize the portfolio employing the proposed ratio. For the SA, we make the neighbor by the operation that changes the structure of the weights in the portfolio. In the numerical experiments, we show that our portfolios keep the good performances when the market trend of the future period becomes different from that of the past period.

Towards resiliency with micro-grids: Portfolio optimization and investment under uncertainty

NASA Astrophysics Data System (ADS)

Gharieh, Kaveh

Energy security and sustained supply of power are critical for community welfare and economic growth. In the face of the increased frequency and intensity of extreme weather conditions which can result in power grid outage, the value of micro-grids to improve the communities' power reliability and resiliency is becoming more important. Micro-grids capability to operate in islanded mode in stressed-out conditions, dramatically decreases the economic loss of critical infrastructure in power shortage occasions. More wide-spread participation of micro-grids in the wholesale energy market in near future, makes the development of new investment models necessary. However, market and price risks in short term and long term along with risk factors' impacts shall be taken into consideration in development of new investment models. This work proposes a set of models and tools to address different problems associated with micro-grid assets including optimal portfolio selection, investment and financing in both community and a sample critical infrastructure (i.e. wastewater treatment plant) levels. The models account for short-term operational volatilities and long-term market uncertainties. A number of analytical methodologies and financial concepts have been adopted to develop the aforementioned models as follows. (1) Capital budgeting planning and portfolio optimization models with Monte Carlo stochastic scenario generation are applied to derive the optimal investment decision for a portfolio of micro-grid assets considering risk factors and multiple sources of uncertainties. (2) Real Option theory, Monte Carlo simulation and stochastic optimization techniques are applied to obtain optimal modularized investment decisions for hydrogen tri-generation systems in wastewater treatment facilities, considering multiple sources of uncertainty. (3) Public Private Partnership (PPP) financing concept coupled with investment horizon approach are applied to estimate public and private parties' revenue shares from a community-level micro-grid project over the course of assets' lifetime considering their optimal operation under uncertainty.

Ant colony algorithm for clustering in portfolio optimization

NASA Astrophysics Data System (ADS)

Subekti, R.; Sari, E. R.; Kusumawati, R.

2018-03-01

This research aims to describe portfolio optimization using clustering methods with ant colony approach. Two stock portfolios of LQ45 Indonesia is proposed based on the cluster results obtained from ant colony optimization (ACO). The first portfolio consists of assets with ant colony displacement opportunities beyond the defined probability limits of the researcher, where the weight of each asset is determined by mean-variance method. The second portfolio consists of two assets with the assumption that each asset is a cluster formed from ACO. The first portfolio has a better performance compared to the second portfolio seen from the Sharpe index.

Numerical approach to optimal portfolio in a power utility regime-switching model

NASA Astrophysics Data System (ADS)

Gyulov, Tihomir B.; Koleva, Miglena N.; Vulkov, Lubin G.

2017-12-01

We consider a system of weakly coupled degenerate semi-linear parabolic equations of optimal portfolio in a regime-switching with power utility function, derived by A.R. Valdez and T. Vargiolu [14]. First, we discuss some basic properties of the solution of this system. Then, we develop and analyze implicit-explicit, flux limited finite difference schemes for the differential problem. Numerical experiments are discussed.

Large deviations and portfolio optimization

NASA Astrophysics Data System (ADS)

Sornette, Didier

Risk control and optimal diversification constitute a major focus in the finance and insurance industries as well as, more or less consciously, in our everyday life. We present a discussion of the characterization of risks and of the optimization of portfolios that starts from a simple illustrative model and ends by a general functional integral formulation. A major item is that risk, usually thought of as one-dimensional in the conventional mean-variance approach, has to be addressed by the full distribution of losses. Furthermore, the time-horizon of the investment is shown to play a major role. We show the importance of accounting for large fluctuations and use the theory of Cramér for large deviations in this context. We first treat a simple model with a single risky asset that exemplifies the distinction between the average return and the typical return and the role of large deviations in multiplicative processes, and the different optimal strategies for the investors depending on their size. We then analyze the case of assets whose price variations are distributed according to exponential laws, a situation that is found to describe daily price variations reasonably well. Several portfolio optimization strategies are presented that aim at controlling large risks. We end by extending the standard mean-variance portfolio optimization theory, first within the quasi-Gaussian approximation and then using a general formulation for non-Gaussian correlated assets in terms of the formalism of functional integrals developed in the field theory of critical phenomena.

Managing the Public Sector Research and Development Portfolio Selection Process: A Case Study of Quantitative Selection and Optimization

DTIC Science & Technology

2016-09-01

PUBLIC SECTOR RESEARCH & DEVELOPMENT PORTFOLIO SELECTION PROCESS: A CASE STUDY OF QUANTITATIVE SELECTION AND OPTIMIZATION by Jason A. Schwartz...PUBLIC SECTOR RESEARCH & DEVELOPMENT PORTFOLIO SELECTION PROCESS: A CASE STUDY OF QUANTITATIVE SELECTION AND OPTIMIZATION 5. FUNDING NUMBERS 6...describing how public sector organizations can implement a research and development (R&D) portfolio optimization strategy to maximize the cost

Developing a framework for energy technology portfolio selection

NASA Astrophysics Data System (ADS)

Davoudpour, Hamid; Ashrafi, Maryam

2012-11-01

Today, the increased consumption of energy in world, in addition to the risk of quick exhaustion of fossil resources, has forced industrial firms and organizations to utilize energy technology portfolio management tools viewed both as a process of diversification of energy sources and optimal use of available energy sources. Furthermore, the rapid development of technologies, their increasing complexity and variety, and market dynamics have made the task of technology portfolio selection difficult. Considering high level of competitiveness, organizations need to strategically allocate their limited resources to the best subset of possible candidates. This paper presents the results of developing a mathematical model for energy technology portfolio selection at a R&D center maximizing support of the organization's strategy and values. The model balances the cost and benefit of the entire portfolio.

Portfolios with fuzzy returns: Selection strategies based on semi-infinite programming

NASA Astrophysics Data System (ADS)

Vercher, Enriqueta

2008-08-01

This paper provides new models for portfolio selection in which the returns on securities are considered fuzzy numbers rather than random variables. The investor's problem is to find the portfolio that minimizes the risk of achieving a return that is not less than the return of a riskless asset. The corresponding optimal portfolio is derived using semi-infinite programming in a soft framework. The return on each asset and their membership functions are described using historical data. The investment risk is approximated by mean intervals which evaluate the downside risk for a given fuzzy portfolio. This approach is illustrated with a numerical example.

Environment and economic risk: An analysis of carbon emission market and portfolio management.

PubMed

Luo, Cuicui; Wu, Desheng

2016-08-01

Climate change has been one of the biggest and most controversial environmental issues of our times. It affects the global economy, environment and human health. Many researchers find that carbon dioxide (CO2) has contributed the most to climate change between 1750 and 2005. In this study, the orthogonal GARCH (OGARCH) model is applied to examine the time-varying correlations in European CO2 allowance, crude oil and stock markets in US, Europe and China during the Protocol's first commitment period. The results show that the correlations between EUA carbon spot price and the equity markets are higher and more volatile in US and Europe than in China. Then the optimal portfolios consisting these five time series are selected by Mean-Variance and Mean-CVAR models. It shows that the optimal portfolio selected by MV-OGARCH model has the best performance. Copyright © 2016 Elsevier Inc. All rights reserved.

Deformed exponentials and portfolio selection

NASA Astrophysics Data System (ADS)

Rodrigues, Ana Flávia P.; Guerreiro, Igor M.; Cavalcante, Charles Casimiro

In this paper, we present a method for portfolio selection based on the consideration on deformed exponentials in order to generalize the methods based on the gaussianity of the returns in portfolio, such as the Markowitz model. The proposed method generalizes the idea of optimizing mean-variance and mean-divergence models and allows a more accurate behavior for situations where heavy-tails distributions are necessary to describe the returns in a given time instant, such as those observed in economic crises. Numerical results show the proposed method outperforms the Markowitz portfolio for the cumulated returns with a good convergence rate of the weights for the assets which are searched by means of a natural gradient algorithm.

Lost opportunities and future avenues to reconcile hydropower and sediment transport in the Mekong Basin through optimal sequencing of dam portfolios.

NASA Astrophysics Data System (ADS)

Castelletti, A.; Schmitt, R. J. P.; Bizzi, S.; Kondolf, G. M.

2017-12-01

Dams are essential to meet growing water and energy demands. While dams cumulatively impact downstream rivers on network-scales, dam development is mostly based on ad-hoc economic and environmental assessments of single dams. Here, we provide evidence that replacing this ad-hoc approach with early strategic planning of entire dam portfolios can greatly reduce conflicts between economic and environmental objectives of dams. In the Mekong Basin (800,000km2), 123 major dam sites (status-quo: 56 built and under construction) could generate 280,000 GWh/yr of hydropower. Cumulatively, dams risk interrupting the basin's sediment dynamics with severe impacts on livelihoods and eco-systems. To evaluate cumulative impacts and benefits of the ad-hoc planned status-quo portfolio, we combine the CASCADE sediment connectivity model with data on hydropower production and sediment trapping at each dam site. We couple CASCADE to a multi-objective genetic algorithm (BORG) identifying a) portfolios resulting in an optimal trade-off between cumulative sediment trapping and hydropower production and b) an optimal development sequence for each portfolio. We perform this analysis first for the pristine basin (i.e., without pre-existing dams) and then starting from the status-quo portfolio, deriving policy recommendations for which dams should be prioritized in the near future. The status-quo portfolio creates a sub-optimal trade-off between hydropower and sediment trapping, exploiting 50 % of the basin's hydro-electric potential and trapping 60 % of the sediment load. Alternative optimal portfolios could have produced equivalent hydropower for 30 % sediment trapping. Imminent development of mega-dams in the lower basin will increase hydropower production by 20 % but increase sediment trapping to >90 %. In contrast, following an optimal development sequence can still increase hydropower by 30 % with limited additional sediment trapping by prioritizing dams in upper parts of the basin. Our findings argue for reconsidering some imminent dam developments in the Mekong. With nearly 3000 dams awaiting development world-wide, results from the Mekong are of global importance, demonstrating that strategic planning and sequencing of dams is instrumental for sustainable development of dams and hydropower.

How Family Status and Social Security Claiming Options Shape Optimal Life Cycle Portfolios

PubMed Central

Hubener, Andreas; Maurer, Raimond; Mitchell, Olivia S.

2017-01-01

We show how optimal household decisions regarding work, retirement, saving, portfolio allocations, and life insurance are shaped by the complex financial options embedded in U.S. Social Security rules and uncertain family transitions. Our life cycle model predicts sharp consumption drops on retirement, an age-62 peak in claiming rates, and earlier claiming by wives versus husbands and single women. Moreover, life insurance is mainly purchased on men’s lives. Our model, which takes Social Security rules seriously, generates wealth and retirement outcomes that are more consistent with the data, in contrast to earlier and less realistic models. PMID:28659659

Transaction fees and optimal rebalancing in the growth-optimal portfolio

NASA Astrophysics Data System (ADS)

Feng, Yu; Medo, Matúš; Zhang, Liang; Zhang, Yi-Cheng

2011-05-01

The growth-optimal portfolio optimization strategy pioneered by Kelly is based on constant portfolio rebalancing which makes it sensitive to transaction fees. We examine the effect of fees on an example of a risky asset with a binary return distribution and show that the fees may give rise to an optimal period of portfolio rebalancing. The optimal period is found analytically in the case of lognormal returns. This result is consequently generalized and numerically verified for broad return distributions and returns generated by a GARCH process. Finally we study the case when investment is rebalanced only partially and show that this strategy can improve the investment long-term growth rate more than optimization of the rebalancing period.

Application of Post Modern Portfolio Theory to Mitigate Risk in International Shipping

DTIC Science & Technology

2011-03-24

The concept of portfolio optimization pioneered by Dr. Harry Markowitz and still used today for investment diversification is applied to the ...is currently referred to as “Post-Modern Portfolio Theory .” It begins with the foundations of portfolio optimization as created by Harry 14... Portfolio Theory ,” and is still considered to be one of the foundations of economic theory , garnering

Formation of the portfolio of high-rise construction projects on the basis of optimization of «risk-return» rate

NASA Astrophysics Data System (ADS)

Uvarova, Svetlana; Kutsygina, Olga; Smorodina, Elena; Gumba, Khuta

2018-03-01

The effectiveness and sustainability of an enterprise are based on the effectiveness and sustainability of its portfolio of projects. When creating a production program for a construction company based on a portfolio of projects and related to the planning and implementation of initiated organizational and economic changes, the problem of finding the optimal "risk-return" ratio of the program (portfolio of projects) is solved. The article proposes and approves the methodology of forming a portfolio of enterprise projects on the basis of the correspondence principle. Optimization of the portfolio of projects on the criterion of "risk-return" also contributes to the company's sustainability.

Portfolio optimization problem with nonidentical variances of asset returns using statistical mechanical informatics.

PubMed

Shinzato, Takashi

2016-12-01

The portfolio optimization problem in which the variances of the return rates of assets are not identical is analyzed in this paper using the methodology of statistical mechanical informatics, specifically, replica analysis. We defined two characteristic quantities of an optimal portfolio, namely, minimal investment risk and investment concentration, in order to solve the portfolio optimization problem and analytically determined their asymptotical behaviors using replica analysis. Numerical experiments were also performed, and a comparison between the results of our simulation and those obtained via replica analysis validated our proposed method.

Portfolio optimization problem with nonidentical variances of asset returns using statistical mechanical informatics

NASA Astrophysics Data System (ADS)

Shinzato, Takashi

2016-12-01

The portfolio optimization problem in which the variances of the return rates of assets are not identical is analyzed in this paper using the methodology of statistical mechanical informatics, specifically, replica analysis. We defined two characteristic quantities of an optimal portfolio, namely, minimal investment risk and investment concentration, in order to solve the portfolio optimization problem and analytically determined their asymptotical behaviors using replica analysis. Numerical experiments were also performed, and a comparison between the results of our simulation and those obtained via replica analysis validated our proposed method.

Optimal Investment Under Transaction Costs: A Threshold Rebalanced Portfolio Approach

NASA Astrophysics Data System (ADS)

Tunc, Sait; Donmez, Mehmet Ali; Kozat, Suleyman Serdar

2013-06-01

We study optimal investment in a financial market having a finite number of assets from a signal processing perspective. We investigate how an investor should distribute capital over these assets and when he should reallocate the distribution of the funds over these assets to maximize the cumulative wealth over any investment period. In particular, we introduce a portfolio selection algorithm that maximizes the expected cumulative wealth in i.i.d. two-asset discrete-time markets where the market levies proportional transaction costs in buying and selling stocks. We achieve this using "threshold rebalanced portfolios", where trading occurs only if the portfolio breaches certain thresholds. Under the assumption that the relative price sequences have log-normal distribution from the Black-Scholes model, we evaluate the expected wealth under proportional transaction costs and find the threshold rebalanced portfolio that achieves the maximal expected cumulative wealth over any investment period. Our derivations can be readily extended to markets having more than two stocks, where these extensions are pointed out in the paper. As predicted from our derivations, we significantly improve the achieved wealth over portfolio selection algorithms from the literature on historical data sets.

A Robust Statistics Approach to Minimum Variance Portfolio Optimization

NASA Astrophysics Data System (ADS)

Yang, Liusha; Couillet, Romain; McKay, Matthew R.

2015-12-01

We study the design of portfolios under a minimum risk criterion. The performance of the optimized portfolio relies on the accuracy of the estimated covariance matrix of the portfolio asset returns. For large portfolios, the number of available market returns is often of similar order to the number of assets, so that the sample covariance matrix performs poorly as a covariance estimator. Additionally, financial market data often contain outliers which, if not correctly handled, may further corrupt the covariance estimation. We address these shortcomings by studying the performance of a hybrid covariance matrix estimator based on Tyler's robust M-estimator and on Ledoit-Wolf's shrinkage estimator while assuming samples with heavy-tailed distribution. Employing recent results from random matrix theory, we develop a consistent estimator of (a scaled version of) the realized portfolio risk, which is minimized by optimizing online the shrinkage intensity. Our portfolio optimization method is shown via simulations to outperform existing methods both for synthetic and real market data.

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

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

Brackney, Larry J.

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

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.

Linearly Adjustable International Portfolios

NASA Astrophysics Data System (ADS)

Fonseca, R. J.; Kuhn, D.; Rustem, B.

2010-09-01

We present an approach to multi-stage international portfolio optimization based on the imposition of a linear structure on the recourse decisions. Multiperiod decision problems are traditionally formulated as stochastic programs. Scenario tree based solutions however can become intractable as the number of stages increases. By restricting the space of decision policies to linear rules, we obtain a conservative tractable approximation to the original problem. Local asset prices and foreign exchange rates are modelled separately, which allows for a direct measure of their impact on the final portfolio value.

Analysis of portfolio optimization with lot of stocks amount constraint: case study index LQ45

NASA Astrophysics Data System (ADS)

Chin, Liem; Chendra, Erwinna; Sukmana, Agus

2018-01-01

To form an optimum portfolio (in the sense of minimizing risk and / or maximizing return), the commonly used model is the mean-variance model of Markowitz. However, there is no amount of lots of stocks constraint. And, retail investors in Indonesia cannot do short selling. So, in this study we will develop an existing model by adding an amount of lot of stocks and short-selling constraints to get the minimum risk of portfolio with and without any target return. We will analyse the stocks listed in the LQ45 index based on the stock market capitalization. To perform this analysis, we will use Solver that available in Microsoft Excel.

Averting HIV Infections in New York City: A Modeling Approach Estimating the Future Impact of Additional Behavioral and Biomedical HIV Prevention Strategies

PubMed Central

Kessler, Jason; Myers, Julie E.; Nucifora, Kimberly A.; Mensah, Nana; Kowalski, Alexis; Sweeney, Monica; Toohey, Christopher; Khademi, Amin; Shepard, Colin; Cutler, Blayne; Braithwaite, R. Scott

2013-01-01

Background New York City (NYC) remains an epicenter of the HIV epidemic in the United States. Given the variety of evidence-based HIV prevention strategies available and the significant resources required to implement each of them, comparative studies are needed to identify how to maximize the number of HIV cases prevented most economically. Methods A new model of HIV disease transmission was developed integrating information from a previously validated micro-simulation HIV disease progression model. Specification and parameterization of the model and its inputs, including the intervention portfolio, intervention effects and costs were conducted through a collaborative process between the academic modeling team and the NYC Department of Health and Mental Hygiene. The model projects the impact of different prevention strategies, or portfolios of prevention strategies, on the HIV epidemic in NYC. Results Ten unique interventions were able to provide a prevention benefit at an annual program cost of less than $360,000, the threshold for consideration as a cost-saving intervention (because of offsets by future HIV treatment costs averted). An optimized portfolio of these specific interventions could result in up to a 34% reduction in new HIV infections over the next 20 years. The cost-per-infection averted of the portfolio was estimated to be $106,378; the total cost was in excess of $2 billion (over the 20 year period, or approximately $100 million per year, on average). The cost-savings of prevented infections was estimated at more than $5 billion (or approximately $250 million per year, on average). Conclusions Optimal implementation of a portfolio of evidence-based interventions can have a substantial, favorable impact on the ongoing HIV epidemic in NYC and provide future cost-saving despite significant initial costs. PMID:24058465

Optimization Of Mean-Semivariance-Skewness Portfolio Selection Model In Fuzzy Random Environment

NASA Astrophysics Data System (ADS)

Chatterjee, Amitava; Bhattacharyya, Rupak; Mukherjee, Supratim; Kar, Samarjit

2010-10-01

The purpose of the paper is to construct a mean-semivariance-skewness portfolio selection model in fuzzy random environment. The objective is to maximize the skewness with predefined maximum risk tolerance and minimum expected return. Here the security returns in the objectives and constraints are assumed to be fuzzy random variables in nature and then the vagueness of the fuzzy random variables in the objectives and constraints are transformed into fuzzy variables which are similar to trapezoidal numbers. The newly formed fuzzy model is then converted into a deterministic optimization model. The feasibility and effectiveness of the proposed method is verified by numerical example extracted from Bombay Stock Exchange (BSE). The exact parameters of fuzzy membership function and probability density function are obtained through fuzzy random simulating the past dates.

Application’s Method of Quadratic Programming for Optimization of Portfolio Selection

NASA Astrophysics Data System (ADS)

Kawamoto, Shigeru; Takamoto, Masanori; Kobayashi, Yasuhiro

Investors or fund-managers face with optimization of portfolio selection, which means that determine the kind and the quantity of investment among several brands. We have developed a method to obtain optimal stock’s portfolio more rapidly from twice to three times than conventional method with efficient universal optimization. The method is characterized by quadratic matrix of utility function and constrained matrices divided into several sub-matrices by focusing on structure of these matrices.

Methane mitigation timelines to inform energy technology evaluation

NASA Astrophysics Data System (ADS)

Roy, Mandira; Edwards, Morgan R.; Trancik, Jessika E.

2015-11-01

Energy technologies emitting differing proportions of methane (CH4) and carbon dioxide (CO2) vary significantly in their relative climate impacts over time, due to the distinct atmospheric lifetimes and radiative efficiencies of the two gases. Standard technology comparisons using the global warming potential (GWP) with a fixed time horizon do not account for the timing of emissions in relation to climate policy goals. Here we develop a portfolio optimization model that incorporates changes in technology impacts based on the temporal proximity of emissions to a radiative forcing (RF) stabilization target. An optimal portfolio, maximizing allowed energy consumption while meeting the RF target, is obtained by year-wise minimization of the marginal RF impact in an intended stabilization year. The optimal portfolio calls for using certain higher-CH4-emitting technologies prior to an optimal switching year, followed by CH4-light technologies as the stabilization year approaches. We apply the model to evaluate transportation technology pairs and find that accounting for dynamic emissions impacts, in place of using the static GWP, can result in CH4 mitigation timelines and technology transitions that allow for significantly greater energy consumption while meeting a climate policy target. The results can inform the forward-looking evaluation of energy technologies by engineers, private investors, and policy makers.

Applying the partitioned multiobjective risk method (PMRM) to portfolio selection.

PubMed

Reyes Santos, Joost; Haimes, Yacov Y

2004-06-01

The analysis of risk-return tradeoffs and their practical applications to portfolio analysis paved the way for Modern Portfolio Theory (MPT), which won Harry Markowitz a 1992 Nobel Prize in Economics. A typical approach in measuring a portfolio's expected return is based on the historical returns of the assets included in a portfolio. On the other hand, portfolio risk is usually measured using volatility, which is derived from the historical variance-covariance relationships among the portfolio assets. This article focuses on assessing portfolio risk, with emphasis on extreme risks. To date, volatility is a major measure of risk owing to its simplicity and validity for relatively small asset price fluctuations. Volatility is a justified measure for stable market performance, but it is weak in addressing portfolio risk under aberrant market fluctuations. Extreme market crashes such as that on October 19, 1987 ("Black Monday") and catastrophic events such as the terrorist attack of September 11, 2001 that led to a four-day suspension of trading on the New York Stock Exchange (NYSE) are a few examples where measuring risk via volatility can lead to inaccurate predictions. Thus, there is a need for a more robust metric of risk. By invoking the principles of the extreme-risk-analysis method through the partitioned multiobjective risk method (PMRM), this article contributes to the modeling of extreme risks in portfolio performance. A measure of an extreme portfolio risk, denoted by f(4), is defined as the conditional expectation for a lower-tail region of the distribution of the possible portfolio returns. This article presents a multiobjective problem formulation consisting of optimizing expected return and f(4), whose solution is determined using Evolver-a software that implements a genetic algorithm. Under business-as-usual market scenarios, the results of the proposed PMRM portfolio selection model are found to be compatible with those of the volatility-based model. However, under extremely unfavorable market conditions, results indicate that f(4) can be a more valid measure of risk than volatility.

A one-layer recurrent neural network for constrained pseudoconvex optimization and its application for dynamic portfolio optimization.

PubMed

Liu, Qingshan; Guo, Zhishan; Wang, Jun

2012-02-01

In this paper, a one-layer recurrent neural network is proposed for solving pseudoconvex optimization problems subject to linear equality and bound constraints. Compared with the existing neural networks for optimization (e.g., the projection neural networks), the proposed neural network is capable of solving more general pseudoconvex optimization problems with equality and bound constraints. Moreover, it is capable of solving constrained fractional programming problems as a special case. The convergence of the state variables of the proposed neural network to achieve solution optimality is guaranteed as long as the designed parameters in the model are larger than the derived lower bounds. Numerical examples with simulation results illustrate the effectiveness and characteristics of the proposed neural network. In addition, an application for dynamic portfolio optimization is discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.

Merton's problem for an investor with a benchmark in a Barndorff-Nielsen and Shephard market.

PubMed

Lennartsson, Jan; Lindberg, Carl

2015-01-01

To try to outperform an externally given benchmark with known weights is the most common equity mandate in the financial industry. For quantitative investors, this task is predominantly approached by optimizing their portfolios consecutively over short time horizons with one-period models. We seek in this paper to provide a theoretical justification to this practice when the underlying market is of Barndorff-Nielsen and Shephard type. This is done by verifying that an investor who seeks to maximize her expected terminal exponential utility of wealth in excess of her benchmark will in fact use an optimal portfolio equivalent to the one-period Markowitz mean-variance problem in continuum under the corresponding Black-Scholes market. Further, we can represent the solution to the optimization problem as in Feynman-Kac form. Hence, the problem, and its solution, is analogous to Merton's classical portfolio problem, with the main difference that Merton maximizes expected utility of terminal wealth, not wealth in excess of a benchmark.

A Bayesian approach for incorporating economic factors in sample size design for clinical trials of individual drugs and portfolios of drugs.

PubMed

Patel, Nitin R; Ankolekar, Suresh

2007-11-30

Classical approaches to clinical trial design ignore economic factors that determine economic viability of a new drug. We address the choice of sample size in Phase III trials as a decision theory problem using a hybrid approach that takes a Bayesian view from the perspective of a drug company and a classical Neyman-Pearson view from the perspective of regulatory authorities. We incorporate relevant economic factors in the analysis to determine the optimal sample size to maximize the expected profit for the company. We extend the analysis to account for risk by using a 'satisficing' objective function that maximizes the chance of meeting a management-specified target level of profit. We extend the models for single drugs to a portfolio of clinical trials and optimize the sample sizes to maximize the expected profit subject to budget constraints. Further, we address the portfolio risk and optimize the sample sizes to maximize the probability of achieving a given target of expected profit.

Strategic biopharmaceutical portfolio development: an analysis of constraint-induced implications.

PubMed

George, Edmund D; Farid, Suzanne S

2008-01-01

Optimizing the structure and development pathway of biopharmaceutical drug portfolios are core concerns to the developer that come with several attached complexities. These include strategic decisions for the choice of drugs, the scheduling of critical activities, and the possible involvement of third parties for development and manufacturing at various stages for each drug. Additional complexities that must be considered include the impact of making such decisions in an uncertain environment. Presented here is the development of a stochastic multi-objective optimization framework designed to address these issues. The framework harnesses the ability of Bayesian networks to characterize the probabilistic structure of superior decisions via machine learning and evolve them to multi-objective optimality. Case studies that entailed three- and five-drug portfolios alongside a range of cash flow constraints were constructed to derive insight from the framework where results demonstrate that a variety of options exist for formulating nondominated strategies in the objective space considered, giving the manufacturer a range of pursuable options. In all cases limitations on cash flow reduce the potential for generating profits for a given probability of success. For the sizes of portfolio considered, results suggest that naïvely applying strategies optimal for a particular size of portfolio to a portfolio of another size is inappropriate. For the five-drug portfolio the most preferred means for development across the set of optimized strategies is to fully integrate development and commercial activities in-house. For the three-drug portfolio, the preferred means of development involves a mixture of in-house, outsourced, and partnered activities. Also, the size of the portfolio appears to have a larger impact on strategy and the quality of objectives than the magnitude of cash flow constraint.

Vast Portfolio Selection with Gross-exposure Constraints*

PubMed Central

Fan, Jianqing; Zhang, Jingjin; Yu, Ke

2012-01-01

We introduce the large portfolio selection using gross-exposure constraints. We show that with gross-exposure constraint the empirically selected optimal portfolios based on estimated covariance matrices have similar performance to the theoretical optimal ones and there is no error accumulation effect from estimation of vast covariance matrices. This gives theoretical justification to the empirical results in Jagannathan and Ma (2003). We also show that the no-short-sale portfolio can be improved by allowing some short positions. The applications to portfolio selection, tracking, and improvements are also addressed. The utility of our new approach is illustrated by simulation and empirical studies on the 100 Fama-French industrial portfolios and the 600 stocks randomly selected from Russell 3000. PMID:23293404

Ship Maintenance Processes with Collaborative Product Lifecycle Management and 3D Terrestrial Laser Scanning Tools: Reducing Costs and Increasing Productivity

DTIC Science & Technology

2011-09-20

optimal portfolio point on the efficient frontier, for example, Portfolio B on the chart in Figure A1. Then, by subsequently changing some of the ... optimized portfolio controlling for risk using the IRM methodology and tool suite. Results indicate that both rapid and incremental implementation...Results of the KVA and SD scenario analysis provided the financial information required to forecast an optimized

Portfolio Purchasing Decision for Mobile Power Equipment of B2C E-Commerce Export Retailer Based on CVaR

NASA Astrophysics Data System (ADS)

Yanchun, Wan; Qiucen, Chen

2017-11-01

Purchasing is an important part of export e-commerce of B2C, which plays an important role on risk and cost control in supply management. From the perspective of risk control, the paper construct a CVaR model for portfolio purchase. We select a heavy sales mobile power equipment from a typical B2C e-commerce export retailer as study sample. This study optimizes the purchasing strategy of this type of mobile power equipment. The research has some reference for similar enterprises in purchasing portfolio decision.

Optimization of urban water supply portfolios combining infrastructure capacity expansion and water use decisions

NASA Astrophysics Data System (ADS)

Medellin-Azuara, J.; Fraga, C. C. S.; Marques, G.; Mendes, C. A.

2015-12-01

The expansion and operation of urban water supply systems under rapidly growing demands, hydrologic uncertainty, and scarce water supplies requires a strategic combination of various supply sources for added reliability, reduced costs and improved operational flexibility. The design and operation of such portfolio of water supply sources merits decisions of what and when to expand, and how much to use of each available sources accounting for interest rates, economies of scale and hydrologic variability. The present research provides a framework and an integrated methodology that optimizes the expansion of various water supply alternatives using dynamic programming and combining both short term and long term optimization of water use and simulation of water allocation. A case study in Bahia Do Rio Dos Sinos in Southern Brazil is presented. The framework couples an optimization model with quadratic programming model in GAMS with WEAP, a rain runoff simulation models that hosts the water supply infrastructure features and hydrologic conditions. Results allow (a) identification of trade offs between cost and reliability of different expansion paths and water use decisions and (b) evaluation of potential gains by reducing water system losses as a portfolio component. The latter is critical in several developing countries where water supply system losses are high and often neglected in favor of more system expansion. Results also highlight the potential of various water supply alternatives including, conservation, groundwater, and infrastructural enhancements over time. The framework proves its usefulness for planning its transferability to similarly urbanized systems.

On the use of genetic algorithm to optimize industrial assets lifecycle management under safety and budget constraints

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

Lonchampt, J.; Fessart, K.

2013-07-01

The purpose of this paper is to describe the method and tool dedicated to optimize investments planning for industrial assets. These investments may either be preventive maintenance tasks, asset enhancements or logistic investments such as spare parts purchases. The two methodological points to investigate in such an issue are: 1. The measure of the profitability of a portfolio of investments 2. The selection and planning of an optimal set of investments 3. The measure of the risk of a portfolio of investments The measure of the profitability of a set of investments in the IPOP tool is synthesised in themore » Net Present Value indicator. The NPV is the sum of the differences of discounted cash flows (direct costs, forced outages...) between the situations with and without a given investment. These cash flows are calculated through a pseudo-Markov reliability model representing independently the components of the industrial asset and the spare parts inventories. The component model has been widely discussed over the years but the spare part model is a new one based on some approximations that will be discussed. This model, referred as the NPV function, takes for input an investments portfolio and gives its NPV. The second issue is to optimize the NPV. If all investments were independent, this optimization would be an easy calculation, unfortunately there are two sources of dependency. The first one is introduced by the spare part model, as if components are indeed independent in their reliability model, the fact that several components use the same inventory induces a dependency. The second dependency comes from economic, technical or logistic constraints, such as a global maintenance budget limit or a safety requirement limiting the residual risk of failure of a component or group of component, making the aggregation of individual optimum not necessary feasible. The algorithm used to solve such a difficult optimization problem is a genetic algorithm. After a description of the features of the software a test case is presented showing the influence of the optimization algorithm parameters on its efficiency to find an optimal investments planning. (authors)« less

Portfolio Decision Analysis Framework for Value-Focused Ecosystem Management

PubMed Central

Convertino, Matteo; Valverde, L. James

2013-01-01

Management of natural resources in coastal ecosystems is a complex process that is made more challenging by the need for stakeholders to confront the prospect of sea level rise and a host of other environmental stressors. This situation is especially true for coastal military installations, where resource managers need to balance conflicting objectives of environmental conservation against military mission. The development of restoration plans will necessitate incorporating stakeholder preferences, and will, moreover, require compliance with applicable federal/state laws and regulations. To promote the efficient allocation of scarce resources in space and time, we develop a portfolio decision analytic (PDA) framework that integrates models yielding policy-dependent predictions for changes in land cover and species metapopulations in response to restoration plans, under different climate change scenarios. In a manner that is somewhat analogous to financial portfolios, infrastructure and natural resources are classified as human and natural assets requiring management. The predictions serve as inputs to a Multi Criteria Decision Analysis model (MCDA) that is used to measure the benefits of restoration plans, as well as to construct Pareto frontiers that represent optimal portfolio allocations of restoration actions and resources. Optimal plans allow managers to maintain or increase asset values by contrasting the overall degradation of the habitat and possible increased risk of species decline against the benefits of mission success. The optimal combination of restoration actions that emerge from the PDA framework allows decision-makers to achieve higher environmental benefits, with equal or lower costs, than those achievable by adopting the myopic prescriptions of the MCDA model. The analytic framework presented here is generalizable for the selection of optimal management plans in any ecosystem where human use of the environment conflicts with the needs of threatened and endangered species. The PDA approach demonstrates the advantages of integrated, top-down management, versus bottom-up management approaches. PMID:23823331

Portfolio Decision Analysis Framework for Value-Focused Ecosystem Management.

PubMed

Convertino, Matteo; Valverde, L James

2013-01-01

Management of natural resources in coastal ecosystems is a complex process that is made more challenging by the need for stakeholders to confront the prospect of sea level rise and a host of other environmental stressors. This situation is especially true for coastal military installations, where resource managers need to balance conflicting objectives of environmental conservation against military mission. The development of restoration plans will necessitate incorporating stakeholder preferences, and will, moreover, require compliance with applicable federal/state laws and regulations. To promote the efficient allocation of scarce resources in space and time, we develop a portfolio decision analytic (PDA) framework that integrates models yielding policy-dependent predictions for changes in land cover and species metapopulations in response to restoration plans, under different climate change scenarios. In a manner that is somewhat analogous to financial portfolios, infrastructure and natural resources are classified as human and natural assets requiring management. The predictions serve as inputs to a Multi Criteria Decision Analysis model (MCDA) that is used to measure the benefits of restoration plans, as well as to construct Pareto frontiers that represent optimal portfolio allocations of restoration actions and resources. Optimal plans allow managers to maintain or increase asset values by contrasting the overall degradation of the habitat and possible increased risk of species decline against the benefits of mission success. The optimal combination of restoration actions that emerge from the PDA framework allows decision-makers to achieve higher environmental benefits, with equal or lower costs, than those achievable by adopting the myopic prescriptions of the MCDA model. The analytic framework presented here is generalizable for the selection of optimal management plans in any ecosystem where human use of the environment conflicts with the needs of threatened and endangered species. The PDA approach demonstrates the advantages of integrated, top-down management, versus bottom-up management approaches.

Mathematical modelling of risk reduction in reinsurance

NASA Astrophysics Data System (ADS)

Balashov, R. B.; Kryanev, A. V.; Sliva, D. E.

2017-01-01

The paper presents a mathematical model of efficient portfolio formation in the reinsurance markets. The presented approach provides the optimal ratio between the expected value of return and the risk of yield values below a certain level. The uncertainty in the return values is conditioned by use of expert evaluations and preliminary calculations, which result in expected return values and the corresponding risk levels. The proposed method allows for implementation of computationally simple schemes and algorithms for numerical calculation of the numerical structure of the efficient portfolios of reinsurance contracts of a given insurance company.

Leptokurtic portfolio theory

NASA Astrophysics Data System (ADS)

Kitt, R.; Kalda, J.

2006-03-01

The question of optimal portfolio is addressed. The conventional Markowitz portfolio optimisation is discussed and the shortcomings due to non-Gaussian security returns are outlined. A method is proposed to minimise the likelihood of extreme non-Gaussian drawdowns of the portfolio value. The theory is called Leptokurtic, because it minimises the effects from “fat tails” of returns. The leptokurtic portfolio theory provides an optimal portfolio for investors, who define their risk-aversion as unwillingness to experience sharp drawdowns in asset prices. Two types of risks in asset returns are defined: a fluctuation risk, that has Gaussian distribution, and a drawdown risk, that deals with distribution tails. These risks are quantitatively measured by defining the “noise kernel” — an ellipsoidal cloud of points in the space of asset returns. The size of the ellipse is controlled with the threshold parameter: the larger the threshold parameter, the larger return are accepted for investors as normal fluctuations. The return vectors falling into the kernel are used for calculation of fluctuation risk. Analogously, the data points falling outside the kernel are used for the calculation of drawdown risks. As a result the portfolio optimisation problem becomes three-dimensional: in addition to the return, there are two types of risks involved. Optimal portfolio for drawdown-averse investors is the portfolio minimising variance outside the noise kernel. The theory has been tested with MSCI North America, Europe and Pacific total return stock indices.

An extended ASLD trading system to enhance portfolio management.

PubMed

Hung, Kei-Keung; Cheung, Yiu-Ming; Xu, Lei

2003-01-01

An adaptive supervised learning decision (ASLD) trading system has been presented by Xu and Cheung (1997) to optimize the expected returns of investment without considering risks. In this paper, we propose an extension of the ASLD system (EASLD), which combines the ASLD with a portfolio optimization scheme to take a balance between the expected returns and risks. This new system not only keeps the learning adaptability of the ASLD, but also dynamically controls the risk in pursuit of great profits by diversifying the capital to a time-varying portfolio of N assets. Consequently, it is shown that: 1) the EASLD system gives the investment risk much smaller than the ASLD one; and 2) more returns are gained through the EASLD system in comparison with the two individual portfolio optimization schemes that statically determine the portfolio weights without adaptive learning. We have justified these two issues by the experiments.

Replica analysis for the duality of the portfolio optimization problem

NASA Astrophysics Data System (ADS)

Shinzato, Takashi

2016-11-01

In the present paper, the primal-dual problem consisting of the investment risk minimization problem and the expected return maximization problem in the mean-variance model is discussed using replica analysis. As a natural extension of the investment risk minimization problem under only a budget constraint that we analyzed in a previous study, we herein consider a primal-dual problem in which the investment risk minimization problem with budget and expected return constraints is regarded as the primal problem, and the expected return maximization problem with budget and investment risk constraints is regarded as the dual problem. With respect to these optimal problems, we analyze a quenched disordered system involving both of these optimization problems using the approach developed in statistical mechanical informatics and confirm that both optimal portfolios can possess the primal-dual structure. Finally, the results of numerical simulations are shown to validate the effectiveness of the proposed method.

Replica analysis for the duality of the portfolio optimization problem.

PubMed

Shinzato, Takashi

2016-11-01

In the present paper, the primal-dual problem consisting of the investment risk minimization problem and the expected return maximization problem in the mean-variance model is discussed using replica analysis. As a natural extension of the investment risk minimization problem under only a budget constraint that we analyzed in a previous study, we herein consider a primal-dual problem in which the investment risk minimization problem with budget and expected return constraints is regarded as the primal problem, and the expected return maximization problem with budget and investment risk constraints is regarded as the dual problem. With respect to these optimal problems, we analyze a quenched disordered system involving both of these optimization problems using the approach developed in statistical mechanical informatics and confirm that both optimal portfolios can possess the primal-dual structure. Finally, the results of numerical simulations are shown to validate the effectiveness of the proposed method.

Continuous-time mean-variance portfolio selection with value-at-risk and no-shorting constraints

NASA Astrophysics Data System (ADS)

Yan, Wei

2012-01-01

An investment problem is considered with dynamic mean-variance(M-V) portfolio criterion under discontinuous prices which follow jump-diffusion processes according to the actual prices of stocks and the normality and stability of the financial market. The short-selling of stocks is prohibited in this mathematical model. Then, the corresponding stochastic Hamilton-Jacobi-Bellman(HJB) equation of the problem is presented and the solution of the stochastic HJB equation based on the theory of stochastic LQ control and viscosity solution is obtained. The efficient frontier and optimal strategies of the original dynamic M-V portfolio selection problem are also provided. And then, the effects on efficient frontier under the value-at-risk constraint are illustrated. Finally, an example illustrating the discontinuous prices based on M-V portfolio selection is presented.

A class of stochastic optimization problems with one quadratic & several linear objective functions and extended portfolio selection model

NASA Astrophysics Data System (ADS)

Xu, Jiuping; Li, Jun

2002-09-01

In this paper a class of stochastic multiple-objective programming problems with one quadratic, several linear objective functions and linear constraints has been introduced. The former model is transformed into a deterministic multiple-objective nonlinear programming model by means of the introduction of random variables' expectation. The reference direction approach is used to deal with linear objectives and results in a linear parametric optimization formula with a single linear objective function. This objective function is combined with the quadratic function using the weighted sums. The quadratic problem is transformed into a linear (parametric) complementary problem, the basic formula for the proposed approach. The sufficient and necessary conditions for (properly, weakly) efficient solutions and some construction characteristics of (weakly) efficient solution sets are obtained. An interactive algorithm is proposed based on reference direction and weighted sums. Varying the parameter vector on the right-hand side of the model, the DM can freely search the efficient frontier with the model. An extended portfolio selection model is formed when liquidity is considered as another objective to be optimized besides expectation and risk. The interactive approach is illustrated with a practical example.

Solving multistage stochastic programming models of portfolio selection with outstanding liabilities

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

Edirisinghe, C.

1994-12-31

Models for portfolio selection in the presence of an outstanding liability have received significant attention, for example, models for pricing options. The problem may be described briefly as follows: given a set of risky securities (and a riskless security such as a bond), and given a set of cash flows, i.e., outstanding liability, to be met at some future date, determine an initial portfolio and a dynamic trading strategy for the underlying securities such that the initial cost of the portfolio is within a prescribed wealth level and the expected cash surpluses arising from trading is maximized. While the tradingmore » strategy should be self-financing, there may also be other restrictions such as leverage and short-sale constraints. Usually the treatment is limited to binomial evolution of uncertainty (of stock price), with possible extensions for developing computational bounds for multinomial generalizations. Posing as stochastic programming models of decision making, we investigate alternative efficient solution procedures under continuous evolution of uncertainty, for discrete time economies. We point out an important moment problem arising in the portfolio selection problem, the solution (or bounds) on which provides the basis for developing efficient computational algorithms. While the underlying stochastic program may be computationally tedious even for a modest number of trading opportunities (i.e., time periods), the derived algorithms may used to solve problems whose sizes are beyond those considered within stochastic optimization.« less

Optimal allocation of trend following strategies

NASA Astrophysics Data System (ADS)

Grebenkov, Denis S.; Serror, Jeremy

2015-09-01

We consider a portfolio allocation problem for trend following (TF) strategies on multiple correlated assets. Under simplifying assumptions of a Gaussian market and linear TF strategies, we derive analytical formulas for the mean and variance of the portfolio return. We construct then the optimal portfolio that maximizes risk-adjusted return by accounting for inter-asset correlations. The dynamic allocation problem for n assets is shown to be equivalent to the classical static allocation problem for n2 virtual assets that include lead-lag corrections in positions of TF strategies. The respective roles of asset auto-correlations and inter-asset correlations are investigated in depth for the two-asset case and a sector model. In contrast to the principle of diversification suggesting to treat uncorrelated assets, we show that inter-asset correlations allow one to estimate apparent trends more reliably and to adjust the TF positions more efficiently. If properly accounted for, inter-asset correlations are not deteriorative but beneficial for portfolio management that can open new profit opportunities for trend followers. These concepts are illustrated using daily returns of three highly correlated futures markets: the E-mini S&P 500, Euro Stoxx 50 index, and the US 10-year T-note futures.

Land-Use Portfolio Modeler, Version 1.0

USGS Publications Warehouse

Taketa, Richard; Hong, Makiko

2010-01-01

Natural hazards pose significant threats to the public safety and economic health of many communities throughout the world. Community leaders and decision-makers continually face the challenges of planning and allocating limited resources to invest in protecting their communities against catastrophic losses from natural-hazard events. Public efforts to assess community vulnerability and encourage loss-reduction measures through mitigation often focused on either aggregating site-specific estimates or adopting standards based upon broad assumptions about regional risks. The site-specific method usually provided the most accurate estimates, but was prohibitively expensive, whereas regional risk assessments were often too general to be of practical use. Policy makers lacked a systematic and quantitative method for conducting a regional-scale risk assessment of natural hazards. In response, Bernknopf and others developed the portfolio model, an intermediate-scale approach to assessing natural-hazard risks and mitigation policy alternatives. The basis for the portfolio-model approach was inspired by financial portfolio theory, which prescribes a method of optimizing return on investment while reducing risk by diversifying investments in different security types. In this context, a security type represents a unique combination of features and hazard-risk level, while financial return is defined as the reduction in losses resulting from an investment in mitigation of chosen securities. Features are selected for mitigation and are modeled like investment portfolios. Earth-science and economic data for the features are combined and processed in order to analyze each of the portfolios, which are then used to evaluate the benefits of mitigating the risk in selected locations. Ultimately, the decision maker seeks to choose a portfolio representing a mitigation policy that maximizes the expected return-on-investment, while minimizing the uncertainty associated with that return-on-investment. The portfolio model, now known as the Land-Use Portfolio Model (LUPM), provided the framework for the development of the Land-Use Portfolio Modeler, Version 1.0 software (LUPM v1.0). The software provides a geographic information system (GIS)-based modeling tool for evaluating alternative risk-reduction mitigation strategies for specific natural-hazard events. The modeler uses information about a specific natural-hazard event and the features exposed to that event within the targeted study region to derive a measure of a given mitigation strategy`s effectiveness. Harnessing the spatial capabilities of a GIS enables the tool to provide a rich, interactive mapping environment in which users can create, analyze, visualize, and compare different

Portfolio evaluation of health programs: a reply to Sendi et al.

PubMed

Bridges, John F P; Terris, Darcey D

2004-05-01

Sendi et al. (Soc. Sci. Med. 57 (2003) 2207) extend previous research on cost-effectiveness analysis to the evaluation of a portfolio of interventions with risky outcomes using a "second best" approach that can identify improvements in efficiency in the allocation of resources. This method, however, cannot be used to directly identify the optimal solution to the resource allocation problem. Theoretically, a stricter adherence to the foundations of portfolio theory would permit direct optimization in portfolio selection, however, when we include uncertainty in our analysis in addition to the traditional concept of risk (which is often mislabelled uncertainty) complexities are introduced that create significant hurdles in the development of practical applications of portfolio theory for health care policy decision making.

Managing the vitamin A program portfolio: a case study of Zambia, 2013-2042.

PubMed

Fiedler, John L; Lividini, Keith

2014-03-01

Micronutrient deficiencies continue to constitute a major burden of disease, particularly in Africa and South Asia. Programs to address micronutrient deficiencies have been increasing in number, type, and scale in recent years, creating an ever-growing need to understand their combined coverage levels, costs, and impacts so as to more effectively combat deficiencies, avoid putting individuals at risk for excess intakes, and ensure the efficient use of public health resources. To analyze combinations of the two current programs--sugar fortification and Child Health Week (CHW)--together with four prospective programs--vegetable oil fortification, wheat flour fortification, maize meal fortification, and biofortified vitamin A maize--to identify Zambia's optimal vitamin A portfolio. Combining program cost estimates and 30-year Zambian food demand projections, together with the Zambian 2005 Living Conditions Monitoring Survey, the annual costs, coverage, impact, and cost-effectiveness of 62 Zambian portfolios were modeled for the period from 2013 to 2042. Optimal portfolios are identified for each of five alternative criteria: average cost-effectiveness, incremental cost-effectiveness, coverage maximization, health impact maximization, and affordability. The most likely scenario is identified to be one that starts with the current portfolio and takes into account all five criteria. Starting with CHW and sugar fortification, it phases in vitamin A maize, oil, wheat flour, and maize meal (in that order) to eventually include all six individual interventions. Combining cost and Household Consumption and Expenditure Survey (HCES) data provides a powerful evidence-generating tool with which to understand how individual micronutrient programs interact and to quantify the tradeoffs involved in selecting alternative program portfolios.

Portfolio optimization in enhanced index tracking with goal programming approach

NASA Astrophysics Data System (ADS)

Siew, Lam Weng; Jaaman, Saiful Hafizah Hj.; Ismail, Hamizun bin

2014-09-01

Enhanced index tracking is a popular form of passive fund management in stock market. Enhanced index tracking aims to generate excess return over the return achieved by the market index without purchasing all of the stocks that make up the index. This can be done by establishing an optimal portfolio to maximize the mean return and minimize the risk. The objective of this paper is to determine the portfolio composition and performance using goal programming approach in enhanced index tracking and comparing it to the market index. Goal programming is a branch of multi-objective optimization which can handle decision problems that involve two different goals in enhanced index tracking, a trade-off between maximizing the mean return and minimizing the risk. The results of this study show that the optimal portfolio with goal programming approach is able to outperform the Malaysia market index which is FTSE Bursa Malaysia Kuala Lumpur Composite Index because of higher mean return and lower risk without purchasing all the stocks in the market index.

Random Matrix Approach for Primal-Dual Portfolio Optimization Problems

NASA Astrophysics Data System (ADS)

Tada, Daichi; Yamamoto, Hisashi; Shinzato, Takashi

2017-12-01

In this paper, we revisit the portfolio optimization problems of the minimization/maximization of investment risk under constraints of budget and investment concentration (primal problem) and the maximization/minimization of investment concentration under constraints of budget and investment risk (dual problem) for the case that the variances of the return rates of the assets are identical. We analyze both optimization problems by the Lagrange multiplier method and the random matrix approach. Thereafter, we compare the results obtained from our proposed approach with the results obtained in previous work. Moreover, we use numerical experiments to validate the results obtained from the replica approach and the random matrix approach as methods for analyzing both the primal and dual portfolio optimization problems.

Minimal investment risk of a portfolio optimization problem with budget and investment concentration constraints

NASA Astrophysics Data System (ADS)

Shinzato, Takashi

2017-02-01

In the present paper, the minimal investment risk for a portfolio optimization problem with imposed budget and investment concentration constraints is considered using replica analysis. Since the minimal investment risk is influenced by the investment concentration constraint (as well as the budget constraint), it is intuitive that the minimal investment risk for the problem with an investment concentration constraint can be larger than that without the constraint (that is, with only the budget constraint). Moreover, a numerical experiment shows the effectiveness of our proposed analysis. In contrast, the standard operations research approach failed to identify accurately the minimal investment risk of the portfolio optimization problem.

Optimal Portfolio Selection Under Concave Price Impact

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

Ma Jin, E-mail: jinma@usc.edu; Song Qingshuo, E-mail: songe.qingshuo@cityu.edu.hk; Xu Jing, E-mail: xujing8023@yahoo.com.cn

2013-06-15

In this paper we study an optimal portfolio selection problem under instantaneous price impact. Based on some empirical analysis in the literature, we model such impact as a concave function of the trading size when the trading size is small. The price impact can be thought of as either a liquidity cost or a transaction cost, but the concavity nature of the cost leads to some fundamental difference from those in the existing literature. We show that the problem can be reduced to an impulse control problem, but without fixed cost, and that the value function is a viscosity solutionmore » to a special type of Quasi-Variational Inequality (QVI). We also prove directly (without using the solution to the QVI) that the optimal strategy exists and more importantly, despite the absence of a fixed cost, it is still in a 'piecewise constant' form, reflecting a more practical perspective.« less

Sharing the cost of river basin adaptation portfolios to climate change: Insights from social justice and cooperative game theory

NASA Astrophysics Data System (ADS)

Girard, Corentin; Rinaudo, Jean-Daniel; Pulido-Velazquez, Manuel

2016-10-01

The adaptation of water resource systems to the potential impacts of climate change requires mixed portfolios of supply and demand adaptation measures. The issue is not only to select efficient, robust, and flexible adaptation portfolios but also to find equitable strategies of cost allocation among the stakeholders. Our work addresses such cost allocation problems by applying two different theoretical approaches: social justice and cooperative game theory in a real case study. First of all, a cost-effective portfolio of adaptation measures at the basin scale is selected using a least-cost optimization model. Cost allocation solutions are then defined based on economic rationality concepts from cooperative game theory (the Core). Second, interviews are conducted to characterize stakeholders' perceptions of social justice principles associated with the definition of alternatives cost allocation rules. The comparison of the cost allocation scenarios leads to contrasted insights in order to inform the decision-making process at the river basin scale and potentially reap the efficiency gains from cooperation in the design of river basin adaptation portfolios.

Portfolio theory and the alternative decision rule of cost-effectiveness analysis: theoretical and practical considerations.

PubMed

Sendi, Pedram; Al, Maiwenn J; Gafni, Amiram; Birch, Stephen

2004-05-01

Bridges and Terris (Soc. Sci. Med. (2004)) critique our paper on the alternative decision rule of economic evaluation in the presence of uncertainty and constrained resources within the context of a portfolio of health care programs (Sendi et al. Soc. Sci. Med. 57 (2003) 2207). They argue that by not adopting a formal portfolio theory approach we overlook the optimal solution. We show that these arguments stem from a fundamental misunderstanding of the alternative decision rule of economic evaluation. In particular, the portfolio theory approach advocated by Bridges and Terris is based on the same theoretical assumptions that the alternative decision rule set out to relax. Moreover, Bridges and Terris acknowledge that the proposed portfolio theory approach may not identify the optimal solution to resource allocation problems. Hence, it provides neither theoretical nor practical improvements to the proposed alternative decision rule.

Robust portfolio selection based on asymmetric measures of variability of stock returns

NASA Astrophysics Data System (ADS)

Chen, Wei; Tan, Shaohua

2009-10-01

This paper addresses a new uncertainty set--interval random uncertainty set for robust optimization. The form of interval random uncertainty set makes it suitable for capturing the downside and upside deviations of real-world data. These deviation measures capture distributional asymmetry and lead to better optimization results. We also apply our interval random chance-constrained programming to robust mean-variance portfolio selection under interval random uncertainty sets in the elements of mean vector and covariance matrix. Numerical experiments with real market data indicate that our approach results in better portfolio performance.

A Portfolio for Optimal Collaboration of Human and Cyber Physical Production Systems in Problem-Solving

ERIC Educational Resources Information Center

Ansari, Fazel; Seidenberg, Ulrich

2016-01-01

This paper discusses the complementarity of human and cyber physical production systems (CPPS). The discourse of complementarity is elaborated by defining five criteria for comparing the characteristics of human and CPPS. Finally, a management portfolio matrix is proposed for examining the feasibility of optimal collaboration between them. The…

A Decision Support Model and Tool to Assist Financial Decision-Making in Universities

ERIC Educational Resources Information Center

Bhayat, Imtiaz; Manuguerra, Maurizio; Baldock, Clive

2015-01-01

In this paper, a model and tool is proposed to assist universities and other mission-based organisations to ascertain systematically the optimal portfolio of projects, in any year, meeting the organisations risk tolerances and available funds. The model and tool presented build on previous work on university operations and decision support systems…

Computing Optimal Stochastic Portfolio Execution Strategies: A Parametric Approach Using Simulations

NASA Astrophysics Data System (ADS)

Moazeni, Somayeh; Coleman, Thomas F.; Li, Yuying

2010-09-01

Computing optimal stochastic portfolio execution strategies under appropriate risk consideration presents great computational challenge. We investigate a parametric approach for computing optimal stochastic strategies using Monte Carlo simulations. This approach allows reduction in computational complexity by computing coefficients for a parametric representation of a stochastic dynamic strategy based on static optimization. Using this technique, constraints can be similarly handled using appropriate penalty functions. We illustrate the proposed approach to minimize the expected execution cost and Conditional Value-at-Risk (CVaR).

Estimating Phenomenological Parameters in Multi-Assets Markets

NASA Astrophysics Data System (ADS)

Raffaelli, Giacomo; Marsili, Matteo

Financial correlations exhibit a non-trivial dynamic behavior. This is reproduced by a simple phenomenological model of a multi-asset financial market, which takes into account the impact of portfolio investment on price dynamics. This captures the fact that correlations determine the optimal portfolio but are affected by investment based on it. Such a feedback on correlations gives rise to an instability when the volume of investment exceeds a critical value. Close to the critical point the model exhibits dynamical correlations very similar to those observed in real markets. We discuss how the model's parameter can be estimated in real market data with a maximum likelihood principle. This confirms the main conclusion that real markets operate close to a dynamically unstable point.

Noisy covariance matrices and portfolio optimization II

NASA Astrophysics Data System (ADS)

Pafka, Szilárd; Kondor, Imre

2003-03-01

Recent studies inspired by results from random matrix theory (Galluccio et al.: Physica A 259 (1998) 449; Laloux et al.: Phys. Rev. Lett. 83 (1999) 1467; Risk 12 (3) (1999) 69; Plerou et al.: Phys. Rev. Lett. 83 (1999) 1471) found that covariance matrices determined from empirical financial time series appear to contain such a high amount of noise that their structure can essentially be regarded as random. This seems, however, to be in contradiction with the fundamental role played by covariance matrices in finance, which constitute the pillars of modern investment theory and have also gained industry-wide applications in risk management. Our paper is an attempt to resolve this embarrassing paradox. The key observation is that the effect of noise strongly depends on the ratio r= n/ T, where n is the size of the portfolio and T the length of the available time series. On the basis of numerical experiments and analytic results for some toy portfolio models we show that for relatively large values of r (e.g. 0.6) noise does, indeed, have the pronounced effect suggested by Galluccio et al. (1998), Laloux et al. (1999) and Plerou et al. (1999) and illustrated later by Laloux et al. (Int. J. Theor. Appl. Finance 3 (2000) 391), Plerou et al. (Phys. Rev. E, e-print cond-mat/0108023) and Rosenow et al. (Europhys. Lett., e-print cond-mat/0111537) in a portfolio optimization context, while for smaller r (around 0.2 or below), the error due to noise drops to acceptable levels. Since the length of available time series is for obvious reasons limited in any practical application, any bound imposed on the noise-induced error translates into a bound on the size of the portfolio. In a related set of experiments we find that the effect of noise depends also on whether the problem arises in asset allocation or in a risk measurement context: if covariance matrices are used simply for measuring the risk of portfolios with a fixed composition rather than as inputs to optimization, the effect of noise on the measured risk may become very small.

Learning through a portfolio of carbon capture and storage demonstration projects

NASA Astrophysics Data System (ADS)

Reiner, David M.

2016-01-01

Carbon dioxide capture and storage (CCS) technology is considered by many to be an essential route to meet climate mitigation targets in the power and industrial sectors. Deploying CCS technologies globally will first require a portfolio of large-scale demonstration projects. These first projects should assist learning by diversity, learning by replication, de-risking the technologies and developing viable business models. From 2005 to 2009, optimism about the pace of CCS rollout led to mutually independent efforts in the European Union, North America and Australia to assemble portfolios of projects. Since 2009, only a few of these many project proposals remain viable, but the initial rationales for demonstration have not been revisited in the face of changing circumstances. Here I argue that learning is now both more difficult and more important given the slow pace of deployment. Developing a more coordinated global portfolio will facilitate learning across projects and may determine whether CCS ever emerges from the demonstration phase.

Directional variance adjustment: bias reduction in covariance matrices based on factor analysis with an application to portfolio optimization.

PubMed

Bartz, Daniel; Hatrick, Kerr; Hesse, Christian W; Müller, Klaus-Robert; Lemm, Steven

2013-01-01

Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA) algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation.

Directional Variance Adjustment: Bias Reduction in Covariance Matrices Based on Factor Analysis with an Application to Portfolio Optimization

PubMed Central

Bartz, Daniel; Hatrick, Kerr; Hesse, Christian W.; Müller, Klaus-Robert; Lemm, Steven

2013-01-01

Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA) algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation. PMID:23844016

Portfolios with nonlinear constraints and spin glasses

NASA Astrophysics Data System (ADS)

Gábor, Adrienn; Kondor, I.

1999-12-01

In a recent paper Galluccio, Bouchaud and Potters demonstrated that a certain portfolio problem with a nonlinear constraint maps exactly onto finding the ground states of a long-range spin glass, with the concomitant nonuniqueness and instability of the optimal portfolios. Here we put forward geometric arguments that lead to qualitatively similar conclusions, without recourse to the methods of spin glass theory, and give two more examples of portfolio problems with convex nonlinear constraints.

A Method for the Selection of Exploration Areas for Unconformity Uranium Deposits

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

Harris, DeVerle P.; Zaluski, Gerard; Marlatt, James

2009-06-15

The method we propose employs two analyses: (1) exploration simulation and risk valuation and (2) portfolio optimization. The first analysis, implemented by the investment worth system (IWS), uses Monte Carlo simulation to integrate a wide spectrum of uncertain and varied components to a relative frequency histogram for net present value of the exploration investment, which is converted to a risk-adjusted value (RAV). Iterative rerunning of the IWS enables the mapping of the relationship of RAV to magnitude of exploration expenditure, X. The second major analysis uses RAV vs. X maps to identify that subset (portfolio) of areas that maximizes themore » RAV of the firm's multiyear exploration budget. The IWS, which is demonstrated numerically, consists of six components based on the geologic description of a hypothetical basin and project area (PA) and a mix of hypothetical and actual conditions of an unidentified area. The geology is quantified and processed by Bayesian belief networks to produce the geology-based inputs required by the IWS. An exploration investment of $60 M produced a highly skewed distribution of net present value (NPV), having mean and median values of $4,160 M and $139 M, respectively. For hypothetical mining firm Minex, the RAV of the exploration investment of $60 M is only $110.7 M. An RAV that is less than 3% of mean NPV reflects the aversion by Minex to risk as well as the magnitude of risk implicit to the highly skewed NPV distribution and the probability of 0.45 for capital loss. Potential benefits of initiating exploration of a portfolio of areas, as contrasted with one area, include increased marginal productivity of exploration as well as reduced probability for nondiscovery. For an exogenously determined multiyear exploration budget, a conceptual framework for portfolio optimization is developed based on marginal RAV exploration products for candidate PAs. PORTFOLIO, a software developed to implement optimization, allocates exploration to PAs so that the RAV of the exploration budget is maximized. Moreover, PORTFOLIO provides a means to examine the impact of magnitude of budget on the composition of the exploration portfolio and the optimum allocation of exploration to PAs that comprise the portfolio. Using fictitious data for five PAs, a numerical demonstration is provided of the use of PORTFOLIO to identify those PAs that comprise the optimum exploration portfolio and to optimally allocate the multiyear budget across portfolio PAs.« less

Sparse and stable Markowitz portfolios.

PubMed

Brodie, Joshua; Daubechies, Ingrid; De Mol, Christine; Giannone, Domenico; Loris, Ignace

2009-07-28

We consider the problem of portfolio selection within the classical Markowitz mean-variance framework, reformulated as a constrained least-squares regression problem. We propose to add to the objective function a penalty proportional to the sum of the absolute values of the portfolio weights. This penalty regularizes (stabilizes) the optimization problem, encourages sparse portfolios (i.e., portfolios with only few active positions), and allows accounting for transaction costs. Our approach recovers as special cases the no-short-positions portfolios, but does allow for short positions in limited number. We implement this methodology on two benchmark data sets constructed by Fama and French. Using only a modest amount of training data, we construct portfolios whose out-of-sample performance, as measured by Sharpe ratio, is consistently and significantly better than that of the naïve evenly weighted portfolio.

Postoptimality analysis in the selection of technology portfolios

NASA Technical Reports Server (NTRS)

Adumitroaie, Virgil; Shelton, Kacie; Elfes, Alberto; Weisbin, Charles R.

2006-01-01

This paper describes an approach for qualifying optimal technology portfolios obtained with a multi-attribute decision support system. The goal is twofold: to gauge the degree of confidence in the optimal solution and to provide the decision-maker with an array of viable selection alternatives, which take into account input uncertainties and possibly satisfy non-technical constraints.

Inverse Statistics and Asset Allocation Efficiency

NASA Astrophysics Data System (ADS)

Bolgorian, Meysam

In this paper using inverse statistics analysis, the effect of investment horizon on the efficiency of portfolio selection is examined. Inverse statistics analysis is a general tool also known as probability distribution of exit time that is used for detecting the distribution of the time in which a stochastic process exits from a zone. This analysis was used in Refs. 1 and 2 for studying the financial returns time series. This distribution provides an optimal investment horizon which determines the most likely horizon for gaining a specific return. Using samples of stocks from Tehran Stock Exchange (TSE) as an emerging market and S&P 500 as a developed market, effect of optimal investment horizon in asset allocation is assessed. It is found that taking into account the optimal investment horizon in TSE leads to more efficiency for large size portfolios while for stocks selected from S&P 500, regardless of portfolio size, this strategy does not only not produce more efficient portfolios, but also longer investment horizons provides more efficiency.

PID feedback controller used as a tactical asset allocation technique: The G.A.M. model

NASA Astrophysics Data System (ADS)

Gandolfi, G.; Sabatini, A.; Rossolini, M.

2007-09-01

The objective of this paper is to illustrate a tactical asset allocation technique utilizing the PID controller. The proportional-integral-derivative (PID) controller is widely applied in most industrial processes; it has been successfully used for over 50 years and it is used by more than 95% of the plants processes. It is a robust and easily understood algorithm that can provide excellent control performance in spite of the diverse dynamic characteristics of the process plant. In finance, the process plant, controlled by the PID controller, can be represented by financial market assets forming a portfolio. More specifically, in the present work, the plant is represented by a risk-adjusted return variable. Money and portfolio managers’ main target is to achieve a relevant risk-adjusted return in their managing activities. In literature and in the financial industry business, numerous kinds of return/risk ratios are commonly studied and used. The aim of this work is to perform a tactical asset allocation technique consisting in the optimization of risk adjusted return by means of asset allocation methodologies based on the PID model-free feedback control modeling procedure. The process plant does not need to be mathematically modeled: the PID control action lies in altering the portfolio asset weights, according to the PID algorithm and its parameters, Ziegler-and-Nichols-tuned, in order to approach the desired portfolio risk-adjusted return efficiently.

Optimization Techniques for Clustering,Connectivity, and Flow Problems in Complex Networks

DTIC Science & Technology

2012-10-01

discrete optimization and for analysis of performance of algorithm portfolios; introducing a metaheuristic framework of variable objective search that...The results of empirical evaluation of the proposed algorithm are also included. 1.3 Theoretical analysis of heuristics and designing new metaheuristic ...analysis of heuristics for inapproximable problems and designing new metaheuristic approaches for the problems of interest; (IV) Developing new models

Explore or Exploit? A Generic Model and an Exactly Solvable Case

NASA Astrophysics Data System (ADS)

Gueudré, Thomas; Dobrinevski, Alexander; Bouchaud, Jean-Philippe

2014-02-01

Finding a good compromise between the exploitation of known resources and the exploration of unknown, but potentially more profitable choices, is a general problem, which arises in many different scientific disciplines. We propose a stylized model for these exploration-exploitation situations, including population or economic growth, portfolio optimization, evolutionary dynamics, or the problem of optimal pinning of vortices or dislocations in disordered materials. We find the exact growth rate of this model for treelike geometries and prove the existence of an optimal migration rate in this case. Numerical simulations in the one-dimensional case confirm the generic existence of an optimum.

Explore or exploit? A generic model and an exactly solvable case.

PubMed

Gueudré, Thomas; Dobrinevski, Alexander; Bouchaud, Jean-Philippe

2014-02-07

Finding a good compromise between the exploitation of known resources and the exploration of unknown, but potentially more profitable choices, is a general problem, which arises in many different scientific disciplines. We propose a stylized model for these exploration-exploitation situations, including population or economic growth, portfolio optimization, evolutionary dynamics, or the problem of optimal pinning of vortices or dislocations in disordered materials. We find the exact growth rate of this model for treelike geometries and prove the existence of an optimal migration rate in this case. Numerical simulations in the one-dimensional case confirm the generic existence of an optimum.

An optimal consumption and investment problem with quadratic utility and negative wealth constraints.

PubMed

Roh, Kum-Hwan; Kim, Ji Yeoun; Shin, Yong Hyun

2017-01-01

In this paper, we investigate the optimal consumption and portfolio selection problem with negative wealth constraints for an economic agent who has a quadratic utility function of consumption and receives a constant labor income. Due to the property of the quadratic utility function, we separate our problem into two cases and derive the closed-form solutions for each case. We also illustrate some numerical implications of the optimal consumption and portfolio.

Sparse and stable Markowitz portfolios

PubMed Central

Brodie, Joshua; Daubechies, Ingrid; De Mol, Christine; Giannone, Domenico; Loris, Ignace

2009-01-01

We consider the problem of portfolio selection within the classical Markowitz mean-variance framework, reformulated as a constrained least-squares regression problem. We propose to add to the objective function a penalty proportional to the sum of the absolute values of the portfolio weights. This penalty regularizes (stabilizes) the optimization problem, encourages sparse portfolios (i.e., portfolios with only few active positions), and allows accounting for transaction costs. Our approach recovers as special cases the no-short-positions portfolios, but does allow for short positions in limited number. We implement this methodology on two benchmark data sets constructed by Fama and French. Using only a modest amount of training data, we construct portfolios whose out-of-sample performance, as measured by Sharpe ratio, is consistently and significantly better than that of the naïve evenly weighted portfolio. PMID:19617537

Investments in energy technological change under uncertainty

NASA Astrophysics Data System (ADS)

Shittu, Ekundayo

2009-12-01

This dissertation addresses the crucial problem of how environmental policy uncertainty influences investments in energy technological change. The rising level of carbon emissions due to increasing global energy consumption calls for policy shift. In order to stem the negative consequences on the climate, policymakers are concerned with carving an optimal regulation that will encourage technology investments. However, decision makers are facing uncertainties surrounding future environmental policy. The first part considers the treatment of technological change in theoretical models. This part has two purposes: (1) to show--through illustrative examples--that technological change can lead to quite different, and surprising, impacts on the marginal costs of pollution abatement. We demonstrate an intriguing and uncommon result that technological change can increase the marginal costs of pollution abatement over some range of abatement; (2) to show the impact, on policy, of this uncommon observation. We find that under the assumption of technical change that can increase the marginal cost of pollution abatement over some range, the ranking of policy instruments is affected. The second part builds on the first by considering the impact of uncertainty in the carbon tax on investments in a portfolio of technologies. We determine the response of energy R&D investments as the carbon tax increases both in terms of overall and technology-specific investments. We determine the impact of risk in the carbon tax on the portfolio. We find that the response of the optimal investment in a portfolio of technologies to an increasing carbon tax depends on the relative costs of the programs and the elasticity of substitution between fossil and non-fossil energy inputs. In the third part, we zoom-in on the portfolio model above to consider how uncertainty in the magnitude and timing of a carbon tax influences investments. Under a two-stage continuous-time optimal control model, we consider the impact of these uncertainties on R&D spending that aims to lower the cost of non-fossil energy technology. We find that our results tally with the classical results because it discourages near-term investment. However, timing uncertainty increases near-term investment.

The CPAT 2.0.2 Domain Model - How CPAT 2.0.2 "Thinks" From an Analyst Perspective.

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

Waddell, Lucas; Muldoon, Frank; Melander, Darryl J.

To help effectively plan the management and modernization of their large and diverse fleets of vehicles, the Program Executive Office Ground Combat Systems (PEO GCS) and the Program Executive Office Combat Support and Combat Service Support (PEO CS &CSS) commissioned the development of a large - scale portfolio planning optimization tool. This software, the Capability Portfolio Analysis Tool (CPAT), creates a detailed schedule that optimally prioritizes the modernization or replacement of vehicles within the fleet - respecting numerous business rules associated with fleet structure, budgets, industrial base, research and testing, etc., while maximizing overall fleet performance through time. This reportmore » contains a description of the organizational fleet structure and a thorough explanation of the business rules that the CPAT formulation follows involving performance, scheduling, production, and budgets. This report, which is an update to the original CPAT domain model published in 2015 (SAND2015 - 4009), covers important new CPAT features. This page intentionally left blank« less

Regionalized LCA-based optimization of building energy supply: method and case study for a Swiss municipality.

PubMed

Saner, Dominik; Vadenbo, Carl; Steubing, Bernhard; Hellweg, Stefanie

2014-07-01

This paper presents a regionalized LCA-based multiobjective optimization model of building energy demand and supply for the case of a Swiss municipality for the minimization of greenhouse gas emissions and particulate matter formation. The results show that the environmental improvement potential is very large: in the optimal case, greenhouse gas emissions from energy supply could be reduced by more than 75% and particulate emissions by over 50% in the municipality. This scenario supposes a drastic shift of heat supply systems from a fossil fuel dominated portfolio to a portfolio consisting of mainly heat pump and woodchip incineration systems. In addition to a change in heat supply technologies, roofs, windows and walls would need to be refurbished in more than 65% of the municipality's buildings. The full potential of the environmental impact reductions will hardly be achieved in reality, particularly in the short term, for example, because of financial constraints and social acceptance, which were not taken into account in this study. Nevertheless, the results of the optimization model can help policy makers to identify the most effective measures for improvement at the decision making level, for example, at the building level for refurbishment and selection of heating systems or at the municipal level for designing district heating networks. Therefore, this work represents a starting point for designing effective incentives to reduce the environmental impact of buildings. While the results of the optimization model are specific to the municipality studied, the model could readily be adapted to other regions.

PrEP as a feature in the optimal landscape of combination HIV prevention in sub-Saharan Africa

PubMed Central

McGillen, Jessica B; Anderson, Sarah-Jane; Hallett, Timothy B

2016-01-01

Introduction The new WHO guidelines recommend offering pre-exposure prophylaxis (PrEP) to people who are at substantial risk of HIV infection. However, where PrEP should be prioritised, and for which population groups, remains an open question. The HIV landscape in sub-Saharan Africa features limited prevention resources, multiple options for achieving cost saving, and epidemic heterogeneity. This paper examines what role PrEP should play in optimal prevention in this complex and dynamic landscape. Methods We use a model that was previously developed to capture subnational HIV transmission in sub-Saharan Africa. With this model, we can consider how prevention funds could be distributed across and within countries throughout sub-Saharan Africa to enable optimal HIV prevention (that is, avert the greatest number of infections for the lowest cost). Here, we focus on PrEP to elucidate where, and to whom, it would optimally be offered in portfolios of interventions (alongside voluntary medical male circumcision, treatment as prevention, and behaviour change communication). Over a range of continental expenditure levels, we use our model to explore prevention patterns that incorporate PrEP, exclude PrEP, or implement PrEP according to a fixed incidence threshold. Results At low-to-moderate levels of total prevention expenditure, we find that the optimal intervention portfolios would include PrEP in only a few regions and primarily for female sex workers (FSW). Prioritisation of PrEP would expand with increasing total expenditure, such that the optimal prevention portfolios would offer PrEP in more subnational regions and increasingly for men who have sex with men (MSM) and the lower incidence general population. The marginal benefit of including PrEP among the available interventions increases with overall expenditure by up to 14% (relative to excluding PrEP). The minimum baseline incidence for the optimal offer of PrEP declines for all population groups as expenditure increases. We find that using a fixed incidence benchmark to guide PrEP decisions would incur considerable losses in impact (up to 7%) compared with an approach that uses PrEP more flexibly in light of prevailing budget conditions. Conclusions Our findings suggest that, for an optimal distribution of prevention resources, choices of whether to implement PrEP in subnational regions should depend on the scope for impact of other possible interventions, local incidence in population groups, and total resources available. If prevention funding were to become restricted in the future, it may be suboptimal to use PrEP according to a fixed incidence benchmark, and other prevention modalities may be more cost-effective. In contrast, expansions in funding could permit PrEP to be used to its full potential in epidemiologically driven prevention portfolios and thereby enable a more cost-effective HIV response across Africa. PMID:27760682

Patent portfolio management: literature review and a proposed model.

PubMed

Conegundes De Jesus, Camila Kiyomi; Salerno, Mario Sergio

2018-05-09

Patents and patent portfolios are gaining attention in the last decades, from the called 'pro-patent era' to the recent billionaire transactions involving patent portfolios. The field is growing in importance, both theoretically and practically and despite having substantial literature on new product development portfolio management, we have not found an article relating this theory to patent portfolios. Areas covered: The paper develops a systematic literature review on patent portfolio management to organize the evolution and tendencies of patent portfolio management, highlighting distinctive features of patent portfolio management. Interview with IP manager of three life sciences companies, including a leading multinational group provided relevant information about patent portfolio management. Expert opinion: Based on the systematic literature review on portfolio management, more specifically, on new product development portfolio theory, and interview the paper proposes the paper proposes a reference model to manage patent portfolios. The model comprises four stages aligned with the three goals of the NPD portfolio management: 1 - Linking strategy of the Company's NPD Portfolio to Patent Portfolio; 2 - Balancing the portfolio in buckets; 3 - Patent Valuation (maximizing valuation); 4 - Regularly reviewing the patent portfolio.

Mean-Reverting Portfolio With Budget Constraint

NASA Astrophysics Data System (ADS)

Zhao, Ziping; Palomar, Daniel P.

2018-05-01

This paper considers the mean-reverting portfolio design problem arising from statistical arbitrage in the financial markets. We first propose a general problem formulation aimed at finding a portfolio of underlying component assets by optimizing a mean-reversion criterion characterizing the mean-reversion strength, taking into consideration the variance of the portfolio and an investment budget constraint. Then several specific problems are considered based on the general formulation, and efficient algorithms are proposed. Numerical results on both synthetic and market data show that our proposed mean-reverting portfolio design methods can generate consistent profits and outperform the traditional design methods and the benchmark methods in the literature.

Assessing the Value of Information for Identifying Optimal Floodplain Management Portfolios

NASA Astrophysics Data System (ADS)

Read, L.; Bates, M.; Hui, R.; Lund, J. R.

2014-12-01

Floodplain management is a complex portfolio problem that can be analyzed from an integrated perspective incorporating traditionally structural and nonstructural options. One method to identify effective strategies for preparing, responding to, and recovering from floods is to optimize for a portfolio of temporary (emergency) and permanent floodplain management options. A risk-based optimization approach to this problem assigns probabilities to specific flood events and calculates the associated expected damages. This approach is currently limited by: (1) the assumption of perfect flood forecast information, i.e. implementing temporary management activities according to the actual flood event may differ from optimizing based on forecasted information and (2) the inability to assess system resilience across a range of possible future events (risk-centric approach). Resilience is defined here as the ability of a system to absorb and recover from a severe disturbance or extreme event. In our analysis, resilience is a system property that requires integration of physical, social, and information domains. This work employs a 3-stage linear program to identify the optimal mix of floodplain management options using conditional probabilities to represent perfect and imperfect flood stages (forecast vs. actual events). We assess the value of information in terms of minimizing damage costs for two theoretical cases - urban and rural systems. We use portfolio analysis to explore how the set of optimal management options differs depending on whether the goal is for the system to be risk-adverse to a specified event or resilient over a range of events.

Minimization of the root of a quadratic functional under a system of affine equality constraints with application to portfolio management

NASA Astrophysics Data System (ADS)

Landsman, Zinoviy

2008-10-01

We present an explicit closed form solution of the problem of minimizing the root of a quadratic functional subject to a system of affine constraints. The result generalizes Z. Landsman, Minimization of the root of a quadratic functional under an affine equality constraint, J. Comput. Appl. Math. 2007, to appear, see , articles in press, where the optimization problem was solved under only one linear constraint. This is of interest for solving significant problems pertaining to financial economics as well as some classes of feasibility and optimization problems which frequently occur in tomography and other fields. The results are illustrated in the problem of optimal portfolio selection and the particular case when the expected return of finance portfolio is certain is discussed.

Regularizing portfolio optimization

NASA Astrophysics Data System (ADS)

Still, Susanne; Kondor, Imre

2010-07-01

The optimization of large portfolios displays an inherent instability due to estimation error. This poses a fundamental problem, because solutions that are not stable under sample fluctuations may look optimal for a given sample, but are, in effect, very far from optimal with respect to the average risk. In this paper, we approach the problem from the point of view of statistical learning theory. The occurrence of the instability is intimately related to over-fitting, which can be avoided using known regularization methods. We show how regularized portfolio optimization with the expected shortfall as a risk measure is related to support vector regression. The budget constraint dictates a modification. We present the resulting optimization problem and discuss the solution. The L2 norm of the weight vector is used as a regularizer, which corresponds to a diversification 'pressure'. This means that diversification, besides counteracting downward fluctuations in some assets by upward fluctuations in others, is also crucial because it improves the stability of the solution. The approach we provide here allows for the simultaneous treatment of optimization and diversification in one framework that enables the investor to trade off between the two, depending on the size of the available dataset.

Promoting Affordability in Defense Acquisitions: A Multi-Period Portfolio Approach

DTIC Science & Technology

2014-04-30

has evolved out of many areas of research, ranging from economics to modern control theory (Powell, 2011). The general form of a dynamic programming...states 5 School of Aeronautics & Astronautics A Portfolio Approach: Background • Balance expected profit (performance) against risk ( variance ) in...investments (Markowitz 1952) • Efficiency frontier of optimal portfolios given investor risk averseness • Extends to multi-period case with various

Forecasting Optimal Solar Energy Supply in Jiangsu Province (China): A Systematic Approach Using Hybrid of Weather and Energy Forecast Models

PubMed Central

Zhao, Xiuli; Yiranbon, Ethel

2014-01-01

The idea of aggregating information is clearly recognizable in the daily lives of all entities whether as individuals or as a group, since time immemorial corporate organizations, governments, and individuals as economic agents aggregate information to formulate decisions. Energy planning represents an investment-decision problem where information needs to be aggregated from credible sources to predict both demand and supply of energy. To do this there are varying methods ranging from the use of portfolio theory to managing risk and maximizing portfolio performance under a variety of unpredictable economic outcomes. The future demand for energy and need to use solar energy in order to avoid future energy crisis in Jiangsu province in China require energy planners in the province to abandon their reliance on traditional, “least-cost,” and stand-alone technology cost estimates and instead evaluate conventional and renewable energy supply on the basis of a hybrid of optimization models in order to ensure effective and reliable supply. Our task in this research is to propose measures towards addressing optimal solar energy forecasting by employing a systematic optimization approach based on a hybrid of weather and energy forecast models. After giving an overview of the sustainable energy issues in China, we have reviewed and classified the various models that existing studies have used to predict the influences of the weather influences and the output of solar energy production units. Further, we evaluate the performance of an exemplary ensemble model which combines the forecast output of two popular statistical prediction methods using a dynamic weighting factor. PMID:24511292

Forecasting optimal solar energy supply in Jiangsu Province (China): a systematic approach using hybrid of weather and energy forecast models.

PubMed

Zhao, Xiuli; Asante Antwi, Henry; Yiranbon, Ethel

2014-01-01

The idea of aggregating information is clearly recognizable in the daily lives of all entities whether as individuals or as a group, since time immemorial corporate organizations, governments, and individuals as economic agents aggregate information to formulate decisions. Energy planning represents an investment-decision problem where information needs to be aggregated from credible sources to predict both demand and supply of energy. To do this there are varying methods ranging from the use of portfolio theory to managing risk and maximizing portfolio performance under a variety of unpredictable economic outcomes. The future demand for energy and need to use solar energy in order to avoid future energy crisis in Jiangsu province in China require energy planners in the province to abandon their reliance on traditional, "least-cost," and stand-alone technology cost estimates and instead evaluate conventional and renewable energy supply on the basis of a hybrid of optimization models in order to ensure effective and reliable supply. Our task in this research is to propose measures towards addressing optimal solar energy forecasting by employing a systematic optimization approach based on a hybrid of weather and energy forecast models. After giving an overview of the sustainable energy issues in China, we have reviewed and classified the various models that existing studies have used to predict the influences of the weather influences and the output of solar energy production units. Further, we evaluate the performance of an exemplary ensemble model which combines the forecast output of two popular statistical prediction methods using a dynamic weighting factor.

Strategic Technology Investment Analysis: An Integrated System Approach

NASA Technical Reports Server (NTRS)

Adumitroaie, V.; Weisbin, C. R.

2010-01-01

Complex technology investment decisions within NASA are increasingly difficult to make such that the end results are satisfying the technical objectives and all the organizational constraints. Due to a restricted science budget environment and numerous required technology developments, the investment decisions need to take into account not only the functional impact on the program goals, but also development uncertainties and cost variations along with maintaining a healthy workforce. This paper describes an approach for optimizing and qualifying technology investment portfolios from the perspective of an integrated system model. The methodology encompasses multi-attribute decision theory elements and sensitivity analysis. The evaluation of the degree of robustness of the recommended portfolio provides the decision-maker with an array of viable selection alternatives, which take into account input uncertainties and possibly satisfy nontechnical constraints. The methodology is presented in the context of assessing capability development portfolios for NASA technology programs.

SPX: The Tenth International Conference on Stochastic Programming

DTIC Science & Technology

2004-10-01

On structuring energy contract portfolios in competitive markets . Antonio Alonso-Ayuso, Universidad Rey Juan Carlos. (p. 28) 2. Mean-risk optimization ...ThA 8:00-9:30 Ballroom South: Portfolio Optimization Chair: Gerd Infanger, Stanford University 1. The impact of serial correlation of returns on ... the L-shaped method is to approximate the non-linear penalty term in the objective by a linear one . We use the implicit LX

Comparison between goal programming and cointegration approaches in enhanced index tracking

NASA Astrophysics Data System (ADS)

Lam, Weng Siew; Jamaan, Saiful Hafizah Hj.

2013-04-01

Index tracking is a popular form of passive fund management in stock market. Passive management is a buy-and-hold strategy that aims to achieve rate of return similar to the market return. Index tracking problem is a problem of reproducing the performance of a stock market index, without purchasing all of the stocks that make up the index. This can be done by establishing an optimal portfolio that minimizes risk or tracking error. An improved index tracking (enhanced index tracking) is a dual-objective optimization problem, a trade-off between maximizing the mean return and minimizing the tracking error. Enhanced index tracking aims to generate excess return over the return achieved by the index. The objective of this study is to compare the portfolio compositions and performances by using two different approaches in enhanced index tracking problem, which are goal programming and cointegration. The result of this study shows that the optimal portfolios for both approaches are able to outperform the Malaysia market index which is Kuala Lumpur Composite Index. Both approaches give different optimal portfolio compositions. Besides, the cointegration approach outperforms the goal programming approach because the cointegration approach gives higher mean return and lower risk or tracking error. Therefore, the cointegration approach is more appropriate for the investors in Malaysia.

Combining Interactive Infrastructure Modeling and Evolutionary Algorithm Optimization for Sustainable Water Resources Design

NASA Astrophysics Data System (ADS)

Smith, R.; Kasprzyk, J. R.; Zagona, E. A.

2013-12-01

Population growth and climate change, combined with difficulties in building new infrastructure, motivate portfolio-based solutions to ensuring sufficient water supply. Powerful simulation models with graphical user interfaces (GUI) are often used to evaluate infrastructure portfolios; these GUI based models require manual modification of the system parameters, such as reservoir operation rules, water transfer schemes, or system capacities. Multiobjective evolutionary algorithm (MOEA) based optimization can be employed to balance multiple objectives and automatically suggest designs for infrastructure systems, but MOEA based decision support typically uses a fixed problem formulation (i.e., a single set of objectives, decisions, and constraints). This presentation suggests a dynamic framework for linking GUI-based infrastructure models with MOEA search. The framework begins with an initial formulation which is solved using a MOEA. Then, stakeholders can interact with candidate solutions, viewing their properties in the GUI model. This is followed by changes in the formulation which represent users' evolving understanding of exigent system properties. Our case study is built using RiverWare, an object-oriented, data-centered model that facilitates the representation of a diverse array of water resources systems. Results suggest that assumptions within the initial MOEA search are violated after investigating tradeoffs and reveal how formulations should be modified to better capture stakeholders' preferences.

The Effect of Mobile Portfolio (M-Portfolio) Supported Mastery Learning Model on Students' Achievement and Their Attitudes towards Using Internet

ERIC Educational Resources Information Center

Ozdemir, Oguzhan; Erdemci, Husamettin

2017-01-01

The term mobile portfolio refers to creating, evaluating and sharing portfolios in mobile environments. Many of the states that pose an obstacle for portfolio usage are now extinguished through mobile portfolios. The aim in this research is to determine the effect of mobile portfolio supported mastery learning model on students' success and…

Interdicting an Adversary’s Economy Viewed As a Trade Sanction Inoperability Input Output Model

DTIC Science & Technology

2017-03-01

set of sectors. The design of an economic sanction, in the context of this thesis, is the selection of the sector or set of sectors to sanction...We propose two optimization models. The first, the Trade Sanction Inoperability Input-output Model (TS-IIM), selects the sector or set of sectors that...Interdependency analysis: Extensions to demand reduction inoperability input-output modeling and portfolio selection . Unpublished doctoral dissertation

Mean-variance portfolio selection for defined-contribution pension funds with stochastic salary.

PubMed

Zhang, Chubing

2014-01-01

This paper focuses on a continuous-time dynamic mean-variance portfolio selection problem of defined-contribution pension funds with stochastic salary, whose risk comes from both financial market and nonfinancial market. By constructing a special Riccati equation as a continuous (actually a viscosity) solution to the HJB equation, we obtain an explicit closed form solution for the optimal investment portfolio as well as the efficient frontier.

Development of an Electronic Portfolio System Success Model: An Information Systems Approach

ERIC Educational Resources Information Center

Balaban, Igor; Mu, Enrique; Divjak, Blazenka

2013-01-01

This research has two main goals: to develop an instrument for assessing Electronic Portfolio (ePortfolio) success and to build a corresponding ePortfolio success model using DeLone and McLean's information systems success model as the theoretical framework. For this purpose, we developed an ePortfolio success measurement instrument and structural…

Stochastic search, optimization and regression with energy applications

NASA Astrophysics Data System (ADS)

Hannah, Lauren A.

Designing clean energy systems will be an important task over the next few decades. One of the major roadblocks is a lack of mathematical tools to economically evaluate those energy systems. However, solutions to these mathematical problems are also of interest to the operations research and statistical communities in general. This thesis studies three problems that are of interest to the energy community itself or provide support for solution methods: R&D portfolio optimization, nonparametric regression and stochastic search with an observable state variable. First, we consider the one stage R&D portfolio optimization problem to avoid the sequential decision process associated with the multi-stage. The one stage problem is still difficult because of a non-convex, combinatorial decision space and a non-convex objective function. We propose a heuristic solution method that uses marginal project values---which depend on the selected portfolio---to create a linear objective function. In conjunction with the 0-1 decision space, this new problem can be solved as a knapsack linear program. This method scales well to large decision spaces. We also propose an alternate, provably convergent algorithm that does not exploit problem structure. These methods are compared on a solid oxide fuel cell R&D portfolio problem. Next, we propose Dirichlet Process mixtures of Generalized Linear Models (DPGLM), a new method of nonparametric regression that accommodates continuous and categorical inputs, and responses that can be modeled by a generalized linear model. We prove conditions for the asymptotic unbiasedness of the DP-GLM regression mean function estimate. We also give examples for when those conditions hold, including models for compactly supported continuous distributions and a model with continuous covariates and categorical response. We empirically analyze the properties of the DP-GLM and why it provides better results than existing Dirichlet process mixture regression models. We evaluate DP-GLM on several data sets, comparing it to modern methods of nonparametric regression like CART, Bayesian trees and Gaussian processes. Compared to existing techniques, the DP-GLM provides a single model (and corresponding inference algorithms) that performs well in many regression settings. Finally, we study convex stochastic search problems where a noisy objective function value is observed after a decision is made. There are many stochastic search problems whose behavior depends on an exogenous state variable which affects the shape of the objective function. Currently, there is no general purpose algorithm to solve this class of problems. We use nonparametric density estimation to take observations from the joint state-outcome distribution and use them to infer the optimal decision for a given query state. We propose two solution methods that depend on the problem characteristics: function-based and gradient-based optimization. We examine two weighting schemes, kernel-based weights and Dirichlet process-based weights, for use with the solution methods. The weights and solution methods are tested on a synthetic multi-product newsvendor problem and the hour-ahead wind commitment problem. Our results show that in some cases Dirichlet process weights offer substantial benefits over kernel based weights and more generally that nonparametric estimation methods provide good solutions to otherwise intractable problems.

Conservation planning under uncertainty in urban development and vegetation dynamics

PubMed Central

Carmel, Yohay

2018-01-01

Systematic conservation planning is a framework for optimally locating and prioritizing areas for conservation. An often-noted shortcoming of most conservation planning studies is that they do not address future uncertainty. The selection of protected areas that are intended to ensure the long-term persistence of biodiversity is often based on a snapshot of the current situation, ignoring processes such as climate change. Scenarios, in the sense of being accounts of plausible futures, can be utilized to identify conservation area portfolios that are robust to future uncertainty. We compared three approaches for utilizing scenarios in conservation area selection: considering a full set of scenarios (all-scenarios portfolio), assuming the realization of specific scenarios, and a reference strategy based on the current situation (current distributions portfolio). Our objective was to compare the robustness of these approaches in terms of their relative performance across future scenarios. We focused on breeding bird species in Israel’s Mediterranean region. We simulated urban development and vegetation dynamics scenarios 60 years into the future using DINAMICA-EGO, a cellular-automata simulation model. For each scenario, we mapped the target species’ available habitat distribution, identified conservation priority areas using the site-selection software MARXAN, and constructed conservation area portfolios using the three aforementioned strategies. We then assessed portfolio performance based on the number of species for which representation targets were met in each scenario. The all-scenarios portfolio consistently outperformed the other portfolios, and was more robust to ‘errors’ (e.g., when an assumed specific scenario did not occur). On average, the all-scenarios portfolio achieved representation targets for five additional species compared with the current distributions portfolio (approximately 33 versus 28 species). Our findings highlight the importance of considering a broad and meaningful set of scenarios, rather than relying on the current situation, the expected occurrence of specific scenarios, or the worst-case scenario. PMID:29621330

Conservation planning under uncertainty in urban development and vegetation dynamics.

PubMed

Troupin, David; Carmel, Yohay

2018-01-01

Systematic conservation planning is a framework for optimally locating and prioritizing areas for conservation. An often-noted shortcoming of most conservation planning studies is that they do not address future uncertainty. The selection of protected areas that are intended to ensure the long-term persistence of biodiversity is often based on a snapshot of the current situation, ignoring processes such as climate change. Scenarios, in the sense of being accounts of plausible futures, can be utilized to identify conservation area portfolios that are robust to future uncertainty. We compared three approaches for utilizing scenarios in conservation area selection: considering a full set of scenarios (all-scenarios portfolio), assuming the realization of specific scenarios, and a reference strategy based on the current situation (current distributions portfolio). Our objective was to compare the robustness of these approaches in terms of their relative performance across future scenarios. We focused on breeding bird species in Israel's Mediterranean region. We simulated urban development and vegetation dynamics scenarios 60 years into the future using DINAMICA-EGO, a cellular-automata simulation model. For each scenario, we mapped the target species' available habitat distribution, identified conservation priority areas using the site-selection software MARXAN, and constructed conservation area portfolios using the three aforementioned strategies. We then assessed portfolio performance based on the number of species for which representation targets were met in each scenario. The all-scenarios portfolio consistently outperformed the other portfolios, and was more robust to 'errors' (e.g., when an assumed specific scenario did not occur). On average, the all-scenarios portfolio achieved representation targets for five additional species compared with the current distributions portfolio (approximately 33 versus 28 species). Our findings highlight the importance of considering a broad and meaningful set of scenarios, rather than relying on the current situation, the expected occurrence of specific scenarios, or the worst-case scenario.

Mean-Variance Portfolio Selection for Defined-Contribution Pension Funds with Stochastic Salary

PubMed Central

Zhang, Chubing

2014-01-01

This paper focuses on a continuous-time dynamic mean-variance portfolio selection problem of defined-contribution pension funds with stochastic salary, whose risk comes from both financial market and nonfinancial market. By constructing a special Riccati equation as a continuous (actually a viscosity) solution to the HJB equation, we obtain an explicit closed form solution for the optimal investment portfolio as well as the efficient frontier. PMID:24782667

Toward Affordable Systems III: Portfolio Management for Army Engineering and Manufacturing Development Programs

DTIC Science & Technology

2012-02-01

a public service of the RAND Corporation. CHILDREN AND FAMILIES EDUCATION AND THE ARTS ENERGY AND ENVIRONMENT HEALTH AND HEALTH CARE INFRASTRUCTURE...agencies use capability portfolio management to optimize capa- bility investments and minimize risk in meeting the DoD needs across the defense...broadly expose potential problem areas—that is, which requirements (or areas of demand) are at risk of not being met by that particular portfolio

Dimensions of design space: a decision-theoretic approach to optimal research design.

PubMed

Conti, Stefano; Claxton, Karl

2009-01-01

Bayesian decision theory can be used not only to establish the optimal sample size and its allocation in a single clinical study but also to identify an optimal portfolio of research combining different types of study design. Within a single study, the highest societal payoff to proposed research is achieved when its sample sizes and allocation between available treatment options are chosen to maximize the expected net benefit of sampling (ENBS). Where a number of different types of study informing different parameters in the decision problem could be conducted, the simultaneous estimation of ENBS across all dimensions of the design space is required to identify the optimal sample sizes and allocations within such a research portfolio. This is illustrated through a simple example of a decision model of zanamivir for the treatment of influenza. The possible study designs include: 1) a single trial of all the parameters, 2) a clinical trial providing evidence only on clinical endpoints, 3) an epidemiological study of natural history of disease, and 4) a survey of quality of life. The possible combinations, samples sizes, and allocation between trial arms are evaluated over a range of cost-effectiveness thresholds. The computational challenges are addressed by implementing optimization algorithms to search the ENBS surface more efficiently over such large dimensions.

Investment portfolio of a pension fund: Stochastic model

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

Bosch-Princep, M.; Fontanals-Albiol, H.

1994-12-31

This paper presents a stochastic programming model that aims at getting the optimal investment portfolio of a Pension Funds. The model has been designed bearing in mind the liabilities of the Funds to its members. The essential characteristic of the objective function and the constraints is the randomness of the coefficients and the right hand side of the constraints, so it`s necessary to use techniques of stochastic mathematical programming to get information about the amount of money that should be assigned to each sort of investment. It`s important to know the risky attitude of the person that has to takemore » decisions towards running risks. It incorporates the relation between the different coefficients of the objective function and constraints of each period of temporal horizon, through lineal and discrete random processes. Likewise, it includes the hypotheses that are related to Spanish law concerning the subject of Pension Funds.« less

Formulation and demonstration of a robust mean variance optimization approach for concurrent airline network and aircraft design

NASA Astrophysics Data System (ADS)

Davendralingam, Navindran

Conceptual design of aircraft and the airline network (routes) on which aircraft fly on are inextricably linked to passenger driven demand. Many factors influence passenger demand for various Origin-Destination (O-D) city pairs including demographics, geographic location, seasonality, socio-economic factors and naturally, the operations of directly competing airlines. The expansion of airline operations involves the identificaion of appropriate aircraft to meet projected future demand. The decisions made in incorporating and subsequently allocating these new aircraft to serve air travel demand affects the inherent risk and profit potential as predicted through the airline revenue management systems. Competition between airlines then translates to latent passenger observations of the routes served between OD pairs and ticket pricing---this in effect reflexively drives future states of demand. This thesis addresses the integrated nature of aircraft design, airline operations and passenger demand, in order to maximize future expected profits as new aircraft are brought into service. The goal of this research is to develop an approach that utilizes aircraft design, airline network design and passenger demand as a unified framework to provide better integrated design solutions in order to maximize expexted profits of an airline. This is investigated through two approaches. The first is a static model that poses the concurrent engineering paradigm above as an investment portfolio problem. Modern financial portfolio optimization techniques are used to leverage risk of serving future projected demand using a 'yet to be introduced' aircraft against potentially generated future profits. Robust optimization methodologies are incorporated to mitigate model sensitivity and address estimation risks associated with such optimization techniques. The second extends the portfolio approach to include dynamic effects of an airline's operations. A dynamic programming approach is employed to simulate the reflexive nature of airline supply-demand interactions by modeling the aggregate changes in demand that would result from tactical allocations of aircraft to maximize profit. The best yet-to-be-introduced aircraft maximizes profit by minimizing the long term fleetwide direct operating costs.

Real-world datasets for portfolio selection and solutions of some stochastic dominance portfolio models.

PubMed

Bruni, Renato; Cesarone, Francesco; Scozzari, Andrea; Tardella, Fabio

2016-09-01

A large number of portfolio selection models have appeared in the literature since the pioneering work of Markowitz. However, even when computational and empirical results are described, they are often hard to replicate and compare due to the unavailability of the datasets used in the experiments. We provide here several datasets for portfolio selection generated using real-world price values from several major stock markets. The datasets contain weekly return values, adjusted for dividends and for stock splits, which are cleaned from errors as much as possible. The datasets are available in different formats, and can be used as benchmarks for testing the performances of portfolio selection models and for comparing the efficiency of the algorithms used to solve them. We also provide, for these datasets, the portfolios obtained by several selection strategies based on Stochastic Dominance models (see "On Exact and Approximate Stochastic Dominance Strategies for Portfolio Selection" (Bruni et al. [2])). We believe that testing portfolio models on publicly available datasets greatly simplifies the comparison of the different portfolio selection strategies.

A Study on the Optimal Generation Mix Based on Portfolio Theory with Considering the Basic Condition for Power Supply

NASA Astrophysics Data System (ADS)

Kato, Moritoshi; Zhou, Yicheng

This paper presents a novel method to analyze the optimal generation mix based on portfolio theory with considering the basic condition for power supply, which means that electricity generation corresponds with load curve. The optimization of portfolio is integrated with the calculation of a capacity factor of each generation in order to satisfy the basic condition for power supply. Besides, each generation is considered to be an asset, and risks of the generation asset both in its operation period and construction period are considered. Environmental measures are evaluated through restriction of CO2 emissions, which are indicated by CO2 price. Numerical examples show the optimal generation mix according to risks such as the deviation of capacity factor of nuclear power or restriction of CO2 emissions, the possibility of introduction of clean coal technology (IGCC, CCS) or renewable energy, and so on. The results of this work will be possibly applied as setting the target of the generation mix for the future according to prospects of risks of each generation and restrictions of CO2 emissions.

Mitigation and adaptation within a climate change policy portfolio: A research program

EPA Science Inventory

It is now recognized that optimal global climate policy is a portfolio of the two key responses for reducing the risks of climate change: mitigation and adaptation. Significant differences between the two responses have inhibited understanding of how to appropriately view these...

Analytic solution to variance optimization with no short positions

NASA Astrophysics Data System (ADS)

Kondor, Imre; Papp, Gábor; Caccioli, Fabio

2017-12-01

We consider the variance portfolio optimization problem with a ban on short selling. We provide an analytical solution by means of the replica method for the case of a portfolio of independent, but not identically distributed, assets. We study the behavior of the solution as a function of the ratio r between the number N of assets and the length T of the time series of returns used to estimate risk. The no-short-selling constraint acts as an asymmetric \

The returns and risks of investment portfolio in a financial market

NASA Astrophysics Data System (ADS)

Li, Jiang-Cheng; Mei, Dong-Cheng

2014-07-01

The returns and risks of investment portfolio in a financial system was investigated by constructing a theoretical model based on the Heston model. After the theoretical model and analysis of portfolio were calculated and analyzed, we find the following: (i) The statistical properties (i.e., the probability distribution, the variance and loss rate of equity portfolio return) between simulation results of the theoretical model and the real financial data obtained from Dow Jones Industrial Average are in good agreement; (ii) The maximum dispersion of the investment portfolio is associated with the maximum stability of the equity portfolio return and minimal investment risks; (iii) An increase of the investment period and a worst investment period are associated with a decrease of stability of the equity portfolio return and a maximum investment risk, respectively.

Learning portfolio models in health regulatory colleges of Ontario, Canada.

PubMed

Tompkins, Marianne; Paquette-Frenette, Denise

2010-01-01

Health regulatory colleges promote continued competence by requiring members to submit yearly portfolios that document learning. Previous studies conclude that portfolios can be valuable tools to promote continuous learning in health college members, but portfolios are time-consuming to complete and difficult to evaluate. This exploratory study compares the features of portfolio models in regulatory colleges, as a basis for future studies. Data were collected through a document review of the portfolio models described on the Web sites of 14 Canadian health regulatory colleges. All models contain 3 common components of self-directed learning: (1) self-diagnosis, (2) learning plan and activities, and (3) self-evaluation. Several include member profiles and peer feedback. A broad range of formal, nonformal, and informal activities are accepted as evidence of learning; a few colleges restrict learners' freedom in selecting these activities. There is a dual philosophy of learning in portfolio models that includes both humanist and technical paradigms. Low numbers of members are selected for audit of completed portfolios. The possibility of last-minute preparation and the lack of support to members who struggle with self-directed learning methods are issues to be resolved. Although portfolios are designed to enhance learning and reflection, quality cannot be ensured unless compliance is enforced, and learning outcomes are measured. Professionals should be guided regarding how to complete portfolios. More health regulatory colleges should announce the number of portfolios they audit. In general, the number of portfolios audited by each profession may need to be increased.

Asset Attribution Stability and Portfolio Construction: An Educational Example

ERIC Educational Resources Information Center

Chong, James T.; Jennings, William P.; Phillips, G. Michael

2014-01-01

This paper illustrates how a third statistic from asset pricing models, the R-squared statistic, may have information that can help in portfolio construction. Using a traditional CAPM model in comparison to an 18-factor Arbitrage Pricing Style Model, a portfolio separation test is conducted. Portfolio returns and risk metrics are compared using…

Optimization principles and the figure of merit for triboelectric generators.

PubMed

Peng, Jun; Kang, Stephen Dongmin; Snyder, G Jeffrey

2017-12-01

Energy harvesting with triboelectric nanogenerators is a burgeoning field, with a growing portfolio of creative application schemes attracting much interest. Although power generation capabilities and its optimization are one of the most important subjects, a satisfactory elemental model that illustrates the basic principles and sets the optimization guideline remains elusive. We use a simple model to clarify how the energy generation mechanism is electrostatic induction but with a time-varying character that makes the optimal matching for power generation more restrictive. By combining multiple parameters into dimensionless variables, we pinpoint the optimum condition with only two independent parameters, leading to predictions of the maximum limit of power density, which allows us to derive the triboelectric material and device figure of merit. We reveal the importance of optimizing device capacitance, not only load resistance, and minimizing the impact of parasitic capacitance. Optimized capacitances can lead to an overall increase in power density of more than 10 times.

An inequality for detecting financial fraud, derived from the Markowitz Optimal Portfolio Theory

NASA Astrophysics Data System (ADS)

Bard, Gregory V.

2016-12-01

The Markowitz Optimal Portfolio Theory, published in 1952, is well-known, and was often taught because it blends Lagrange Multipliers, matrices, statistics, and mathematical finance. However, the theory faded from prominence in American investing, as Business departments at US universities shifted from techniques based on mathematics, finance, and statistics, to focus instead on leadership, public speaking, interpersonal skills, advertising, etc… The author proposes a new application of Markowitz's Theory: the detection of a fairly broad category of financial fraud (called "Ponzi schemes" in American newspapers) by looking at a particular inequality derived from the Markowitz Optimal Portfolio Theory, relating volatility and expected rate of return. For example, one recent Ponzi scheme was that of Bernard Madoff, uncovered in December 2008, which comprised fraud totaling 64,800,000,000 US dollars [23]. The objective is to compare investments with the "efficient frontier" as predicted by Markowitz's theory. Violations of the inequality should be impossible in theory; therefore, in practice, violations might indicate fraud.

Self-Averaging Property of Minimal Investment Risk of Mean-Variance Model.

PubMed

Shinzato, Takashi

2015-01-01

In portfolio optimization problems, the minimum expected investment risk is not always smaller than the expected minimal investment risk. That is, using a well-known approach from operations research, it is possible to derive a strategy that minimizes the expected investment risk, but this strategy does not always result in the best rate of return on assets. Prior to making investment decisions, it is important to an investor to know the potential minimal investment risk (or the expected minimal investment risk) and to determine the strategy that will maximize the return on assets. We use the self-averaging property to analyze the potential minimal investment risk and the concentrated investment level for the strategy that gives the best rate of return. We compare the results from our method with the results obtained by the operations research approach and with those obtained by a numerical simulation using the optimal portfolio. The results of our method and the numerical simulation are in agreement, but they differ from that of the operations research approach.

Minimizing the regrets of long-term urban floodplain management decisions under deeply uncertain climate change

NASA Astrophysics Data System (ADS)

Hecht, J. S.; Kirshen, P. H.; Vogel, R. M.

2016-12-01

Making long-term floodplain management decisions under uncertain climate change is a major urban planning challenge of the 21stcentury. To support these efforts, we introduce a screening-level optimization model that identifies adaptation portfolios by minimizing the regrets associated with their flood-control and damage costs under different climate change trajectories that are deeply uncertain, i.e. have probabilities that cannot be specified plausibly. This mixed integer program explicitly considers the coupled damage-reduction impacts of different floodwall designs and property-scale investments (first-floor elevation, wet floodproofing of basements, permanent retreat and insurance), recommends implementation schedules, and assesses impacts to stakeholders residing in three types of homes. An application to a stylized municipality illuminates many nonlinear system dynamics stemming from large fixed capital costs, infrastructure design thresholds, and discharge-depth-damage relationships. If stakeholders tolerate mild damage, floodwalls that fully protect a community from large design events are less cost-effective than portfolios featuring both smaller floodwalls and property-scale measures. Potential losses of property tax revenue from permanent retreat motivate municipal property-tax initiatives for adaptation financing. Yet, insurance incentives for first-floor elevation may discourage locally financed floodwalls, in turn making lower-income residents more vulnerable to severe flooding. A budget constraint analysis underscores the benefits of flexible floodwall designs with low incremental expansion costs while near-optimal solutions demonstrate the scheduling flexibility of many property-scale measures. Finally, an equity analysis shows the importance of evaluating the overpayment and under-design regrets of recommended adaptation portfolios for each stakeholder and contrasts them to single-scenario model results.

The role of CSP in the electricity system of South Africa - technical operation, grid constraints, market structure and economics

NASA Astrophysics Data System (ADS)

Kost, Christoph; Friebertshäuser, Chris; Hartmann, Niklas; Fluri, Thomas; Nitz, Peter

2017-06-01

This paper analyses the role of solar technologies (CSP and PV) and their interaction in the South African electricity system by using a fundamental electricity system modelling (ENTIGRIS-SouthAfrica). The model is used to analyse the South African long-term electricity generation portfolio mix, optimized site selection and required transmission capacities until the year 2050. Hereby especially the location and grid integration of solar technology (PV and CSP) and wind power plants is analysed. This analysis is carried out by using detailed resource assessment of both technologies. A cluster approach is presented to reduce complexity by integrating the data in an optimization model.

A class of multi-period semi-variance portfolio for petroleum exploration and development

NASA Astrophysics Data System (ADS)

Guo, Qiulin; Li, Jianzhong; Zou, Caineng; Guo, Yujuan; Yan, Wei

2012-10-01

Variance is substituted by semi-variance in Markowitz's portfolio selection model. For dynamic valuation on exploration and development projects, one period portfolio selection is extended to multi-period. In this article, a class of multi-period semi-variance exploration and development portfolio model is formulated originally. Besides, a hybrid genetic algorithm, which makes use of the position displacement strategy of the particle swarm optimiser as a mutation operation, is applied to solve the multi-period semi-variance model. For this class of portfolio model, numerical results show that the mode is effective and feasible.

Integrated wetland management for waterfowl and shorebirds at Mattamuskeet National Wildlife Refuge, North Carolina

USGS Publications Warehouse

Tavernia, Brian G.; Stanton, John D.; Lyons, James E.

2017-11-22

Mattamuskeet National Wildlife Refuge (MNWR) offers a mix of open water, marsh, forest, and cropland habitats on 20,307 hectares in coastal North Carolina. In 1934, Federal legislation (Executive Order 6924) established MNWR to benefit wintering waterfowl and other migratory bird species. On an annual basis, the refuge staff decide how to manage 14 impoundments to benefit not only waterfowl during the nonbreeding season, but also shorebirds during fall and spring migration. In making these decisions, the challenge is to select a portfolio, or collection, of management actions for the impoundments that optimizes use by the three groups of birds while respecting budget constraints. In this study, a decision support tool was developed for these annual management decisions.Within the decision framework, there are three different management objectives: shorebird-use days during fall and spring migrations, and waterfowl-use days during the nonbreeding season. Sixteen potential management actions were identified for impoundments; each action represents a combination of hydroperiod and vegetation manipulation. Example hydroperiods include semi-permanent and seasonal drawdowns, and vegetation manipulations include mechanical-chemical treatment, burning, disking, and no action. Expert elicitation was used to build a Bayesian Belief Network (BBN) model that predicts shorebird- and waterfowl-use days for each potential management action. The BBN was parameterized for a representative impoundment, MI-9, and predictions were re-scaled for this impoundment to predict outcomes at other impoundments on the basis of size. Parameter estimates in the BBN model can be updated using observations from ongoing monitoring that is part of the Integrated Waterbird Management and Monitoring (IWMM) program.The optimal portfolio of management actions depends on the importance, that is, weights, assigned to the three objectives, as well as the budget. Five scenarios with a variety of objective weights and budgets were developed. Given the large number of possible portfolios (1614), a heuristic genetic algorithm was used to identify a management action portfolio that maximized use-day objectives while respecting budget constraints. The genetic algorithm identified a portfolio of management actions for each of the five scenarios, enabling refuge staff to explore the sensitivity of their management decisions to objective weights and budget constraints.The decision framework developed here provides a transparent, defensible, and testable foundation for decision making at MNWR. The BBN model explicitly structures and parameterizes a mental model previously used by an expert to assign management actions to the impoundments. With ongoing IWMM monitoring, predictions from the model can be tested, and model parameters updated, to reflect empirical observations. This framework is intended to be a living document that can be updated to reflect changes in the decision context (for example, new objectives or constraints, or new models to compete with the current BBN model). Rather than a mandate to refuge staff, this framework is intended to be a decision support tool; tool outputs can become part of the deliberations of refuge staff when making difficult management decisions for multiple objectives.

Risk-aware multi-armed bandit problem with application to portfolio selection

PubMed Central

Huo, Xiaoguang

2017-01-01

Sequential portfolio selection has attracted increasing interest in the machine learning and quantitative finance communities in recent years. As a mathematical framework for reinforcement learning policies, the stochastic multi-armed bandit problem addresses the primary difficulty in sequential decision-making under uncertainty, namely the exploration versus exploitation dilemma, and therefore provides a natural connection to portfolio selection. In this paper, we incorporate risk awareness into the classic multi-armed bandit setting and introduce an algorithm to construct portfolio. Through filtering assets based on the topological structure of the financial market and combining the optimal multi-armed bandit policy with the minimization of a coherent risk measure, we achieve a balance between risk and return. PMID:29291122

Risk-aware multi-armed bandit problem with application to portfolio selection.

PubMed

Huo, Xiaoguang; Fu, Feng

2017-11-01

Sequential portfolio selection has attracted increasing interest in the machine learning and quantitative finance communities in recent years. As a mathematical framework for reinforcement learning policies, the stochastic multi-armed bandit problem addresses the primary difficulty in sequential decision-making under uncertainty, namely the exploration versus exploitation dilemma, and therefore provides a natural connection to portfolio selection. In this paper, we incorporate risk awareness into the classic multi-armed bandit setting and introduce an algorithm to construct portfolio. Through filtering assets based on the topological structure of the financial market and combining the optimal multi-armed bandit policy with the minimization of a coherent risk measure, we achieve a balance between risk and return.

Coupling long and short term decisions in the design of urban water supply infrastructure for added reliability and flexibility

NASA Astrophysics Data System (ADS)

Marques, G.; Fraga, C. C. S.; Medellin-Azuara, J.

2016-12-01

The expansion and operation of urban water supply systems under growing demands, hydrologic uncertainty and water scarcity requires a strategic combination of supply sources for reliability, reduced costs and improved operational flexibility. The design and operation of such portfolio of water supply sources involves integration of long and short term planning to determine what and when to expand, and how much to use of each supply source accounting for interest rates, economies of scale and hydrologic variability. This research presents an integrated methodology coupling dynamic programming optimization with quadratic programming to optimize the expansion (long term) and operations (short term) of multiple water supply alternatives. Lagrange Multipliers produced by the short-term model provide a signal about the marginal opportunity cost of expansion to the long-term model, in an iterative procedure. A simulation model hosts the water supply infrastructure and hydrologic conditions. Results allow (a) identification of trade offs between cost and reliability of different expansion paths and water use decisions; (b) evaluation of water transfers between urban supply systems; and (c) evaluation of potential gains by reducing water system losses as a portfolio component. The latter is critical in several developing countries where water supply system losses are high and often neglected in favor of more system expansion.

Linking Portfolio Development to Clinical Supervision: A Case Study.

ERIC Educational Resources Information Center

Zepeda, Sally J.

2002-01-01

Describes a model for portfolio supervision based on the results of a 2-year study of one elementary school's experience in implementing portfolio supervision. Includes four propositions that guided the development of the model. Describes the skills inherent in portfolio supervision. Provides general guidelines for implementation of the portfolio…

Roy's safety-first portfolio principle in financial risk management of disastrous events.

PubMed

Chiu, Mei Choi; Wong, Hoi Ying; Li, Duan

2012-11-01

Roy pioneers the concept and practice of risk management of disastrous events via his safety-first principle for portfolio selection. More specifically, his safety-first principle advocates an optimal portfolio strategy generated from minimizing the disaster probability, while subject to the budget constraint and the mean constraint that the expected final wealth is not less than a preselected disaster level. This article studies the dynamic safety-first principle in continuous time and its application in asset and liability management. We reveal that the distortion resulting from dropping the mean constraint, as a common practice to approximate the original Roy's setting, either leads to a trivial case or changes the problem nature completely to a target-reaching problem, which produces a highly leveraged trading strategy. Recognizing the ill-posed nature of the corresponding Lagrangian method when retaining the mean constraint, we invoke a wisdom observed from a limited funding-level regulation of pension funds and modify the original safety-first formulation accordingly by imposing an upper bound on the funding level. This model revision enables us to solve completely the safety-first asset-liability problem by a martingale approach and to derive an optimal policy that follows faithfully the spirit of the safety-first principle and demonstrates a prominent nature of fighting for the best and preventing disaster from happening. © 2012 Society for Risk Analysis.

On portfolio risk diversification

NASA Astrophysics Data System (ADS)

Takada, Hellinton H.; Stern, Julio M.

2017-06-01

The first portfolio risk diversification strategy was put into practice by the All Weather fund in 1996. The idea of risk diversification is related to the risk contribution of each available asset class or investment factor to the total portfolio risk. The maximum diversification or the risk parity allocation is achieved when the set of risk contributions is given by a uniform distribution. Meucci (2009) introduced the maximization of the Rényi entropy as part of a leverage constrained optimization problem to achieve such diversified risk contributions when dealing with uncorrelated investment factors. A generalization of the risk parity is the risk budgeting when there is a prior for the distribution of the risk contributions. Our contribution is the generalization of the existent optimization frameworks to be able to solve the risk budgeting problem. In addition, our framework does not possess any leverage constraint.

Replica approach to mean-variance portfolio optimization

NASA Astrophysics Data System (ADS)

Varga-Haszonits, Istvan; Caccioli, Fabio; Kondor, Imre

2016-12-01

We consider the problem of mean-variance portfolio optimization for a generic covariance matrix subject to the budget constraint and the constraint for the expected return, with the application of the replica method borrowed from the statistical physics of disordered systems. We find that the replica symmetry of the solution does not need to be assumed, but emerges as the unique solution of the optimization problem. We also check the stability of this solution and find that the eigenvalues of the Hessian are positive for r  =  N/T  <  1, where N is the dimension of the portfolio and T the length of the time series used to estimate the covariance matrix. At the critical point r  =  1 a phase transition is taking place. The out of sample estimation error blows up at this point as 1/(1  -  r), independently of the covariance matrix or the expected return, displaying the universality not only of the critical exponent, but also the critical point. As a conspicuous illustration of the dangers of in-sample estimates, the optimal in-sample variance is found to vanish at the critical point inversely proportional to the divergent estimation error.

The Heterogeneous Investment Horizon and Dynamic Strategies for Asset Allocation

NASA Astrophysics Data System (ADS)

Xiong, Heping; Xu, Yiheng; Xiao, Yi

This paper discusses the influence of the portfolio rebalancing strategy on the efficiency of long-term investment portfolios under the assumption of independent stationary distribution of returns. By comparing the efficient sets of the stochastic rebalancing strategy, the simple rebalancing strategy and the buy-and-hold strategy with specific data examples, we find that the stochastic rebalancing strategy is optimal, while the simple rebalancing strategy is of the lowest efficiency. In addition, the simple rebalancing strategy lowers the efficiency of the portfolio instead of improving it.

A study of correlations in the stock market

NASA Astrophysics Data System (ADS)

Sharma, Chandradew; Banerjee, Kinjal

2015-08-01

We study the various sectors of the Bombay Stock Exchange (BSE) for a period of 8 years from April 2006 to March 2014. Using the data of daily returns of a period of eight years we make a direct model free analysis of the pattern of the sectorial indices movement and the correlations among them. Our analysis shows significant auto correlation among the individual sectors and also strong cross-correlation among sectors. We also find that auto correlations in some of the sectors persist in time. This is a very significant result and has not been reported so far in Indian context. These findings will be very useful in model building for prediction of price movement of equities, derivatives and portfolio management. We show that the Random Walk Hypothesis is not applicable in modeling the Indian market and mean-variance-skewness-kurtosis based portfolio optimization might be required. We also find that almost all sectors are highly correlated during large fluctuation periods and have only moderate correlation during normal periods.

Three essays on multi-level optimization models and applications

NASA Astrophysics Data System (ADS)

Rahdar, Mohammad

The general form of a multi-level mathematical programming problem is a set of nested optimization problems, in which each level controls a series of decision variables independently. However, the value of decision variables may also impact the objective function of other levels. A two-level model is called a bilevel model and can be considered as a Stackelberg game with a leader and a follower. The leader anticipates the response of the follower and optimizes its objective function, and then the follower reacts to the leader's action. The multi-level decision-making model has many real-world applications such as government decisions, energy policies, market economy, network design, etc. However, there is a lack of capable algorithms to solve medium and large scale these types of problems. The dissertation is devoted to both theoretical research and applications of multi-level mathematical programming models, which consists of three parts, each in a paper format. The first part studies the renewable energy portfolio under two major renewable energy policies. The potential competition for biomass for the growth of the renewable energy portfolio in the United States and other interactions between two policies over the next twenty years are investigated. This problem mainly has two levels of decision makers: the government/policy makers and biofuel producers/electricity generators/farmers. We focus on the lower-level problem to predict the amount of capacity expansions, fuel production, and power generation. In the second part, we address uncertainty over demand and lead time in a multi-stage mathematical programming problem. We propose a two-stage tri-level optimization model in the concept of rolling horizon approach to reducing the dimensionality of the multi-stage problem. In the third part of the dissertation, we introduce a new branch and bound algorithm to solve bilevel linear programming problems. The total time is reduced by solving a smaller relaxation problem in each node and decreasing the number of iterations. Computational experiments show that the proposed algorithm is faster than the existing ones.

Renewable Energy Resources Portfolio Optimization in the Presence of Demand Response

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

Behboodi, Sahand; Chassin, David P.; Crawford, Curran

In this paper we introduce a simple cost model of renewable integration and demand response that can be used to determine the optimal mix of generation and demand response resources. The model includes production cost, demand elasticity, uncertainty costs, capacity expansion costs, retirement and mothballing costs, and wind variability impacts to determine the hourly cost and revenue of electricity delivery. The model is tested on the 2024 planning case for British Columbia and we find that cost is minimized with about 31% renewable generation. We also find that demand responsive does not have a significant impact on cost at themore » hourly level. The results suggest that the optimal level of renewable resource is not sensitive to a carbon tax or demand elasticity, but it is highly sensitive to the renewable resource installation cost.« less

The q-dependent detrended cross-correlation analysis of stock market

NASA Astrophysics Data System (ADS)

Zhao, Longfeng; Li, Wei; Fenu, Andrea; Podobnik, Boris; Wang, Yougui; Stanley, H. Eugene

2018-02-01

Properties of the q-dependent cross-correlation matrices of the stock market have been analyzed by using random matrix theory and complex networks. The correlation structures of the fluctuations at different magnitudes have unique properties. The cross-correlations among small fluctuations are much stronger than those among large fluctuations. The large and small fluctuations are dominated by different groups of stocks. We use complex network representation to study these q-dependent matrices and discover some new identities. By utilizing those q-dependent correlation-based networks, we are able to construct some portfolios of those more independent stocks which consistently perform better. The optimal multifractal order for portfolio optimization is around q  =  2 under the mean-variance portfolio framework, and q\\in[2, 6] under the expected shortfall criterion. These results have deepened our understanding regarding the collective behavior of the complex financial system.

Risk and utility in portfolio optimization

NASA Astrophysics Data System (ADS)

Cohen, Morrel H.; Natoli, Vincent D.

2003-06-01

Modern portfolio theory (MPT) addresses the problem of determining the optimum allocation of investment resources among a set of candidate assets. In the original mean-variance approach of Markowitz, volatility is taken as a proxy for risk, conflating uncertainty with risk. There have been many subsequent attempts to alleviate that weakness which, typically, combine utility and risk. We present here a modification of MPT based on the inclusion of separate risk and utility criteria. We define risk as the probability of failure to meet a pre-established investment goal. We define utility as the expectation of a utility function with positive and decreasing marginal value as a function of yield. The emphasis throughout is on long investment horizons for which risk-free assets do not exist. Analytic results are presented for a Gaussian probability distribution. Risk-utility relations are explored via empirical stock-price data, and an illustrative portfolio is optimized using the empirical data.

Two-faced property of a market factor in asset pricing and diversification effect

NASA Astrophysics Data System (ADS)

Eom, Cheoljun

2017-04-01

This study empirically investigates the test hypothesis that a market factor acting as a representative common factor in the pricing models has a negative influence on constructing a well-diversified portfolio from the Markowitz mean-variance optimization function (MVOF). We use the comparative correlation matrix (C-CM) method to control a single eigenvalue among all eigenvalues included in the sample correlation matrix (S-CM), through the random matrix theory (RMT). In particular, this study observes the effect of the largest eigenvalue that has the property of the market factor. According to the results, the largest eigenvalue has the highest explanatory power on the stock return changes. The C-CM without the largest eigenvalue in the S-CM constructs a more diversified portfolio capable of improving the practical applicability of the MVOF. Moreover, the more diversified portfolio constructed from this C-CM has better out-of-sample performance in the future period. These results support the test hypothesis for the two-faced property of the market factor, defined by the largest eigenvalue.

Portable parallel portfolio optimization in the Aurora Financial Management System

NASA Astrophysics Data System (ADS)

Laure, Erwin; Moritsch, Hans

2001-07-01

Financial planning problems are formulated as large scale, stochastic, multiperiod, tree structured optimization problems. An efficient technique for solving this kind of problems is the nested Benders decomposition method. In this paper we present a parallel, portable, asynchronous implementation of this technique. To achieve our portability goals we elected the programming language Java for our implementation and used a high level Java based framework, called OpusJava, for expressing the parallelism potential as well as synchronization constraints. Our implementation is embedded within a modular decision support tool for portfolio and asset liability management, the Aurora Financial Management System.

Decision-making in product portfolios of pharmaceutical research and development – managing streams of innovation in highly regulated markets

PubMed Central

Jekunen, Antti

2014-01-01

Decision-making is a core function of any drug development firm. Developing drugs demands a firm to be highly innovative, while at the same time the activity is strictly regulated. Successful drug development offers the right to apply for a long-term patent that confers exclusive marketing rights. This article addresses the issue of what constitutes an adequate portfolio of drugs for a drug development firm and how it might be managed successfully. The paper investigates decision-making in the industry and specifically in the development of oncology drugs from various perspectives: the need for decisions, their timing, decision-making at the project level, the optimal portfolio, tools for portfolio analysis, the evaluation of patents, and finally the importance of the drug portfolio. Drug development decisions as important organizational elements should get more emphasis, and decisions in drug portfolio using modern decision-making methods should be used more widely than what currently happens. Structured, informed decisions would help avoiding late terminations of drugs in Phase III development. An improved research and development pipeline and drug portfolio management are the major elements in the general strategy targeting success. PMID:25364229

Decision-making in product portfolios of pharmaceutical research and development--managing streams of innovation in highly regulated markets.

PubMed

Jekunen, Antti

2014-01-01

Decision-making is a core function of any drug development firm. Developing drugs demands a firm to be highly innovative, while at the same time the activity is strictly regulated. Successful drug development offers the right to apply for a long-term patent that confers exclusive marketing rights. This article addresses the issue of what constitutes an adequate portfolio of drugs for a drug development firm and how it might be managed successfully. The paper investigates decision-making in the industry and specifically in the development of oncology drugs from various perspectives: the need for decisions, their timing, decision-making at the project level, the optimal portfolio, tools for portfolio analysis, the evaluation of patents, and finally the importance of the drug portfolio. Drug development decisions as important organizational elements should get more emphasis, and decisions in drug portfolio using modern decision-making methods should be used more widely than what currently happens. Structured, informed decisions would help avoiding late terminations of drugs in Phase III development. An improved research and development pipeline and drug portfolio management are the major elements in the general strategy targeting success.

Fuzzy portfolio model with fuzzy-input return rates and fuzzy-output proportions

NASA Astrophysics Data System (ADS)

Tsaur, Ruey-Chyn

2015-02-01

In the finance market, a short-term investment strategy is usually applied in portfolio selection in order to reduce investment risk; however, the economy is uncertain and the investment period is short. Further, an investor has incomplete information for selecting a portfolio with crisp proportions for each chosen security. In this paper we present a new method of constructing fuzzy portfolio model for the parameters of fuzzy-input return rates and fuzzy-output proportions, based on possibilistic mean-standard deviation models. Furthermore, we consider both excess or shortage of investment in different economic periods by using fuzzy constraint for the sum of the fuzzy proportions, and we also refer to risks of securities investment and vagueness of incomplete information during the period of depression economics for the portfolio selection. Finally, we present a numerical example of a portfolio selection problem to illustrate the proposed model and a sensitivity analysis is realised based on the results.

Postoptimality Analysis in the Selection of Technology Portfolios

NASA Technical Reports Server (NTRS)

Adumitroaie, Virgil; Shelton, Kacie; Elfes, Alberto; Weisbin, Charles R.

2006-01-01

This slide presentation reviews a process of postoptimally analysing the selection of technology portfolios. The rationale for the analysis stems from the need for consistent, transparent and auditable decision making processes and tools. The methodology is used to assure that project investments are selected through an optimization of net mission value. The main intent of the analysis is to gauge the degree of confidence in the optimal solution and to provide the decision maker with an array of viable selection alternatives which take into account input uncertainties and possibly satisfy non-technical constraints. A few examples of the analysis are reviewed. The goal of the postoptimality study is to enhance and improve the decision-making process by providing additional qualifications and substitutes to the optimal solution.

Optimizing Eco-Efficiency Across the Procurement Portfolio.

PubMed

Pelton, Rylie E O; Li, Mo; Smith, Timothy M; Lyon, Thomas P

2016-06-07

Manufacturing organizations' environmental impacts are often attributable to processes in the firm's upstream supply chain. Environmentally preferable procurement (EPP) and the establishment of environmental purchasing criteria can potentially reduce these indirect impacts. Life-cycle assessment (LCA) can help identify the purchasing criteria that are most effective in reducing environmental impacts. However, the high costs of LCA and the problems associated with the comparability of results have limited efforts to integrate procurement performance with quantitative organizational environmental performance targets. Moreover, environmental purchasing criteria, when implemented, are often established on a product-by-product basis without consideration of other products in the procurement portfolio. We develop an approach that utilizes streamlined LCA methods, together with linear programming, to determine optimal portfolios of product impact-reduction opportunities under budget constraints. The approach is illustrated through a simulated breakfast cereal manufacturing firm procuring grain, containerboard boxes, plastic packaging, electricity, and industrial cleaning solutions. Results suggest that extending EPP decisions and resources to the portfolio level, recently made feasible through the methods illustrated herein, can provide substantially greater CO2e and water-depletion reductions per dollar spend than a product-by-product approach, creating opportunities for procurement organizations to participate in firm-wide environmental impact reduction targets.

Self-Averaging Property of Minimal Investment Risk of Mean-Variance Model

PubMed Central

Shinzato, Takashi

2015-01-01

In portfolio optimization problems, the minimum expected investment risk is not always smaller than the expected minimal investment risk. That is, using a well-known approach from operations research, it is possible to derive a strategy that minimizes the expected investment risk, but this strategy does not always result in the best rate of return on assets. Prior to making investment decisions, it is important to an investor to know the potential minimal investment risk (or the expected minimal investment risk) and to determine the strategy that will maximize the return on assets. We use the self-averaging property to analyze the potential minimal investment risk and the concentrated investment level for the strategy that gives the best rate of return. We compare the results from our method with the results obtained by the operations research approach and with those obtained by a numerical simulation using the optimal portfolio. The results of our method and the numerical simulation are in agreement, but they differ from that of the operations research approach. PMID:26225761

Correlations and risk contagion between mixed assets and mixed-asset portfolio VaR measurements in a dynamic view: An application based on time varying copula models

NASA Astrophysics Data System (ADS)

Han, Yingying; Gong, Pu; Zhou, Xiang

2016-02-01

In this paper, we apply time varying Gaussian and SJC copula models to study the correlations and risk contagion between mixed assets: financial (stock), real estate and commodity (gold) assets in China firstly. Then we study the dynamic mixed-asset portfolio risk through VaR measurement based on the correlations computed by the time varying copulas. This dynamic VaR-copula measurement analysis has never been used on mixed-asset portfolios. The results show the time varying estimations fit much better than the static models, not only for the correlations and risk contagion based on time varying copulas, but also for the VaR-copula measurement. The time varying VaR-SJC copula models are more accurate than VaR-Gaussian copula models when measuring more risky portfolios with higher confidence levels. The major findings suggest that real estate and gold play a role on portfolio risk diversification and there exist risk contagion and flight to quality between mixed-assets when extreme cases happen, but if we take different mixed-asset portfolio strategies with the varying of time and environment, the portfolio risk will be reduced.

ECLIPPx: an innovative model for reflective portfolios in life-long learning.

PubMed

Cheung, C Ronny

2011-03-01

For healthcare professionals, the educational portfolio is the most widely used component of lifelong learning - a vital aspect of modern medical practice. When used effectively, portfolios provide evidence of continuous learning and promote reflective practice. But traditional portfolio models are in danger of becoming outmoded, in the face of changing expectations of healthcare provider competences today. Portfolios in health care have generally focused on competencies in clinical skills. However, many other domains of professional development, such as professionalism and leadership skills, are increasingly important for doctors and health care professionals, and must be addressed in amassing evidence for training and revalidation. There is a need for modern health care learning portfolios to reflect this sea change. A new model for categorising the health care portfolios of professionals is proposed. The ECLIPPx model is based on personal practice, and divides the evidence of ongoing professional learning into four categories: educational development; clinical practice; leadership, innovation and professionalism; and personal experience. The ECLIPPx model offers a new approach for personal reflection and longitudinal learning, one that gives flexibility to the user whilst simultaneously encompassing the many relatively new areas of competence and expertise that are now required of a modern doctor. © Blackwell Publishing Ltd 2011.

Potential barriers to the application of multi-factor portfolio analysis in public hospitals: evidence from a pilot study in the Netherlands.

PubMed

Pavlova, Milena; Tsiachristas, Apostolos; Vermaeten, Gerhard; Groot, Wim

2009-01-01

Portfolio analysis is a business management tool that can assist health care managers to develop new organizational strategies. The application of portfolio analysis to US hospital settings has been frequently reported. In Europe however, the application of this technique has received little attention, especially concerning public hospitals. Therefore, this paper examines the peculiarities of portfolio analysis and its applicability to the strategic management of European public hospitals. The analysis is based on a pilot application of a multi-factor portfolio analysis in a Dutch university hospital. The nature of portfolio analysis and the steps in a multi-factor portfolio analysis are reviewed along with the characteristics of the research setting. Based on these data, a multi-factor portfolio model is developed and operationalized. The portfolio model is applied in a pilot investigation to analyze the market attractiveness and hospital strengths with regard to the provision of three orthopedic services: knee surgery, hip surgery, and arthroscopy. The pilot portfolio analysis is discussed to draw conclusions about potential barriers to the overall adoption of portfolio analysis in the management of a public hospital. Copyright (c) 2008 John Wiley & Sons, Ltd.

A Many-Objective Approach to Developing Adaptive Water Supply Portfolios in the 'Research Triangle' Region of North Carolina

NASA Astrophysics Data System (ADS)

Zeff, H. B.; Kasprzyk, J. R.; Reed, P. M.; Characklis, G. W.

2012-12-01

This study uses many-objective evolutionary optimization to quantify the tradeoffs water utilities face when developing flexible water shortage response plans. Alternatives to infrastructure development, such as temporary demand management programs and inter-utility water transfer agreements, allow local water providers to develop portfolios of water supply options capable of adapting to changing hydrologic conditions and growing water demand. The extent to which these options are implemented will be determined by a number of conflicting operational and financial considerations. An integrated reservoir simulation model including four large water utilities in the 'Research Triangle' region of North Carolina is used to evaluate the potential tradeoffs resulting from regional demands on shared infrastructure, customer concerns, and the financial uncertainty caused by the intermittent and irregular nature of drought. Instead of providing one optimal solution, multi-objective evolutionary algorithms (MOEAs) use the concept of non-dominations to discover a set of portfolio options in which no solution is inferior to any other solution in all objectives. Interactive visual analytics enable water providers to explore these tradeoffs and develop water shortage response plans tailored to their individual circumstances. The simulation model is evaluated under a number of different formulations to help identify and visualize the impacts of water efficiency, revenue/cost variability, consumer effects, and inter-utility cooperation. The different problems are formulated by adding portfolio options and objectives in such a way that the lower dimensional problem formulations are sub-sets of the full formulation. The full formulation considers reservoir reliability, water use restriction frequency, total water transfer allotment, total costs, revenue/cost variability, and additional consumer losses during restrictions. The simulation results highlight the inadequacy of lower order, cost-benefit type analyses to evaluate water management techniques as they move beyond the construction of large storage infrastructure. This work can help water providers develop the analytical tools to evaluate complex, adaptive techniques that are becoming more attractive in an era of growing municipal demand, risking infrastructure costs, and uncertain hydrology.

Acquisition Management for Systems-of-Systems: Analysis of Alternatives via Computational Exploratory Model

DTIC Science & Technology

2012-02-03

node to the analysis of eigenmodes (connected trees /networks) of disruption sequences. The identification of disruption eigenmodes is particularly...investment portfolio approach enables the identification of optimal SoS network topologies and provides a tool for acquisition professionals to...a program based on its ability to provide a new capability for a given cost, and not on its ability to meet specific performance requirements ( Spacy

Long-range Ising model for credit portfolios with heterogeneous credit exposures

NASA Astrophysics Data System (ADS)

Kato, Kensuke

2016-11-01

We propose the finite-size long-range Ising model as a model for heterogeneous credit portfolios held by a financial institution in the view of econophysics. The model expresses the heterogeneity of the default probability and the default correlation by dividing a credit portfolio into multiple sectors characterized by credit rating and industry. The model also expresses the heterogeneity of the credit exposure, which is difficult to evaluate analytically, by applying the replica exchange Monte Carlo method to numerically calculate the loss distribution. To analyze the characteristics of the loss distribution for credit portfolios with heterogeneous credit exposures, we apply this model to various credit portfolios and evaluate credit risk. As a result, we show that the tail of the loss distribution calculated by this model has characteristics that are different from the tail of the loss distribution of the standard models used in credit risk modeling. We also show that there is a possibility of different evaluations of credit risk according to the pattern of heterogeneity.

Noisy covariance matrices and portfolio optimization

NASA Astrophysics Data System (ADS)

Pafka, S.; Kondor, I.

2002-05-01

According to recent findings [#!bouchaud!#,#!stanley!#], empirical covariance matrices deduced from financial return series contain such a high amount of noise that, apart from a few large eigenvalues and the corresponding eigenvectors, their structure can essentially be regarded as random. In [#!bouchaud!#], e.g., it is reported that about 94% of the spectrum of these matrices can be fitted by that of a random matrix drawn from an appropriately chosen ensemble. In view of the fundamental role of covariance matrices in the theory of portfolio optimization as well as in industry-wide risk management practices, we analyze the possible implications of this effect. Simulation experiments with matrices having a structure such as described in [#!bouchaud!#,#!stanley!#] lead us to the conclusion that in the context of the classical portfolio problem (minimizing the portfolio variance under linear constraints) noise has relatively little effect. To leading order the solutions are determined by the stable, large eigenvalues, and the displacement of the solution (measured in variance) due to noise is rather small: depending on the size of the portfolio and on the length of the time series, it is of the order of 5 to 15%. The picture is completely different, however, if we attempt to minimize the variance under non-linear constraints, like those that arise e.g. in the problem of margin accounts or in international capital adequacy regulation. In these problems the presence of noise leads to a serious instability and a high degree of degeneracy of the solutions.

Risk Evaluation for Identification and Intervention in Dual Use Research of Concern (DURC) for International Biological R&D Activity

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

Jones, Katherine A.; DeMenno, Mercy; Hoffman, Matthew John

This report summarizes the work performed as part of a Laboratory Directed Research and Development project focused on evaluating and mitigating risk associated with biological dual use research of concern. The academic and scientific community has identified the funding stage as the appropriate place to intervene and mitigate risk, so the framework developed here uses a portfolio-level approach and balances biosafety and biosecurity risks, anticipated project benefits, and available mitigations to identify the best available investment strategies subject to cost constraints. The modeling toolkit was designed for decision analysis for dual use research of concern, but is flexible enough tomore » support a wide variety of portfolio-level funding decisions where risk/benefit tradeoffs are involved. Two mathematical optimization models with two solution methods are included to accommodate stakeholders with varying levels of certainty about priorities between metrics. An example case study is presented.« less

Combinatorial Algorithms for Portfolio Optimization Problems - Case of Risk Moderate Investor

NASA Astrophysics Data System (ADS)

Juarna, A.

2017-03-01

Portfolio optimization problem is a problem of finding optimal combination of n stocks from N ≥ n available stocks that gives maximal aggregate return and minimal aggregate risk. In this paper given N = 43 from the IDX (Indonesia Stock Exchange) group of the 45 most-traded stocks, known as the LQ45, with p = 24 data of monthly returns for each stock, spanned over interval 2013-2014. This problem actually is a combinatorial one where its algorithm is constructed based on two considerations: risk moderate type of investor and maximum allowed correlation coefficient between every two eligible stocks. The main outputs resulted from implementation of the algorithms is a multiple curve of three portfolio’s attributes, e.g. the size, the ratio of return to risk, and the percentage of negative correlation coefficient for every two chosen stocks, as function of maximum allowed correlation coefficient between each two stocks. The output curve shows that the portfolio contains three stocks with ratio of return to risk at 14.57 if the maximum allowed correlation coefficient between every two eligible stocks is negative and contains 19 stocks with maximum allowed correlation coefficient 0.17 to get maximum ratio of return to risk at 25.48.

The Teaching Portfolio: Capturing the Scholarship in Teaching.

ERIC Educational Resources Information Center

Edgerton, Russell; And Others

This report argues a case for the use of professional teaching portfolios by educators in higher education, advances a point of view about portfolio issues, and offers examples of portfolio entries. A work-sample-plus-reflection model is presented as a guide for what might be included in a portfolio and why it might be used at a particular campus.…

Maximizing and minimizing investment concentration with constraints of budget and investment risk

NASA Astrophysics Data System (ADS)

Shinzato, Takashi

2018-01-01

In this paper, as a first step in examining the properties of a feasible portfolio subset that is characterized by budget and risk constraints, we assess the maximum and minimum of the investment concentration using replica analysis. To do this, we apply an analytical approach of statistical mechanics. We note that the optimization problem considered in this paper is the dual problem of the portfolio optimization problem discussed in the literature, and we verify that these optimal solutions are also dual. We also present numerical experiments, in which we use the method of steepest descent that is based on Lagrange's method of undetermined multipliers, and we compare the numerical results to those obtained by replica analysis in order to assess the effectiveness of our proposed approach.

Wavelet evolutionary network for complex-constrained portfolio rebalancing

NASA Astrophysics Data System (ADS)

Suganya, N. C.; Vijayalakshmi Pai, G. A.

2012-07-01

Portfolio rebalancing problem deals with resetting the proportion of different assets in a portfolio with respect to changing market conditions. The constraints included in the portfolio rebalancing problem are basic, cardinality, bounding, class and proportional transaction cost. In this study, a new heuristic algorithm named wavelet evolutionary network (WEN) is proposed for the solution of complex-constrained portfolio rebalancing problem. Initially, the empirical covariance matrix, one of the key inputs to the problem, is estimated using the wavelet shrinkage denoising technique to obtain better optimal portfolios. Secondly, the complex cardinality constraint is eliminated using k-means cluster analysis. Finally, WEN strategy with logical procedures is employed to find the initial proportion of investment in portfolio of assets and also rebalance them after certain period. Experimental studies of WEN are undertaken on Bombay Stock Exchange, India (BSE200 index, period: July 2001-July 2006) and Tokyo Stock Exchange, Japan (Nikkei225 index, period: March 2002-March 2007) data sets. The result obtained using WEN is compared with the only existing counterpart named Hopfield evolutionary network (HEN) strategy and also verifies that WEN performs better than HEN. In addition, different performance metrics and data envelopment analysis are carried out to prove the robustness and efficiency of WEN over HEN strategy.

Crude oil price forecasting based on hybridizing wavelet multiple linear regression model, particle swarm optimization techniques, and principal component analysis.

PubMed

Shabri, Ani; Samsudin, Ruhaidah

2014-01-01

Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR) is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA) is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO) is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI), has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series.

Crude Oil Price Forecasting Based on Hybridizing Wavelet Multiple Linear Regression Model, Particle Swarm Optimization Techniques, and Principal Component Analysis

PubMed Central

Shabri, Ani; Samsudin, Ruhaidah

2014-01-01

Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR) is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA) is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO) is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI), has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series. PMID:24895666

Influence of credit scoring on the dynamics of Markov chain

NASA Astrophysics Data System (ADS)

Galina, Timofeeva

2015-11-01

Markov processes are widely used to model the dynamics of a credit portfolio and forecast the portfolio risk and profitability. In the Markov chain model the loan portfolio is divided into several groups with different quality, which determined by presence of indebtedness and its terms. It is proposed that dynamics of portfolio shares is described by a multistage controlled system. The article outlines mathematical formalization of controls which reflect the actions of the bank's management in order to improve the loan portfolio quality. The most important control is the organization of approval procedure of loan applications. The credit scoring is studied as a control affecting to the dynamic system. Different formalizations of "good" and "bad" consumers are proposed in connection with the Markov chain model.

A web-based portfolio model as the students' final assignment: Dealing with the development of higher education trend

NASA Astrophysics Data System (ADS)

Utanto, Yuli; Widhanarto, Ghanis Putra; Maretta, Yoris Adi

2017-03-01

This study aims to develop a web-based portfolio model. The model developed in this study could reveal the effectiveness of the new model in experiments conducted at research respondents in the department of curriculum and educational technology FIP Unnes. In particular, the further research objectives to be achieved through this development of research, namely: (1) Describing the process of implementing a portfolio in a web-based model; (2) Assessing the effectiveness of web-based portfolio model for the final task, especially in Web-Based Learning courses. This type of research is the development of research Borg and Gall (2008: 589) says "educational research and development (R & D) is a process used to develop and validate educational production". The series of research and development carried out starting with exploration and conceptual studies, followed by testing and evaluation, and also implementation. For the data analysis, the technique used is simple descriptive analysis, analysis of learning completeness, which then followed by prerequisite test for normality and homogeneity to do T - test. Based on the data analysis, it was concluded that: (1) a web-based portfolio model can be applied to learning process in higher education; (2) The effectiveness of web-based portfolio model with field data from the respondents of large group trial participants (field trial), the number of respondents who reached mastery learning (a score of 60 and above) were 24 people (92.3%) in which it indicates that the web-based portfolio model is effective. The conclusion of this study is that a web-based portfolio model is effective. The implications of the research development of this model, the next researcher is expected to be able to use the guideline of the development model based on the research that has already been conducted to be developed on other subjects.

The Capability Portfolio Analysis Tool (CPAT): A Mixed Integer Linear Programming Formulation for Fleet Modernization Analysis (Version 2.0.2).

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

Waddell, Lucas; Muldoon, Frank; Henry, Stephen Michael

In order to effectively plan the management and modernization of their large and diverse fleets of vehicles, Program Executive Office Ground Combat Systems (PEO GCS) and Program Executive Office Combat Support and Combat Service Support (PEO CS&CSS) commis- sioned the development of a large-scale portfolio planning optimization tool. This software, the Capability Portfolio Analysis Tool (CPAT), creates a detailed schedule that optimally prioritizes the modernization or replacement of vehicles within the fleet - respecting numerous business rules associated with fleet structure, budgets, industrial base, research and testing, etc., while maximizing overall fleet performance through time. This paper contains a thor-more » ough documentation of the terminology, parameters, variables, and constraints that comprise the fleet management mixed integer linear programming (MILP) mathematical formulation. This paper, which is an update to the original CPAT formulation document published in 2015 (SAND2015-3487), covers the formulation of important new CPAT features.« less

Purpose and Pedagogy: A Conceptual Model for an ePortfolio

ERIC Educational Resources Information Center

Buyarski, Catherine A.; Aaron, Robert W.; Hansen, Michele J.; Hollingsworth, Cynthia D.; Johnson, Charles A.; Kahn, Susan; Landis, Cynthia M.; Pedersen, Joan S.; Powell, Amy A.

2015-01-01

This conceptual model emerged from the need to balance multiple purposes and perspectives associated with developing an ePortfolio designed to promote student development and success. A comprehensive review of literature from various disciplines, theoretical frameworks, and scholarship, including self-authorship, reflection, ePortfolio pedagogy,…

Maximizing the U.S. Army’s Future Contribution to Global Security Using the Capability Portfolio Analysis Tool (CPAT)

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

Davis, Scott J.; Edwards, Shatiel B.; Teper, Gerald E.

We report that recent budget reductions have posed tremendous challenges to the U.S. Army in managing its portfolio of ground combat systems (tanks and other fighting vehicles), thus placing many important programs at risk. To address these challenges, the Army and a supporting team developed and applied the Capability Portfolio Analysis Tool (CPAT) to optimally invest in ground combat modernization over the next 25–35 years. CPAT provides the Army with the analytical rigor needed to help senior Army decision makers allocate scarce modernization dollars to protect soldiers and maintain capability overmatch. CPAT delivers unparalleled insight into multiple-decade modernization planning usingmore » a novel multiphase mixed-integer linear programming technique and illustrates a cultural shift toward analytics in the Army’s acquisition thinking and processes. CPAT analysis helped shape decisions to continue modernization of the $10 billion Stryker family of vehicles (originally slated for cancellation) and to strategically reallocate over $20 billion to existing modernization programs by not pursuing the Ground Combat Vehicle program as originally envisioned. Ultimately, more than 40 studies have been completed using CPAT, applying operations research methods to optimally prioritize billions of taxpayer dollars and allowing Army acquisition executives to base investment decisions on analytically rigorous evaluations of portfolio trade-offs.« less

Maximizing the U.S. Army’s Future Contribution to Global Security Using the Capability Portfolio Analysis Tool (CPAT)

DOE PAGES

Davis, Scott J.; Edwards, Shatiel B.; Teper, Gerald E.; ...

2016-02-01

We report that recent budget reductions have posed tremendous challenges to the U.S. Army in managing its portfolio of ground combat systems (tanks and other fighting vehicles), thus placing many important programs at risk. To address these challenges, the Army and a supporting team developed and applied the Capability Portfolio Analysis Tool (CPAT) to optimally invest in ground combat modernization over the next 25–35 years. CPAT provides the Army with the analytical rigor needed to help senior Army decision makers allocate scarce modernization dollars to protect soldiers and maintain capability overmatch. CPAT delivers unparalleled insight into multiple-decade modernization planning usingmore » a novel multiphase mixed-integer linear programming technique and illustrates a cultural shift toward analytics in the Army’s acquisition thinking and processes. CPAT analysis helped shape decisions to continue modernization of the $10 billion Stryker family of vehicles (originally slated for cancellation) and to strategically reallocate over $20 billion to existing modernization programs by not pursuing the Ground Combat Vehicle program as originally envisioned. Ultimately, more than 40 studies have been completed using CPAT, applying operations research methods to optimally prioritize billions of taxpayer dollars and allowing Army acquisition executives to base investment decisions on analytically rigorous evaluations of portfolio trade-offs.« less

Multivariate Markov chain modeling for stock markets

NASA Astrophysics Data System (ADS)

Maskawa, Jun-ichi

2003-06-01

We study a multivariate Markov chain model as a stochastic model of the price changes of portfolios in the framework of the mean field approximation. The time series of price changes are coded into the sequences of up and down spins according to their signs. We start with the discussion for small portfolios consisting of two stock issues. The generalization of our model to arbitrary size of portfolio is constructed by a recurrence relation. The resultant form of the joint probability of the stationary state coincides with Gibbs measure assigned to each configuration of spin glass model. Through the analysis of actual portfolios, it has been shown that the synchronization of the direction of the price changes is well described by the model.

Optimal Dynamic Strategies for Index Tracking and Algorithmic Trading

NASA Astrophysics Data System (ADS)

Ward, Brian

In this thesis we study dynamic strategies for index tracking and algorithmic trading. Tracking problems have become ever more important in Financial Engineering as investors seek to precisely control their portfolio risks and exposures over different time horizons. This thesis analyzes various tracking problems and elucidates the tracking errors and strategies one can employ to minimize those errors and maximize profit. In Chapters 2 and 3, we study the empirical tracking properties of exchange traded funds (ETFs), leveraged ETFs (LETFs), and futures products related to spot gold and the Chicago Board Option Exchange (CBOE) Volatility Index (VIX), respectively. These two markets provide interesting and differing examples for understanding index tracking. We find that static strategies work well in the nonleveraged case for gold, but fail to track well in the corresponding leveraged case. For VIX, tracking via neither ETFs, nor futures\\ portfolios succeeds, even in the nonleveraged case. This motivates the need for dynamic strategies, some of which we construct in these two chapters and further expand on in Chapter 4. There, we analyze a framework for index tracking and risk exposure control through financial derivatives. We derive a tracking condition that restricts our exposure choices and also define a slippage process that characterizes the deviations from the index over longer horizons. The framework is applied to a number of models, for example, Black Scholes model and Heston model for equity index tracking, as well as the Square Root (SQR) model and the Concatenated Square Root (CSQR) model for VIX tracking. By specifying how each of these models fall into our framework, we are able to understand the tracking errors in each of these models. Finally, Chapter 5 analyzes a tracking problem of a different kind that arises in algorithmic trading: schedule following for optimal execution. We formulate and solve a stochastic control problem to obtain the optimal trading rates using both market and limit orders. There is a quadratic terminal penalty to ensure complete liquidation as well as a trade speed limiter and trader director to provide better control on the trading rates. The latter two penalties allow the trader to tailor the magnitude and sign (respectively) of the optimal trading rates. We demonstrate the applicability of the model to following a benchmark schedule. In addition, we identify conditions on the model parameters to ensure optimality of the controls and finiteness of the associated value functions. Throughout the chapter, numerical simulations are provided to demonstrate the properties of the optimal trading rates.

Fuzzy bi-objective linear programming for portfolio selection problem with magnitude ranking function

NASA Astrophysics Data System (ADS)

Kusumawati, Rosita; Subekti, Retno

2017-04-01

Fuzzy bi-objective linear programming (FBOLP) model is bi-objective linear programming model in fuzzy number set where the coefficients of the equations are fuzzy number. This model is proposed to solve portfolio selection problem which generate an asset portfolio with the lowest risk and the highest expected return. FBOLP model with normal fuzzy numbers for risk and expected return of stocks is transformed into linear programming (LP) model using magnitude ranking function.

Loss aversion, large deviation preferences and optimal portfolio weights for some classes of return processes

NASA Astrophysics Data System (ADS)

Duffy, Ken; Lobunets, Olena; Suhov, Yuri

2007-05-01

We propose a model of a loss averse investor who aims to maximize his expected wealth under certain constraints. The constraints are that he avoids, with high probability, incurring an (suitably defined) unacceptable loss. The methodology employed comes from the theory of large deviations. We explore a number of fundamental properties of the model and illustrate its desirable features. We demonstrate its utility by analyzing assets that follow some commonly used financial return processes: Fractional Brownian Motion, Jump Diffusion, Variance Gamma and Truncated Lévy.

An Artificial Bee Colony Algorithm for Uncertain Portfolio Selection

PubMed Central

Chen, Wei

2014-01-01

Portfolio selection is an important issue for researchers and practitioners. In this paper, under the assumption that security returns are given by experts' evaluations rather than historical data, we discuss the portfolio adjusting problem which takes transaction costs and diversification degree of portfolio into consideration. Uncertain variables are employed to describe the security returns. In the proposed mean-variance-entropy model, the uncertain mean value of the return is used to measure investment return, the uncertain variance of the return is used to measure investment risk, and the entropy is used to measure diversification degree of portfolio. In order to solve the proposed model, a modified artificial bee colony (ABC) algorithm is designed. Finally, a numerical example is given to illustrate the modelling idea and the effectiveness of the proposed algorithm. PMID:25089292

An artificial bee colony algorithm for uncertain portfolio selection.

PubMed

Chen, Wei

2014-01-01

Portfolio selection is an important issue for researchers and practitioners. In this paper, under the assumption that security returns are given by experts' evaluations rather than historical data, we discuss the portfolio adjusting problem which takes transaction costs and diversification degree of portfolio into consideration. Uncertain variables are employed to describe the security returns. In the proposed mean-variance-entropy model, the uncertain mean value of the return is used to measure investment return, the uncertain variance of the return is used to measure investment risk, and the entropy is used to measure diversification degree of portfolio. In order to solve the proposed model, a modified artificial bee colony (ABC) algorithm is designed. Finally, a numerical example is given to illustrate the modelling idea and the effectiveness of the proposed algorithm.

Robust Active Portfolio Management

DTIC Science & Technology

2006-11-27

the Markowitz mean-variance model led to development of the Capital Asset Pricing Model ( CAPM ) for asset pricing [35, 29, 23] which remains one of the...active portfolio management. Our model uses historical returns and equilibrium expected returns predicted by the CAPM to identify assets that are...incorrectly priced in the market. There is a fundamental inconsistency between the CAPM and active portfolio management. The CAPM assumes that markets are

Between Public and Private: Politics, Governance, and the New Portfolio Models for Urban School Reform

ERIC Educational Resources Information Center

Bulkley, Katrina E., Ed.; Henig, Jeffrey R., Ed.; Levin, Henry M., Ed.

2010-01-01

"Between Public and Private" examines an innovative approach to school district management that has been adopted by a number of urban districts in recent years: a portfolio management model, in which "a central office oversees a portfolio of schools offering diverse organizational and curricular themes, including traditional public…

The Rise of Student Growth Portfolio Models in Tennessee

ERIC Educational Resources Information Center

Stone, Zachary

2017-01-01

Over the last several years, Tennessee has rapidly expanded the use of student growth portfolio models for the purpose of teacher evaluation. Participation, both in the number of districts and teachers, has increased steadily since portfolios were first introduced during the 2011-12 school year, and we expect that participation will continue to…

Evaluation of load flow and grid expansion in a unit-commitment and expansion optimization model SciGRID International Conference on Power Grid Modelling

NASA Astrophysics Data System (ADS)

Senkpiel, Charlotte; Biener, Wolfgang; Shammugam, Shivenes; Längle, Sven

2018-02-01

Energy system models serve as a basis for long term system planning. Joint optimization of electricity generating technologies, storage systems and the electricity grid leads to lower total system cost compared to an approach in which the grid expansion follows a given technology portfolio and their distribution. Modelers often face the problem of finding a good tradeoff between computational time and the level of detail that can be modeled. This paper analyses the differences between a transport model and a DC load flow model to evaluate the validity of using a simple but faster transport model within the system optimization model in terms of system reliability. The main findings in this paper are that a higher regional resolution of a system leads to better results compared to an approach in which regions are clustered as more overloads can be detected. An aggregation of lines between two model regions compared to a line sharp representation has little influence on grid expansion within a system optimizer. In a DC load flow model overloads can be detected in a line sharp case, which is therefore preferred. Overall the regions that need to reinforce the grid are identified within the system optimizer. Finally the paper recommends the usage of a load-flow model to test the validity of the model results.

Modeling stock prices in a portfolio using multidimensional geometric brownian motion

NASA Astrophysics Data System (ADS)

Maruddani, Di Asih I.; Trimono

2018-05-01

Modeling and forecasting stock prices of public corporates are important studies in financial analysis, due to their stock price characteristics. Stocks investments give a wide variety of risks. Taking a portfolio of several stocks is one way to minimize risk. Stochastic process of single stock price movements model can be formulated in Geometric Brownian Motion (GBM) model. But for a portfolio that consist more than one corporate stock, we need an expansion of GBM Model. In this paper, we use multidimensional Geometric Brownian Motion model. This paper aims to model and forecast two stock prices in a portfolio. These are PT. Matahari Department Store Tbk and PT. Telekomunikasi Indonesia Tbk on period January 4, 2016 until April 21, 2017. The goodness of stock price forecast value is based on Mean Absolute Percentage Error (MAPE). As the results, we conclude that forecast two stock prices in a portfolio using multidimensional GBM give less MAPE than using GBM for single stock price respectively. We conclude that multidimensional GBM is more appropriate for modeling stock prices, because the price of each stock affects each other.

Optimal trading strategies—a time series approach

NASA Astrophysics Data System (ADS)

Bebbington, Peter A.; Kühn, Reimer

2016-05-01

Motivated by recent advances in the spectral theory of auto-covariance matrices, we are led to revisit a reformulation of Markowitz’ mean-variance portfolio optimization approach in the time domain. In its simplest incarnation it applies to a single traded asset and allows an optimal trading strategy to be found which—for a given return—is minimally exposed to market price fluctuations. The model is initially investigated for a range of synthetic price processes, taken to be either second order stationary, or to exhibit second order stationary increments. Attention is paid to consequences of estimating auto-covariance matrices from small finite samples, and auto-covariance matrix cleaning strategies to mitigate against these are investigated. Finally we apply our framework to real world data.

Internationally coordinated multi-mission planning is now critical to sustain the space-based rainfall observations needed for managing floods globally

NASA Astrophysics Data System (ADS)

Reed, Patrick M.; Chaney, Nathaniel W.; Herman, Jonathan D.; Ferringer, Matthew P.; Wood, Eric F.

2015-02-01

At present 4 of 10 dedicated rainfall observing satellite systems have exceeded their design life, some by more than a decade. Here, we show operational implications for flood management of a ‘collapse’ of space-based rainfall observing infrastructure as well as the high-value opportunities for a globally coordinated portfolio of satellite missions and data services. Results show that the current portfolio of rainfall missions fails to meet operational data needs for flood management, even when assuming a perfectly coordinated data product from all current rainfall-focused missions (i.e., the full portfolio). In the full portfolio, satellite-based rainfall data deficits vary across the globe and may preclude climate adaptation in locations vulnerable to increasing flood risks. Moreover, removing satellites that are currently beyond their design life (i.e., the reduced portfolio) dramatically increases data deficits globally and could cause entire high intensity flood events to be unobserved. Recovery from the reduced portfolio is possible with internationally coordinated replenishment of as few as 2 of the 4 satellite systems beyond their design life, yielding rainfall data coverages that outperform the current full portfolio (i.e., an optimized portfolio of eight satellites can outperform ten satellites). This work demonstrates the potential for internationally coordinated satellite replenishment and data services to substantially enhance the cost-effectiveness, sustainability and operational value of space-based rainfall observations in managing evolving flood risks.

E-Portfolios: Concepts, Designs, and Integration within Student Affairs

ERIC Educational Resources Information Center

Garis, Jeff W.

2007-01-01

This chapter provides an overview of e-portfolio concepts and designs. It describes a model that outlines an array of dimensions for the categorization of e-portfolio systems, reviews selected systems, and makes observations regarding the importance for student affairs units to understand, collaborate, and include e-portfolio systems within their…

Two Portfolio Systems: EFL Students' Perceptions of Writing Ability, Text Improvement, and Feedback

ERIC Educational Resources Information Center

Lam, Ricky

2013-01-01

Research into portfolio assessment ("PA") typically describes teachers' development and implementation of different portfolio models in their respective teaching contexts, however, not much attention is paid to student perceptions of the portfolio approach or its impact on the learning of writing. To this end, this study aims to…

φq-field theory for portfolio optimization: “fat tails” and nonlinear correlations

NASA Astrophysics Data System (ADS)

Sornette, D.; Simonetti, P.; Andersen, J. V.

2000-08-01

Physics and finance are both fundamentally based on the theory of random walks (and their generalizations to higher dimensions) and on the collective behavior of large numbers of correlated variables. The archetype examplifying this situation in finance is the portfolio optimization problem in which one desires to diversify on a set of possibly dependent assets to optimize the return and minimize the risks. The standard mean-variance solution introduced by Markovitz and its subsequent developments is basically a mean-field Gaussian solution. It has severe limitations for practical applications due to the strongly non-Gaussian structure of distributions and the nonlinear dependence between assets. Here, we present in details a general analytical characterization of the distribution of returns for a portfolio constituted of assets whose returns are described by an arbitrary joint multivariate distribution. In this goal, we introduce a non-linear transformation that maps the returns onto Gaussian variables whose covariance matrix provides a new measure of dependence between the non-normal returns, generalizing the covariance matrix into a nonlinear covariance matrix. This nonlinear covariance matrix is chiseled to the specific fat tail structure of the underlying marginal distributions, thus ensuring stability and good conditioning. The portfolio distribution is then obtained as the solution of a mapping to a so-called φq field theory in particle physics, of which we offer an extensive treatment using Feynman diagrammatic techniques and large deviation theory, that we illustrate in details for multivariate Weibull distributions. The interaction (non-mean field) structure in this field theory is a direct consequence of the non-Gaussian nature of the distribution of asset price returns. We find that minimizing the portfolio variance (i.e. the relatively “small” risks) may often increase the large risks, as measured by higher normalized cumulants. Extensive empirical tests are presented on the foreign exchange market that validate satisfactorily the theory. For “fat tail” distributions, we show that an adequate prediction of the risks of a portfolio relies much more on the correct description of the tail structure rather than on their correlations. For the case of asymmetric return distributions, our theory allows us to generalize the return-risk efficient frontier concept to incorporate the dimensions of large risks embedded in the tail of the asset distributions. We demonstrate that it is often possible to increase the portfolio return while decreasing the large risks as quantified by the fourth and higher-order cumulants. Exact theoretical formulas are validated by empirical tests.

Macroscopic relationship in primal-dual portfolio optimization problem

NASA Astrophysics Data System (ADS)

Shinzato, Takashi

2018-02-01

In the present paper, using a replica analysis, we examine the portfolio optimization problem handled in previous work and discuss the minimization of investment risk under constraints of budget and expected return for the case that the distribution of the hyperparameters of the mean and variance of the return rate of each asset are not limited to a specific probability family. Findings derived using our proposed method are compared with those in previous work to verify the effectiveness of our proposed method. Further, we derive a Pythagorean theorem of the Sharpe ratio and macroscopic relations of opportunity loss. Using numerical experiments, the effectiveness of our proposed method is demonstrated for a specific situation.

Coupling Modern Portfolio Theory and Marxan enhances the efficiency of Lesser White-fronted Goose's (Anser erythropus) habitat conservation.

PubMed

Liang, Jie; Gao, Xiang; Zeng, Guangming; Hua, Shanshan; Zhong, Minzhou; Li, Xiaodong; Li, Xin

2018-01-09

Climate change and human activities cause uncertain changes to species biodiversity by altering their habitat. The uncertainty of climate change requires planners to balance the benefit and cost of making conservation plan. Here optimal protection approach for Lesser White-fronted Goose (LWfG) by coupling Modern Portfolio Theory (MPT) and Marxan selection were proposed. MPT was used to provide suggested weights of investment for protected area (PA) and reduce the influence of climatic uncertainty, while Marxan was utilized to choose a series of specific locations for PA. We argued that through combining these two commonly used techniques with the conservation plan, including assets allocation and PA chosing, the efficiency of rare bird's protection would be enhanced. In MPT analyses, the uncertainty of conservation-outcome can be reduced while conservation effort was allocated in Hunan, Jiangxi and Yangtze River delta. In Marxan model, the optimal location for habitat restorations based on existing nature reserve was identified. Clear priorities for the location and allocation of assets could be provided based on this research, and it could help decision makers to build conservation strategy for LWfG.

Optimizing cropland cover for stable food production in Sub-Saharan Africa using simulated yield and Modern Portfolio Theory

NASA Astrophysics Data System (ADS)

Bodin, P.; Olin, S.; Pugh, T. A. M.; Arneth, A.

2014-12-01

Food security can be defined as stable access to food of good nutritional quality. In Sub Saharan Africa access to food is strongly linked to local food production and the capacity to generate enough calories to sustain the local population. Therefore it is important in these regions to generate not only sufficiently high yields but also to reduce interannual variability in food production. Traditionally, climate impact simulation studies have focused on factors that underlie maximum productivity ignoring the variability in yield. By using Modern Portfolio Theory, a method stemming from economics, we here calculate optimum current and future crop selection that maintain current yield while minimizing variance, vs. maintaining variance while maximizing yield. Based on simulated yield using the LPJ-GUESS dynamic vegetation model, the results show that current cropland distribution for many crops is close to these optimum distributions. Even so, the optimizations displayed substantial potential to either increase food production and/or to decrease its variance regionally. Our approach can also be seen as a method to create future scenarios for the sown areas of crops in regions where local food production is important for food security.

The national portfolio for postgraduate family medicine training in South Africa: a descriptive study of acceptability, educational impact, and usefulness for assessment.

PubMed

Jenkins, Louis; Mash, Bob; Derese, Anselme

2013-07-25

Since 2007 a portfolio of learning has become a requirement for assessment of postgraduate family medicine training by the Colleges of Medicine of South Africa. A uniform portfolio of learning has been developed and content validity established among the eight postgraduate programmes. The aim of this study was to investigate the portfolio's acceptability, educational impact, and perceived usefulness for assessment of competence. Two structured questionnaires of 35 closed and open-ended questions were delivered to 53 family physician supervisors and 48 registrars who had used the portfolio. Categorical and nominal/ordinal data were analysed using simple descriptive statistics. The open-ended questions were analysed with ATLAS.ti software. Half of registrars did not find the portfolio clear, practical or feasible. Workshops on portfolio use, learning, and supervision were supported, and brief dedicated time daily for reflection and writing. Most supervisors felt the portfolio reflected an accurate picture of learning, but just over half of registrars agreed. While the portfolio helped with reflection on learning, participants were less convinced about how it helped them plan further learning. Supervisors graded most rotations, suggesting understanding the summative aspect, while only 61% of registrars reflected on rotations, suggesting the formative aspects are not yet optimally utilised. Poor feedback, the need for protected academic time, and pressure of service delivery impacting negatively on learning. This first introduction of a national portfolio for postgraduate training in family medicine in South Africa faces challenges similar to those in other countries. Acceptability of the portfolio relates to a clear purpose and guide, flexible format with tools available in the workplace, and appreciating the changing educational environment from university-based to national assessments. The role of the supervisor in direct observations of the registrar and dedicated educational meetings, giving feedback and support, cannot be overemphasized.

Using genetic algorithm to solve a new multi-period stochastic optimization model

NASA Astrophysics Data System (ADS)

Zhang, Xin-Li; Zhang, Ke-Cun

2009-09-01

This paper presents a new asset allocation model based on the CVaR risk measure and transaction costs. Institutional investors manage their strategic asset mix over time to achieve favorable returns subject to various uncertainties, policy and legal constraints, and other requirements. One may use a multi-period portfolio optimization model in order to determine an optimal asset mix. Recently, an alternative stochastic programming model with simulated paths was proposed by Hibiki [N. Hibiki, A hybrid simulation/tree multi-period stochastic programming model for optimal asset allocation, in: H. Takahashi, (Ed.) The Japanese Association of Financial Econometrics and Engineering, JAFFE Journal (2001) 89-119 (in Japanese); N. Hibiki A hybrid simulation/tree stochastic optimization model for dynamic asset allocation, in: B. Scherer (Ed.), Asset and Liability Management Tools: A Handbook for Best Practice, Risk Books, 2003, pp. 269-294], which was called a hybrid model. However, the transaction costs weren't considered in that paper. In this paper, we improve Hibiki's model in the following aspects: (1) The risk measure CVaR is introduced to control the wealth loss risk while maximizing the expected utility; (2) Typical market imperfections such as short sale constraints, proportional transaction costs are considered simultaneously. (3) Applying a genetic algorithm to solve the resulting model is discussed in detail. Numerical results show the suitability and feasibility of our methodology.

Performance of the reverse Helmbold universal portfolio

NASA Astrophysics Data System (ADS)

Tan, Choon Peng; Kuang, Kee Seng; Lee, Yap Jia

2017-04-01

The universal portfolio is an important investment strategy in a stock market where no stochastic model is assumed for the stock prices. The zero-gradient set of the objective function estimating the next-day portfolio which contains the reverse Kullback-Leibler order-alpha divergence is considered. From the zero-gradient set, the explicit, reverse Helmbold universal portfolio is obtained. The performance of the explicit, reverse Helmbold universal portfolio is studied by running them on some stock-price data sets from the local stock exchange. It is possible to increase the wealth of the investor by using these portfolios in investment.

Mathematical model of the loan portfolio dynamics in the form of Markov chain considering the process of new customers attraction

NASA Astrophysics Data System (ADS)

Bozhalkina, Yana

2017-12-01

Mathematical model of the loan portfolio structure change in the form of Markov chain is explored. This model considers in one scheme both the process of customers attraction, their selection based on the credit score, and loans repayment. The model describes the structure and volume of the loan portfolio dynamics, which allows to make medium-term forecasts of profitability and risk. Within the model corrective actions of bank management in order to increase lending volumes or to reduce the risk are formalized.

Optimal portfolio design to reduce climate-related conservation uncertainty in the Prairie Pothole Region.

PubMed

Ando, Amy W; Mallory, Mindy L

2012-04-24

Climate change is likely to alter the spatial distributions of species and habitat types but the nature of such change is uncertain. Thus, climate change makes it difficult to implement standard conservation planning paradigms. Previous work has suggested some approaches to cope with such uncertainty but has not harnessed all of the benefits of risk diversification. We adapt Modern Portfolio Theory (MPT) to optimal spatial targeting of conservation activity, using wetland habitat conservation in the Prairie Pothole Region (PPR) as an example. This approach finds the allocations of conservation activity among subregions of the planning area that maximize the expected conservation returns for a given level of uncertainty or minimize uncertainty for a given expected level of returns. We find that using MPT instead of simple diversification in the PPR can achieve a value of the conservation objective per dollar spent that is 15% higher for the same level of risk. MPT-based portfolios can also have 21% less uncertainty over benefits or 6% greater expected benefits than the current portfolio of PPR conservation. Total benefits from conservation investment are higher if returns are defined in terms of benefit-cost ratios rather than benefits alone. MPT-guided diversification can work to reduce the climate-change-induced uncertainty of future ecosystem-service benefits from many land policy and investment initiatives, especially when outcomes are negatively correlated between subregions of a planning area.

Optimal portfolio design to reduce climate-related conservation uncertainty in the Prairie Pothole Region

PubMed Central

Ando, Amy W.; Mallory, Mindy L.

2012-01-01

Climate change is likely to alter the spatial distributions of species and habitat types but the nature of such change is uncertain. Thus, climate change makes it difficult to implement standard conservation planning paradigms. Previous work has suggested some approaches to cope with such uncertainty but has not harnessed all of the benefits of risk diversification. We adapt Modern Portfolio Theory (MPT) to optimal spatial targeting of conservation activity, using wetland habitat conservation in the Prairie Pothole Region (PPR) as an example. This approach finds the allocations of conservation activity among subregions of the planning area that maximize the expected conservation returns for a given level of uncertainty or minimize uncertainty for a given expected level of returns. We find that using MPT instead of simple diversification in the PPR can achieve a value of the conservation objective per dollar spent that is 15% higher for the same level of risk. MPT-based portfolios can also have 21% less uncertainty over benefits or 6% greater expected benefits than the current portfolio of PPR conservation. Total benefits from conservation investment are higher if returns are defined in terms of benefit–cost ratios rather than benefits alone. MPT-guided diversification can work to reduce the climate-change–induced uncertainty of future ecosystem-service benefits from many land policy and investment initiatives, especially when outcomes are negatively correlated between subregions of a planning area. PMID:22451914

A conceptual framework for economic optimization of an animal health surveillance portfolio.

PubMed

Guo, X; Claassen, G D H; Oude Lansink, A G J M; Saatkamp, H W

2016-04-01

Decision making on hazard surveillance in livestock product chains is a multi-hazard, multi-stakeholder, and multi-criteria process that includes a variety of decision alternatives. The multi-hazard aspect means that the allocation of the scarce resource for surveillance should be optimized from the point of view of a surveillance portfolio (SP) rather than a single hazard. In this paper, we present a novel conceptual approach for economic optimization of a SP to address the resource allocation problem for a surveillance organization from a theoretical perspective. This approach uses multi-criteria techniques to evaluate the performances of different settings of a SP, taking cost-benefit aspects of surveillance and stakeholders' preferences into account. The credibility of the approach has also been checked for conceptual validity, data needs and operational validity; the application potentials of the approach are also discussed.

Efficient Location Uncertainty Treatment for Probabilistic Modelling of Portfolio Loss from Earthquake Events

NASA Astrophysics Data System (ADS)

Scheingraber, Christoph; Käser, Martin; Allmann, Alexander

2017-04-01

Probabilistic seismic risk analysis (PSRA) is a well-established method for modelling loss from earthquake events. In the insurance industry, it is widely employed for probabilistic modelling of loss to a distributed portfolio. In this context, precise exposure locations are often unknown, which results in considerable loss uncertainty. The treatment of exposure uncertainty has already been identified as an area where PSRA would benefit from increased research attention. However, so far, epistemic location uncertainty has not been in the focus of a large amount of research. We propose a new framework for efficient treatment of location uncertainty. To demonstrate the usefulness of this novel method, a large number of synthetic portfolios resembling real-world portfolios is systematically analyzed. We investigate the effect of portfolio characteristics such as value distribution, portfolio size, or proportion of risk items with unknown coordinates on loss variability. Several sampling criteria to increase the computational efficiency of the framework are proposed and put into the wider context of well-established Monte-Carlo variance reduction techniques. The performance of each of the proposed criteria is analyzed.

An optimization-based approach for facility energy management with uncertainties, and, Power portfolio optimization in deregulated electricity markets with risk management

NASA Astrophysics Data System (ADS)

Xu, Jun

Topic 1. An Optimization-Based Approach for Facility Energy Management with Uncertainties. Effective energy management for facilities is becoming increasingly important in view of the rising energy costs, the government mandate on the reduction of energy consumption, and the human comfort requirements. This part of dissertation presents a daily energy management formulation and the corresponding solution methodology for HVAC systems. The problem is to minimize the energy and demand costs through the control of HVAC units while satisfying human comfort, system dynamics, load limit constraints, and other requirements. The problem is difficult in view of the fact that the system is nonlinear, time-varying, building-dependent, and uncertain; and that the direct control of a large number of HVAC components is difficult. In this work, HVAC setpoints are the control variables developed on top of a Direct Digital Control (DDC) system. A method that combines Lagrangian relaxation, neural networks, stochastic dynamic programming, and heuristics is developed to predict the system dynamics and uncontrollable load, and to optimize the setpoints. Numerical testing and prototype implementation results show that our method can effectively reduce total costs, manage uncertainties, and shed the load, is computationally efficient. Furthermore, it is significantly better than existing methods. Topic 2. Power Portfolio Optimization in Deregulated Electricity Markets with Risk Management. In a deregulated electric power system, multiple markets of different time scales exist with various power supply instruments. A load serving entity (LSE) has multiple choices from these instruments to meet its load obligations. In view of the large amount of power involved, the complex market structure, risks in such volatile markets, stringent constraints to be satisfied, and the long time horizon, a power portfolio optimization problem is of critical importance but difficulty for an LSE to serve the load, maximize its profit, and manage risks. In this topic, a mid-term power portfolio optimization problem with risk management is presented. Key instruments are considered, risk terms based on semi-variances of spot market transactions are introduced, and penalties on load obligation violations are added to the objective function to improve algorithm convergence and constraint satisfaction. To overcome the inseparability of the resulting problem, a surrogate optimization framework is developed enabling a decomposition and coordination approach. Numerical testing results show that our method effectively provides decisions for various instruments to maximize profit, manage risks, and is computationally efficient.

Application and project portfolio valuation using enterprise architecture and business requirements modelling

NASA Astrophysics Data System (ADS)

Quartel, Dick; Steen, Maarten W. A.; Lankhorst, Marc M.

2012-05-01

This article describes an architecture-based approach to IT valuation. This approach offers organisations an instrument to valuate their application and project portfolios and to make well-balanced decisions about IT investments. The value of a software application is assessed in terms of its contribution to a selection of business goals. Based on such assessments, the value of different applications can be compared, and requirements for innovation, development, maintenance and phasing out can be identified. IT projects are proposed to realise the requirements. The value of each project is assessed in terms of the value it adds to one or more applications. This value can be obtained by relating the 'as-is' application portfolio to the 'to-be' portfolio that is being proposed by the project portfolio. In this way, projects can be ranked according to their added value, given a certain selection of business goals. The approach uses ArchiMate to model the relationship between software applications, business processes, services and products. In addition, two language extensions are used to model the relationship of these elements to business goals and requirements and to projects and project portfolios. The approach is illustrated using the portfolio method of Bedell and has been implemented in BiZZdesign Architect.

The national portfolio for postgraduate family medicine training in South Africa: a descriptive study of acceptability, educational impact, and usefulness for assessment

PubMed Central

2013-01-01

Background Since 2007 a portfolio of learning has become a requirement for assessment of postgraduate family medicine training by the Colleges of Medicine of South Africa. A uniform portfolio of learning has been developed and content validity established among the eight postgraduate programmes. The aim of this study was to investigate the portfolio’s acceptability, educational impact, and perceived usefulness for assessment of competence. Methods Two structured questionnaires of 35 closed and open-ended questions were delivered to 53 family physician supervisors and 48 registrars who had used the portfolio. Categorical and nominal/ordinal data were analysed using simple descriptive statistics. The open-ended questions were analysed with ATLAS.ti software. Results Half of registrars did not find the portfolio clear, practical or feasible. Workshops on portfolio use, learning, and supervision were supported, and brief dedicated time daily for reflection and writing. Most supervisors felt the portfolio reflected an accurate picture of learning, but just over half of registrars agreed. While the portfolio helped with reflection on learning, participants were less convinced about how it helped them plan further learning. Supervisors graded most rotations, suggesting understanding the summative aspect, while only 61% of registrars reflected on rotations, suggesting the formative aspects are not yet optimally utilised. Poor feedback, the need for protected academic time, and pressure of service delivery impacting negatively on learning. Conclusion This first introduction of a national portfolio for postgraduate training in family medicine in South Africa faces challenges similar to those in other countries. Acceptability of the portfolio relates to a clear purpose and guide, flexible format with tools available in the workplace, and appreciating the changing educational environment from university-based to national assessments. The role of the supervisor in direct observations of the registrar and dedicated educational meetings, giving feedback and support, cannot be overemphasized. PMID:23885806

Medicare Part D and Portfolio Choice.

PubMed

Ayyagari, Padmaja; He, Daifeng

2016-05-01

This study evaluates the impact of medical expenditure risk on portfolio choice among the elderly. The risk of large medical expenditures can be substantial for elderly individuals and is only partially mitigated by access to health insurance. The presence of deductibles, copayments, and other cost-sharing mechanisms implies that medical spending risk can be viewed as an undiversifiable background risk. Economic theory suggests that increases in background risk reduce the optimal financial risk that an individual or household is willing to bear (Pratt and Zeckhauser 1987; Elmendorf and Kimball 2000). In this study, we evaluate this hypothesis by estimating the impact of the introduction of the Medicare Part D program, which significantly reduced prescription drug spending risk for seniors, on portfolio choice.

Model-Informed Drug Development for Ixazomib, an Oral Proteasome Inhibitor.

PubMed

Gupta, Neeraj; Hanley, Michael J; Diderichsen, Paul M; Yang, Huyuan; Ke, Alice; Teng, Zhaoyang; Labotka, Richard; Berg, Deborah; Patel, Chirag; Liu, Guohui; van de Velde, Helgi; Venkatakrishnan, Karthik

2018-02-15

Model-informed drug development (MIDD) was central to the development of the oral proteasome inhibitor ixazomib, facilitating internal decisions (switch from body surface area (BSA)-based to fixed dosing, inclusive phase III trials, portfolio prioritization of ixazomib-based combinations, phase III dose for maintenance treatment), regulatory review (model-informed QT analysis, benefit-risk of 4 mg dose), and product labeling (absolute bioavailability and intrinsic/extrinsic factors). This review discusses the impact of MIDD in enabling patient-centric therapeutic optimization during the development of ixazomib. © 2017 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Statement of Rear Admiral Nevin P. Carr, Jr., United States Navy Chief of Naval Research before the Terrorism, Unconventional Threats and Capabilities Subcommittee of the House Armed Services Committee on The Fiscal year 2011 Budget Request

DTIC Science & Technology

2010-03-23

foundation of our S&T portfolio by developing a broad base of scientific knowledge from which INP, FNC, and quick reaction efforts are generated...optimally tailoring experiences, in real-time, to current cognitive and physiological states of the learner. A unique human systems design approach is...efforts include modeling human responses to blast, ballistic, and blunt trauma, as well as modeling physical and cognitive effects of blast exposure and

Estimated correlation matrices and portfolio optimization

NASA Astrophysics Data System (ADS)

Pafka, Szilárd; Kondor, Imre

2004-11-01

Correlations of returns on various assets play a central role in financial theory and also in many practical applications. From a theoretical point of view, the main interest lies in the proper description of the structure and dynamics of correlations, whereas for the practitioner the emphasis is on the ability of the models to provide adequate inputs for the numerous portfolio and risk management procedures used in the financial industry. The theory of portfolios, initiated by Markowitz, has suffered from the “curse of dimensions” from the very outset. Over the past decades a large number of different techniques have been developed to tackle this problem and reduce the effective dimension of large bank portfolios, but the efficiency and reliability of these procedures are extremely hard to assess or compare. In this paper, we propose a model (simulation)-based approach which can be used for the systematical testing of all these dimensional reduction techniques. To illustrate the usefulness of our framework, we develop several toy models that display some of the main characteristic features of empirical correlations and generate artificial time series from them. Then, we regard these time series as empirical data and reconstruct the corresponding correlation matrices which will inevitably contain a certain amount of noise, due to the finiteness of the time series. Next, we apply several correlation matrix estimators and dimension reduction techniques introduced in the literature and/or applied in practice. As in our artificial world the only source of error is the finite length of the time series and, in addition, the “true” model, hence also the “true” correlation matrix, are precisely known, therefore in sharp contrast with empirical studies, we can precisely compare the performance of the various noise reduction techniques. One of our recurrent observations is that the recently introduced filtering technique based on random matrix theory performs consistently well in all the investigated cases. Based on this experience, we believe that our simulation-based approach can also be useful for the systematic investigation of several related problems of current interest in finance.

Compromise Approach-Based Genetic Algorithm for Constrained Multiobjective Portfolio Selection Model

NASA Astrophysics Data System (ADS)

Li, Jun

In this paper, fuzzy set theory is incorporated into a multiobjective portfolio selection model for investors’ taking into three criteria: return, risk and liquidity. The cardinality constraint, the buy-in threshold constraint and the round-lots constraints are considered in the proposed model. To overcome the difficulty of evaluation a large set of efficient solutions and selection of the best one on non-dominated surface, a compromise approach-based genetic algorithm is presented to obtain a compromised solution for the proposed constrained multiobjective portfolio selection model.

Multi-period project portfolio selection under risk considerations and stochastic income

NASA Astrophysics Data System (ADS)

Tofighian, Ali Asghar; Moezzi, Hamid; Khakzar Barfuei, Morteza; Shafiee, Mahmood

2018-02-01

This paper deals with multi-period project portfolio selection problem. In this problem, the available budget is invested on the best portfolio of projects in each period such that the net profit is maximized. We also consider more realistic assumptions to cover wider range of applications than those reported in previous studies. A novel mathematical model is presented to solve the problem, considering risks, stochastic incomes, and possibility of investing extra budget in each time period. Due to the complexity of the problem, an effective meta-heuristic method hybridized with a local search procedure is presented to solve the problem. The algorithm is based on genetic algorithm (GA), which is a prominent method to solve this type of problems. The GA is enhanced by a new solution representation and well selected operators. It also is hybridized with a local search mechanism to gain better solution in shorter time. The performance of the proposed algorithm is then compared with well-known algorithms, like basic genetic algorithm (GA), particle swarm optimization (PSO), and electromagnetism-like algorithm (EM-like) by means of some prominent indicators. The computation results show the superiority of the proposed algorithm in terms of accuracy, robustness and computation time. At last, the proposed algorithm is wisely combined with PSO to improve the computing time considerably.

Perceptions of a continuing professional development portfolio model to enhance the scholarship of teaching and learning.

PubMed

Tofade, Toyin; Abate, Marie; Fu, Yunting

2014-04-01

To obtain feedback about the potential usefulness of a continuing professional development (CPD) portfolio for enhancing a faculty or practitioner's scholarship of teaching and learning (SoTL). A CPD portfolio approach to the SoTL was distributed in advance to registrants of the 2011 Annual AACP Teacher's Seminar. In an interactive workshop, faculty facilitators described a model for a CPD process applied to the development of an individual's SoTL. During the workshop, participants were asked to complete the initial sections of the portfolio to develop a personal plan for success in the SoTL. Post workshop, an evaluation form was distributed to the participants to obtain feedback about the CPD approach. Completed evaluation forms were collected, collated, and summarized. A total of 53 (14.1%) workshop participants completed the evaluation form of the 375 attendees. In all, 25 assistant professors, 14 associate professors, 4 full professors, 10 residents/students, 22 clinical, and 2 research faculty submitted evaluations. The proposed uses for the portfolio model selected most often by the responders were for personal development, faculty evaluation, increasing the SoTL, new faculty development, preceptor development, and residency training. A structured CPD portfolio model might be useful for the professional development of the SoTL.

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

Capability and Development Risk Management in System-of-Systems Architectures: A Portfolio Approach to Decision-Making

DTIC Science & Technology

2012-04-30

tool that provides a means of balancing capability development against cost and interdependent risks through the use of modern portfolio theory ...Focardi, 2007; Tutuncu & Cornuejols, 2007) that are extensions of modern portfolio and control theory . The reformulation allows for possible changes...Acquisition: Wave Model context • An Investment Portfolio Approach – Mean Variance Approach – Mean - Variance : A Robust Version • Concept

Portfolio careers for medical graduates: implications for postgraduate training and workforce planning.

PubMed

Eyre, Harris A; Mitchell, Rob D; Milford, Will; Vaswani, Nitin; Moylan, Steven

2014-06-01

Portfolio careers in medicine can be defined as significant involvement in one or more portfolios of activity beyond a practitioner's primary clinical role, either concurrently or in sequence. Portfolio occupations may include medical education, research, administration, legal medicine, the arts, engineering, business and consulting, leadership, politics and entrepreneurship. Despite significant interest among junior doctors, portfolios are poorly integrated with prevocational and speciality training programs in Australia. The present paper seeks to explore this issue. More formal systems for portfolio careers in Australia have the potential to increase job satisfaction, flexibility and retention, as well as diversify trainee skill sets. Although there are numerous benefits from involvement in portfolio careers, there are also risks to the trainee, employing health service and workforce modelling. Formalising pathways to portfolio careers relies on assessing stakeholder interest, enhancing flexibility in training programs, developing support programs, mentorship and coaching schemes and improving support structures in health services.

Effect of portfolio assessment on student learning in prenatal training for midwives.

PubMed

Kariman, Nourossadat; Moafi, Farnoosh

2011-01-01

The tendency to use portfolios for evaluation has been developed with the aim of optimizing the culture of assessment. The present study was carried out to determine the effect of using portfolios as an evaluation method on midwifery students' learning and satisfaction in prenatal practical training. In this prospective cohort study, all midwifery students in semester four (n=40), were randomly allocated to portfolio and routine evaluation groups. Based on their educational goals, the portfolio groups prepared packages which consisted of a complete report of the history, physical examinations, and methods of patient management (as evaluated by a checklist) for women who visited a prenatal clinic. During the last day of their course, a posttest, clinical exam, and student satisfaction form were completed. The two groups' mean age, mean pretest scores, and their prerequisite course that they should have taken in the previous semester were similar. The mean difference in the pre and post test scores for the two groups' knowledge and comprehension levels did not differ significantly (P>0.05). The average scores on questions in Bloom's taxonomy 2 and 3 of the portfolio group were significantly greater than those of the routine evaluation group (P=0.002, P=0.03, respectively). The mean of the two groups' clinical exam scores was significantly different. The portfolio group's mean scores on generating diagnostic and therapeutic solutions and the ability to apply theory in practice were higher than those of the routine group. Overall, students' satisfaction scores in the two evaluation methods were relatively similar. Portfolio evaluation provides the opportunity for more learning by increasing the student's participation in the learning process and helping them to apply theory in practice.

Integration of Linear Dynamic Emission and Climate Models with Air Traffic Simulations

NASA Technical Reports Server (NTRS)

Sridhar, Banavar; Ng, Hok K.; Chen, Neil Y.

2012-01-01

Future air traffic management systems are required to balance the conflicting objectives of maximizing safety and efficiency of traffic flows while minimizing the climate impact of aviation emissions and contrails. Integrating emission and climate models together with air traffic simulations improve the understanding of the complex interaction between the physical climate system, carbon and other greenhouse gas emissions and aviation activity. This paper integrates a national-level air traffic simulation and optimization capability with simple climate models and carbon cycle models, and climate metrics to assess the impact of aviation on climate. The capability can be used to make trade-offs between extra fuel cost and reduction in global surface temperature change. The parameters in the simulation can be used to evaluate the effect of various uncertainties in emission models and contrails and the impact of different decision horizons. Alternatively, the optimization results from the simulation can be used as inputs to other tools that monetize global climate impacts like the FAA s Aviation Environmental Portfolio Management Tool for Impacts.

System-of-Systems Technology-Portfolio-Analysis Tool

NASA Technical Reports Server (NTRS)

O'Neil, Daniel; Mankins, John; Feingold, Harvey; Johnson, Wayne

2012-01-01

Advanced Technology Life-cycle Analysis System (ATLAS) is a system-of-systems technology-portfolio-analysis software tool. ATLAS affords capabilities to (1) compare estimates of the mass and cost of an engineering system based on competing technological concepts; (2) estimate life-cycle costs of an outer-space-exploration architecture for a specified technology portfolio; (3) collect data on state-of-the-art and forecasted technology performance, and on operations and programs; and (4) calculate an index of the relative programmatic value of a technology portfolio. ATLAS facilitates analysis by providing a library of analytical spreadsheet models for a variety of systems. A single analyst can assemble a representation of a system of systems from the models and build a technology portfolio. Each system model estimates mass, and life-cycle costs are estimated by a common set of cost models. Other components of ATLAS include graphical-user-interface (GUI) software, algorithms for calculating the aforementioned index, a technology database, a report generator, and a form generator for creating the GUI for the system models. At the time of this reporting, ATLAS is a prototype, embodied in Microsoft Excel and several thousand lines of Visual Basic for Applications that run on both Windows and Macintosh computers.

Developing Portfolios of Water Supply Transfers

NASA Astrophysics Data System (ADS)

Characklis, G. W.; Kirsch, B. R.; Ramsey, J.; Dillard, K. E.; Kelley, C. T.

2005-12-01

Most cities rely on firm water supply capacity to meet demand, but increasing scarcity and supply costs are encouraging greater use of temporary transfers (e.g., spot leases, options). This raises questions regarding how best to coordinate the use of these transfers in meeting cost and reliability objectives. This work combines a hydrologic-water market simulation with an optimization approach to identify portfolios of permanent rights, options and leases that minimize expected costs of meeting a city's annual demand with a specified reliability. Spot market prices are linked to hydrologic conditions and described by monthly lease price distributions which are used to price options via a risk neutral approach. Monthly choices regarding when and how much water to acquire through temporary transfers are made on the basis of anticipatory decision rules related to the ratio of expected supply-to-expected demand. The simulation is linked with an algorithm that uses an implicit filtering search method designed for solution surfaces that exhibit high frequency, low amplitude noise. This simulation-optimization approach is applied to a region that currently supports an active water market, with results suggesting that the use of temporary transfers can reduce expected water supply costs substantially, while still maintaining high reliability levels. Also evaluated are tradeoffs between expected costs and cost variability that occur with variation in a portfolio's distribution of rights, options and leases. While this work represents firm supply capacity as permanent water rights, a similar approach could be used to develop portfolios integrating options and/or leases with hard supply infrastructure.

Marshall Application Realignment System (MARS) Architecture

NASA Technical Reports Server (NTRS)

Belshe, Andrea; Sutton, Mandy

2010-01-01

The Marshall Application Realignment System (MARS) Architecture project was established to meet the certification requirements of the Department of Defense Architecture Framework (DoDAF) V2.0 Federal Enterprise Architecture Certification (FEAC) Institute program and to provide added value to the Marshall Space Flight Center (MSFC) Application Portfolio Management process. The MARS Architecture aims to: (1) address the NASA MSFC Chief Information Officer (CIO) strategic initiative to improve Application Portfolio Management (APM) by optimizing investments and improving portfolio performance, and (2) develop a decision-aiding capability by which applications registered within the MSFC application portfolio can be analyzed and considered for retirement or decommission. The MARS Architecture describes a to-be target capability that supports application portfolio analysis against scoring measures (based on value) and overall portfolio performance objectives (based on enterprise needs and policies). This scoring and decision-aiding capability supports the process by which MSFC application investments are realigned or retired from the application portfolio. The MARS Architecture is a multi-phase effort to: (1) conduct strategic architecture planning and knowledge development based on the DoDAF V2.0 six-step methodology, (2) describe one architecture through multiple viewpoints, (3) conduct portfolio analyses based on a defined operational concept, and (4) enable a new capability to support the MSFC enterprise IT management mission, vision, and goals. This report documents Phase 1 (Strategy and Design), which includes discovery, planning, and development of initial architecture viewpoints. Phase 2 will move forward the process of building the architecture, widening the scope to include application realignment (in addition to application retirement), and validating the underlying architecture logic before moving into Phase 3. The MARS Architecture key stakeholders are most interested in Phase 3 because this is where the data analysis, scoring, and recommendation capability is realized. Stakeholders want to see the benefits derived from reducing the steady-state application base and identify opportunities for portfolio performance improvement and application realignment.

Measure for Measure: Using Portfolios in K-8 Mathematics.

ERIC Educational Resources Information Center

Kuhs, Therese M.

This book attempts to portray the reality that teachers face when trying to use portfolios. It uses anecdotes and examples that help carry important messages about portfolio use and contains model conversations and interactions. The conversations between teachers and students demonstrate strategies for involving children in the assessment process…

Complex Moving Parts: Assessment Systems and Electronic Portfolios

ERIC Educational Resources Information Center

Larkin, Martha J.; Robertson, Royce L.

2013-01-01

The largest college within an online university of over 50,000 students invested significant resources in translating a complex assessment system focused on continuous improvement and national accreditation into an effective and efficient electronic portfolio (ePortfolio). The team building the system needed a model to address problems met…

The Career Advancement Portfolio. Advancement for Low-Wage Workers

ERIC Educational Resources Information Center

Jobs for the Future, 2006

2006-01-01

Jobs for the Future created the "Career Advancement Portfolio" as central to its commitment to developing, implementing, and advocating for models, strategies, and policies that enable adults to advance toward economic self-sufficiency for themselves and their families. The "Portfolio" brings together the most innovative workforce development…

The Pentagonal E-Portfolio Model for Selecting, Adopting, Building, and Implementing an E-Portfolio

ERIC Educational Resources Information Center

Buzzetto-More, Nicole; Alade, Ayodele

2008-01-01

Electronic portfolios are a student-centered outcomes-based assessment regime involving learners in the gathering, selection, and organization of artifacts synthesized into a compilation purposed to demonstrate knowledge, skills, and/or achievements supported by reflections that articulate the relevance, credibility, and meaning of the artifacts…

Linear and nonlinear market correlations: Characterizing financial crises and portfolio optimization.

PubMed

Haluszczynski, Alexander; Laut, Ingo; Modest, Heike; Räth, Christoph

2017-12-01

Pearson correlation and mutual information-based complex networks of the day-to-day returns of U.S. S&P500 stocks between 1985 and 2015 have been constructed to investigate the mutual dependencies of the stocks and their nature. We show that both networks detect qualitative differences especially during (recent) turbulent market periods, thus indicating strongly fluctuating interconnections between the stocks of different companies in changing economic environments. A measure for the strength of nonlinear dependencies is derived using surrogate data and leads to interesting observations during periods of financial market crises. In contrast to the expectation that dependencies reduce mainly to linear correlations during crises, we show that (at least in the 2008 crisis) nonlinear effects are significantly increasing. It turns out that the concept of centrality within a network could potentially be used as some kind of an early warning indicator for abnormal market behavior as we demonstrate with the example of the 2008 subprime mortgage crisis. Finally, we apply a Markowitz mean variance portfolio optimization and integrate the measure of nonlinear dependencies to scale the investment exposure. This leads to significant outperformance as compared to a fully invested portfolio.

Linear and nonlinear market correlations: Characterizing financial crises and portfolio optimization

NASA Astrophysics Data System (ADS)

Haluszczynski, Alexander; Laut, Ingo; Modest, Heike; Räth, Christoph

2017-12-01

Pearson correlation and mutual information-based complex networks of the day-to-day returns of U.S. S&P500 stocks between 1985 and 2015 have been constructed to investigate the mutual dependencies of the stocks and their nature. We show that both networks detect qualitative differences especially during (recent) turbulent market periods, thus indicating strongly fluctuating interconnections between the stocks of different companies in changing economic environments. A measure for the strength of nonlinear dependencies is derived using surrogate data and leads to interesting observations during periods of financial market crises. In contrast to the expectation that dependencies reduce mainly to linear correlations during crises, we show that (at least in the 2008 crisis) nonlinear effects are significantly increasing. It turns out that the concept of centrality within a network could potentially be used as some kind of an early warning indicator for abnormal market behavior as we demonstrate with the example of the 2008 subprime mortgage crisis. Finally, we apply a Markowitz mean variance portfolio optimization and integrate the measure of nonlinear dependencies to scale the investment exposure. This leads to significant outperformance as compared to a fully invested portfolio.

A Balanced Portfolio Model For Improving Health: Concept And Vermont's Experience.

PubMed

Hester, James

2018-04-01

A successful strategy for improving population health requires acting in several sectors by implementing a portfolio of interventions. The mix of interventions should be both tailored to meet the community's needs and balanced in several dimensions-for example, time frame, level of risk, and target population. One obstacle is finding sustainable financing for both the interventions and the community infrastructure needed. This article first summarizes Vermont's experience as a laboratory for health reform. It then presents a conceptual model for a community-based population health strategy, using a balanced portfolio and diversified funding approaches. The article then reviews Vermont's population health initiative, including an example of a balanced portfolio and lessons learned from the state's experience.

New ventures require accurate risk analyses and adjustments.

PubMed

Eastaugh, S R

2000-01-01

For new business ventures to succeed, healthcare executives need to conduct robust risk analyses and develop new approaches to balance risk and return. Risk analysis involves examination of objective risks and harder-to-quantify subjective risks. Mathematical principles applied to investment portfolios also can be applied to a portfolio of departments or strategic business units within an organization. The ideal business investment would have a high expected return and a low standard deviation. Nonetheless, both conservative and speculative strategies should be considered in determining an organization's optimal service line and helping the organization manage risk.

For Portfolio Supporters, Skeptics, and Would-Be Adopters: Some Thoughts from CRPE

ERIC Educational Resources Information Center

Lake, Robin; Jochim, Ashley

2017-01-01

The Center on Reinventing Public Education (CRPE) designed the portfolio model based on the idea that we should move away from a "school system" to, instead, "a system of schools." In essence: school boards should focus on overseeing a "portfolio" of distinctive schools rather than directly running a set of…

Parent-Child Portfolios: "Look--This Book Is All about Us!"

ERIC Educational Resources Information Center

Appl, Dolores J.; Leavitt, Jessica E.; Ryan, Melissa A.

2014-01-01

A team of facilitators describe the process and content of portfolios they create for families attending weekly playgroup sessions based on the philosophy and practices of the Parents Interacting with Infants (PIWI) model. The parent-child portfolios are a form of authentic assessment and highlight children's development within the context of…

Exact probability distribution functions for Parrondo's games

NASA Astrophysics Data System (ADS)

Zadourian, Rubina; Saakian, David B.; Klümper, Andreas

2016-12-01

We study the discrete time dynamics of Brownian ratchet models and Parrondo's games. Using the Fourier transform, we calculate the exact probability distribution functions for both the capital dependent and history dependent Parrondo's games. In certain cases we find strong oscillations near the maximum of the probability distribution with two limiting distributions for odd and even number of rounds of the game. Indications of such oscillations first appeared in the analysis of real financial data, but now we have found this phenomenon in model systems and a theoretical understanding of the phenomenon. The method of our work can be applied to Brownian ratchets, molecular motors, and portfolio optimization.

Optimal Financial Knowledge and Wealth Inequality*

PubMed Central

Lusardi, Annamaria; Michaud, Pierre-Carl; Mitchell, Olivia S.

2017-01-01

We show that financial knowledge is a key determinant of wealth inequality in a stochastic lifecycle model with endogenous financial knowledge accumulation, where financial knowledge enables individuals to better allocate lifetime resources in a world of uncertainty and imperfect insurance. Moreover, because of how the U.S. social insurance system works, better-educated individuals have most to gain from investing in financial knowledge. Our parsimonious specification generates substantial wealth inequality relative to a one-asset saving model and one where returns on wealth depend on portfolio composition alone. We estimate that 30–40 percent of retirement wealth inequality is accounted for by financial knowledge. PMID:28555088

Exact probability distribution functions for Parrondo's games.

PubMed

Zadourian, Rubina; Saakian, David B; Klümper, Andreas

2016-12-01

We study the discrete time dynamics of Brownian ratchet models and Parrondo's games. Using the Fourier transform, we calculate the exact probability distribution functions for both the capital dependent and history dependent Parrondo's games. In certain cases we find strong oscillations near the maximum of the probability distribution with two limiting distributions for odd and even number of rounds of the game. Indications of such oscillations first appeared in the analysis of real financial data, but now we have found this phenomenon in model systems and a theoretical understanding of the phenomenon. The method of our work can be applied to Brownian ratchets, molecular motors, and portfolio optimization.

Diversified models for portfolio selection based on uncertain semivariance

NASA Astrophysics Data System (ADS)

Chen, Lin; Peng, Jin; Zhang, Bo; Rosyida, Isnaini

2017-02-01

Since the financial markets are complex, sometimes the future security returns are represented mainly based on experts' estimations due to lack of historical data. This paper proposes a semivariance method for diversified portfolio selection, in which the security returns are given subjective to experts' estimations and depicted as uncertain variables. In the paper, three properties of the semivariance of uncertain variables are verified. Based on the concept of semivariance of uncertain variables, two types of mean-semivariance diversified models for uncertain portfolio selection are proposed. Since the models are complex, a hybrid intelligent algorithm which is based on 99-method and genetic algorithm is designed to solve the models. In this hybrid intelligent algorithm, 99-method is applied to compute the expected value and semivariance of uncertain variables, and genetic algorithm is employed to seek the best allocation plan for portfolio selection. At last, several numerical examples are presented to illustrate the modelling idea and the effectiveness of the algorithm.

Report Carding: A Model for Foundation Portfolio Assessment

ERIC Educational Resources Information Center

Schmitz, Connie C.; Schillo, Barbara A.

2005-01-01

This article reviews changes in the accountability landscape that have occurred for foundations in recent years and several precedents for foundation performance assessment. The authors then present a model of portfolio assessment that is used for organizational accountability and learning. This model, which was piloted in 2002 and 2003 for the…

Portfolios: An Alternative Method of Student and Program Assessment

PubMed Central

Hannam, Susan E.

1995-01-01

The use of performance-based evaluation and alternative assessment techniques has become essential for curriculum programs seeking Commission of Accreditation of Allied Health Education Programs (CAAHEP) accreditation. In athletic training education, few assessment models exist to assess student performance over the entire course of their educational program. This article describes a model of assessment-a student athletic training portfolio of “best works.” The portfolio can serve as a method to assess student development and to assess program effectiveness. The goals of the program include purposes specific to the five NATA performance domains. In addition, four types of portfolio evidence are described: artifacts, attestations, productions, and reproductions. Quality assignments and projects completed by students as they progress through a six-semester program are identified relative to the type of evidence and the domain(s) they represent. The portfolio assists with student development, provides feedback for curriculum planning, allows for student/faculty collaboration and “coaching” of the student, and assists with job searching. This information will serve as a useful model for those athletic training programs looking for an alternative method of assessing student and program outcomes. PMID:16558359

Cryptographic Combinatorial Securities Exchanges

NASA Astrophysics Data System (ADS)

Thorpe, Christopher; Parkes, David C.

We present a useful new mechanism that facilitates the atomic exchange of many large baskets of securities in a combinatorial exchange. Cryptography prevents information about the securities in the baskets from being exploited, enhancing trust. Our exchange offers institutions who wish to trade large positions a new alternative to existing methods of block trading: they can reduce transaction costs by taking advantage of other institutions’ available liquidity, while third party liquidity providers guarantee execution—preserving their desired portfolio composition at all times. In our exchange, institutions submit encrypted orders which are crossed, leaving a “remainder”. The exchange proves facts about the portfolio risk of this remainder to third party liquidity providers without revealing the securities in the remainder, the knowledge of which could also be exploited. The third parties learn either (depending on the setting) the portfolio risk parameters of the remainder itself, or how their own portfolio risk would change if they were to incorporate the remainder into a portfolio they submit. In one setting, these third parties submit bids on the commission, and the winner supplies necessary liquidity for the entire exchange to clear. This guaranteed clearing, coupled with external price discovery from the primary markets for the securities, sidesteps difficult combinatorial optimization problems. This latter method of proving how taking on the remainder would change risk parameters of one’s own portfolio, without revealing the remainder’s contents or its own risk parameters, is a useful protocol of independent interest.

Adaptive Portfolio Optimization for Multiple Electricity Markets Participation.

PubMed

Pinto, Tiago; Morais, Hugo; Sousa, Tiago M; Sousa, Tiago; Vale, Zita; Praca, Isabel; Faia, Ricardo; Pires, Eduardo Jose Solteiro

2016-08-01

The increase of distributed energy resources, mainly based on renewable sources, requires new solutions that are able to deal with this type of resources' particular characteristics (namely, the renewable energy sources intermittent nature). The smart grid concept is increasing its consensus as the most suitable solution to facilitate the small players' participation in electric power negotiations while improving energy efficiency. The opportunity for players' participation in multiple energy negotiation environments (smart grid negotiation in addition to the already implemented market types, such as day-ahead spot markets, balancing markets, intraday negotiations, bilateral contracts, forward and futures negotiations, and among other) requires players to take suitable decisions on whether to, and how to participate in each market type. This paper proposes a portfolio optimization methodology, which provides the best investment profile for a market player, considering different market opportunities. The amount of power that each supported player should negotiate in each available market type in order to maximize its profits, considers the prices that are expected to be achieved in each market, in different contexts. The price forecasts are performed using artificial neural networks, providing a specific database with the expected prices in the different market types, at each time. This database is then used as input by an evolutionary particle swarm optimization process, which originates the most advantage participation portfolio for the market player. The proposed approach is tested and validated with simulations performed in multiagent simulator of competitive electricity markets, using real electricity markets data from the Iberian operator-MIBEL.

Improving the Flexibility of Optimization-Based Decision Aiding Frameworks for Integrated Water Resource Management

NASA Astrophysics Data System (ADS)

Guillaume, J. H.; Kasprzyk, J. R.

2013-12-01

Deep uncertainty refers to situations in which stakeholders cannot agree on the full suite of risks for their system or their probabilities. Additionally, systems are often managed for multiple, conflicting objectives such as minimizing cost, maximizing environmental quality, and maximizing hydropower revenues. Many objective analysis (MOA) uses a quantitative model combined with evolutionary optimization to provide a tradeoff set of potential solutions to a planning problem. However, MOA is often performed using a single, fixed problem conceptualization. Focus on development of a single formulation can introduce an "inertia" into the problem solution, such that issues outside the initial formulation are less likely to ever be addressed. This study uses the Iterative Closed Question Methodology (ICQM) to continuously reframe the optimization problem, providing iterative definition and reflection for stakeholders. By using a series of directed questions to look beyond a problem's existing modeling representation, ICQM seeks to provide a working environment within which it is easy to modify the motivating question, assumptions, and model identification in optimization problems. The new approach helps identify and reduce bottle-necks introduced by properties of both the simulation model and optimization approach that reduce flexibility in generation and evaluation of alternatives. It can therefore help introduce new perspectives on the resolution of conflicts between objectives. The Lower Rio Grande Valley portfolio planning problem is used as a case study.

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

Cutler, Dylan; Frank, Stephen; Slovensky, Michelle

Rich, well-organized building performance and energy consumption data enable a host of analytic capabilities for building owners and operators, from basic energy benchmarking to detailed fault detection and system optimization. Unfortunately, data integration for building control systems is challenging and costly in any setting. Large portfolios of buildings--campuses, cities, and corporate portfolios--experience these integration challenges most acutely. These large portfolios often have a wide array of control systems, including multiple vendors and nonstandard communication protocols. They typically have complex information technology (IT) networks and cybersecurity requirements and may integrate distributed energy resources into their infrastructure. Although the challenges are significant,more » the integration of control system data has the potential to provide proportionally greater value for these organizations through portfolio-scale analytics, comprehensive demand management, and asset performance visibility. As a large research campus, the National Renewable Energy Laboratory (NREL) experiences significant data integration challenges. To meet them, NREL has developed an architecture for effective data collection, integration, and analysis, providing a comprehensive view of data integration based on functional layers. The architecture is being evaluated on the NREL campus through deployment of three pilot implementations.« less

An integrated portfolio optimisation procedure based on data envelopment analysis, artificial bee colony algorithm and genetic programming

NASA Astrophysics Data System (ADS)

Hsu, Chih-Ming

2014-12-01

Portfolio optimisation is an important issue in the field of investment/financial decision-making and has received considerable attention from both researchers and practitioners. However, besides portfolio optimisation, a complete investment procedure should also include the selection of profitable investment targets and determine the optimal timing for buying/selling the investment targets. In this study, an integrated procedure using data envelopment analysis (DEA), artificial bee colony (ABC) and genetic programming (GP) is proposed to resolve a portfolio optimisation problem. The proposed procedure is evaluated through a case study on investing in stocks in the semiconductor sub-section of the Taiwan stock market for 4 years. The potential average 6-month return on investment of 9.31% from 1 November 2007 to 31 October 2011 indicates that the proposed procedure can be considered a feasible and effective tool for making outstanding investment plans, and thus making profits in the Taiwan stock market. Moreover, it is a strategy that can help investors to make profits even when the overall stock market suffers a loss.

Portfolio theory of optimal isometric force production: Variability predictions and nonequilibrium fluctuation dissipation theorem

NASA Astrophysics Data System (ADS)

Frank, T. D.; Patanarapeelert, K.; Beek, P. J.

2008-05-01

We derive a fundamental relationship between the mean and the variability of isometric force. The relationship arises from an optimal collection of active motor units such that the force variability assumes a minimum (optimal isometric force). The relationship is shown to be independent of the explicit motor unit properties and of the dynamical features of isometric force production. A constant coefficient of variation in the asymptotic regime and a nonequilibrium fluctuation-dissipation theorem for optimal isometric force are predicted.

Conflicts in Coalitions: A Stability Analysis of Robust Multi-City Regional Water Supply Portfolios

NASA Astrophysics Data System (ADS)

Gold, D.; Trindade, B. C.; Reed, P. M.; Characklis, G. W.

2017-12-01

Regional cooperation among water utilities can improve the robustness of urban water supply portfolios to deeply uncertain future conditions such as those caused by climate change or population growth. Coordination mechanisms such as water transfers, coordinated demand management, and shared infrastructure, can improve the efficiency of resource allocation and delay the need for new infrastructure investments. Regionalization does however come at a cost. Regionally coordinated water supply plans may be vulnerable to any emerging instabilities in the regional coalition. If one or more regional actors does not cooperate or follow the required regional actions in a time of crisis, the overall system performance may degrade. Furthermore, when crafting regional water supply portfolios, decision makers must choose a framework for measuring the performance of regional policies based on the evaluation of the objective values for each individual actor. Regional evaluations may inherently favor one actor's interests over those of another. This work focuses on four interconnected water utilities in the Research Triangle region of North Carolina for which robust regional water supply portfolios have previously been designed using multi-objective optimization to maximize the robustness of the worst performing utility across several objectives. This study 1) examines the sensitivity of portfolio performance to deviations from prescribed actions by individual utilities, 2) quantifies the implications of the regional formulation used to evaluate robustness for the portfolio performance of each individual utility and 3) elucidates the inherent regional tensions and conflicts that exist between utilities under this regionalization scheme through visual diagnostics of the system under simulated drought scenarios. Results of this analysis will help inform the creation of future regional water supply portfolios and provide insight into the nature of multi-actor water supply systems.

Portfolio Development and the Assessment of Prior Learning: Perspectives, Models and Practices. Second Edition

ERIC Educational Resources Information Center

Michelson, Elana; Mandell, Alan

2004-01-01

For over thirty years, portfolios have been used to help adult learners gain recognition for their prior learning and take greater control of their educational experiences. The portfolio has become a distinctive means of assessing such learning, serving as a meaningful alternative to conventional papers and standardized testing. This book provides…

Local Politics and Portfolio Management Models: National Reform Ideas and Local Control

ERIC Educational Resources Information Center

Bulkley, Katrina E.; Henig, Jeffrey R.

2015-01-01

Amid the growth of charter schools, autonomous schools, and private management organizations, an increasing number of urban districts are moving toward a portfolio management model (PMM). In a PMM, the district central office oversees schools that operate under a variety of governance models. The expansion of PMMs raises questions about local…

Critical asset and portfolio risk analysis: an all-hazards framework.

PubMed

Ayyub, Bilal M; McGill, William L; Kaminskiy, Mark

2007-08-01

This article develops a quantitative all-hazards framework for critical asset and portfolio risk analysis (CAPRA) that considers both natural and human-caused hazards. Following a discussion on the nature of security threats, the need for actionable risk assessments, and the distinction between asset and portfolio-level analysis, a general formula for all-hazards risk analysis is obtained that resembles the traditional model based on the notional product of consequence, vulnerability, and threat, though with clear meanings assigned to each parameter. Furthermore, a simple portfolio consequence model is presented that yields first-order estimates of interdependency effects following a successful attack on an asset. Moreover, depending on the needs of the decisions being made and available analytical resources, values for the parameters in this model can be obtained at a high level or through detailed systems analysis. Several illustrative examples of the CAPRA methodology are provided.

Learning to Select Supplier Portfolios for Service Supply Chain

PubMed Central

Zhang, Rui; Li, Jingfei; Wu, Shaoyu; Meng, Dabin

2016-01-01

The research on service supply chain has attracted more and more focus from both academia and industrial community. In a service supply chain, the selection of supplier portfolio is an important and difficult problem due to the fact that a supplier portfolio may include multiple suppliers from a variety of fields. To address this problem, we propose a novel supplier portfolio selection method based on a well known machine learning approach, i.e., Ranking Neural Network (RankNet). In the proposed method, we regard the problem of supplier portfolio selection as a ranking problem, which integrates a large scale of decision making features into a ranking neural network. Extensive simulation experiments are conducted, which demonstrate the feasibility and effectiveness of the proposed method. The proposed supplier portfolio selection model can be applied in a real corporation easily in the future. PMID:27195756

Myopia management: multihospital portfolio planning.

PubMed

Irish, G G

1987-10-01

The acquisition and divestiture of organizational business units demonstrate management's strategy in response to an evolving marketplace. From a strategic perspective, the most significant danger to a corporation is not having the "right" portfolio of businesses or products to respond to the marketplace. This article describes a conceptual model that a multihospital system executive might use to determine the growth and diversification of the organization's portfolio of businesses. The model involves the application of market, financial, and microeconomic theories in a logical sequence to assist management in making business acquisition and divestiture decisions.

Transitioning from Students to Professionals: Using a Writing across the Curriculum Model to Scaffold Portfolio Development

ERIC Educational Resources Information Center

Elliott, Lori; Daily, Nancy Lee; Fredricks, Lori; Graham, Meadow Sherrill

2008-01-01

Teacher educators have found portfolios to be a valuable way to judge readiness for student-teaching and initial certification as well as an effective means of examining and validating teacher preparation programs. Tension exists between using the portfolio as a product for evaluation and maintaining its focus as a personal examination, synthesis,…

Portfolio Practices in Higher Education in Norway in an International Perspective: Macro-, Meso- and Micro-Level Influences

ERIC Educational Resources Information Center

Dysthe, Olga; Engelsen, Knut Steinar

2011-01-01

The point of departure for this article is the "chameleon" aspect of portfolios and the diversity of portfolio models and practices in higher education on the international arena today. Our aim is to investigate the contextual character of this diversity by using Norwegian higher education as an example and to show how macro-level…

Are Integrated Portfolio Systems the Answer? An Evaluation of a Web-Based Portfolio System to Improve Preservice Teachers' Reflective Thinking Skills

ERIC Educational Resources Information Center

Oner, Diler; Adadan, Emine

2016-01-01

This study investigated the effectiveness of an integrated web-based portfolio system, namely the BOUNCE System, which primarily focuses on improving preservice teachers' reflective thinking skills. BOUNCE©, the software component of the system, was designed and developed to support a teaching practice model including a cycle of activities to be…

Reflective Practice: The Scholarship of Teaching and Learning. The CEET Faculty Development Program on Teaching and Learning. Second Edition: 2009 College Portfolio. Volumes I-IV

ERIC Educational Resources Information Center

Scarborough, Jule Dee

2009-01-01

"2009 Portfolio: The Second Edition of the College of Engineering's Portfolio" presents the 2009 Faculty Development Program on Teaching & Learning (TL) new content, modified models, new process and procedures, especially the new Instructional Analysis and Design Process Map, new PowerPoint presentations, modified teaching and…

Markov model of the loan portfolio dynamics considering influence of management and external economic factors

NASA Astrophysics Data System (ADS)

Bozhalkina, Yana; Timofeeva, Galina

2016-12-01

Mathematical model of loan portfolio in the form of a controlled Markov chain with discrete time is considered. It is assumed that coefficients of migration matrix depend on corrective actions and external factors. Corrective actions include process of receiving applications, interaction with existing solvent and insolvent clients. External factors are macroeconomic indicators, such as inflation and unemployment rates, exchange rates, consumer price indices, etc. Changes in corrective actions adjust the intensity of transitions in the migration matrix. The mathematical model for forecasting the credit portfolio structure taking into account a cumulative impact of internal and external changes is obtained.

High throughput ADME screening: practical considerations, impact on the portfolio and enabler of in silico ADME models.

PubMed

Hop, Cornelis E C A; Cole, Mark J; Davidson, Ralph E; Duignan, David B; Federico, James; Janiszewski, John S; Jenkins, Kelly; Krueger, Suzanne; Lebowitz, Rebecca; Liston, Theodore E; Mitchell, Walter; Snyder, Mark; Steyn, Stefan J; Soglia, John R; Taylor, Christine; Troutman, Matt D; Umland, John; West, Michael; Whalen, Kevin M; Zelesky, Veronica; Zhao, Sabrina X

2008-11-01

Evaluation and optimization of drug metabolism and pharmacokinetic data plays an important role in drug discovery and development and several reliable in vitro ADME models are available. Recently higher throughput in vitro ADME screening facilities have been established in order to be able to evaluate an appreciable fraction of synthesized compounds. The ADME screening process can be dissected in five distinct steps: (1) plate management of compounds in need of in vitro ADME data, (2) optimization of the MS/MS method for the compounds, (3) in vitro ADME experiments and sample clean up, (4) collection and reduction of the raw LC-MS/MS data and (5) archival of the processed ADME data. All steps will be described in detail and the value of the data on drug discovery projects will be discussed as well. Finally, in vitro ADME screening can generate large quantities of data obtained under identical conditions to allow building of reliable in silico models.

Data centers as dispatchable loads to harness stranded power

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

Kim, Kibaek; Yang, Fan; Zavala, Victor M.

Here, we analyze how traditional data center placement and optimal placement of dispatchable data centers affect power grid efficiency. We use detailed network models, stochastic optimization formulations, and diverse renewable generation scenarios to perform our analysis. Our results reveal that significant spillage and stranded power will persist in power grids as wind power levels are increased. A counter-intuitive finding is that collocating data centers with inflexible loads next to wind farms has limited impacts on renewable portfolio standard (RPS) goals because it provides limited system-level flexibility. Such an approach can, in fact, increase stranded power and fossil-fueled generation. In contrast,more » optimally placing data centers that are dispatchable provides system-wide flexibility, reduces stranded power, and improves efficiency. In short, optimally placed dispatchable computing loads can enable better scaling to high RPS. In our case study, we find that these dispatchable computing loads are powered to 60-80% of their requested capacity, indicating that there are significant economic incentives provided by stranded power.« less

Data centers as dispatchable loads to harness stranded power

DOE PAGES

Kim, Kibaek; Yang, Fan; Zavala, Victor M.; ...

2016-07-20

Here, we analyze how traditional data center placement and optimal placement of dispatchable data centers affect power grid efficiency. We use detailed network models, stochastic optimization formulations, and diverse renewable generation scenarios to perform our analysis. Our results reveal that significant spillage and stranded power will persist in power grids as wind power levels are increased. A counter-intuitive finding is that collocating data centers with inflexible loads next to wind farms has limited impacts on renewable portfolio standard (RPS) goals because it provides limited system-level flexibility. Such an approach can, in fact, increase stranded power and fossil-fueled generation. In contrast,more » optimally placing data centers that are dispatchable provides system-wide flexibility, reduces stranded power, and improves efficiency. In short, optimally placed dispatchable computing loads can enable better scaling to high RPS. In our case study, we find that these dispatchable computing loads are powered to 60-80% of their requested capacity, indicating that there are significant economic incentives provided by stranded power.« less

Market Intelligence Guide

DTIC Science & Technology

2012-01-05

learn about the latest designs , trends in fashion, and scientific breakthroughs in chair ergonomics . Using this tradeshow, the Furnishings Commodity...these tools is essential to designing the optimal contract that reaps the most value from the exchange. Therefore, this market intelligence guide is...portfolio matrix) that are transferrable to the not-for-profit sector are absent. Each of these tools is essential to designing the optimal contract that

Investment strategy due to the minimization of portfolio noise level by observations of coarse-grained entropy

NASA Astrophysics Data System (ADS)

Urbanowicz, Krzysztof; Hołyst, Janusz A.

2004-12-01

Using a recently developed method of noise level estimation that makes use of properties of the coarse-grained entropy, we have analyzed the noise level for the Dow Jones index and a few stocks from the New York Stock Exchange. We have found that the noise level ranges from 40% to 80% of the signal variance. The condition of a minimal noise level has been applied to construct optimal portfolios from selected shares. We show that the implementation of a corresponding threshold investment strategy leads to positive returns for historical data.

Random matrix theory and portfolio optimization in Moroccan stock exchange

NASA Astrophysics Data System (ADS)

El Alaoui, Marwane

2015-09-01

In this work, we use random matrix theory to analyze eigenvalues and see if there is a presence of pertinent information by using Marčenko-Pastur distribution. Thus, we study cross-correlation among stocks of Casablanca Stock Exchange. Moreover, we clean correlation matrix from noisy elements to see if the gap between predicted risk and realized risk would be reduced. We also analyze eigenvectors components distributions and their degree of deviations by computing the inverse participation ratio. This analysis is a way to understand the correlation structure among stocks of Casablanca Stock Exchange portfolio.

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.…

Developing a Model for ePortfolio Design: A Studio Approach

ERIC Educational Resources Information Center

Carpenter, Russell; Apostel, Shawn; Hyndman, June Overton

2012-01-01

After developing and testing a model for integrative collaboration at Eastern Kentucky University's Noel Studio for Academic Creativity, we offer results that highlight the potential for peer review to significantly and positively impact the ePortfolio design process for students. The results of this classroom/studio collaboration suggest that…

A Qualitative Approach to Portfolios: The Early Assessment for Exceptional Potential Model.

ERIC Educational Resources Information Center

Shaklee, Beverly D.; Viechnicki, Karen J.

1995-01-01

The Early Assessment for Exceptional Potential portfolio assessment model assesses children as exceptional learners, users, generators, and pursuers of knowledge. It is based on use of authentic learning opportunities; interaction of assessment, curriculum, and instruction; multiple criteria derived from multiple sources; and systematic teacher…

Profiles and portfolios of adolescent school-based extracurricular activity participation.

PubMed

Feldman, A F; Matjasko, J L

2007-04-01

The current study presented a new description of adolescent school-based activity participation, in the form of mutually exclusive activity portfolios, and described the kinds of youth that participate in each portfolio. These portfolios included (1) Sports Only, (2) Academics Only, (3) School Only, (4) Performance Only, (5) Multiple Activities, and (6) Non-Participation. Findings indicated that youth demographic characteristics and school size differentiated between different kinds of activity participation as well as nonparticipation. More detailed activity portfolios were also identified that were complex and demonstrate the difficulty of examining participation beyond larger, more inclusive groupings. The Multiple Activity portfolio emerged as a unique group worthy of further examination. Characteristics of non-participators included: lower socioeconomic status, lower grades, and attended larger schools. Hispanic adolescents were also less likely to participate in school-based extracurricular activities. Findings from this study inform ecological models of adolescent development as well as school and social policy.

Studies on combined model based on functional objectives of large scale complex engineering

NASA Astrophysics Data System (ADS)

Yuting, Wang; Jingchun, Feng; Jiabao, Sun

2018-03-01

As various functions were included in large scale complex engineering, and each function would be conducted with completion of one or more projects, combined projects affecting their functions should be located. Based on the types of project portfolio, the relationship of projects and their functional objectives were analyzed. On that premise, portfolio projects-technics based on their functional objectives were introduced, then we studied and raised the principles of portfolio projects-technics based on the functional objectives of projects. In addition, The processes of combined projects were also constructed. With the help of portfolio projects-technics based on the functional objectives of projects, our research findings laid a good foundation for management of large scale complex engineering portfolio management.

A portfolio approach to evaluating natural hazard mitigation policies: An Application to lateral-spread ground failure in Coastal California

USGS Publications Warehouse

Bernknopf, R.L.; Dinitz, L.B.; Rabinovici, S.J.M.; Evans, A.M.

2001-01-01

In the past, efforts to prevent catastrophic losses from natural hazards have largely been undertaken by individual property owners based on site-specific evaluations of risks to particular buildings. Public efforts to assess community vulnerability and encourage mitigation have focused on either aggregating site-specific estimates or adopting standards based upon broad assumptions about regional risks. This paper develops an alternative, intermediate-scale approach to regional risk assessment and the evaluation of community mitigation policies. Properties are grouped into types with similar land uses and levels of hazard, and hypothetical community mitigation strategies for protecting these properties are modeled like investment portfolios. The portfolios consist of investments in mitigation against the risk to a community posed by a specific natural hazard, and are defined by a community's mitigation budget and the proportion of the budget invested in locations of each type. The usefulness of this approach is demonstrated through an integrated assessment of earthquake-induced lateral-spread ground failure risk in the Watsonville, California area. Data from the magnitude 6.9 Loma Prieta earthquake of 1989 are used to model lateral-spread ground failure susceptibility. Earth science and economic data are combined and analyzed in a Geographic Information System (GIS). The portfolio model is then used to evaluate the benefits of mitigating the risk in different locations. Two mitigation policies, one that prioritizes mitigation by land use type and the other by hazard zone, are compared with a status quo policy of doing no further mitigation beyond that which already exists. The portfolio representing the hazard zone rule yields a higher expected return than the land use portfolio does: However, the hazard zone portfolio experiences a higher standard deviation. Therefore, neither portfolio is clearly preferred. The two mitigation policies both reduce expected losses and increase overall expected community wealth compared to the status quo policy.

Business Model Evaluation for an Advanced Multimedia Service Portfolio

NASA Astrophysics Data System (ADS)

Pisciella, Paolo; Zoric, Josip; Gaivoronski, Alexei A.

In this paper we analyze quantitatively a business model for the collaborative provision of an advanced mobile data service portfolio composed of three multimedia services: Video on Demand, Internet Protocol Television and User Generated Content. We provide a description of the provision system considering the relation occurring between tecnical aspects and business aspects for each agent providing the basic multimedia service. Such a techno-business analysis is then projected into a mathematical model dealing with the problem of the definition of incentives between the different agents involved in a collaborative service provision. Through the implementation of this model we aim at shaping the behaviour of each of the contributing agents modifying the level of profitability that the Service Portfolio yields to each of them.

Neural network for solving convex quadratic bilevel programming problems.

PubMed

He, Xing; Li, Chuandong; Huang, Tingwen; Li, Chaojie

2014-03-01

In this paper, using the idea of successive approximation, we propose a neural network to solve convex quadratic bilevel programming problems (CQBPPs), which is modeled by a nonautonomous differential inclusion. Different from the existing neural network for CQBPP, the model has the least number of state variables and simple structure. Based on the theory of nonsmooth analysis, differential inclusions and Lyapunov-like method, the limit equilibrium points sequence of the proposed neural networks can approximately converge to an optimal solution of CQBPP under certain conditions. Finally, simulation results on two numerical examples and the portfolio selection problem show the effectiveness and performance of the proposed neural network. Copyright © 2013 Elsevier Ltd. All rights reserved.

How to manage future groundwater resource of China under climate change and urbanization: An optimal stage investment design from modern portfolio theory.

PubMed

Hua, Shanshan; Liang, Jie; Zeng, Guangming; Xu, Min; Zhang, Chang; Yuan, Yujie; Li, Xiaodong; Li, Ping; Liu, Jiayu; Huang, Lu

2015-11-15

Groundwater management in China has been facing challenges from both climate change and urbanization and is considered as a national priority nowadays. However, unprecedented uncertainty exists in future scenarios making it difficult to formulate management planning paradigms. In this paper, we apply modern portfolio theory (MPT) to formulate an optimal stage investment of groundwater contamination remediation in China. This approach generates optimal weights of investment to each stage of the groundwater management and helps maximize expected return while minimizing overall risk in the future. We find that the efficient frontier of investment displays an upward-sloping shape in risk-return space. The expected value of groundwater vulnerability index increases from 0.6118 to 0.6230 following with the risk of uncertainty increased from 0.0118 to 0.0297. If management investment is constrained not to exceed certain total cost until 2050 year, the efficient frontier could help decision makers make the most appropriate choice on the trade-off between risk and return. Copyright © 2015 Elsevier Ltd. All rights reserved.

Developing Water Resource Security in a Greenhouse Gas Constrained Context - A Case Study in California

NASA Astrophysics Data System (ADS)

Tarroja, B.; Aghakouchak, A.; Samuelsen, S.

2015-12-01

The onset of drought conditions in regions such as California due to shortfalls in precipitation has brought refreshed attention to the vulnerability of our water supply paradigm to changes in climate patterns. In the face of a changing climate which can exacerbate drought conditions in already dry areas, building resiliency into our water supply infrastructure requires some decoupling of water supply availability from climate behavior through conservation, efficiency, and alternative water supply measures such as desalination and water reuse. The installation of these measures requires varying degrees of direct energy inputs and/or impacts the energy usage of the water supply infrastructure (conveyance, treatment, distribution, wastewater treatment). These impacts have implications for greenhouse gas emissions from direct fuel usage or impacts on the emissions from the electric grid. At the scale that these measures may need to be deployed to secure water supply availability, especially under climate change impacted hydrology, they can potentially pose obstacles for meeting greenhouse gas emissions reduction and renewable utilization goals. Therefore, the portfolio of these measures must be such that detrimental impacts on greenhouse gas emissions are minimized. This study combines climate data with a water reservoir network model and an electric grid dispatch model for the water-energy system of California to evaluate 1) the different pathways and scale of alternative water resource measures needed to secure water supply availability and 2) the impacts of following these pathways on the ability to meet greenhouse gas and renewable utilization goals. It was discovered that depending on the water supply measure portfolio implemented, impacts on greenhouse gas emissions and renewable utilization can either be beneficial or detrimental, and optimizing the portfolio is more important under climate change conditions due to the scale of measures required.

Random matrix theory filters and currency portfolio optimisation

NASA Astrophysics Data System (ADS)

Daly, J.; Crane, M.; Ruskin, H. J.

2010-04-01

Random matrix theory (RMT) filters have recently been shown to improve the optimisation of financial portfolios. This paper studies the effect of three RMT filters on realised portfolio risk, using bootstrap analysis and out-of-sample testing. We considered the case of a foreign exchange and commodity portfolio, weighted towards foreign exchange, and consisting of 39 assets. This was intended to test the limits of RMT filtering, which is more obviously applicable to portfolios with larger numbers of assets. We considered both equally and exponentially weighted covariance matrices, and observed that, despite the small number of assets involved, RMT filters reduced risk in a way that was consistent with a much larger S&P 500 portfolio. The exponential weightings indicated showed good consistency with the value suggested by Riskmetrics, in contrast to previous results involving stocks. This decay factor, along with the low number of past moves preferred in the filtered, equally weighted case, displayed a trend towards models which were reactive to recent market changes. On testing portfolios with fewer assets, RMT filtering provided less or no overall risk reduction. In particular, no long term out-of-sample risk reduction was observed for a portfolio consisting of 15 major currencies and commodities.

Students' reflections in a portfolio pilot: highlighting professional issues.

PubMed

Haffling, Ann-Christin; Beckman, Anders; Pahlmblad, Annika; Edgren, Gudrun

2010-01-01

Portfolios are highlighted as potential assessment tools for professional competence. Although students' self-reflections are considered to be central in the portfolio, the content of reflections in practice-based portfolios is seldom analysed. To investigate whether students' reflections include sufficient dimensions of professional competence, notwithstanding a standardized portfolio format, and to evaluate students' satisfaction with the portfolio. Thirty-five voluntary final-year medical students piloted a standardized portfolio in a general practice (GP) attachment at Lund University, Sweden. Students' portfolio reflections were based upon documentary evidence from practice, and aimed to demonstrate students' learning. The reflections were qualitatively analysed, using a framework approach. Students' evaluations of the portfolio were subjected to quantitative and qualitative analysis. Among professional issues, an integration of cognitive, affective and practical dimensions in clinical practice was provided by students' reflections. The findings suggested an emphasis on affective issues, particularly on self-awareness of feelings, attitudes and concerns. In addition, ethical problems, clinical reasoning strategies and future communication skills training were subjects of several reflective commentaries. Students' reflections on their consultation skills demonstrated their endeavour to achieve structure in the medical interview by negotiation of an agenda for the consultation, keeping the interview on track, and using internal summarizing. The importance of active listening and exploration of patient's perspective was also emphasized. In students' case summaries, illustrating characteristic attributes of GP, the dominating theme was 'patient-centred care', including the patient-doctor relationship, holistic modelling and longitudinal continuity. Students were satisfied with the portfolio, but improved instructions were needed. A standardized portfolio in a defined course with a limited timeframe provided ample opportunities for reflections on professional issues. Support by mentors and a final examiner interview contributed to the success of the portfolio with students. The interview also allowed students to deepen their reflections and to receive feedback.

q-Gaussian distributions of leverage returns, first stopping times, and default risk valuations

NASA Astrophysics Data System (ADS)

Katz, Yuri A.; Tian, Li

2013-10-01

We study the probability distributions of daily leverage returns of 520 North American industrial companies that survive de-listing during the financial crisis, 2006-2012. We provide evidence that distributions of unbiased leverage returns of all individual firms belong to the class of q-Gaussian distributions with the Tsallis entropic parameter within the interval 1

Authentic assessment based showcase portfolio on learning of mathematical problem solving in senior high school

NASA Astrophysics Data System (ADS)

Sukmawati, Zuhairoh, Faihatuz

2017-05-01

The purpose of this research was to develop authentic assessment model based on showcase portfolio on learning of mathematical problem solving. This research used research and development Method (R & D) which consists of four stages of development that: Phase I, conducting a preliminary study. Phase II, determining the purpose of developing and preparing the initial model. Phase III, trial test of instrument for the initial draft model and the initial product. The respondents of this research are the students of SMAN 8 and SMAN 20 Makassar. The collection of data was through observation, interviews, documentation, student questionnaire, and instrument tests mathematical solving abilities. The data were analyzed with descriptive and inferential statistics. The results of this research are authentic assessment model design based on showcase portfolio which involves: 1) Steps in implementing the authentic assessment based Showcase, assessment rubric of cognitive aspects, assessment rubric of affective aspects, and assessment rubric of skill aspect. 2) The average ability of the students' problem solving which is scored by using authentic assessment based on showcase portfolio was in high category and the students' response in good category.

Developing evaluation instrument based on CIPP models on the implementation of portfolio assessment

NASA Astrophysics Data System (ADS)

Kurnia, Feni; Rosana, Dadan; Supahar

2017-08-01

This study aimed to develop an evaluation instrument constructed by CIPP model on the implementation of portfolio assessment in science learning. This study used research and development (R & D) method; adapting 4-D by the development of non-test instrument, and the evaluation instrument constructed by CIPP model. CIPP is the abbreviation of Context, Input, Process, and Product. The techniques of data collection were interviews, questionnaires, and observations. Data collection instruments were: 1) the interview guidelines for the analysis of the problems and the needs, 2) questionnaire to see level of accomplishment of portfolio assessment instrument, and 3) observation sheets for teacher and student to dig up responses to the portfolio assessment instrument. The data obtained was quantitative data obtained from several validators. The validators consist of two lecturers as the evaluation experts, two practitioners (science teachers), and three colleagues. This paper shows the results of content validity obtained from the validators and the analysis result of the data obtained by using Aikens' V formula. The results of this study shows that the evaluation instrument based on CIPP models is proper to evaluate the implementation of portfolio assessment instruments. Based on the experts' judgments, practitioners, and colleagues, the Aikens' V coefficient was between 0.86-1,00 which means that it is valid and can be used in the limited trial and operational field trial.

Flightdeck Automation Problems (FLAP) Model for Safety Technology Portfolio Assessment

NASA Technical Reports Server (NTRS)

Ancel, Ersin; Shih, Ann T.

2014-01-01

NASA's Aviation Safety Program (AvSP) develops and advances methodologies and technologies to improve air transportation safety. The Safety Analysis and Integration Team (SAIT) conducts a safety technology portfolio assessment (PA) to analyze the program content, to examine the benefits and risks of products with respect to program goals, and to support programmatic decision making. The PA process includes systematic identification of current and future safety risks as well as tracking several quantitative and qualitative metrics to ensure the program goals are addressing prominent safety risks accurately and effectively. One of the metrics within the PA process involves using quantitative aviation safety models to gauge the impact of the safety products. This paper demonstrates the role of aviation safety modeling by providing model outputs and evaluating a sample of portfolio elements using the Flightdeck Automation Problems (FLAP) model. The model enables not only ranking of the quantitative relative risk reduction impact of all portfolio elements, but also highlighting the areas with high potential impact via sensitivity and gap analyses in support of the program office. Although the model outputs are preliminary and products are notional, the process shown in this paper is essential to a comprehensive PA of NASA's safety products in the current program and future programs/projects.

NREL Multiphysics Modeling Tools and ISC Device for Designing Safer Li-Ion Batteries

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

Pesaran, Ahmad A.; Yang, Chuanbo

2016-03-24

The National Renewable Energy Laboratory has developed a portfolio of multiphysics modeling tools to aid battery designers better understand the response of lithium ion batteries to abusive conditions. We will discuss this portfolio, which includes coupled electrical, thermal, chemical, electrochemical, and mechanical modeling. These models can simulate the response of a cell to overheating, overcharge, mechanical deformation, nail penetration, and internal short circuit. Cell-to-cell thermal propagation modeling will be discussed.

Uncertain programming models for portfolio selection with uncertain returns

NASA Astrophysics Data System (ADS)

Zhang, Bo; Peng, Jin; Li, Shengguo

2015-10-01

In an indeterminacy economic environment, experts' knowledge about the returns of securities consists of much uncertainty instead of randomness. This paper discusses portfolio selection problem in uncertain environment in which security returns cannot be well reflected by historical data, but can be evaluated by the experts. In the paper, returns of securities are assumed to be given by uncertain variables. According to various decision criteria, the portfolio selection problem in uncertain environment is formulated as expected-variance-chance model and chance-expected-variance model by using the uncertainty programming. Within the framework of uncertainty theory, for the convenience of solving the models, some crisp equivalents are discussed under different conditions. In addition, a hybrid intelligent algorithm is designed in the paper to provide a general method for solving the new models in general cases. At last, two numerical examples are provided to show the performance and applications of the models and algorithm.

The difference between LSMC and replicating portfolio in insurance liability modeling.

PubMed

Pelsser, Antoon; Schweizer, Janina

2016-01-01

Solvency II requires insurers to calculate the 1-year value at risk of their balance sheet. This involves the valuation of the balance sheet in 1 year's time. As for insurance liabilities, closed-form solutions to their value are generally not available, insurers turn to estimation procedures. While pure Monte Carlo simulation set-ups are theoretically sound, they are often infeasible in practice. Therefore, approximation methods are exploited. Among these, least squares Monte Carlo (LSMC) and portfolio replication are prominent and widely applied in practice. In this paper, we show that, while both are variants of regression-based Monte Carlo methods, they differ in one significant aspect. While the replicating portfolio approach only contains an approximation error, which converges to zero in the limit, in LSMC a projection error is additionally present, which cannot be eliminated. It is revealed that the replicating portfolio technique enjoys numerous advantages and is therefore an attractive model choice.

GRA prospectus: optimizing design and management of protected areas

USGS Publications Warehouse

Bernknopf, Richard; Halsing, David

2001-01-01

Protected areas comprise one major type of global conservation effort that has been in the form of parks, easements, or conservation concessions. Though protected areas are increasing in number and size throughout tropical ecosystems, there is no systematic method for optimally targeting specific local areas for protection, designing the protected area, and monitoring it, or for guiding follow-up actions to manage it or its surroundings over the long run. Without such a system, conservation projects often cost more than necessary and/or risk protecting ecosystems and biodiversity less efficiently than desired. Correcting these failures requires tools and strategies for improving the placement, design, and long-term management of protected areas. The objective of this project is to develop a set of spatially based analytical tools to improve the selection, design, and management of protected areas. In this project, several conservation concessions will be compared using an economic optimization technique. The forest land use portfolio model is an integrated assessment that measures investment in different land uses in a forest. The case studies of individual tropical ecosystems are developed as forest (land) use and preservation portfolios in a geographic information system (GIS). Conservation concessions involve a private organization purchasing development and resource access rights in a certain area and retiring them. Forests are put into conservation, and those people who would otherwise have benefited from extracting resources or selling the right to do so are compensated. Concessions are legal agreements wherein the exact amount and nature of the compensation result from a negotiated agreement between an agent of the conservation community and the local community. Funds are placed in a trust fund, and annual payments are made to local communities and regional/national governments. The payments are made pending third-party verification that the forest expanse and quality have been maintained.

An e-Portfolio-Based Model for the Application and Sharing of College English ESP MOOCs

ERIC Educational Resources Information Center

Chen, Jinshi

2017-01-01

The informationalized knowledge sharing of MOOCs not only promotes the change of teaching concept and the reform of teaching methodology, but also provides a new opportunity for the teaching resource integration and sharing between different universities. The present study has constructed an e-Portfolio-based model for the application and sharing…

Adding MUFA to a dietary portfolio of cholesterol-lowering foods reduces apoAI fractional catabolic rate in subjects with dyslipidaemia.

PubMed

Labonté, Marie-Ève; Jenkins, David J A; Lewis, Gary F; Chiavaroli, Laura; Wong, Julia M W; Kendall, Cyril W C; Hogue, Jean-Charles; Couture, Patrick; Lamarche, Benoît

2013-08-28

The present randomised parallel study assessed the impact of adding MUFA to a dietary portfolio of cholesterol-lowering foods on the intravascular kinetics of apoAI- and apoB-containing lipoproteins in subjects with dyslipidaemia. A sample of sixteen men and postmenopausal women consumed a run-in stabilisation diet for 4 weeks. Subjects were then randomly assigned to an experimental dietary portfolio either high or low in MUFA for another 4 weeks. MUFA substituted 13·0% of total energy from carbohydrate (CHO) in the high-MUFA dietary portfolio. Lipoprotein kinetics were assessed after the run-in and portfolio diets using a primed, constant infusion of [2H3]leucine and multicompartmental modelling. The high-MUFA dietary portfolio resulted in higher apoAI pool size (PS) compared with the low-MUFA dietary portfolio (15·9% between-diet difference, P¼0·03). This difference appeared to be mainly attributable to a reduction in apoAI fractional catabolic rate (FCR) after the high-MUFA diet (25·6%, P¼0·02 v. pre-diet values), with no significant change in production rate. The high-MUFA dietary portfolio tended to reduce LDL apoB100 PS compared with the low-MUFA dietary portfolio (228·5% between-diet that adding MUFA to a dietary portfolio of cholesterol-lowering foods provides the added advantage of raising HDL primarily through a reduction in HDL clearance rate. Replacing CHO with MUFA in a dietary portfolio may also lead to reductions in LDL apoB100 concentrations primarily by increasing LDL clearance rate, thus potentiating further the well-known cholesterol-lowering effect of this diet.

Portfolio choice in retirement: Health risk and the demand for annuities, housing, and risky assets*

PubMed Central

Yogo, Motohiro

2016-01-01

In a life-cycle model, a retiree faces stochastic health depreciation and chooses consumption, health expenditure, and the allocation of wealth between bonds, stocks, and housing. The model explains key facts about asset allocation and health expenditure across health status and age. The portfolio share in stocks is low overall and is positively related to health, especially for younger retirees. The portfolio share in housing is negatively related to health for younger retirees and falls significantly in age. Finally, out-of-pocket health expenditure as a share of income is negatively related to health and rises in age. PMID:27766005

Portfolio choice in retirement: Health risk and the demand for annuities, housing, and risky assets.

PubMed

Yogo, Motohiro

2016-06-01

In a life-cycle model, a retiree faces stochastic health depreciation and chooses consumption, health expenditure, and the allocation of wealth between bonds, stocks, and housing. The model explains key facts about asset allocation and health expenditure across health status and age. The portfolio share in stocks is low overall and is positively related to health, especially for younger retirees. The portfolio share in housing is negatively related to health for younger retirees and falls significantly in age. Finally, out-of-pocket health expenditure as a share of income is negatively related to health and rises in age.

Oneida Tribe of Indians of Wisconsin Energy Optimization Model

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

Troge, Michael

2014-12-01

Oneida Nation is located in Northeast Wisconsin. The reservation is approximately 96 square miles (8 miles x 12 miles), or 65,000 acres. The greater Green Bay area is east and adjacent to the reservation. A county line roughly splits the reservation in half; the west half is in Outagamie County and the east half is in Brown County. Land use is predominantly agriculture on the west 2/3 and suburban on the east 1/3 of the reservation. Nearly 5,000 tribally enrolled members live in the reservation with a total population of about 21,000. Tribal ownership is scattered across the reservation andmore » is about 23,000 acres. Currently, the Oneida Tribe of Indians of Wisconsin (OTIW) community members and facilities receive the vast majority of electrical and natural gas services from two of the largest investor-owned utilities in the state, WE Energies and Wisconsin Public Service. All urban and suburban buildings have access to natural gas. About 15% of the population and five Tribal facilities are in rural locations and therefore use propane as a primary heating fuel. Wood and oil are also used as primary or supplemental heat sources for a small percent of the population. Very few renewable energy systems, used to generate electricity and heat, have been installed on the Oneida Reservation. This project was an effort to develop a reasonable renewable energy portfolio that will help Oneida to provide a leadership role in developing a clean energy economy. The Energy Optimization Model (EOM) is an exploration of energy opportunities available to the Tribe and it is intended to provide a decision framework to allow the Tribe to make the wisest choices in energy investment with an organizational desire to establish a renewable portfolio standard (RPS).« less

The Point of No Return? Interest Groups, School Board Elections and the Sustainment of the Portfolio Management Model in Post-Katrina New Orleans

ERIC Educational Resources Information Center

Welsh, Richard; Hall, Michelle

2018-01-01

Context: Given the growing popularity of the portfolio management model (PMM) as a method of improving education, it is important to examine how these market-based reforms are sustained over time and how the politics of sustaining this model have substantial policy implications. Purpose of Study: The purpose of this article is to examine important…

Adding flexibility to the search for robust portfolios in non-linear water resource planning

NASA Astrophysics Data System (ADS)

Tomlinson, James; Harou, Julien

2017-04-01

To date robust optimisation of water supply systems has sought to find portfolios or strategies that are robust to a range of uncertainties or scenarios. The search for a single portfolio that is robust in all scenarios is necessarily suboptimal compared to portfolios optimised for a single scenario deterministic future. By contrast establishing a separate portfolio for each future scenario is unhelpful to the planner who must make a single decision today under deep uncertainty. In this work we show that a middle ground is possible by allowing a small number of different portfolios to be found that are each robust to a different subset of the global scenarios. We use evolutionary algorithms and a simple water resource system model to demonstrate this approach. The primary contribution is to demonstrate that flexibility can be added to the search for portfolios, in complex non-linear systems, at the expense of complete robustness across all future scenarios. In this context we define flexibility as the ability to design a portfolio in which some decisions are delayed, but those decisions that are not delayed are themselves shown to be robust to the future. We recognise that some decisions in our portfolio are more important than others. An adaptive portfolio is found by allowing no flexibility for these near-term "important" decisions, but maintaining flexibility in the remaining longer term decisions. In this sense we create an effective 2-stage decision process for a non-linear water resource supply system. We show how this reduces a measure of regret versus the inflexible robust solution for the same system.

Untangling complex networks: risk minimization in financial markets through accessible spin glass ground states

PubMed Central

Lisewski, Andreas Martin; Lichtarge, Olivier

2010-01-01

Recurrent international financial crises inflict significant damage to societies and stress the need for mechanisms or strategies to control risk and tamper market uncertainties. Unfortunately, the complex network of market interactions often confounds rational approaches to optimize financial risks. Here we show that investors can overcome this complexity and globally minimize risk in portfolio models for any given expected return, provided the relative margin requirement remains below a critical, empirically measurable value. In practice, for markets with centrally regulated margin requirements, a rational stabilization strategy would be keeping margins small enough. This result follows from ground states of the random field spin glass Ising model that can be calculated exactly through convex optimization when relative spin coupling is limited by the norm of the network's Laplacian matrix. In that regime, this novel approach is robust to noise in empirical data and may be also broadly relevant to complex networks with frustrated interactions that are studied throughout scientific fields. PMID:20625477

Untangling complex networks: Risk minimization in financial markets through accessible spin glass ground states

NASA Astrophysics Data System (ADS)

Lisewski, Andreas Martin; Lichtarge, Olivier

2010-08-01

Recurrent international financial crises inflict significant damage to societies and stress the need for mechanisms or strategies to control risk and tamper market uncertainties. Unfortunately, the complex network of market interactions often confounds rational approaches to optimize financial risks. Here we show that investors can overcome this complexity and globally minimize risk in portfolio models for any given expected return, provided the margin requirement remains below a critical, empirically measurable value. In practice, for markets with centrally regulated margin requirements, a rational stabilization strategy would be keeping margins small enough. This result follows from ground states of the random field spin glass Ising model that can be calculated exactly through convex optimization when relative spin coupling is limited by the norm of the network’s Laplacian matrix. In that regime, this novel approach is robust to noise in empirical data and may be also broadly relevant to complex networks with frustrated interactions that are studied throughout scientific fields.

Optimal Solar PV Arrays Integration for Distributed Generation

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

Omitaomu, Olufemi A; Li, Xueping

2012-01-01

Solar photovoltaic (PV) systems hold great potential for distributed energy generation by installing PV panels on rooftops of residential and commercial buildings. Yet challenges arise along with the variability and non-dispatchability of the PV systems that affect the stability of the grid and the economics of the PV system. This paper investigates the integration of PV arrays for distributed generation applications by identifying a combination of buildings that will maximize solar energy output and minimize system variability. Particularly, we propose mean-variance optimization models to choose suitable rooftops for PV integration based on Markowitz mean-variance portfolio selection model. We further introducemore » quantity and cardinality constraints to result in a mixed integer quadratic programming problem. Case studies based on real data are presented. An efficient frontier is obtained for sample data that allows decision makers to choose a desired solar energy generation level with a comfortable variability tolerance level. Sensitivity analysis is conducted to show the tradeoffs between solar PV energy generation potential and variability.« less

Untangling complex networks: risk minimization in financial markets through accessible spin glass ground states.

PubMed

Lisewski, Andreas Martin; Lichtarge, Olivier

2010-08-15

Recurrent international financial crises inflict significant damage to societies and stress the need for mechanisms or strategies to control risk and tamper market uncertainties. Unfortunately, the complex network of market interactions often confounds rational approaches to optimize financial risks. Here we show that investors can overcome this complexity and globally minimize risk in portfolio models for any given expected return, provided the relative margin requirement remains below a critical, empirically measurable value. In practice, for markets with centrally regulated margin requirements, a rational stabilization strategy would be keeping margins small enough. This result follows from ground states of the random field spin glass Ising model that can be calculated exactly through convex optimization when relative spin coupling is limited by the norm of the network's Laplacian matrix. In that regime, this novel approach is robust to noise in empirical data and may be also broadly relevant to complex networks with frustrated interactions that are studied throughout scientific fields.

Model Checking with Multi-Threaded IC3 Portfolios

DTIC Science & Technology

2015-01-15

different runs varies randomly depending on the thread interleaving. The use of a portfolio of solvers to maximize the likelihood of a quick solution is...empirically show (cf. Sec. 5.2) that the predictions based on this formula have high accuracy. Note that each solver in the portfolio potentially searches...speedup of over 300. We also show that widening the proof search of ic3 by randomizing its SAT solver is not as effective as paral- lelization

Optimized spatial priorities for biodiversity conservation in China: a systematic conservation planning perspective.

PubMed

Wu, Ruidong; Long, Yongcheng; Malanson, George P; Garber, Paul A; Zhang, Shuang; Li, Diqiang; Zhao, Peng; Wang, Longzhu; Duo, Hairui

2014-01-01

By addressing several key features overlooked in previous studies, i.e. human disturbance, integration of ecosystem- and species-level conservation features, and principles of complementarity and representativeness, we present the first national-scale systematic conservation planning for China to determine the optimized spatial priorities for biodiversity conservation. We compiled a spatial database on the distributions of ecosystem- and species-level conservation features, and modeled a human disturbance index (HDI) by aggregating information using several socioeconomic proxies. We ran Marxan with two scenarios (HDI-ignored and HDI-considered) to investigate the effects of human disturbance, and explored the geographic patterns of the optimized spatial conservation priorities. Compared to when HDI was ignored, the HDI-considered scenario resulted in (1) a marked reduction (∼9%) in the total HDI score and a slight increase (∼7%) in the total area of the portfolio of priority units, (2) a significant increase (∼43%) in the total irreplaceable area and (3) more irreplaceable units being identified in almost all environmental zones and highly-disturbed provinces. Thus the inclusion of human disturbance is essential for cost-effective priority-setting. Attention should be targeted to the areas that are characterized as moderately-disturbed, <2,000 m in altitude, and/or intermediately- to extremely-rugged in terrain to identify potentially important regions for implementing cost-effective conservation. We delineated 23 primary large-scale priority areas that are significant for conserving China's biodiversity, but those isolated priority units in disturbed regions are in more urgent need of conservation actions so as to prevent immediate and severe biodiversity loss. This study presents a spatially optimized national-scale portfolio of conservation priorities--effectively representing the overall biodiversity of China while minimizing conflicts with economic development. Our results offer critical insights for current conservation and strategic land-use planning in China. The approach is transferable and easy to implement by end-users, and applicable for national- and local-scale systematic conservation prioritization practices.

Optimized Spatial Priorities for Biodiversity Conservation in China: A Systematic Conservation Planning Perspective

PubMed Central

Wu, Ruidong; Long, Yongcheng; Malanson, George P.; Garber, Paul A.; Zhang, Shuang; Li, Diqiang; Zhao, Peng; Wang, Longzhu; Duo, Hairui

2014-01-01

By addressing several key features overlooked in previous studies, i.e. human disturbance, integration of ecosystem- and species-level conservation features, and principles of complementarity and representativeness, we present the first national-scale systematic conservation planning for China to determine the optimized spatial priorities for biodiversity conservation. We compiled a spatial database on the distributions of ecosystem- and species-level conservation features, and modeled a human disturbance index (HDI) by aggregating information using several socioeconomic proxies. We ran Marxan with two scenarios (HDI-ignored and HDI-considered) to investigate the effects of human disturbance, and explored the geographic patterns of the optimized spatial conservation priorities. Compared to when HDI was ignored, the HDI-considered scenario resulted in (1) a marked reduction (∼9%) in the total HDI score and a slight increase (∼7%) in the total area of the portfolio of priority units, (2) a significant increase (∼43%) in the total irreplaceable area and (3) more irreplaceable units being identified in almost all environmental zones and highly-disturbed provinces. Thus the inclusion of human disturbance is essential for cost-effective priority-setting. Attention should be targeted to the areas that are characterized as moderately-disturbed, <2,000 m in altitude, and/or intermediately- to extremely-rugged in terrain to identify potentially important regions for implementing cost-effective conservation. We delineated 23 primary large-scale priority areas that are significant for conserving China's biodiversity, but those isolated priority units in disturbed regions are in more urgent need of conservation actions so as to prevent immediate and severe biodiversity loss. This study presents a spatially optimized national-scale portfolio of conservation priorities – effectively representing the overall biodiversity of China while minimizing conflicts with economic development. Our results offer critical insights for current conservation and strategic land-use planning in China. The approach is transferable and easy to implement by end-users, and applicable for national- and local-scale systematic conservation prioritization practices. PMID:25072933

From Metacognition to Practice Cognition: The DNP e-Portfolio to Promote Integrated Learning.

PubMed

Anderson, Kelley M; DesLauriers, Patricia; Horvath, Catherine H; Slota, Margaret; Farley, Jean Nelson

2017-08-01

Educating Doctor of Nursing Practice (DNP) students for an increasingly complex health care environment requires novel applications of learning concepts and technology. A deliberate and thoughtful process is required to integrate concepts of the DNP program into practice paradigm changes to subsequently improve students' abilities to innovate solutions to complex practice problems. The authors constructed or participated in electronic portfolio development inspired by theories of metacognition and integrated learning. The objective was to develop DNP student's reflection, integration of concepts, and technological capabilities to foster the deliberative competencies related to the DNP Essentials and the foundations of the DNP program. The pedagogical process demonstrates how e-portfolios adapted into the doctoral-level curriculum for DNP students can address the Essentials and foster the development of metacognitive capabilities, which translates into practice changes. The authors suggest that this pedagogical approach has the potential to optimize reflective and deliberative competencies among DNP students. [J Nurs Educ. 2017;56(8):497-500.]. Copyright 2017, SLACK Incorporated.

Development of a web database portfolio system with PACS connectivity for undergraduate health education and continuing professional development.

PubMed

Ng, Curtise K C; White, Peter; McKay, Janice C

2009-04-01

Increasingly, the use of web database portfolio systems is noted in medical and health education, and for continuing professional development (CPD). However, the functions of existing systems are not always aligned with the corresponding pedagogy and hence reflection is often lost. This paper presents the development of a tailored web database portfolio system with Picture Archiving and Communication System (PACS) connectivity, which is based on the portfolio pedagogy. Following a pre-determined portfolio framework, a system model with the components of web, database and mail servers, server side scripts, and a Query/Retrieve (Q/R) broker for conversion between Hypertext Transfer Protocol (HTTP) requests and Q/R service class of Digital Imaging and Communication in Medicine (DICOM) standard, is proposed. The system was piloted with seventy-seven volunteers. A tailored web database portfolio system (http://radep.hti.polyu.edu.hk) was developed. Technological arrangements for reinforcing portfolio pedagogy include popup windows (reminders) with guidelines and probing questions of 'collect', 'select' and 'reflect' on evidence of development/experience, limitation in the number of files (evidence) to be uploaded, the 'Evidence Insertion' functionality to link the individual uploaded artifacts with reflective writing, capability to accommodate diversity of contents and convenient interfaces for reviewing portfolios and communication. Evidence to date suggests the system supports users to build their portfolios with sound hypertext reflection under a facilitator's guidance, and with reviewers to monitor students' progress providing feedback and comments online in a programme-wide situation.

Investigation of Multi-Criteria Decision Consistency: A Triplex Approach to Optimal Oilfield Portfolio Investment Decisions

NASA Astrophysics Data System (ADS)

Qaradaghi, Mohammed

Complexity of the capital intensive oil and gas portfolio investments is continuously growing. It is manifested in the constant increase in the type, number and degree of risks and uncertainties, which consequently lead to more challenging decision making problems. A typical complex decision making problem in petroleum exploration and production (E&P) is the selection and prioritization of oilfields/projects in a portfolio investment. Prioritizing oilfields maybe required for different purposes, including the achievement of a targeted production and allocation of limited available development resources. These resources cannot be distributed evenly nor can they be allocated based on the oilfield size or production capacity alone since various other factors need to be considered simultaneously. These factors may include subsurface complexity, size of reservoir, plateau production and needed infrastructure in addition to other issues of strategic concern, such as socio-economic, environmental and fiscal policies, particularly when the decision making involves governments or national oil companies. Therefore, it would be imperative to employ decision aiding tools that not only address these factors, but also incorporate the decision makers' preferences clearly and accurately. However, the tools commonly used in project portfolio selection and optimization, including intuitive approaches, vary in their focus and strength in addressing the different criteria involved in such decision problems. They are also disadvantaged by a number of drawbacks, which may include lacking the capacity to address multiple and interrelated criteria, uncertainty and risk, project relationship with regard to value contribution and optimum resource utilization, non-monetary attributes, decision maker's knowledge and expertise, in addition to varying levels of ease of use and other practical and theoretical drawbacks. These drawbacks have motivated researchers to investigate other tools and techniques that can provide more flexibility and inclusiveness in the decision making process, such as Multi-Criteria Decision Making (MCDM) methods. However, it can be observed that the MCDM literature: 1) is primarily focused on suggesting certain MCDM techniques to specific problems without providing sufficient evidence for their selection, 2) is inadequate in addressing MCDM in E&P portfolio selection and prioritization compared with other fields, and 3) does not address prioritizing brownfields (i.e., developed oilfields). This research study aims at addressing the above drawbacks through combining three MCDM methods (i.e., AHP, PROMETHEE and TOPSIS) into a single decision making tool that can support optimal oilfield portfolio investment decisions by helping determine the share of each oilfield of the total development resources allocated. Selecting these methods is reinforced by a pre-deployment and post-deployment validation framework. In addition, this study proposes a two-dimensional consistency test to verify the output coherence or prioritization stability of the MCDM methods in comparison with an intuitive approach. Nine scenarios representing all possible outcomes of the internal and external consistency tests are further proposed to reach a conclusion. The methodology is applied to a case study of six major oilfields in Iraq to generate percentage shares of each oilfield of a total production target that is in line with Iraq's aspiration to increase oil production. However, the methodology is intended to be applicable to other E&P portfolio investment prioritization scenarios by taking the specific contextual characteristics into consideration.

Quantitative tools link portfolio management with use of technology

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

Anderson, R.N.; Boulanger, A.; Amaefule, J.

1998-11-30

The exploration and production (E and P) business is in the midst of a major transformation from an emphasis on cost-cutting to more diverse portfolio management practices. The industry has found that it is not easy to simultaneously optimize net present value (NPV), return on investment (ROI), and long-term growth. The result has been the adaptation of quantitative business practices that rival their subsurface geological equivalents in sophistication and complexity. The computational tools assess the risk-reward tradeoffs inherent in the upstream linkages between (1) the application of advanced technologies to improve success in exploration and in exploitation (reservoir evaluation, drilling,more » producing, and delivery to market) and (2) the maximization of both short- and long-term profitability. Exploitation is a critical link to the industry`s E and P profitability, as can be seen from the correlation between earnings growth of the international majors and production growth. The paper discusses the use of tools to optimize exploitation.« less

Does health affect portfolio choice?

PubMed

Love, David A; Smith, Paul A

2010-12-01

A number of recent studies find that poor health is empirically associated with a safer portfolio allocation. It is difficult to say, however, whether this relationship is truly causal. Both health status and portfolio choice are influenced by unobserved characteristics such as risk attitudes, impatience, information, and motivation, and these unobserved factors, if not adequately controlled for, can induce significant bias in the estimates of asset demand equations. Using the 1992-2006 waves of the Health and Retirement Study, we investigate how much of the connection between health and portfolio choice is causal and how much is due to the effects of unobserved heterogeneity. Accounting for unobserved heterogeneity with fixed effects and correlated random effects models, we find that health does not appear to significantly affect portfolio choice among single households. For married households, we find a small effect (about 2-3 percentage points) from being in the lowest of five self-reported health categories. Copyright © 2009 John Wiley & Sons, Ltd.

Stock Portfolio Structure of Individual Investors Infers Future Trading Behavior

PubMed Central

Bohlin, Ludvig; Rosvall, Martin

2014-01-01

Although the understanding of and motivation behind individual trading behavior is an important puzzle in finance, little is known about the connection between an investor's portfolio structure and her trading behavior in practice. In this paper, we investigate the relation between what stocks investors hold, and what stocks they buy, and show that investors with similar portfolio structures to a great extent trade in a similar way. With data from the central register of shareholdings in Sweden, we model the market in a similarity network, by considering investors as nodes, connected with links representing portfolio similarity. From the network, we find investor groups that not only identify different investment strategies, but also represent individual investors trading in a similar way. These findings suggest that the stock portfolios of investors hold meaningful information, which could be used to earn a better understanding of stock market dynamics. PMID:25068302

Stock portfolio structure of individual investors infers future trading behavior.

PubMed

Bohlin, Ludvig; Rosvall, Martin

2014-01-01

Although the understanding of and motivation behind individual trading behavior is an important puzzle in finance, little is known about the connection between an investor's portfolio structure and her trading behavior in practice. In this paper, we investigate the relation between what stocks investors hold, and what stocks they buy, and show that investors with similar portfolio structures to a great extent trade in a similar way. With data from the central register of shareholdings in Sweden, we model the market in a similarity network, by considering investors as nodes, connected with links representing portfolio similarity. From the network, we find investor groups that not only identify different investment strategies, but also represent individual investors trading in a similar way. These findings suggest that the stock portfolios of investors hold meaningful information, which could be used to earn a better understanding of stock market dynamics.

Combined optimization model for sustainable energization strategy

NASA Astrophysics Data System (ADS)

Abtew, Mohammed Seid

Access to energy is a foundation to establish a positive impact on multiple aspects of human development. Both developed and developing countries have a common concern of achieving a sustainable energy supply to fuel economic growth and improve the quality of life with minimal environmental impacts. The Least Developing Countries (LDCs), however, have different economic, social, and energy systems. Prevalence of power outage, lack of access to electricity, structural dissimilarity between rural and urban regions, and traditional fuel dominance for cooking and the resultant health and environmental hazards are some of the distinguishing characteristics of these nations. Most energy planning models have been designed for developed countries' socio-economic demographics and have missed the opportunity to address special features of the poor countries. An improved mixed-integer programming energy-source optimization model is developed to address limitations associated with using current energy optimization models for LDCs, tackle development of the sustainable energization strategies, and ensure diversification and risk management provisions in the selected energy mix. The Model predicted a shift from traditional fuels reliant and weather vulnerable energy source mix to a least cost and reliable modern clean energy sources portfolio, a climb on the energy ladder, and scored multifaceted economic, social, and environmental benefits. At the same time, it represented a transition strategy that evolves to increasingly cleaner energy technologies with growth as opposed to an expensive solution that leapfrogs immediately to the cleanest possible, overreaching technologies.

Integration of a Portfolio-based Approach to Evaluate Aerospace R and D Problem Formulation Into a Parametric Synthesis Tool

NASA Astrophysics Data System (ADS)

Oza, Amit R.

The focus of this study is to improve R&D effectiveness towards aerospace and defense planning in the early stages of the product development lifecycle. Emphasis is on: correct formulation of a decision problem, with special attention to account for data relationships between the individual design problem and the system capability required to size the aircraft, understanding of the meaning of the acquisition strategy objective and subjective data requirements that are required to arrive at a balanced analysis and/or "correct" mix of technology projects, understanding the meaning of the outputs that can be created from the technology analysis, and methods the researcher can use at effectively support decisions at the acquisition and conceptual design levels through utilization of a research and development portfolio strategy. The primary objectives of this study are to: (1) determine what strategy should be used to initialize conceptual design parametric sizing processes during requirements analysis for the materiel solution analysis stage of the product development lifecycle when utilizing data already constructed in the latter phase when working with a generic database management system synthesis tool integration architecture for aircraft design , and (2) assess how these new data relationships can contribute for innovative decision-making when solving acquisition hardware/technology portfolio problems. As such, an automated composable problem formulation system is developed to consider data interactions for the system architecture that manages acquisition pre-design concept refinement portfolio management, and conceptual design parametric sizing requirements. The research includes a way to: • Formalize the data storage and implement the data relationship structure with a system architecture automated through a database management system. • Allow for composable modeling, in terms of level of hardware abstraction, for the product model, mission model, and operational constraint model data blocks in the pre-design stages. • Allow the product model, mission model, and operational constraint model to be cross referenced with a generic aircraft synthesis capability to identify disciplinary analysis methods and processes. • Allow for matching, comparison, and balancing of the aircraft hardware portfolio to the associated developmental and technology risk metrics. • Allow for visualization technology portfolio decision space. The problem formulation architecture is finally implemented and verified for a generic hypersonic vehicle research demonstrator where a portfolio of technology hardware are measured for developmental and technology risks, prioritized by the researcher risk constraints, and the data generated delivered to a novel aircraft synthesis tool to confirm vehicle feasibility.

Optimal portfolio selection in a Lévy market with uncontrolled cash flow and only risky assets

NASA Astrophysics Data System (ADS)

Zeng, Yan; Li, Zhongfei; Wu, Huiling

2013-03-01

This article considers an investor who has an exogenous cash flow evolving according to a Lévy process and invests in a financial market consisting of only risky assets, whose prices are governed by exponential Lévy processes. Two continuous-time portfolio selection problems are studied for the investor. One is a benchmark problem, and the other is a mean-variance problem. The first problem is solved by adopting the stochastic dynamic programming approach, and the obtained results are extended to the second problem by employing the duality theory. Closed-form solutions of these two problems are derived. Some existing results are found to be special cases of our results.

Effects of correlations and fees in random multiplicative environments: Implications for portfolio management.

PubMed

Alper, Ofer; Somekh-Baruch, Anelia; Pirvandy, Oz; Schaps, Malka; Yaari, Gur

2017-08-01

Geometric Brownian motion (GBM) is frequently used to model price dynamics of financial assets, and a weighted average of multiple GBMs is commonly used to model a financial portfolio. Diversified portfolios can lead to an increased exponential growth compared to a single asset by effectively reducing the effective noise. The sum of GBM processes is no longer a log-normal process and has a complex statistical properties. The nonergodicity of the weighted average process results in constant degradation of the exponential growth from the ensemble average toward the time average. One way to stay closer to the ensemble average is to maintain a balanced portfolio: keep the relative weights of the different assets constant over time. To keep these proportions constant, whenever assets values change, it is necessary to rebalance their relative weights, exposing this strategy to fees (transaction costs). Two strategies that were suggested in the past for cases that involve fees are rebalance the portfolio periodically and rebalance it in a partial way. In this paper, we study these two strategies in the presence of correlations and fees. We show that using periodic and partial rebalance strategies, it is possible to maintain a steady exponential growth while minimizing the losses due to fees. We also demonstrate how these redistribution strategies perform in a phenomenal way on real-world market data, despite the fact that not all assumptions of the model hold in these real-world systems. Our results have important implications for stochastic dynamics in general and to portfolio management in particular, as we show that there is a superior alternative to the common buy-and-hold strategy, even in the presence of correlations and fees.

Effects of correlations and fees in random multiplicative environments: Implications for portfolio management

NASA Astrophysics Data System (ADS)

Alper, Ofer; Somekh-Baruch, Anelia; Pirvandy, Oz; Schaps, Malka; Yaari, Gur

2017-08-01

Geometric Brownian motion (GBM) is frequently used to model price dynamics of financial assets, and a weighted average of multiple GBMs is commonly used to model a financial portfolio. Diversified portfolios can lead to an increased exponential growth compared to a single asset by effectively reducing the effective noise. The sum of GBM processes is no longer a log-normal process and has a complex statistical properties. The nonergodicity of the weighted average process results in constant degradation of the exponential growth from the ensemble average toward the time average. One way to stay closer to the ensemble average is to maintain a balanced portfolio: keep the relative weights of the different assets constant over time. To keep these proportions constant, whenever assets values change, it is necessary to rebalance their relative weights, exposing this strategy to fees (transaction costs). Two strategies that were suggested in the past for cases that involve fees are rebalance the portfolio periodically and rebalance it in a partial way. In this paper, we study these two strategies in the presence of correlations and fees. We show that using periodic and partial rebalance strategies, it is possible to maintain a steady exponential growth while minimizing the losses due to fees. We also demonstrate how these redistribution strategies perform in a phenomenal way on real-world market data, despite the fact that not all assumptions of the model hold in these real-world systems. Our results have important implications for stochastic dynamics in general and to portfolio management in particular, as we show that there is a superior alternative to the common buy-and-hold strategy, even in the presence of correlations and fees.

Measuring Value-at-Risk and Expected Shortfall of crude oil portfolio using extreme value theory and vine copula

NASA Astrophysics Data System (ADS)

Yu, Wenhua; Yang, Kun; Wei, Yu; Lei, Likun

2018-01-01

Volatilities of crude oil price have important impacts on the steady and sustainable development of world real economy. Thus it is of great academic and practical significance to model and measure the volatility and risk of crude oil markets accurately. This paper aims to measure the Value-at-Risk (VaR) and Expected Shortfall (ES) of a portfolio consists of four crude oil assets by using GARCH-type models, extreme value theory (EVT) and vine copulas. The backtesting results show that the combination of GARCH-type-EVT models and vine copula methods can produce accurate risk measures of the oil portfolio. Mixed R-vine copula is more flexible and superior to other vine copulas. Different GARCH-type models, which can depict the long-memory and/or leverage effect of oil price volatilities, however offer similar marginal distributions of the oil returns.

A non-autonomous optimal control model of renewable energy production under the aspect of fluctuating supply and learning by doing.

PubMed

Moser, Elke; Grass, Dieter; Tragler, Gernot

Given the constantly raising world-wide energy demand and the accompanying increase in greenhouse gas emissions that pushes the progression of climate change, the possibly most important task in future is to find a carbon-low energy supply that finds the right balance between sustainability and energy security. For renewable energy generation, however, especially the second aspect turns out to be difficult as the supply of renewable sources underlies strong volatility. Further on, investment costs for new technologies are so high that competitiveness with conventional energy forms is hard to achieve. To address this issue, we analyze in this paper a non-autonomous optimal control model considering the optimal composition of a portfolio that consists of fossil and renewable energy and which is used to cover the energy demand of a small country. While fossil energy is assumed to be constantly available, the supply of the renewable resource fluctuates seasonally. We further on include learning effects for the renewable energy technology, which will underline the importance of considering the whole life span of such a technology for long-term energy planning decisions.

Assessing the Development of Medical Students’ Personal and Professional Skills by Portfolio

PubMed Central

Yielder, Jill; Moir, Fiona

2016-01-01

The introduction of a new domain of learning for Personal and Professional Skills in the medical program at the University of Auckland in New Zealand has involved the compilation of a portfolio for assessment. This departure from the traditional assessment methods predominantly used in the past has been challenging to design, introduce, and maintain as a relevant and authentic assessment method. We present the portfolio format along with the process for its introduction and appraise the challenges, strengths, and limitations of the approach within the context of the current literature. We then outline a cyclical model of evaluation used to monitor and fine-tune the portfolio tasks and implementation process, in response to student and assessor feedback. The portfolios have illustrated the level of insight, maturity, and synthesis of personal and professional qualities that students are capable of achieving. The Auckland medical program strives to foster these qualities in its students, and the portfolio provides an opportunity for students to demonstrate their reflective abilities. Moreover, the creation of a Personal and Professional Skills domain with the portfolio as its key assessment emphasizes the importance of reflective practice and personal and professional development and gives a clear message that these are fundamental longitudinal elements of the program. PMID:29349315

Assessing the Development of Medical Students' Personal and Professional Skills by Portfolio.

PubMed

Yielder, Jill; Moir, Fiona

2016-01-01

The introduction of a new domain of learning for Personal and Professional Skills in the medical program at the University of Auckland in New Zealand has involved the compilation of a portfolio for assessment. This departure from the traditional assessment methods predominantly used in the past has been challenging to design, introduce, and maintain as a relevant and authentic assessment method. We present the portfolio format along with the process for its introduction and appraise the challenges, strengths, and limitations of the approach within the context of the current literature. We then outline a cyclical model of evaluation used to monitor and fine-tune the portfolio tasks and implementation process, in response to student and assessor feedback. The portfolios have illustrated the level of insight, maturity, and synthesis of personal and professional qualities that students are capable of achieving. The Auckland medical program strives to foster these qualities in its students, and the portfolio provides an opportunity for students to demonstrate their reflective abilities. Moreover, the creation of a Personal and Professional Skills domain with the portfolio as its key assessment emphasizes the importance of reflective practice and personal and professional development and gives a clear message that these are fundamental longitudinal elements of the program.

Capacity planning for batch and perfusion bioprocesses across multiple biopharmaceutical facilities.

PubMed

Siganporia, Cyrus C; Ghosh, Soumitra; Daszkowski, Thomas; Papageorgiou, Lazaros G; Farid, Suzanne S

2014-01-01

Production planning for biopharmaceutical portfolios becomes more complex when products switch between fed-batch and continuous perfusion culture processes. This article describes the development of a discrete-time mixed integer linear programming (MILP) model to optimize capacity plans for multiple biopharmaceutical products, with either batch or perfusion bioprocesses, across multiple facilities to meet quarterly demands. The model comprised specific features to account for products with fed-batch or perfusion culture processes such as sequence-dependent changeover times, continuous culture constraints, and decoupled upstream and downstream operations that permit independent scheduling of each. Strategic inventory levels were accounted for by applying cost penalties when they were not met. A rolling time horizon methodology was utilized in conjunction with the MILP model and was shown to obtain solutions with greater optimality in less computational time than the full-scale model. The model was applied to an industrial case study to illustrate how the framework aids decisions regarding outsourcing capacity to third party manufacturers or building new facilities. The impact of variations on key parameters such as demand or titres on the optimal production plans and costs was captured. The analysis identified the critical ratio of in-house to contract manufacturing organization (CMO) manufacturing costs that led the optimization results to favor building a future facility over using a CMO. The tool predicted that if titres were higher than expected then the optimal solution would allocate more production to in-house facilities, where manufacturing costs were lower. Utilization graphs indicated when capacity expansion should be considered. © 2014 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers.

Capacity Planning for Batch and Perfusion Bioprocesses Across Multiple Biopharmaceutical Facilities

PubMed Central

Siganporia, Cyrus C; Ghosh, Soumitra; Daszkowski, Thomas; Papageorgiou, Lazaros G; Farid, Suzanne S

2014-01-01

Production planning for biopharmaceutical portfolios becomes more complex when products switch between fed-batch and continuous perfusion culture processes. This article describes the development of a discrete-time mixed integer linear programming (MILP) model to optimize capacity plans for multiple biopharmaceutical products, with either batch or perfusion bioprocesses, across multiple facilities to meet quarterly demands. The model comprised specific features to account for products with fed-batch or perfusion culture processes such as sequence-dependent changeover times, continuous culture constraints, and decoupled upstream and downstream operations that permit independent scheduling of each. Strategic inventory levels were accounted for by applying cost penalties when they were not met. A rolling time horizon methodology was utilized in conjunction with the MILP model and was shown to obtain solutions with greater optimality in less computational time than the full-scale model. The model was applied to an industrial case study to illustrate how the framework aids decisions regarding outsourcing capacity to third party manufacturers or building new facilities. The impact of variations on key parameters such as demand or titres on the optimal production plans and costs was captured. The analysis identified the critical ratio of in-house to contract manufacturing organization (CMO) manufacturing costs that led the optimization results to favor building a future facility over using a CMO. The tool predicted that if titres were higher than expected then the optimal solution would allocate more production to in-house facilities, where manufacturing costs were lower. Utilization graphs indicated when capacity expansion should be considered. © 2013 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 30:594–606, 2014 PMID:24376262

Selection and optimization of hits from a high-throughput phenotypic screen against Trypanosoma cruzi.

PubMed

Keenan, Martine; Alexander, Paul W; Chaplin, Jason H; Abbott, Michael J; Diao, Hugo; Wang, Zhisen; Best, Wayne M; Perez, Catherine J; Cornwall, Scott M J; Keatley, Sarah K; Thompson, R C Andrew; Charman, Susan A; White, Karen L; Ryan, Eileen; Chen, Gong; Ioset, Jean-Robert; von Geldern, Thomas W; Chatelain, Eric

2013-10-01

Inhibitors of Trypanosoma cruzi with novel mechanisms of action are urgently required to diversify the current clinical and preclinical pipelines. Increasing the number and diversity of hits available for assessment at the beginning of the discovery process will help to achieve this aim. We report the evaluation of multiple hits generated from a high-throughput screen to identify inhibitors of T. cruzi and from these studies the discovery of two novel series currently in lead optimization. Lead compounds from these series potently and selectively inhibit growth of T. cruzi in vitro and the most advanced compound is orally active in a subchronic mouse model of T. cruzi infection. High-throughput screening of novel compound collections has an important role to play in diversifying the trypanosomatid drug discovery portfolio. A new T. cruzi inhibitor series with good drug-like properties and promising in vivo efficacy has been identified through this process.

Using multiobjective tradeoff sets and Multivariate Regression Trees to identify critical and robust decisions for long term water utility planning

NASA Astrophysics Data System (ADS)

Smith, R.; Kasprzyk, J. R.; Balaji, R.

2017-12-01

In light of deeply uncertain factors like future climate change and population shifts, responsible resource management will require new types of information and strategies. For water utilities, this entails potential expansion and efficient management of water supply infrastructure systems for changes in overall supply; changes in frequency and severity of climate extremes such as droughts and floods; and variable demands, all while accounting for conflicting long and short term performance objectives. Multiobjective Evolutionary Algorithms (MOEAs) are emerging decision support tools that have been used by researchers and, more recently, water utilities to efficiently generate and evaluate thousands of planning portfolios. The tradeoffs between conflicting objectives are explored in an automated way to produce (often large) suites of portfolios that strike different balances of performance. Once generated, the sets of optimized portfolios are used to support relatively subjective assertions of priorities and human reasoning, leading to adoption of a plan. These large tradeoff sets contain information about complex relationships between decisions and between groups of decisions and performance that, until now, has not been quantitatively described. We present a novel use of Multivariate Regression Trees (MRTs) to analyze tradeoff sets to reveal these relationships and critical decisions. Additionally, when MRTs are applied to tradeoff sets developed for different realizations of an uncertain future, they can identify decisions that are robust across a wide range of conditions and produce fundamental insights about the system being optimized.

Managing the Facilities Portfolio: New Book Addresses Elimination of $60 Billion Problem.

ERIC Educational Resources Information Center

Rush, Sean; And Others

1991-01-01

This excerpt from "Managing the Facilities Portfolio: A Practical Approach to Institutional Renewal and Deferred Maintenance" offers higher education business officers a conceptual framework comprising four steps: (1) establish baseline; (2) estimate needs; (3) compare model alternatives; and (4) report to management. (DB)

A methodology for comprehensive strategic planning and program prioritization

NASA Astrophysics Data System (ADS)

Raczynski, Christopher Michael

2008-10-01

This process developed in this work, Strategy Optimization for the Allocation of Resources (SOAR), is a strategic planning methodology based off Integrated Product and Process Development and systems engineering techniques. Utilizing a top down approach, the process starts with the creation of the organization vision and its measures of effectiveness. These measures are prioritized based on their application to external world scenarios which will frame the future. The programs which will be used to accomplish this vision are identified by decomposing the problem. Information is gathered on the programs as to the application, cost, schedule, risk, and other pertinent information. The relationships between the levels of the hierarchy are mapped utilizing subject matter experts. These connections are then utilized to determine the overall benefit of the programs to the vision of the organization. Through a Multi-Objective Genetic Algorithm a tradespace of potential program portfolios can be created amongst which the decision maker can allocate resources. The information and portfolios are presented to the decision maker through the use of a Decision Support System which collects and visualizes all the data in a single location. This methodology was tested utilizing a science and technology planning exercise conducted by the United States Navy. A thorough decomposition was defined and technology programs identified which had the potential to provide benefit to the vision. The prioritization of the top level capabilities was performed through the use of a rank ordering scheme and a previous naval application was used to demonstrate a cumulative voting scheme. Voting was performed utilizing the Nominal Group Technique to capture the relationships between the levels of the hierarchy. Interrelationships between the technologies were identified and a MOGA was utilized to optimize portfolios with respect to these constraints and information was placed in a DSS. This formulation allowed the decision makers to assess which portfolio could provide the greatest benefit to the Navy while still fitting within the funding profile.

Research Staff | Geothermal Technologies | NREL

Science.gov Websites

Position Email Phone Akar, Sertac Energy Analyst - Geothermal Sertac.Akar@nrel.gov 303-275-3725 Augustine -Geoscience Kate Young joined NREL in 2008. She has worked on analysis of geothermal exploration, drilling ) Toolkit, the Geothermal Resource Portfolio Optimization and Reporting Technique (GeoRePORT), and the

Pedagogical Strategies for Incorporating Behavioral Finance Concepts in Investment Courses

ERIC Educational Resources Information Center

Adams, Michael; Mullins, Terry; Thornton, Barry

2007-01-01

The traditional approach to teaching a course in investments is predicated upon the efficient market hypothesis, modern portfolio theory, and the assumption that decision-makers are rational, wealth optimizing entities. Recent developments in the arena of behavioral finance (BF) have raised questions about this approach. Although the idea of…

A predictive modeling approach to increasing the economic effectiveness of disease management programs.

PubMed

Bayerstadler, Andreas; Benstetter, Franz; Heumann, Christian; Winter, Fabian

2014-09-01

Predictive Modeling (PM) techniques are gaining importance in the worldwide health insurance business. Modern PM methods are used for customer relationship management, risk evaluation or medical management. This article illustrates a PM approach that enables the economic potential of (cost-) effective disease management programs (DMPs) to be fully exploited by optimized candidate selection as an example of successful data-driven business management. The approach is based on a Generalized Linear Model (GLM) that is easy to apply for health insurance companies. By means of a small portfolio from an emerging country, we show that our GLM approach is stable compared to more sophisticated regression techniques in spite of the difficult data environment. Additionally, we demonstrate for this example of a setting that our model can compete with the expensive solutions offered by professional PM vendors and outperforms non-predictive standard approaches for DMP selection commonly used in the market.

Leveraging OpenStudio's Application Programming Interfaces: Preprint

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

Long, N.; Ball, B.; Goldwasser, D.

2013-11-01

OpenStudio development efforts have been focused on providing Application Programming Interfaces (APIs) where users are able to extend OpenStudio without the need to compile the open source libraries. This paper will discuss the basic purposes and functionalities of the core libraries that have been wrapped with APIs including the Building Model, Results Processing, Advanced Analysis, UncertaintyQuantification, and Data Interoperability through Translators. Several building energy modeling applications have been produced using OpenStudio's API and Software Development Kits (SDK) including the United States Department of Energy's Asset ScoreCalculator, a mobile-based audit tool, an energy design assistance reporting protocol, and a portfolio scalemore » incentive optimization analysismethodology. Each of these software applications will be discussed briefly and will describe how the APIs were leveraged for various uses including high-level modeling, data transformations from detailed building audits, error checking/quality assurance of models, and use of high-performance computing for mass simulations.« less

Beginning science teachers' performances: Assessment in times of reform

NASA Astrophysics Data System (ADS)

Budzinsky, Fie K.

2000-10-01

The current reform in science education and the research on effective teaching and student learning have reinforced the importance of teacher competency. To better measure performances in the teaching of science, performance assessment has been added to Connecticut's licensure process for beginning science teachers. Teaching portfolios are used to document teaching and learning over time. Portfolios, however, are not without problems. One of the major concerns with the portfolio assessment process is its subjectivity. Assessors may not have opportunities to ask clarifying or follow-up questions to enhance the interpretation of a teacher's performance. In addition, portfolios often contain components based on self-documentation, which are subjective. Furthermore, the use of portfolios raises test equity issues. These concerns present challenges for persons in charge of establishing the validity of a portfolio-based licensure process. In high-stakes decision processes, such as teaching licensure, the validity of the assessment instruments must be studied. The primary purpose of this study was to explore the criterion-related validity of the Connecticut State Department of Education's Beginning Science Teaching Portfolio by comparing the interpretations of performances from science teaching portfolios to those derived from another assessment method, the Expert Science Teaching Educational and Evaluation Model, (ESTEEM). The analysis of correlations between the Beginning Science Teaching Portfolio and ESTEEM instrument scores was the primary method for establishing support for validity. The results indicated moderate correlations between all Beginning Science Teaching Portfolio and ESTEEM category and total variables. Multiple regression was used to examine whether differences existed in beginning science teachers' performances based on gender, poverty group, school level, and science discipline taught. None of these variables significantly contributed to the explanation of variance in the ESTEEM (p > .05), but poverty group and gender were significant predictors of portfolio performances, accounting for 21% of the total variance. Finally, data from interviews, written surveys, and beginning teacher attendance records at state-supported seminars were analyzed qualitatively and quantitatively. This information provided insight about the quality and quantity of support beginning science teachers received in their efforts to document, via the science teaching portfolio, their abilities to implement the Connecticut Professional Science Teaching Standards.

Curve fitting of the corporate recovery rates: the comparison of Beta distribution estimation and kernel density estimation.

PubMed

Chen, Rongda; Wang, Ze

2013-01-01

Recovery rate is essential to the estimation of the portfolio's loss and economic capital. Neglecting the randomness of the distribution of recovery rate may underestimate the risk. The study introduces two kinds of models of distribution, Beta distribution estimation and kernel density distribution estimation, to simulate the distribution of recovery rates of corporate loans and bonds. As is known, models based on Beta distribution are common in daily usage, such as CreditMetrics by J.P. Morgan, Portfolio Manager by KMV and Losscalc by Moody's. However, it has a fatal defect that it can't fit the bimodal or multimodal distributions such as recovery rates of corporate loans and bonds as Moody's new data show. In order to overcome this flaw, the kernel density estimation is introduced and we compare the simulation results by histogram, Beta distribution estimation and kernel density estimation to reach the conclusion that the Gaussian kernel density distribution really better imitates the distribution of the bimodal or multimodal data samples of corporate loans and bonds. Finally, a Chi-square test of the Gaussian kernel density estimation proves that it can fit the curve of recovery rates of loans and bonds. So using the kernel density distribution to precisely delineate the bimodal recovery rates of bonds is optimal in credit risk management.

Object-Oriented Bayesian Networks (OOBN) for Aviation Accident Modeling and Technology Portfolio Impact Assessment

NASA Technical Reports Server (NTRS)

Shih, Ann T.; Ancel, Ersin; Jones, Sharon M.

2012-01-01

The concern for reducing aviation safety risk is rising as the National Airspace System in the United States transforms to the Next Generation Air Transportation System (NextGen). The NASA Aviation Safety Program is committed to developing an effective aviation safety technology portfolio to meet the challenges of this transformation and to mitigate relevant safety risks. The paper focuses on the reasoning of selecting Object-Oriented Bayesian Networks (OOBN) as the technique and commercial software for the accident modeling and portfolio assessment. To illustrate the benefits of OOBN in a large and complex aviation accident model, the in-flight Loss-of-Control Accident Framework (LOCAF) constructed as an influence diagram is presented. An OOBN approach not only simplifies construction and maintenance of complex causal networks for the modelers, but also offers a well-organized hierarchical network that is easier for decision makers to exploit the model examining the effectiveness of risk mitigation strategies through technology insertions.

An indexing and price movement model for managing pension funds.

PubMed

Freeman, H R

1994-10-01

A model for the investment of pension funds has been created that combines passive and active portfolio management strategies. The model uses a passive index fund to reduce the amount spent in transaction costs. It applies a percentage band that identifies the portion of the portfolio that should be committed to equity investments at various stages of the market movement cycle. Finally, it uses price movement trigger points to dictate when pension funds should be moved into and withdrawn from stock market investments.

Renewable Energy used in State Renewable Portfolio Standards Yielded

Science.gov Websites

. Renewable Portfolio Standards also shows national water withdrawals and water consumption by fossil-fuel methodologies, while recognizing that states could perform their own more-detailed assessments," NREL's , respectively. Ranges are presented as the models and methodologies used are sensitive to multiple parameters

On the Endogeneity of the Mean-Variance Efficient Frontier.

ERIC Educational Resources Information Center

Somerville, R. A.; O'Connell, Paul G. J.

2002-01-01

Explains that the endogeneity of the efficient frontier in the mean-variance model of portfolio selection is commonly obscured in portfolio selection literature and in widely used textbooks. Demonstrates endogeneity and discusses the impact of parameter changes on the mean-variance efficient frontier and on the beta coefficients of individual…

Time is money: Rational life cycle inertia and the delegation of investment management.

PubMed

Kim, Hugh Hoikwang; Maurer, Raimond; Mitchell, Olivia S

2016-08-01

Many households display inertia in investment management over their life cycles. Our calibrated dynamic life cycle portfolio choice model can account for such an apparently 'irrational' outcome, by incorporating the fact that investors must forgo acquiring job-specific skills when they spend time managing their money, and their efficiency in financial decision making varies with age. Resulting inertia patterns mesh well with findings from prior studies and our own empirical results from Panel Study of Income Dynamics (PSID) data. We also analyze how people optimally choose between actively managing their assets versus delegating the task to financial advisors. Delegation proves valuable to both the young and the old. Our calibrated model quantifies welfare gains from including investment time and money costs as well as delegation in a life cycle setting.

Drugs for Neglected Diseases initiative model of drug development for neglected diseases: current status and future challenges.

PubMed

Ioset, Jean-Robert; Chang, Shing

2011-09-01

The Drugs for Neglected Diseases initiative (DNDi) is a patients' needs-driven organization committed to the development of new treatments for neglected diseases. Created in 2003, DNDi has delivered four improved treatments for malaria, sleeping sickness and visceral leishmaniasis. A main DNDi challenge is to build a solid R&D portfolio for neglected diseases and to deliver preclinical candidates in a timely manner using an original model based on partnership. To address this challenge DNDi has remodeled its discovery activities from a project-based academic-bound network to a fully integrated process-oriented platform in close collaboration with pharmaceutical companies. This discovery platform relies on dedicated screening capacity and lead-optimization consortia supported by a pragmatic, structured and pharmaceutical-focused compound sourcing strategy.

Trimming a hazard logic tree with a new model-order-reduction technique

USGS Publications Warehouse

Porter, Keith; Field, Edward; Milner, Kevin R

2017-01-01

The size of the logic tree within the Uniform California Earthquake Rupture Forecast Version 3, Time-Dependent (UCERF3-TD) model can challenge risk analyses of large portfolios. An insurer or catastrophe risk modeler concerned with losses to a California portfolio might have to evaluate a portfolio 57,600 times to estimate risk in light of the hazard possibility space. Which branches of the logic tree matter most, and which can one ignore? We employed two model-order-reduction techniques to simplify the model. We sought a subset of parameters that must vary, and the specific fixed values for the remaining parameters, to produce approximately the same loss distribution as the original model. The techniques are (1) a tornado-diagram approach we employed previously for UCERF2, and (2) an apparently novel probabilistic sensitivity approach that seems better suited to functions of nominal random variables. The new approach produces a reduced-order model with only 60 of the original 57,600 leaves. One can use the results to reduce computational effort in loss analyses by orders of magnitude.

Comprehensive Education Portfolio with a Career Focus

ERIC Educational Resources Information Center

Kruger, Evonne J.; Holtzman, Diane M.; Dagavarian, Debra A.

2013-01-01

There are many types of student portfolios used within academia: the prior learning portfolio, credentialing portfolio, developmental portfolio, capstone portfolio, individual course portfolio, and the comprehensive education portfolio. The comprehensive education portfolio (CEP), as used by the authors, is a student portfolio, developed over…

Switching portfolios.

PubMed

Singer, Y

1997-08-01

A constant rebalanced portfolio is an asset allocation algorithm which keeps the same distribution of wealth among a set of assets along a period of time. Recently, there has been work on on-line portfolio selection algorithms which are competitive with the best constant rebalanced portfolio determined in hindsight (Cover, 1991; Helmbold et al., 1996; Cover and Ordentlich, 1996). By their nature, these algorithms employ the assumption that high returns can be achieved using a fixed asset allocation strategy. However, stock markets are far from being stationary and in many cases the wealth achieved by a constant rebalanced portfolio is much smaller than the wealth achieved by an ad hoc investment strategy that adapts to changes in the market. In this paper we present an efficient portfolio selection algorithm that is able to track a changing market. We also describe a simple extension of the algorithm for the case of a general transaction cost, including the transactions cost models recently investigated in (Blum and Kalai, 1997). We provide a simple analysis of the competitiveness of the algorithm and check its performance on real stock data from the New York Stock Exchange accumulated during a 22-year period. On this data, our algorithm outperforms all the algorithms referenced above, with and without transaction costs.

Using Minimax Regret Optimization to Search for Multi-Stakeholder Solutions to Deeply Uncertain Flood Hazards under Climate Change

NASA Astrophysics Data System (ADS)

Kirshen, P. H.; Hecht, J. S.; Vogel, R. M.

2015-12-01

Prescribing long-term urban floodplain management plans under the deep uncertainty of climate change is a challenging endeavor. To address this, we have implemented and tested with stakeholders a parsimonious multi-stage mixed integer programming (MIP) model that identifies the optimal time period(s) for implementing publicly and privately financed adaptation measures. Publicly funded measures include reach-scale flood barriers, flood insurance, and buyout programs to encourage property owners in flood-prone areas to retreat from the floodplain. Measures privately funded by property owners consist of property-scale floodproofing options, such as raising building foundations, as well as investments in flood insurance or retreat from flood-prone areas. The objective function to minimize the sum of flood control and damage costs in all planning stages for different property types during floods of different severities. There are constraints over time for flow mass balances, construction of flood management alternatives and their cumulative implementation, budget allocations, and binary decisions. Damages are adjusted for flood control investments. In recognition of the deep uncertainty of GCM-derived climate change scenarios, we employ the minimax regret criterion to identify adaptation portfolios robust to different climate change trajectories. As an example, we identify publicly and privately funded adaptation measures for a stylized community based on the estuarine community of Exeter, New Hampshire, USA. We explore the sensitivity of recommended portfolios to different ranges of climate changes, and costs associated with economies of scale and flexible infrastructure design as well as different municipal budget constraints.

Using GeoRePORT to report socio-economic potential for geothermal development

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

Young, Katherine R.; Levine, Aaron

The Geothermal Resource Portfolio Optimization and Reporting Tool (GeoRePORT, http://en.openei.org/wiki/GeoRePORT) was developed for reporting resource grades and project readiness levels, providing the U.S. Department of Energy a consistent and comprehensible means of evaluating projects. The tool helps funding organizations (1) quantitatively identify barriers, (2) develop measureable goals, (3) objectively evaluate proposals, including contribution to goals, (4) monitor progress, and (5) report portfolio performance. GeoRePORT assesses three categories: geological, technical, and socio-economic. Here, we describe GeoRePORT, then focus on the socio-economic assessment and its applications for assessing deployment potential in the U.S. Socio-economic attributes include land access, permitting, transmission, and market.

The Portfolio Creation Model Developed for the Capital Investment Program Plan Review (CIPPR)

DTIC Science & Technology

2014-11-12

Basinger, Director, DCI, CFD Scientific Letter The PORTFOLIO CREATION MODEL developed for the Capital Investment Program Plan Review (CIPPR) To inform...senior management about CIPPR decision support, this scientific letter has been prepared upon request [1] to clarify some of the key concepts about...delivery process as laid out in the Defence Project Approval Directive (PAD). 1 With respect to the list above, the subject of this scientific letter is

A portfolio-based approach to optimize proof-of-concept clinical trials.

PubMed

Mallinckrodt, Craig; Molenberghs, Geert; Persinger, Charles; Ruberg, Stephen; Sashegyi, Andreas; Lindborg, Stacy

2012-01-01

Improving proof-of-concept (PoC) studies is a primary lever for improving drug development. Since drug development is often done by institutions that work on multiple drugs simultaneously, the present work focused on optimum choices for rates of false positive (α) and false negative (β) results across a portfolio of PoC studies. Simple examples and a newly derived equation provided conceptual understanding of basic principles regarding optimum choices of α and β in PoC trials. In examples that incorporated realistic development costs and constraints, the levels of α and β that maximized the number of approved drugs and portfolio value varied by scenario. Optimum choices were sensitive to the probability the drug was effective and to the proportion of total investment cost prior to establishing PoC. Results of the present investigation agree with previous research in that it is important to assess optimum levels of α and β. However, the present work also highlighted the need to consider cost structure using realistic input parameters relevant to the question of interest.

Effectiveness of bank credit activity evaluation with application of economic and mathematic modeling

NASA Astrophysics Data System (ADS)

Galeeva, G. M.; Zagladina, E. N.; Kadeeva, E. N.

2018-05-01

The paper presents data on the influence of the most significant factors having impact on the credit portfolio volume, as well as conducts correlation and regression analysis with the subsequent construction of the trend for a short period. Credit activity is understood as the bank activity in the formation of a credit portfolio. Considering the structure of the bank credit portfolio, it can be observed that it consists of credits granted by the bank particularly for legal entities, individuals and other banks. Herewith, it is necessary to understand that any decrease in the credit portfolio will adversely affect the financial stability and effectiveness of any commercial bank. Moreover, during crisis periods, the policy and practice of banks have been determined as quite aggressive and conducted as such with regard to interest rates. The dynamics of credit portfolio volume has been selected as an independent factor due to the reason that it can fully explain the current development situation and the effectiveness of the bank credit policy. Considering the dependent factors, their influence will be assessed by the credit portfolio volume indicator. The authors have distinguished the following ones among them: the volume of credits granted to individuals; the volume of credits granted to legal entities; the amount of overdue credits in the credit portfolio; bank investments in the securities; inflation; key rate.

Optimizing your options: Extracting the full economic value of transmission when planning under uncertainty

DOE PAGES

Munoz, Francisco D.; Watson, Jean -Paul; Hobbs, Benjamin F.

2015-06-04

In this study, the anticipated magnitude of needed investments in new transmission infrastructure in the U.S. requires that these be allocated in a way that maximizes the likelihood of achieving society's goals for power system operation. The use of state-of-the-art optimization tools can identify cost-effective investment alternatives, extract more benefits out of transmission expansion portfolios, and account for the huge economic, technology, and policy uncertainties that the power sector faces over the next several decades.

Optimizing Aggregation Scenarios for Integrating Renewable Energy into the U.S. Electric Grid

NASA Astrophysics Data System (ADS)

Corcoran, B. A.; Jacobson, M. Z.

2010-12-01

This study is an analysis of 2006 and 2007 electric load data, wind speed and solar irradiance data, and existing hydroelectric, geothermal, and other power plant data to quantify benefits of aggregating clean electric power from various Federal Energy Regulatory Commission (FERC) regions in the contiguous United States. First, various time series, statistics, and probability methods are applied to the electric load data to determine if there are any desirable demand-side results—specifically reducing variability and/or coincidence of peak events, which could reduce the amount of required carbon-based generators—in combining the electricity demands from geographically and temporally diverse areas. Second, an optimization algorithm is applied to determine the least-cost portfolio of energy resources to meet the electric load for a range of renewable portfolio standards (RPS’s) for each FERC region and for various aggregation scenarios. Finally, the installed capacities, ramp rates, standard deviation, and corresponding generator requirements from these optimization test runs are compared against the transmission requirements to determine the most economical organizational structure of the contiguous U.S. electric grid. Ideally, results from this study will help to justify and identify a possible structure of a federal RPS and offer insight into how to best organize regions for transmission planning.

Forecasting VaR and ES of stock index portfolio: A Vine copula method

NASA Astrophysics Data System (ADS)

Zhang, Bangzheng; Wei, Yu; Yu, Jiang; Lai, Xiaodong; Peng, Zhenfeng

2014-12-01

Risk measurement has both theoretical and practical significance in risk management. Using daily sample of 10 international stock indices, firstly this paper models the internal structures among different stock markets with C-Vine, D-Vine and R-Vine copula models. Secondly, the Value-at-Risk (VaR) and Expected Shortfall (ES) of the international stock markets portfolio are forecasted using Monte Carlo method based on the estimated dependence of different Vine copulas. Finally, the accuracy of VaR and ES measurements obtained from different statistical models are evaluated by UC, IND, CC and Posterior analysis. The empirical results show that the VaR forecasts at the quantile levels of 0.9, 0.95, 0.975 and 0.99 with three kinds of Vine copula models are sufficiently accurate. Several traditional methods, such as historical simulation, mean-variance and DCC-GARCH models, fail to pass the CC backtesting. The Vine copula methods can accurately forecast the ES of the portfolio on the base of VaR measurement, and D-Vine copula model is superior to other Vine copulas.

The Lesson Observation On-Line (Evidence Portfolio) Platform

ERIC Educational Resources Information Center

Cooper, David G.

2015-01-01

At a time when teacher training is being moved to school-based programmes it is important to engage in a research-informed dialogue about creating more distinctive, and cost-effective 21st century models of teacher training. Three years ago I began feasibility field testing the Lesson Observation On-line (Evidence Portfolio) Platform [LOOP]…

Implementing Curriculum-Based Learning Portfolio: A Case Study in Taiwan

ERIC Educational Resources Information Center

Chen, Shu-Chin Susan; Cheng, Yu-Pay

2011-01-01

The main purpose of this descriptive research is to examine and document the development of a curriculum-based learning portfolio model for children in a preschool for three-six-year-olds in Taiwan. Data collection methods adopted include classroom observation, in-depth interviews, questionnaires and documentation. Participants include a preschool…

A Research Experience Using Portfolios for Assessing College Teaching

ERIC Educational Resources Information Center

Cisneros-Cohernour, Edith J.; Stake, Robert E.

2014-01-01

In this article, we use the findings of a study conducted in a university in the southeast of Mexico to examine strengths and limitations of portfolios to assess formatively the quality of teaching. The research is part of the study: Model for the Development and Evaluation of Academic Competencies, involving researchers from six Mexican…

From ePortfolios to iPortfolios: The Find, Refine, Design, and Bind Model

ERIC Educational Resources Information Center

Foti, Sebastian; Ring, Gail L.

2008-01-01

During the past two decades, educational institutions around the world began formalizing the process of collecting student work as a means of showcasing student accomplishments and ultimately providing students a forum for reflecting on their accomplishments. In this article, the authors propose a redefinition of the electronic portfolio…

Portfolio Based Faculty Development Conversations: A Model for Increasing Teaching Efficacy

ERIC Educational Resources Information Center

Crawford, Sabrina

2017-01-01

A shift in higher education towards increasing accountability for teaching effectiveness has institutions reevaluating how they utilize faculty evaluation tools. The purpose of this case study was to probe perceptions on the value of using teaching portfolios, supported by PLC conversations between faculty and deans, as an evaluation strategy that…

A Primer on Applying Monte Carlo Simulation, Real Options Analysis, Knowledge Value Added, Forecasting, and Portfolio Optimization

DTIC Science & Technology

2010-02-08

popular pastime. Even in Biblical accounts, Roman soldiers cast lots for Christ’s robes. In earlier times, chance was something that occurred in nature...with the advent of blazing fast computing technology, our modern world of uncertainty can be explained with much more elegance through

Peer Collaboration: Improving Teaching through Comprehensive Peer Review

ERIC Educational Resources Information Center

Smith, Shelley L.

2014-01-01

This article includes a brief rationale and review of the literature on peer review of teaching (PRT). Based on that literature review, it offers a proposal for an optimal formative review process that results in a teaching portfolio that would reflect a faculty member's efforts and successes in a critically reflective PRT process, and contributes…

Portfolio optimization for seed selection in diverse weather scenarios.

PubMed

Marko, Oskar; Brdar, Sanja; Panić, Marko; Šašić, Isidora; Despotović, Danica; Knežević, Milivoje; Crnojević, Vladimir

2017-01-01

The aim of this work was to develop a method for selection of optimal soybean varieties for the American Midwest using data analytics. We extracted the knowledge about 174 varieties from the dataset, which contained information about weather, soil, yield and regional statistical parameters. Next, we predicted the yield of each variety in each of 6,490 observed subregions of the Midwest. Furthermore, yield was predicted for all the possible weather scenarios approximated by 15 historical weather instances contained in the dataset. Using predicted yields and covariance between varieties through different weather scenarios, we performed portfolio optimisation. In this way, for each subregion, we obtained a selection of varieties, that proved superior to others in terms of the amount and stability of yield. According to the rules of Syngenta Crop Challenge, for which this research was conducted, we aggregated the results across all subregions and selected up to five soybean varieties that should be distributed across the network of seed retailers. The work presented in this paper was the winning solution for Syngenta Crop Challenge 2017.

Portfolio optimization for seed selection in diverse weather scenarios

PubMed Central

Brdar, Sanja; Panić, Marko; Šašić, Isidora; Despotović, Danica; Knežević, Milivoje; Crnojević, Vladimir

2017-01-01

The aim of this work was to develop a method for selection of optimal soybean varieties for the American Midwest using data analytics. We extracted the knowledge about 174 varieties from the dataset, which contained information about weather, soil, yield and regional statistical parameters. Next, we predicted the yield of each variety in each of 6,490 observed subregions of the Midwest. Furthermore, yield was predicted for all the possible weather scenarios approximated by 15 historical weather instances contained in the dataset. Using predicted yields and covariance between varieties through different weather scenarios, we performed portfolio optimisation. In this way, for each subregion, we obtained a selection of varieties, that proved superior to others in terms of the amount and stability of yield. According to the rules of Syngenta Crop Challenge, for which this research was conducted, we aggregated the results across all subregions and selected up to five soybean varieties that should be distributed across the network of seed retailers. The work presented in this paper was the winning solution for Syngenta Crop Challenge 2017. PMID:28863173

Using an Integrated Hydrologic-Economic Model to Develop Minimum Cost Water Supply Portfolios and Manage Supply Risk

NASA Astrophysics Data System (ADS)

Characklis, G. W.; Ramsey, J.

2004-12-01

Water scarcity has become a reality in many areas as a result of population growth, fewer available sources, and reduced tolerance for the environmental impacts of developing the new supplies that do exist. As a result, successfully managing future water supply risk will become more dependent on coordinating the use of existing resources. Toward that end, flexible supply strategies that can rapidly respond to hydrologic variability will provide communities with increasing economic advantages, particularly if the frequency of more extreme events (e.g., drought) increases due to global climate change. Markets for established commodities (e.g., oil, gas) often provide a framework for efficiently responding to changes in supply and demand. Water markets, however, have remained relatively crude, with most transactions involving permanent transfers and long regulatory processes. Recently, interest in the use of flexible short-term transfers (e.g., leases, options) has begun to motivate consideration of more sophisticated strategies for managing supply risk, strategies similar to those used in more mature markets. In this case, communities can benefit from some of the advantages that water enjoys over other commodities, in particular, the ability to accurately characterize the stochastic nature of supply and demand through hydrologic modeling. Hydrologic-economic models are developed for two different water scarce regions supporting active water markets: Edward Aquifer and Lower Rio Grande Valley. These models are used to construct portfolios of water supply transfers (e.g., permanent transfers, options, and spot leases) that minimize the cost of meeting a probabilistic reliability constraint. Real and simulated spot price distributions allow each type of transfer to be priced in a manner consistent with financial theory (e.g., Black-Scholes). Market simulations are integrated with hydrologic models such that variability in supply and demand are linked with price behavior. Decisions on when and how much water to lease (or exercise, in the case of options) are made on the basis of anticipatory rules based on the ratio of expected supply to expected demand, and are used to evaluate the economic consequences of a utilityAƒAøAøâ_sA¬Aøâ_zAøs attitude toward risk. The marginal cost of supply reliability is also explored by varying the water supply reliability constraint, an important consideration as the rising expense of new source development may encourage some communities to accept a nominal number of supply shortfalls. Results demonstrate how changes in the distribution of various transfer types within a portfolio can affect its cost and reliability. Results also suggest that substantial savings can be obtained through the use of market-based risk management strategies, with optimal portfolio costs averaging as much as 35 percent less than the costs of meeting reliability targets through the maintenance of firm capacity. Both the conceptual and modeling approach described in this work are likely to have increasing application as water scarcity continues to drive the search for more efficient approaches to water resource management.

Application of Project Portfolio Management

NASA Astrophysics Data System (ADS)

Pankowska, Malgorzata

The main goal of the chapter is the presentation of the application project portfolio management approach to support development of e-Municipality and public administration information systems. The models of how people publish and utilize information on the web have been transformed continually. Instead of simply viewing on static web pages, users publish their own content through blogs and photo- and video-sharing slides. Analysed in this chapter, ICT (Information Communication Technology) projects for municipalities cover the mixture of the static web pages, e-Government information systems, and Wikis. So, for the management of the ICT projects' mixtures the portfolio project management approach is proposed.

Reliability of Portfolio: A Closer Look at Findings from Recent Publications

ERIC Educational Resources Information Center

Oskay, Ozge Ozyalcin; Schallies, Michael; Morgil, Inci

2008-01-01

In this review article, conventional portfolio assessment and new developments in portfolio assessment are investigated. The concept of portfolio, portfolio building steps, contents of portfolio, evaluation of portfolio, advantages, disadvantages and concerns in using portfolio as well as validity and reliability of portfolio assessment are…

Consumerism as a branding opportunity.

PubMed

Treash, M; Adams, R

1998-01-01

Managing a customer portfolio at the individual level is the most difficult and most promising endeavor. An individual level consumer portfolio does not mean creating marketing materials and advertising campaigns customized for every member of your health plan. What it does mean is developing segmentation models based on consumer preferences extracted directly from your members, not socioeconomic or other demographic models. The most important information to extract is perceptions on how much and what kind of value members want from the organization.

Land-use planning for nearshore ecosystem services—the Puget Sound Ecosystem Portfolio Model

USGS Publications Warehouse

Byrd, Kristin

2011-01-01

The 2,500 miles of shoreline and nearshore areas of Puget Sound, Washington, provide multiple benefits to people—"ecosystem services"—including important fishing, shellfishing, and recreation industries. To help resource managers plan for expected growth in coming decades, the U.S. Geological Survey Western Geographic Science Center has developed the Puget Sound Ecosystem Portfolio Model (PSEPM). Scenarios of urban growth and shoreline modifications serve as model inputs to develop alternative futures of important nearshore features such as water quality and beach habitats. Model results will support regional long-term planning decisions for the Puget Sound region.

Optimal execution with price impact under Cumulative Prospect Theory

NASA Astrophysics Data System (ADS)

Zhao, Jingdong; Zhu, Hongliang; Li, Xindan

2018-01-01

Optimal execution of a stock (or portfolio) has been widely studied in academia and in practice over the past decade, and minimizing transaction costs is a critical point. However, few researchers consider the psychological factors for the traders. What are traders truly concerned with - buying low in the paper accounts or buying lower compared to others? We consider the optimal trading strategies in terms of the price impact and Cumulative Prospect Theory and identify some specific properties. Our analyses indicate that a large proportion of the execution volume is distributed at both ends of the transaction time. But the trader's optimal strategies may not be implemented at the same transaction size and speed in different market environments.

The string prediction models as invariants of time series in the forex market

NASA Astrophysics Data System (ADS)

Pincak, R.

2013-12-01

In this paper we apply a new approach of string theory to the real financial market. The models are constructed with an idea of prediction models based on the string invariants (PMBSI). The performance of PMBSI is compared to support vector machines (SVM) and artificial neural networks (ANN) on an artificial and a financial time series. A brief overview of the results and analysis is given. The first model is based on the correlation function as invariant and the second one is an application based on the deviations from the closed string/pattern form (PMBCS). We found the difference between these two approaches. The first model cannot predict the behavior of the forex market with good efficiency in comparison with the second one which is, in addition, able to make relevant profit per year. The presented string models could be useful for portfolio creation and financial risk management in the banking sector as well as for a nonlinear statistical approach to data optimization.

A comprehensive dairy valorization model.

PubMed

Banaszewska, A; Cruijssen, F; van der Vorst, J G A J; Claassen, G D H; Kampman, J L

2013-02-01

Dairy processors face numerous challenges resulting from both unsteady dairy markets and some specific characteristics of dairy supply chains. To maintain a competitive position on the market, companies must look beyond standard solutions currently used in practice. This paper presents a comprehensive dairy valorization model that serves as a decision support tool for mid-term allocation of raw milk to end products and production planning. The developed model was used to identify the optimal product portfolio composition. The model allocates raw milk to the most profitable dairy products while accounting for important constraints (i.e., recipes, composition variations, dairy production interdependencies, seasonality, demand, supply, capacities, and transportation flows). The inclusion of all relevant constraints and the ease of understanding dairy production dynamics make the model comprehensive. The developed model was tested at the international dairy processor FrieslandCampina (Amersfoort, the Netherlands). The structure of the model and its output were discussed in multiple sessions with and approved by relevant FrieslandCampina employees. The elements included in the model were considered necessary to optimally valorize raw milk. To illustrate the comprehensiveness and functionality of the model, we analyzed the effect of seasonality on milk valorization. A large difference in profit and a shift in the allocation of milk showed that seasonality has a considerable impact on the valorization of raw milk. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

A Collaborative Neurodynamic Approach to Multiple-Objective Distributed Optimization.

PubMed

Yang, Shaofu; Liu, Qingshan; Wang, Jun

2018-04-01

This paper is concerned with multiple-objective distributed optimization. Based on objective weighting and decision space decomposition, a collaborative neurodynamic approach to multiobjective distributed optimization is presented. In the approach, a system of collaborative neural networks is developed to search for Pareto optimal solutions, where each neural network is associated with one objective function and given constraints. Sufficient conditions are derived for ascertaining the convergence to a Pareto optimal solution of the collaborative neurodynamic system. In addition, it is proved that each connected subsystem can generate a Pareto optimal solution when the communication topology is disconnected. Then, a switching-topology-based method is proposed to compute multiple Pareto optimal solutions for discretized approximation of Pareto front. Finally, simulation results are discussed to substantiate the performance of the collaborative neurodynamic approach. A portfolio selection application is also given.

The use of integer programming to select bulls across breeding companies with volume price discounts.

PubMed

McConnel, M B; Galligan, D T

2004-10-01

Optimization programs are currently used to aid in the selection of bulls to be used in herd breeding programs. While these programs offer a systematic approach to the problem of semen selection, they ignore the impact of volume discounts. Volume discounts are discounts that vary depending on the number of straws purchased. The dynamic nature of volume discounts means that, in order to be adequately accounted for, they must be considered in the optimization routine. Failing to do this creates a missed economic opportunity because the potential benefits of optimally selecting and combining breeding company discount opportunities are not captured. To address these issues, an integer program was created which used binary decision variables to incorporate the effects of quantity discounts into the optimization program. A consistent set of trait criteria was used to select a group of bulls from 3 sample breeding companies. Three different selection programs were used to select the bulls, 2 traditional methods and the integer method. After the discounts were applied using each method, the integer program resulted in the lowest cost portfolio of bulls. A sensitivity analysis showed that the integer program also resulted in a low cost portfolio when the genetic trait goals were changed to be more or less stringent. In the sample application, a net benefit of the new approach over the traditional approaches was a 12.3 to 20.0% savings in semen cost.

Enabling Systemic Change: Creating an ePortfolio Implementation Framework through Design and Development Research for Use by Higher Education Professionals

ERIC Educational Resources Information Center

Blevins, Samantha; Brill, Jennifer

2017-01-01

Drawing from a design and development research approach, specifically model research, this study investigated the perspectives of higher education faculty and administrators regarding their experiences with a university-wide electronic portfolio implementation initiative. Participants in the study were fifty-two faculty and administrators at a…

Evaluating Processes and Platforms for Potential ePortfolio Use: The Role of the Middle Agent

ERIC Educational Resources Information Center

Slade, Christine; Murfin, Keith; Readman, Kylie

2013-01-01

With the changing face of higher education comes a demand to include new technological tools. Universities need to build their capacity to respond to new technology-related challenges. The introduction of ePortfolios is a significant strategy in this response. A number of organizational change management models are used to analyze the…

Using Portfolios to Improve Teaching Quality: The Case of a Small Business School

ERIC Educational Resources Information Center

Stewart, Ian

2004-01-01

In this study, the author applies B. K. Curry's (1992) model of organizational institutionalization to a case study involving efforts to implement course and teaching portfolios in a small business school. This article is based on the personal observations of those involved and the published literature on the subject. Both teaching and course…

Analysis of the Technology Acceptance Model in Examining Students' Behavioural Intention to Use an e-Portfolio System

ERIC Educational Resources Information Center

Shroff, Ronnie H.; Deneen, Christopher C.; Ng, Eugenia M. W.

2011-01-01

In recent years, instructors have had an increasing interest in integrating Internet based technologies into their classroom as part of the learning environment. Compared to studies on other information systems, student users' behaviour towards e-portfolios have not been assessed and thoroughly understood. This paper analyses the "Technology…

First Year Student Adjustment, Success, and Retention: Structural Models of Student Persistence Using Electronic Portfolios

ERIC Educational Resources Information Center

Sandler, Martin E.

2010-01-01

This study explores the deployment of electronic portfolios to a university-wide cohort of freshman undergraduates that included a subgroup of at-risk and lower academically prepared learners. Five evaluative dimensions based on persistence and engagement theory were included in the development of four assessment rubrics exploring goal clarity,…

Successful healthcare programs and projects: organization portfolio management essentials.

PubMed

Pickens, Scott; Solak, Jamie

2005-01-01

Many healthcare organization projects take more time and resources than planned and fail to deliver desired business outcomes. Healthcare IT is a major component of many projects and often undeservedly receives the blame for failure. Poor results are often not a result of faulty healthcare IT or poor project management or poor project execution alone. Many projects fail because of poor portfolio management--poor planning and management of the portfolio of initiatives designed to meet an organization's strategic goals. Because resources are limited, portfolio management enables organizations to more strategically allocate and manage their resources so care delivery, service delivery, and initiatives that advance organizations toward their strategic goals, including healthcare IT initiatives, can be accomplished at the levels of quality and service desired by an organization. Proper portfolio management is the essential foundation for program and project success and supports overall organization success. Without portfolio management, even programs and projects that execute flawlessly may not meet desired objectives. This article discusses the essential requirements for porfolio management. These include opportunity identification, return on investment (ROI) forecast, project prioritization, capacity planning (inclusive of human, financial, capital, and facilities resources), work scheduling, program and project management and execution, and project performance and value assessment. Portfolio management is essential to successful healthcare project execution. Theories are drawn from the Organizational Project Management Maturity Model (OPM3) work of the Project Management Institute and other leading strategy, planning, and organization change management research institutes.

Risk of portfolio with simulated returns based on copula model

NASA Astrophysics Data System (ADS)

Razak, Ruzanna Ab; Ismail, Noriszura

2015-02-01

The commonly used tool for measuring risk of a portfolio with equally weighted stocks is variance-covariance method. Under extreme circumstances, this method leads to significant underestimation of actual risk due to its multivariate normality assumption of the joint distribution of stocks. The purpose of this research is to compare the actual risk of portfolio with the simulated risk of portfolio in which the joint distribution of two return series is predetermined. The data used is daily stock prices from the ASEAN market for the period January 2000 to December 2012. The copula approach is applied to capture the time varying dependence among the return series. The results shows that the chosen copula families are not suitable to present the dependence structures of each bivariate returns. Exception for the Philippines-Thailand pair where by t copula distribution appears to be the appropriate choice to depict its dependence. Assuming that the t copula distribution is the joint distribution of each paired series, simulated returns is generated and value-at-risk (VaR) is then applied to evaluate the risk of each portfolio consisting of two simulated return series. The VaR estimates was found to be symmetrical due to the simulation of returns via elliptical copula-GARCH approach. By comparison, it is found that the actual risks are underestimated for all pairs of portfolios except for Philippines-Thailand. This study was able to show that disregard of the non-normal dependence structure of two series will result underestimation of actual risk of the portfolio.

Time is money: Rational life cycle inertia and the delegation of investment management

PubMed Central

Kim, Hugh Hoikwang; Maurer, Raimond; Mitchell, Olivia S.

2016-01-01

Many households display inertia in investment management over their life cycles. Our calibrated dynamic life cycle portfolio choice model can account for such an apparently ‘irrational’ outcome, by incorporating the fact that investors must forgo acquiring job-specific skills when they spend time managing their money, and their efficiency in financial decision making varies with age. Resulting inertia patterns mesh well with findings from prior studies and our own empirical results from Panel Study of Income Dynamics (PSID) data. We also analyze how people optimally choose between actively managing their assets versus delegating the task to financial advisors. Delegation proves valuable to both the young and the old. Our calibrated model quantifies welfare gains from including investment time and money costs as well as delegation in a life cycle setting. PMID:28344380

Dependence and risk assessment for oil prices and exchange rate portfolios: A wavelet based approach

NASA Astrophysics Data System (ADS)

Aloui, Chaker; Jammazi, Rania

2015-10-01

In this article, we propose a wavelet-based approach to accommodate the stylized facts and complex structure of financial data, caused by frequent and abrupt changes of markets and noises. Specifically, we show how the combination of both continuous and discrete wavelet transforms with traditional financial models helps improve portfolio's market risk assessment. In the empirical stage, three wavelet-based models (wavelet-EGARCH with dynamic conditional correlations, wavelet-copula, and wavelet-extreme value) are considered and applied to crude oil price and US dollar exchange rate data. Our findings show that the wavelet-based approach provides an effective and powerful tool for detecting extreme moments and improving the accuracy of VaR and Expected Shortfall estimates of oil-exchange rate portfolios after noise is removed from the original data.

Modeling the impacts of two age-related portfolio effects on recruitment variability with and without a marine reserve.

PubMed

McGilliard, Carey R; Punt, André E; Hilborn, Ray; Essington, Tim

2017-10-01

Many rockfish species are long-lived and thought to be susceptible to being overfished. Hypotheses about the importance of older female rockfish to population persistence have led to arguments that marine reserves are needed to ensure the sustainability of rockfish populations. However, the implications of these hypotheses for rockfish population dynamics are still unclear. We modeled two mechanisms by which reducing the proportion of older fish in a population has been hypothesized to influence sustainability, and explored whether these mechanisms influenced mean population dynamics and recruitment variability. We explored whether populations with these mechanisms could be managed more sustainably with a marine reserve in addition to a constant fishing mortality rate (F) than with a constant F alone. Both hypotheses can be seen as portfolio effects whereby risk of recruitment failure is spread over a "portfolio" of maternal ages. First, we modeled a spawning window effect whereby mothers of different ages spawned in different times or locations (windows) with local environmental conditions. Second, we modeled an offspring size effect whereby older mothers produced larger offspring than younger mothers, where length of a starvation period over which offspring could survive increased with maternal age. Recruitment variability resulting from both models was 55-65% lower than for models without maternal age-related portfolio effects in the absence of fishing and increased with increases in Fs for both models. An offspring size effect caused lower output reproductive rates such that the specified reproductive rate input as a model parameter was no longer the realized rate measured as the reproductive rate observed in model results; this quirk is not addressed in previous analyses of offspring size effects. We conducted a standardization such that offspring size effect and control models had the same observed reproductive rates. A comparison of long-term catch, the probability of falling below a biomass threshold, and recruitment variability over a range of exploitation rates for models with an age-related portfolio effect showed no benefit of a marine reserve implemented in addition to a constant F (as compared to a constant F alone) for populations with sedentary adults and sedentary or mobile larvae. © 2017 by the Ecological Society of America.

From aggregation to interpretation: how assessors judge complex data in a competency-based portfolio.

PubMed

Oudkerk Pool, Andrea; Govaerts, Marjan J B; Jaarsma, Debbie A D C; Driessen, Erik W

2018-05-01

While portfolios are increasingly used to assess competence, the validity of such portfolio-based assessments has hitherto remained unconfirmed. The purpose of the present research is therefore to further our understanding of how assessors form judgments when interpreting the complex data included in a competency-based portfolio. Eighteen assessors appraised one of three competency-based mock portfolios while thinking aloud, before taking part in semi-structured interviews. A thematic analysis of the think-aloud protocols and interviews revealed that assessors reached judgments through a 3-phase cyclical cognitive process of acquiring, organizing, and integrating evidence. Upon conclusion of the first cycle, assessors reviewed the remaining portfolio evidence to look for confirming or disconfirming evidence. Assessors were inclined to stick to their initial judgments even when confronted with seemingly disconfirming evidence. Although assessors reached similar final (pass-fail) judgments of students' professional competence, they differed in their information-processing approaches and the reasoning behind their judgments. Differences sprung from assessors' divergent assessment beliefs, performance theories, and inferences about the student. Assessment beliefs refer to assessors' opinions about what kind of evidence gives the most valuable and trustworthy information about the student's competence, whereas assessors' performance theories concern their conceptualizations of what constitutes professional competence and competent performance. Even when using the same pieces of information, assessors furthermore differed with respect to inferences about the student as a person as well as a (future) professional. Our findings support the notion that assessors' reasoning in judgment and decision-making varies and is guided by their mental models of performance assessment, potentially impacting feedback and the credibility of decisions. Our findings also lend further credence to the assertion that portfolios should be judged by multiple assessors who should, moreover, thoroughly substantiate their judgments. Finally, it is suggested that portfolios be designed in such a way that they facilitate the selection of and navigation through the portfolio evidence.

77 FR 7219 - Self-Regulatory Organizations; NYSE Arca, Inc.; Order Granting Approval of a Proposed Rule Change...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-10

... market and a national market system, and, in general, to protect investors and the public interest. The... in, securities. Quotation and last- sale information for the Shares will be available via the... subscription basis.\\21\\ In addition, for each Fund, the Indicative Optimized Portfolio Value (``IOPV'') will be...

75 FR 71158 - Self-Regulatory Organizations; NYSE Arca, Inc.; Notice of Filing of Proposed Rule Change Relating...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-22

...://www.cfe.cboe.com ), automated quotation systems, published or other public sources, or on-line [[Page... and last-sale information regarding the Shares will be disseminated through the facilities of the... Optimized Portfolio Value (``IOPV'') will be calculated. The IOPV is an indicator of the value of the VIX...

Estimation and prediction under local volatility jump-diffusion model

NASA Astrophysics Data System (ADS)

Kim, Namhyoung; Lee, Younhee

2018-02-01

Volatility is an important factor in operating a company and managing risk. In the portfolio optimization and risk hedging using the option, the value of the option is evaluated using the volatility model. Various attempts have been made to predict option value. Recent studies have shown that stochastic volatility models and jump-diffusion models reflect stock price movements accurately. However, these models have practical limitations. Combining them with the local volatility model, which is widely used among practitioners, may lead to better performance. In this study, we propose a more effective and efficient method of estimating option prices by combining the local volatility model with the jump-diffusion model and apply it using both artificial and actual market data to evaluate its performance. The calibration process for estimating the jump parameters and local volatility surfaces is divided into three stages. We apply the local volatility model, stochastic volatility model, and local volatility jump-diffusion model estimated by the proposed method to KOSPI 200 index option pricing. The proposed method displays good estimation and prediction performance.

Household portfolio choices, health status and health care systems: A cross-country analysis based on SHARE.

PubMed

Atella, Vincenzo; Brunetti, Marianna; Maestas, Nicole

2012-05-01

Health risk is increasingly viewed as an important form of background risk that affects household portfolio decisions. However, its role might be mediated by the presence of a protective full-coverage national health service that could reduce households' probability of incurring current and future out-of-pocket medical expenditures. We use SHARE data to study the influence of current health status and future health risk on the decision to hold risky assets, across ten European countries with different health systems, each offering a different degree of protection against out-of-pocket medical expenditures. We find robust empirical evidence that perceived health status matters more than objective health status and, consistent with the theory of background risk, health risk affects portfolio choices only in countries with less protective health care systems. Furthermore, portfolio decisions consistent with background risk models are observed only with respect to middle-aged and highly-educated investors.

The Development of Statistics Textbook Supported with ICT and Portfolio-Based Assessment

NASA Astrophysics Data System (ADS)

Hendikawati, Putriaji; Yuni Arini, Florentina

2016-02-01

This research was development research that aimed to develop and produce a Statistics textbook model that supported with information and communication technology (ICT) and Portfolio-Based Assessment. This book was designed for students of mathematics at the college to improve students’ ability in mathematical connection and communication. There were three stages in this research i.e. define, design, and develop. The textbooks consisted of 10 chapters which each chapter contains introduction, core materials and include examples and exercises. The textbook developed phase begins with the early stages of designed the book (draft 1) which then validated by experts. Revision of draft 1 produced draft 2 which then limited test for readability test book. Furthermore, revision of draft 2 produced textbook draft 3 which simulated on a small sample to produce a valid model textbook. The data were analysed with descriptive statistics. The analysis showed that the Statistics textbook model that supported with ICT and Portfolio-Based Assessment valid and fill up the criteria of practicality.

Domestic Violence and Social Responsibility in Contemporary Spanish Cinema: A Portfolio View of Behavioral Dynamics

ERIC Educational Resources Information Center

Zanzana, Habib

2010-01-01

Domestic abuse continues to claim many lives in Spain despite a series of new laws to protect women and to punish abusers. This essay explores the cultural influences of contemporary Spanish cinema on domestic violence. Four films are assessed against a Portfolio Model of social responsibility that uses two basic dimensions: realism and human…

Optimizing the discovery organization for innovation.

PubMed

Sams-Dodd, Frank

2005-08-01

Strategic management is the process of adapting organizational structure and management principles to fit the strategic goal of the business unit. The pharmaceutical industry has generally been expert at optimizing its organizations for drug development, but has rarely implemented different structures for the early discovery process, where the objective is innovation and the transformation of innovation into drug projects. Here, a set of strategic management methods is proposed, covering team composition, organizational structure, management principles and portfolio management, which are designed to increase the level of innovation in the early drug discovery process.

Status of portfolios in undergraduate medical education in the LCME accredited US medical school.

PubMed

Chertoff, Jason; Wright, Ashleigh; Novak, Maureen; Fantone, Joseph; Fleming, Amy; Ahmed, Toufeeq; Green, Marianne M; Kalet, Adina; Linsenmeyer, Machelle; Jacobs, Joshua; Dokter, Christina; Zaidi, Zareen

2016-09-01

We sought to investigate the number of US medical schools utilizing portfolios, the format of portfolios, information technology (IT) innovations, purpose of portfolios and their ability to engage faculty and students. A 21-question survey regarding portfolios was sent to the 141 LCME-accredited, US medical schools. The response rate was 50% (71/141); 47% of respondents (33/71) reported that their medical school used portfolios in some form. Of those, 7% reported the use of paper-based portfolios and 76% use electronic portfolios. Forty-five percent reported portfolio use for formative evaluation only; 48% for both formative and summative evaluation, and 3% for summative evaluation alone. Seventy-two percent developed a longitudinal, competency-based portfolio. The most common feature of portfolios was reflective writing (79%). Seventy-three percent allow access to the portfolio off-campus, 58% allow usage of tablets and mobile devices, and 9% involve social media within the portfolio. Eighty percent and 69% agreed that the portfolio engaged students and faculty, respectively. Ninety-seven percent reported that the portfolios used at their institution have room for improvement. While there is significant variation in the purpose and structure of portfolios in the medical schools surveyed, most schools using portfolios reported a high level of engagement with students and faculty.

Estimation of value at risk in currency exchange rate portfolio using asymmetric GJR-GARCH Copula

NASA Astrophysics Data System (ADS)

Nurrahmat, Mohamad Husein; Noviyanti, Lienda; Bachrudin, Achmad

2017-03-01

In this study, we discuss the problem in measuring the risk in a portfolio based on value at risk (VaR) using asymmetric GJR-GARCH Copula. The approach based on the consideration that the assumption of normality over time for the return can not be fulfilled, and there is non-linear correlation for dependent model structure among the variables that lead to the estimated VaR be inaccurate. Moreover, the leverage effect also causes the asymmetric effect of dynamic variance and shows the weakness of the GARCH models due to its symmetrical effect on conditional variance. Asymmetric GJR-GARCH models are used to filter the margins while the Copulas are used to link them together into a multivariate distribution. Then, we use copulas to construct flexible multivariate distributions with different marginal and dependence structure, which is led to portfolio joint distribution does not depend on the assumptions of normality and linear correlation. VaR obtained by the analysis with confidence level 95% is 0.005586. This VaR derived from the best Copula model, t-student Copula with marginal distribution of t distribution.

Dynamics of market correlations: Taxonomy and portfolio analysis

NASA Astrophysics Data System (ADS)

Onnela, J.-P.; Chakraborti, A.; Kaski, K.; Kertész, J.; Kanto, A.

2003-11-01

The time dependence of the recently introduced minimum spanning tree description of correlations between stocks, called the “asset tree” has been studied in order to reflect the financial market taxonomy. The nodes of the tree are identified with stocks and the distance between them is a unique function of the corresponding element of the correlation matrix. By using the concept of a central vertex, chosen as the most strongly connected node of the tree, an important characteristic is defined by the mean occupation layer. During crashes, due to the strong global correlation in the market, the tree shrinks topologically, and this is shown by a low value of the mean occupation layer. The tree seems to have a scale-free structure where the scaling exponent of the degree distribution is different for “business as usual” and “crash” periods. The basic structure of the tree topology is very robust with respect to time. We also point out that the diversification aspect of portfolio optimization results in the fact that the assets of the classic Markowitz portfolio are always located on the outer leaves of the tree. Technical aspects such as the window size dependence of the investigated quantities are also discussed.

Dynamics of market correlations: taxonomy and portfolio analysis.

PubMed

Onnela, J-P; Chakraborti, A; Kaski, K; Kertész, J; Kanto, A

2003-11-01

The time dependence of the recently introduced minimum spanning tree description of correlations between stocks, called the "asset tree" has been studied in order to reflect the financial market taxonomy. The nodes of the tree are identified with stocks and the distance between them is a unique function of the corresponding element of the correlation matrix. By using the concept of a central vertex, chosen as the most strongly connected node of the tree, an important characteristic is defined by the mean occupation layer. During crashes, due to the strong global correlation in the market, the tree shrinks topologically, and this is shown by a low value of the mean occupation layer. The tree seems to have a scale-free structure where the scaling exponent of the degree distribution is different for "business as usual" and "crash" periods. The basic structure of the tree topology is very robust with respect to time. We also point out that the diversification aspect of portfolio optimization results in the fact that the assets of the classic Markowitz portfolio are always located on the outer leaves of the tree. Technical aspects such as the window size dependence of the investigated quantities are also discussed.

Optimal investment in a portfolio of HIV prevention programs.

PubMed

Zaric, G S; Brandeau, M L

2001-01-01

In this article, the authors determine the optimal allocation of HIV prevention funds and investigate the impact of different allocation methods on health outcomes. The authors present a resource allocation model that can be used to determine the allocation of HIV prevention funds that maximizes quality-adjusted life years (or life years) gained or HIV infections averted in a population over a specified time horizon. They apply the model to determine the allocation of a limited budget among 3 types of HIV prevention programs in a population of injection drug users and nonusers: needle exchange programs, methadone maintenance treatment, and condom availability programs. For each prevention program, the authors estimate a production function that relates the amount invested to the associated change in risky behavior. The authors determine the optimal allocation of funds for both objective functions for a high-prevalence population and a low-prevalence population. They also consider the allocation of funds under several common rules of thumb that are used to allocate HIV prevention resources. It is shown that simpler allocation methods (e.g., allocation based on HIV incidence or notions of equity among population groups) may lead to alloctions that do not yield the maximum health benefit. The optimal allocation of HIV prevention funds in a population depends on HIV prevalence and incidence, the objective function, the production functions for the prevention programs, and other factors. Consideration of cost, equity, and social and political norms may be important when allocating HIV prevention funds. The model presented in this article can help decision makers determine the health consequences of different allocations of funds.

Theory of Financial Risk and Derivative Pricing

NASA Astrophysics Data System (ADS)

Bouchaud, Jean-Philippe; Potters, Marc

2009-01-01

Foreword; Preface; 1. Probability theory: basic notions; 2. Maximum and addition of random variables; 3. Continuous time limit, Ito calculus and path integrals; 4. Analysis of empirical data; 5. Financial products and financial markets; 6. Statistics of real prices: basic results; 7. Non-linear correlations and volatility fluctuations; 8. Skewness and price-volatility correlations; 9. Cross-correlations; 10. Risk measures; 11. Extreme correlations and variety; 12. Optimal portfolios; 13. Futures and options: fundamental concepts; 14. Options: hedging and residual risk; 15. Options: the role of drift and correlations; 16. Options: the Black and Scholes model; 17. Options: some more specific problems; 18. Options: minimum variance Monte-Carlo; 19. The yield curve; 20. Simple mechanisms for anomalous price statistics; Index of most important symbols; Index.

Theory of Financial Risk and Derivative Pricing - 2nd Edition

NASA Astrophysics Data System (ADS)

Bouchaud, Jean-Philippe; Potters, Marc

2003-12-01

Foreword; Preface; 1. Probability theory: basic notions; 2. Maximum and addition of random variables; 3. Continuous time limit, Ito calculus and path integrals; 4. Analysis of empirical data; 5. Financial products and financial markets; 6. Statistics of real prices: basic results; 7. Non-linear correlations and volatility fluctuations; 8. Skewness and price-volatility correlations; 9. Cross-correlations; 10. Risk measures; 11. Extreme correlations and variety; 12. Optimal portfolios; 13. Futures and options: fundamental concepts; 14. Options: hedging and residual risk; 15. Options: the role of drift and correlations; 16. Options: the Black and Scholes model; 17. Options: some more specific problems; 18. Options: minimum variance Monte-Carlo; 19. The yield curve; 20. Simple mechanisms for anomalous price statistics; Index of most important symbols; Index.

Entropy-based financial asset pricing.

PubMed

Ormos, Mihály; Zibriczky, Dávid

2014-01-01

We investigate entropy as a financial risk measure. Entropy explains the equity premium of securities and portfolios in a simpler way and, at the same time, with higher explanatory power than the beta parameter of the capital asset pricing model. For asset pricing we define the continuous entropy as an alternative measure of risk. Our results show that entropy decreases in the function of the number of securities involved in a portfolio in a similar way to the standard deviation, and that efficient portfolios are situated on a hyperbola in the expected return-entropy system. For empirical investigation we use daily returns of 150 randomly selected securities for a period of 27 years. Our regression results show that entropy has a higher explanatory power for the expected return than the capital asset pricing model beta. Furthermore we show the time varying behavior of the beta along with entropy.

Entropy-Based Financial Asset Pricing

PubMed Central

Ormos, Mihály; Zibriczky, Dávid

2014-01-01

We investigate entropy as a financial risk measure. Entropy explains the equity premium of securities and portfolios in a simpler way and, at the same time, with higher explanatory power than the beta parameter of the capital asset pricing model. For asset pricing we define the continuous entropy as an alternative measure of risk. Our results show that entropy decreases in the function of the number of securities involved in a portfolio in a similar way to the standard deviation, and that efficient portfolios are situated on a hyperbola in the expected return – entropy system. For empirical investigation we use daily returns of 150 randomly selected securities for a period of 27 years. Our regression results show that entropy has a higher explanatory power for the expected return than the capital asset pricing model beta. Furthermore we show the time varying behavior of the beta along with entropy. PMID:25545668

Financial Crisis: A New Measure for Risk of Pension Fund Portfolios

PubMed Central

Cadoni, Marinella; Melis, Roberta; Trudda, Alessandro

2015-01-01

It has been argued that pension funds should have limitations on their asset allocation, based on the risk profile of the different financial instruments available on the financial markets. This issue proves to be highly relevant at times of market crisis, when a regulation establishing limits to risk taking for pension funds could prevent defaults. In this paper we present a framework for evaluating the risk level of a single financial instrument or a portfolio. By assuming that the log asset returns can be described by a multifractional Brownian motion, we evaluate the risk using the time dependent Hurst parameter H(t) which models volatility. To provide a measure of the risk, we model the Hurst parameter with a random variable with mixture of beta distribution. We prove the efficacy of the methodology by implementing it on different risk level financial instruments and portfolios. PMID:26086529

Financial Crisis: A New Measure for Risk of Pension Fund Portfolios.

PubMed

Cadoni, Marinella; Melis, Roberta; Trudda, Alessandro

2015-01-01

It has been argued that pension funds should have limitations on their asset allocation, based on the risk profile of the different financial instruments available on the financial markets. This issue proves to be highly relevant at times of market crisis, when a regulation establishing limits to risk taking for pension funds could prevent defaults. In this paper we present a framework for evaluating the risk level of a single financial instrument or a portfolio. By assuming that the log asset returns can be described by a multifractional Brownian motion, we evaluate the risk using the time dependent Hurst parameter H(t) which models volatility. To provide a measure of the risk, we model the Hurst parameter with a random variable with mixture of beta distribution. We prove the efficacy of the methodology by implementing it on different risk level financial instruments and portfolios.

The effects of portfolio purchasing on a specialized subject collection.

PubMed

Murphy, Sarah Anne

2007-01-01

To examine the impact of portfolio purchasing on a small, highly specialized medical collection at The Ohio State University. In this citation analysis, cited references for articles published by faculty in the College of Veterinary Medicine between 2000 and 2004 were collected and analyzed to determine whether The Ohio State University Libraries provided print or electronic access to the publications cited or the publishers of the cited journals, and whether the university purchased a subscription to each journal or received the subscription through a consortium-sponsored portfolio purchasing agreement. Of the 419 journals veterinary faculty cited more than 10 times, only 13 (3.1%) were in Zone 1, and 63 (15.0%) were in Zone 2 of the Bradford distribution, a citation analysis model which demonstrates that a small number of journals account for the bulk of literature utilized in any established field. Of these, only 23 (5.5%) were procured through an OhioLINK or other consortium portfolio purchasing agreement. The costs of acquiring a publisher's portfolio, even through a consortium, should be balanced with the costs of purchasing content required to provide a balanced collection for all user populations.

The effects of portfolio purchasing on a specialized subject collection

PubMed Central

Murphy, Sarah Anne

2007-01-01

Objective: To examine the impact of portfolio purchasing on a small, highly specialized medical collection at The Ohio State University. Methodology: In this citation analysis, cited references for articles published by faculty in the College of Veterinary Medicine between 2000 and 2004 were collected and analyzed to determine whether The Ohio State University Libraries provided print or electronic access to the publications cited or the publishers of the cited journals, and whether the university purchased a subscription to each journal or received the subscription through a consortium-sponsored portfolio purchasing agreement. Results: Of the 419 journals veterinary faculty cited more than 10 times, only 13 (3.1%) were in Zone 1, and 63 (15.0%) were in Zone 2 of the Bradford distribution, a citation analysis model which demonstrates that a small number of journals account for the bulk of literature utilized in any established field. Of these, only 23 (5.5%) were procured through an OhioLINK or other consortium portfolio purchasing agreement. Discussion/Conclusion: The costs of acquiring a publisher's portfolio, even through a consortium, should be balanced with the costs of purchasing content required to provide a balanced collection for all user populations. PMID:17252061

Computational Support for Technology- Investment Decisions

NASA Technical Reports Server (NTRS)

Adumitroaie, Virgil; Hua, Hook; Lincoln, William; Block, Gary; Mrozinski, Joseph; Shelton, Kacie; Weisbin, Charles; Elfes, Alberto; Smith, Jeffrey

2007-01-01

Strategic Assessment of Risk and Technology (START) is a user-friendly computer program that assists human managers in making decisions regarding research-and-development investment portfolios in the presence of uncertainties and of non-technological constraints that include budgetary and time limits, restrictions related to infrastructure, and programmatic and institutional priorities. START facilitates quantitative analysis of technologies, capabilities, missions, scenarios and programs, and thereby enables the selection and scheduling of value-optimal development efforts. START incorporates features that, variously, perform or support a unique combination of functions, most of which are not systematically performed or supported by prior decision- support software. These functions include the following: Optimal portfolio selection using an expected-utility-based assessment of capabilities and technologies; Temporal investment recommendations; Distinctions between enhancing and enabling capabilities; Analysis of partial funding for enhancing capabilities; and Sensitivity and uncertainty analysis. START can run on almost any computing hardware, within Linux and related operating systems that include Mac OS X versions 10.3 and later, and can run in Windows under the Cygwin environment. START can be distributed in binary code form. START calls, as external libraries, several open-source software packages. Output is in Excel (.xls) file format.

The Business Change Initiative: A Novel Approach to Improved Cost and Schedule Management

NASA Technical Reports Server (NTRS)

Shinn, Stephen A.; Bryson, Jonathan; Klein, Gerald; Lunz-Ruark, Val; Majerowicz, Walt; McKeever, J.; Nair, Param

2016-01-01

Goddard Space Flight Center's Flight Projects Directorate employed a Business Change Initiative (BCI) to infuse a series of activities coordinated to drive improved cost and schedule performance across Goddard's missions. This sustaining change framework provides a platform to manage and implement cost and schedule control techniques throughout the project portfolio. The BCI concluded in December 2014, deploying over 100 cost and schedule management changes including best practices, tools, methods, training, and knowledge sharing. The new business approach has driven the portfolio to improved programmatic performance. The last eight launched GSFC missions have optimized cost, schedule, and technical performance on a sustained basis to deliver on time and within budget, returning funds in many cases. While not every future mission will boast such strong performance, improved cost and schedule tools, management practices, and ongoing comprehensive evaluations of program planning and control methods to refine and implement best practices will continue to provide a framework for sustained performance. This paper will describe the tools, techniques, and processes developed during the BCI and the utilization of collaborative content management tools to disseminate project planning and control techniques to ensure continuous collaboration and optimization of cost and schedule management in the future.

On application of vector optimization in the problem of formation of portfolio of counterparties

NASA Astrophysics Data System (ADS)

Gorbich, A. L.; Medvedeva, M. A.; Medvedev, M. A.

2016-12-01

For the effective functioning of any enterprise it is necessary to choose the right partners: suppliers of raw material, buyers of finished products, with which the company interacts in the course of their business. However, the presence on the market of big amounts of enterprises makes the choice the most appropriate among them very difficult and requires the ability to objectively assess of the possible partners, based on multilateral analysis of their activities. This analysis can be carried out based on the solution of multiobjective problems of mathematical programming by using the methods of vector optimization. The work considers existing methods of selection of counterparties, as well as the theoretical foundations for the proposed methodology. It also describes a computer program that analyzes the raw data for contractors and allows choosing the best portfolio of suppliers of enterprise. The feature of selection of counterparties is that today's market has a large number of enterprises in similar activities. Successful choice of contractor will help to avoid unpleasant situations and financial losses, as well as to find a reliable partner in his person for the implementation of the production strategy of the company.

[Services portfolio of a department of endocrinology and clinical nutrition].

PubMed

Vicente Delgado, Almudena; Gómez Enterría, Pilar; Tinahones Madueño, Francisco

2011-03-01

Endocrinology and Clinical Nutrition are branches of Medicine that deal with the study of physiology of body glands and hormones and their disorders, intermediate metabolism of nutrients, enteral and parenteral nutrition, promotion of health by prevention of diet-related diseases, and appropriate use of the diagnostic, therapeutic, and preventive tools related to these disciplines. Development of Endocrinology and Clinical Nutrition support services requires accurate definition and management of a number of complex resources, both human and material, as well as adequate planning of the care provided. It is therefore essential to know the services portfolio of an ideal Department of Endocrinology and Clinical Nutrition because this is a useful, valid and necessary tool to optimize the available resources, to increase efficiency, and to improve the quality of care. Copyright © 2010 SEEN. Published by Elsevier Espana. All rights reserved.

Environmental Risk Profiling of the Volta Delta, Ghana

NASA Astrophysics Data System (ADS)

Nyarko, B. K.; Appeaning-Addo, K.; Amisigo, B.

2017-12-01

Volta Delta communities find it difficult to absorb or bear risk at different levels, because of the physical and economic impacts of environmental hazards. In this regards various agencies and organizations have in recent years launched initiatives to measure and identify risk areas with a set of indicators and indices. The theory underpinning this study is concepts of Modern Portfolio Theory (MPT). The Cox proportional hazards regression model will be used as the model for the risk profile. Finding the optimal level of environmental risk for activities in the Volta Delta considering the risk required, risk capacity and risk tolerance. Using data from different sources, an environmental risk profile was developed for the Volta Delta. The result indicates that risks are distributed across the Delta. However, areas that have government interventions, such as sea defense system and irrigation facilities have less threat. In addition wealthy areas do effectively reduce the threat of any form of disaster.

Composing problem solvers for simulation experimentation: a case study on steady state estimation.

PubMed

Leye, Stefan; Ewald, Roland; Uhrmacher, Adelinde M

2014-01-01

Simulation experiments involve various sub-tasks, e.g., parameter optimization, simulation execution, or output data analysis. Many algorithms can be applied to such tasks, but their performance depends on the given problem. Steady state estimation in systems biology is a typical example for this: several estimators have been proposed, each with its own (dis-)advantages. Experimenters, therefore, must choose from the available options, even though they may not be aware of the consequences. To support those users, we propose a general scheme to aggregate such algorithms to so-called synthetic problem solvers, which exploit algorithm differences to improve overall performance. Our approach subsumes various aggregation mechanisms, supports automatic configuration from training data (e.g., via ensemble learning or portfolio selection), and extends the plugin system of the open source modeling and simulation framework James II. We show the benefits of our approach by applying it to steady state estimation for cell-biological models.

The type k universal portfolio generated by the f-divergence

NASA Astrophysics Data System (ADS)

Tan, Choon Peng; Seng, Kuang Kee

2017-11-01

The logarithm of the estimated next-day wealth return is approximated by k terms of its Taylor series. The resulting Type k universal portfolio generated by the f -divergence is obtained. An implicit form of the portfolio is also obtained by exploiting the mean-value theorem. An empirical study of the performance of the portfolio is focused on the Type 2 Helmbold universal portfolio. A few generalizations of the Helmbold universal portfolio have recently been studied, namely the reverse Helmbold and the parametric Helmbold portfolios. This new type of portfolio can be regarded a contribution to the inventory of Helmbold related universal portfolios. It is verified experimentally that an investor's wealth can be significantly increased by using the Type 2 Helmbold portfolio in investment.

Curriculum-Referenced Test Development Workshop Series, Addendum to Workshops Two and Three: Using Portfolios in Instruction and Assessment.

ERIC Educational Resources Information Center

Arter, Judith A.

An overview of the state of the art of using portfolios for assessment and instruction (AAI) and an annotated bibliography of articles focusing on portfolios are provided. Using portfolios for AAI has become a popular practice; however, portfolios are not always clearly defined. A working definition of portfolio is provided: a portfolio is a…

Business models and leadership styles in small medical device and bio-science businesses--examples in a region and their implications.

PubMed

Williams, D J; Hourd, P C

2004-01-01

This paper reviews the leadership styles and business models found in small technologically based businesses operating in the healthcare sector within one of the UK regions, the East Midlands. The most frequently encountered business model strands were 1) mixed economies: that fund development with service income; cross-sectoral product portfolios; and decoupled business portfolios led by a single entrepreneur and 2) scale sensitive "stay small" models including the avoidance of venture capital; "early exit"; and virtual business strands. There was found to be little correlation between leadership style and business model for the small number of businesses surveyed. The avoidance of venture capital is in direct contrast to adjacent regions.

Performance of salmon fishery portfolios across western North America.

PubMed

Griffiths, Jennifer R; Schindler, Daniel E; Armstrong, Jonathan B; Scheuerell, Mark D; Whited, Diane C; Clark, Robert A; Hilborn, Ray; Holt, Carrie A; Lindley, Steven T; Stanford, Jack A; Volk, Eric C

2014-12-01

Quantifying the variability in the delivery of ecosystem services across the landscape can be used to set appropriate management targets, evaluate resilience and target conservation efforts. Ecosystem functions and services may exhibit portfolio-type dynamics, whereby diversity within lower levels promotes stability at more aggregated levels. Portfolio theory provides a framework to characterize the relative performance among ecosystems and the processes that drive differences in performance. We assessed Pacific salmon Oncorhynchus spp. portfolio performance across their native latitudinal range focusing on the reliability of salmon returns as a metric with which to assess the function of salmon ecosystems and their services to humans. We used the Sharpe ratio (e.g. the size of the total salmon return to the portfolio relative to its variability (risk)) to evaluate the performance of Chinook and sockeye salmon portfolios across the west coast of North America. We evaluated the effects on portfolio performance from the variance of and covariance among salmon returns within each portfolio, and the association between portfolio performance and watershed attributes. We found a positive latitudinal trend in the risk-adjusted performance of Chinook and sockeye salmon portfolios that also correlated negatively with anthropogenic impact on watersheds (e.g. dams and land-use change). High-latitude Chinook salmon portfolios were on average 2·5 times more reliable, and their portfolio risk was mainly due to low variance in the individual assets. Sockeye salmon portfolios were also more reliable at higher latitudes, but sources of risk varied among the highest performing portfolios. Synthesis and applications . Portfolio theory provides a straightforward method for characterizing the resilience of salmon ecosystems and their services. Natural variability in portfolio performance among undeveloped watersheds provides a benchmark for restoration efforts. Locally and regionally, assessing the sources of portfolio risk can guide actions to maintain existing resilience (protect habitat and disturbance regimes that maintain response diversity; employ harvest strategies sensitive to different portfolio components) or improve restoration activities. Improving our understanding of portfolio reliability may allow for management of natural resources that is robust to ongoing environmental change. Portfolio theory provides a straightforward method for characterizing the resilience of salmon ecosystems and their services. Natural variability in portfolio performance among undeveloped watersheds provides a benchmark for restoration efforts. Locally and regionally, assessing the sources of portfolio risk can guide actions to maintain existing resilience (protect habitat and disturbance regimes that maintain response diversity; employ harvest strategies sensitive to different portfolio components) or improve restoration activities. Improving our understanding of portfolio reliability may allow for management of natural resources that is robust to ongoing environmental change.

Performance of salmon fishery portfolios across western North America

PubMed Central

Griffiths, Jennifer R; Schindler, Daniel E; Armstrong, Jonathan B; Scheuerell, Mark D; Whited, Diane C; Clark, Robert A; Hilborn, Ray; Holt, Carrie A; Lindley, Steven T; Stanford, Jack A; Volk, Eric C

2014-01-01

Quantifying the variability in the delivery of ecosystem services across the landscape can be used to set appropriate management targets, evaluate resilience and target conservation efforts. Ecosystem functions and services may exhibit portfolio-type dynamics, whereby diversity within lower levels promotes stability at more aggregated levels. Portfolio theory provides a framework to characterize the relative performance among ecosystems and the processes that drive differences in performance. We assessed Pacific salmon Oncorhynchus spp. portfolio performance across their native latitudinal range focusing on the reliability of salmon returns as a metric with which to assess the function of salmon ecosystems and their services to humans. We used the Sharpe ratio (e.g. the size of the total salmon return to the portfolio relative to its variability (risk)) to evaluate the performance of Chinook and sockeye salmon portfolios across the west coast of North America. We evaluated the effects on portfolio performance from the variance of and covariance among salmon returns within each portfolio, and the association between portfolio performance and watershed attributes. We found a positive latitudinal trend in the risk-adjusted performance of Chinook and sockeye salmon portfolios that also correlated negatively with anthropogenic impact on watersheds (e.g. dams and land-use change). High-latitude Chinook salmon portfolios were on average 2·5 times more reliable, and their portfolio risk was mainly due to low variance in the individual assets. Sockeye salmon portfolios were also more reliable at higher latitudes, but sources of risk varied among the highest performing portfolios. Synthesis and applications. Portfolio theory provides a straightforward method for characterizing the resilience of salmon ecosystems and their services. Natural variability in portfolio performance among undeveloped watersheds provides a benchmark for restoration efforts. Locally and regionally, assessing the sources of portfolio risk can guide actions to maintain existing resilience (protect habitat and disturbance regimes that maintain response diversity; employ harvest strategies sensitive to different portfolio components) or improve restoration activities. Improving our understanding of portfolio reliability may allow for management of natural resources that is robust to ongoing environmental change. Portfolio theory provides a straightforward method for characterizing the resilience of salmon ecosystems and their services. Natural variability in portfolio performance among undeveloped watersheds provides a benchmark for restoration efforts. Locally and regionally, assessing the sources of portfolio risk can guide actions to maintain existing resilience (protect habitat and disturbance regimes that maintain response diversity; employ harvest strategies sensitive to different portfolio components) or improve restoration activities. Improving our understanding of portfolio reliability may allow for management of natural resources that is robust to ongoing environmental change. PMID:25552746

Assessing Zambia's industrial fortification options: getting beyond changes in prevalence and cost-effectiveness.

PubMed

Fiedler, John L; Lividini, Keith; Kabaghe, Gladys; Zulu, Rodah; Tehinse, John; Bermudez, Odilia I; Jallier, Vincent; Guyondet, Christophe

2013-12-01

Background. Since fortification of sugar with vitamin A was mandated in 1998, Zambia's fortification program has not changed, while the country remains plagued by high rates ofmicronutrient deficiencies. Objective. To provide evidence-based fortification options with the hope of reinvigorating the Zambian fortification program. Methods. Zambia's 2006 Living Conditions Monitoring Survey is used to estimate the apparent intakes of vitamin A, iron, and zinc, as well as the apparent consumption levels and coverage of four fortification vehicles. Fourteen alternativefoodfortification portfolios are modeled, and their costs, impacts, average cost-effectiveness, and incremental cost-effectiveness are calculated using three alternative impact measures. Results. Alternative impact measures result in different rank orderings of the portfolios. The most cost-effective portfolio is vegetable oil, which has a cost per disability-adjusted life-year (DALY) saved ranging from 12% to 25% of that of sugar, depending on the impact measure used. The public health impact of fortified vegetable oil, however, is relatively modest. Additional criteria beyond cost-effectiveness are introduced and used to rank order the portfolios. The size of the public health impact, the total cost, and the incremental cost-effectiveness of phasing in multiple vehicle portfolios over time are analyzed. Conclusions. Assessing fortification portfolios by measuring changes in the prevalence of inadequate intakes underestimates impact. A more sensitive measure, which also takes into account change in the Estimated Average Requirement (EAR) gap, is provided by a dose-response-based approach to estimating the number ofDALYs saved. There exist highly cost-effective fortification intervention portfolios with substantial public health impacts and variable price tags that could help improve Zambians' nutrition status.

Household portfolio choices, health status and health care systems: A cross-country analysis based on SHARE

PubMed Central

Atella, Vincenzo; Brunetti, Marianna; Maestas, Nicole

2013-01-01

Health risk is increasingly viewed as an important form of background risk that affects household portfolio decisions. However, its role might be mediated by the presence of a protective full-coverage national health service that could reduce households’ probability of incurring current and future out-of-pocket medical expenditures. We use SHARE data to study the influence of current health status and future health risk on the decision to hold risky assets, across ten European countries with different health systems, each offering a different degree of protection against out-of-pocket medical expenditures. We find robust empirical evidence that perceived health status matters more than objective health status and, consistent with the theory of background risk, health risk affects portfolio choices only in countries with less protective health care systems. Furthermore, portfolio decisions consistent with background risk models are observed only with respect to middle-aged and highly-educated investors. PMID:23885134

Modeling and using a web-based and tutored portfolio to support certification of professional competence in transfusion medicine

PubMed Central

Staccini, Pascal; Rouger, Philippe

2008-01-01

In order to manage a nationwide assessment program leading to certification of professional competence in blood transfusion throughout France, the National Institute of Blood Transfusion (INTS) and the University of Nice-Sophia Antipolis designed and developed a structured and tutored web-based portfolio. The entire process of certification has been approved by the national healthcare agency (HAS). Eleven assessment programs have been written. The structure of this e-portfolio is based on a matrix of actions defined according to standards of practice. For each action, elements of proof are uploaded by the physician and peer-reviewed by an expert (a tutor) before validation. The electronic portfolio stores all the history of the actions performed by users. This tracking feature generates alerts which are e-mailed to users (physicians and tutors) according to a list of monitored events. After one year of design and development, the application is now being used routinely. PMID:18999167

Development and use of mathematical models and software frameworks for integrated analysis of agricultural systems and associated water use impacts

USGS Publications Warehouse

Fowler, K. R.; Jenkins, E.W.; Parno, M.; Chrispell, J.C.; Colón, A. I.; Hanson, Randall T.

2016-01-01

The development of appropriate water management strategies requires, in part, a methodology for quantifying and evaluating the impact of water policy decisions on regional stakeholders. In this work, we describe the framework we are developing to enhance the body of resources available to policy makers, farmers, and other community members in their e orts to understand, quantify, and assess the often competing objectives water consumers have with respect to usage. The foundation for the framework is the construction of a simulation-based optimization software tool using two existing software packages. In particular, we couple a robust optimization software suite (DAKOTA) with the USGS MF-OWHM water management simulation tool to provide a flexible software environment that will enable the evaluation of one or multiple (possibly competing) user-defined (or stakeholder) objectives. We introduce the individual software components and outline the communication strategy we defined for the coupled development. We present numerical results for case studies related to crop portfolio management with several defined objectives. The objectives are not optimally satisfied for any single user class, demonstrating the capability of the software tool to aid in the evaluation of a variety of competing interests.

Risk analytics for hedge funds

NASA Astrophysics Data System (ADS)

Pareek, Ankur

2005-05-01

The rapid growth of the hedge fund industry presents significant business opportunity for the institutional investors particularly in the form of portfolio diversification. To facilitate this, there is a need to develop a new set of risk analytics for investments consisting of hedge funds, with the ultimate aim to create transparency in risk measurement without compromising the proprietary investment strategies of hedge funds. As well documented in the literature, use of dynamic options like strategies by most of the hedge funds make their returns highly non-normal with fat tails and high kurtosis, thus rendering Value at Risk (VaR) and other mean-variance analysis methods unsuitable for hedge fund risk quantification. This paper looks at some unique concerns for hedge fund risk management and will particularly concentrate on two approaches from physical world to model the non-linearities and dynamic correlations in hedge fund portfolio returns: Self Organizing Criticality (SOC) and Random Matrix Theory (RMT).Random Matrix Theory analyzes correlation matrix between different hedge fund styles and filters random noise from genuine correlations arising from interactions within the system. As seen in the results of portfolio risk analysis, it leads to a better portfolio risk forecastability and thus to optimum allocation of resources to different hedge fund styles. The results also prove the efficacy of self-organized criticality and implied portfolio correlation as a tool for risk management and style selection for portfolios of hedge funds, being particularly effective during non-linear market crashes.

System dynamic modelling to assess economic viability and risk trade-offs for ecological restoration in South Africa.

PubMed

Crookes, D J; Blignaut, J N; de Wit, M P; Esler, K J; Le Maitre, D C; Milton, S J; Mitchell, S A; Cloete, J; de Abreu, P; Fourie nee Vlok, H; Gull, K; Marx, D; Mugido, W; Ndhlovu, T; Nowell, M; Pauw, M; Rebelo, A

2013-05-15

Can markets assist by providing support for ecological restoration, and if so, under what conditions? The first step in addressing this question is to develop a consistent methodology for economic evaluation of ecological restoration projects. A risk analysis process was followed in which a system dynamics model was constructed for eight diverse case study sites where ecological restoration is currently being pursued. Restoration costs vary across each of these sites, as do the benefits associated with restored ecosystem functioning. The system dynamics model simulates the ecological, hydrological and economic benefits of ecological restoration and informs a portfolio mapping exercise where payoffs are matched against the likelihood of success of a project, as well as a number of other factors (such as project costs and risk measures). This is the first known application that couples ecological restoration with system dynamics and portfolio mapping. The results suggest an approach that is able to move beyond traditional indicators of project success, since the effect of discounting is virtually eliminated. We conclude that systems dynamic modelling with portfolio mapping can guide decisions on when markets for restoration activities may be feasible. Copyright © 2013 Elsevier Ltd. All rights reserved.

Preparedness Portfolios and Portfolio Studios

ERIC Educational Resources Information Center

Turns, Jennifer; Sattler, Brook; Eliot, Matt; Kilgore, Deborah; Mobrand, Kathryn

2012-01-01

We live in a time of great enthusiasm for the role that e-Portfolios can play in education and a time of exploration in which educators and researchers are investigating different approaches to using ePortfolios to differentially support educational goals. In this paper, we focus on preparedness portfolios and portfolio studios as two key…

Discrete Time McKean–Vlasov Control Problem: A Dynamic Programming Approach

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

Pham, Huyên, E-mail: pham@math.univ-paris-diderot.fr; Wei, Xiaoli, E-mail: tyswxl@gmail.com

We consider the stochastic optimal control problem of nonlinear mean-field systems in discrete time. We reformulate the problem into a deterministic control problem with marginal distribution as controlled state variable, and prove that dynamic programming principle holds in its general form. We apply our method for solving explicitly the mean-variance portfolio selection and the multivariate linear-quadratic McKean–Vlasov control problem.

An application of almost marginal conditional stochastic dominance (AMCSD) on forming efficient portfolios

NASA Astrophysics Data System (ADS)

Slamet, Isnandar; Mardiana Putri Carissa, Siska; Pratiwi, Hasih

2017-10-01

Investors always seek an efficient portfolio which is a portfolio that has a maximum return on specific risk or minimal risk on specific return. Almost marginal conditional stochastic dominance (AMCSD) criteria can be used to form the efficient portfolio. The aim of this research is to apply the AMCSD criteria to form an efficient portfolio of bank shares listed in the LQ-45. This criteria is used when there are areas that do not meet the criteria of marginal conditional stochastic dominance (MCSD). On the other words, this criteria can be derived from quotient of areas that violate the MCSD criteria with the area that violate and not violate the MCSD criteria. Based on the data bank stocks listed on LQ-45, it can be stated that there are 38 efficient portfolios of 420 portfolios where each portfolio comprises of 4 stocks and 315 efficient portfolios of 1710 portfolios with each of portfolio has 3 stocks.

Structural Models that Manage IT Portfolio Affecting Business Value of Enterprise Architecture

NASA Astrophysics Data System (ADS)

Kamogawa, Takaaki

This paper examines the structural relationships between Information Technology (IT) governance and Enterprise Architecture (EA), with the objective of enhancing business value in the enterprise society. Structural models consisting of four related hypotheses reveal the relationship between IT governance and EA in the improvement of business values. We statistically examined the hypotheses by analyzing validated questionnaire items from respondents within firms listed on the Japanese stock exchange who were qualified to answer them. We concluded that firms which have organizational ability controlled by IT governance are more likely to deliver business value based on IT portfolio management.

Portfolio use and practices in US colleges and schools of pharmacy.

PubMed

Skrabal, Maryann Z; Turner, Paul D; Jones, Rhonda M; Tilleman, Jennifer A; Coover, Kelli L

2012-04-10

To identify the prevalence of portfolio use in US pharmacy programs, common components of portfolios, and advantages of and limitations to using portfolios. A cross-sectional electronic survey instrument was sent to experiential coordinators at US colleges and schools of pharmacy to collect data on portfolio content, methods, training and resource requirements, and benefits and challenges of portfolio use. Most colleges and schools of pharmacy (61.8%) use portfolios in experiential courses and the majority (67.1%) formally assess them, but there is wide variation regarding content and assessment. The majority of respondents used student portfolios as a formative evaluation primarily in the experiential curriculum. Although most colleges and schools of pharmacy have a portfolio system in place, few are using them to fulfill accreditation requirements. Colleges and schools need to carefully examine the intended purpose of their portfolio system and follow-through with implementation and maintenance of a system that meets their goals.

BBN-Based Portfolio Risk Assessment for NASA Technology R&D Outcome

NASA Technical Reports Server (NTRS)

Geuther, Steven C.; Shih, Ann T.

2016-01-01

The NASA Aeronautics Research Mission Directorate (ARMD) vision falls into six strategic thrusts that are aimed to support the challenges of the Next Generation Air Transportation System (NextGen). In order to achieve the goals of the ARMD vision, the Airspace Operations and Safety Program (AOSP) is committed to developing and delivering new technologies. To meet the dual challenges of constrained resources and timely technology delivery, program portfolio risk assessment is critical for communication and decision-making. This paper describes how Bayesian Belief Network (BBN) is applied to assess the probability of a technology meeting the expected outcome. The network takes into account the different risk factors of technology development and implementation phases. The use of BBNs allows for all technologies of projects in a program portfolio to be separately examined and compared. In addition, the technology interaction effects are modeled through the application of object-oriented BBNs. The paper discusses the development of simplified project risk BBNs and presents various risk results. The results presented include the probability of project risks not meeting success criteria, the risk drivers under uncertainty via sensitivity analysis, and what-if analysis. Finally, the paper shows how program portfolio risk can be assessed using risk results from BBNs of projects in the portfolio.

Using Continuing Professional Development with Portfolio in a Pharmaceutics Course.

PubMed

Schneider, Jennifer; O'Hara, Kate; Munro, Irene

2016-11-07

The introduction of Continuing Professional Development (CPD) to encourage individual life-long learning as a way of maintaining professional competency in pharmacy has faced resistance. To investigate ways to address this barrier we included CPD with portfolio in a university Pharmaceutics course. Underpinning knowledge for the course was delivered using a flipped classroom approach and students used the CPD model to address clinical scenarios presented in a simulated pharmacy setting. Students produced portfolio items for the different case scenarios and submitted these for assessment. This provided the opportunity for students to carry out repeated application of the CPD cycle and, in so doing, develop skills in critical thinking for self-reflection and self-evaluation. This course was designed to encourage the development of higher level learning skills for future self-directed learning. Thirty six students submitted a completed portfolio. Twenty nine students achieved a result of >70%, five students scored between 57%-69%, one student obtained a mark of 50% and one student failed. The end of course survey revealed that while students found portfolio development challenging (40%), they also reported that it was effective for self-learning (54%). Differentiating between the concepts "reflection" and "evaluation" in CPD was problematic for some students and the use of clearer, simpler language should be used to explain these processes in future CPD work.

Interdependence between Greece and other European stock markets: A comparison of wavelet and VMD copula, and the portfolio implications

NASA Astrophysics Data System (ADS)

Shahzad, Syed Jawad Hussain; Kumar, Ronald Ravinesh; Ali, Sajid; Ameer, Saba

2016-09-01

The interdependence of Greece and other European stock markets and the subsequent portfolio implications are examined in wavelet and variational mode decomposition domain. In applying the decomposition techniques, we analyze the structural properties of data and distinguish between short and long term dynamics of stock market returns. First, the GARCH-type models are fitted to obtain the standardized residuals. Next, different copula functions are evaluated, and based on the conventional information criteria and time varying parameter, Joe-Clayton copula is chosen to model the tail dependence between the stock markets. The short-run lower tail dependence time paths show a sudden increase in comovement during the global financial crises. The results of the long-run dependence suggest that European stock markets have higher interdependence with Greece stock market. Individual country's Value at Risk (VaR) separates the countries into two distinct groups. Finally, the two-asset portfolio VaR measures provide potential markets for Greece stock market investment diversification.

Problems of Mathematical Finance by Stochastic Control Methods

NASA Astrophysics Data System (ADS)

Stettner, Łukasz

The purpose of this paper is to present main ideas of mathematics of finance using the stochastic control methods. There is an interplay between stochastic control and mathematics of finance. On the one hand stochastic control is a powerful tool to study financial problems. On the other hand financial applications have stimulated development in several research subareas of stochastic control in the last two decades. We start with pricing of financial derivatives and modeling of asset prices, studying the conditions for the absence of arbitrage. Then we consider pricing of defaultable contingent claims. Investments in bonds lead us to the term structure modeling problems. Special attention is devoted to historical static portfolio analysis called Markowitz theory. We also briefly sketch dynamic portfolio problems using viscosity solutions to Hamilton-Jacobi-Bellman equation, martingale-convex analysis method or stochastic maximum principle together with backward stochastic differential equation. Finally, long time portfolio analysis for both risk neutral and risk sensitive functionals is introduced.

Aspect-Oriented Model-Driven Software Product Line Engineering

NASA Astrophysics Data System (ADS)

Groher, Iris; Voelter, Markus

Software product line engineering aims to reduce development time, effort, cost, and complexity by taking advantage of the commonality within a portfolio of similar products. The effectiveness of a software product line approach directly depends on how well feature variability within the portfolio is implemented and managed throughout the development lifecycle, from early analysis through maintenance and evolution. This article presents an approach that facilitates variability implementation, management, and tracing by integrating model-driven and aspect-oriented software development. Features are separated in models and composed of aspect-oriented composition techniques on model level. Model transformations support the transition from problem to solution space models. Aspect-oriented techniques enable the explicit expression and modularization of variability on model, template, and code level. The presented concepts are illustrated with a case study of a home automation system.

Self-consistent asset pricing models

NASA Astrophysics Data System (ADS)

Malevergne, Y.; Sornette, D.

2007-08-01

We discuss the foundations of factor or regression models in the light of the self-consistency condition that the market portfolio (and more generally the risk factors) is (are) constituted of the assets whose returns it is (they are) supposed to explain. As already reported in several articles, self-consistency implies correlations between the return disturbances. As a consequence, the alphas and betas of the factor model are unobservable. Self-consistency leads to renormalized betas with zero effective alphas, which are observable with standard OLS regressions. When the conditions derived from internal consistency are not met, the model is necessarily incomplete, which means that some sources of risk cannot be replicated (or hedged) by a portfolio of stocks traded on the market, even for infinite economies. Analytical derivations and numerical simulations show that, for arbitrary choices of the proxy which are different from the true market portfolio, a modified linear regression holds with a non-zero value αi at the origin between an asset i's return and the proxy's return. Self-consistency also introduces “orthogonality” and “normality” conditions linking the betas, alphas (as well as the residuals) and the weights of the proxy portfolio. Two diagnostics based on these orthogonality and normality conditions are implemented on a basket of 323 assets which have been components of the S&P500 in the period from January 1990 to February 2005. These two diagnostics show interesting departures from dynamical self-consistency starting about 2 years before the end of the Internet bubble. Assuming that the CAPM holds with the self-consistency condition, the OLS method automatically obeys the resulting orthogonality and normality conditions and therefore provides a simple way to self-consistently assess the parameters of the model by using proxy portfolios made only of the assets which are used in the CAPM regressions. Finally, the factor decomposition with the self-consistency condition derives a risk-factor decomposition in the multi-factor case which is identical to the principal component analysis (PCA), thus providing a direct link between model-driven and data-driven constructions of risk factors. This correspondence shows that PCA will therefore suffer from the same limitations as the CAPM and its multi-factor generalization, namely lack of out-of-sample explanatory power and predictability. In the multi-period context, the self-consistency conditions force the betas to be time-dependent with specific constraints.

The Application of Portfolios to Assess Progress in Writing of EFL Students at Secondary Schools in Banda Aceh

ERIC Educational Resources Information Center

Eridafithri

2015-01-01

Portfolios are one of the alternatives that can be used for writing assessment. Portfolios are not common in the curriculum. The lack of dissemination to language teachers have made portfolios disregarded. In order to encourage teachers to use portfolios for assessment of writing, they need to have adequate information about portfolios, how they…

Integrating Physical Actions and Financial Instruments to Manage Environmental Financial Risk

NASA Astrophysics Data System (ADS)

Foster, B.

2016-12-01

Exposure to extreme weather events can be reduced through physical actions (e.g., dams/reservoirs) or mitigated financially (e.g., insurance). Often physical actions involve investments in expensive infrastructure that reduce exposure, but whose benefits are only occasionally realized. Financial risk management does not reduce the impacts of an event, but rather redistributes them temporally, albeit at a cost. Nonetheless, these costs are typically much smaller, at least in the short run, than those incurred for physical actions. Financial strategies are also more flexible than physical ones in the face of an uncertain future. Financial contracts specifically designed to manage extreme environmental risks are becoming more common and can either replace or complement infrastructural investments as part of a risk management portfolio. In order to make optimal decisions as to the relative levels of physical and financial risk mitigation to employ, it is necessary to understand the relative merits of each strategy. This research develops a method for analyzing tradeoffs between physical and financial risk management strategies. We identify the unique cost and benefit properties of each strategy and integrate them into a single model that details the tradeoffs involved in various portfolios of physical and financial strategies. These methods are then applied to evaluate decisions to pursue emergency dredging during drought on the Mississippi River, which is used to mitigate the increased costs and/or reduced revenues barge operators face when water levels are low. Currently the U.S. Army Corps of Engineers funds most emergency dredging operations during major droughts and they are considering more intensive strategies for future droughts. Barge carriers and shippers though could manage at least some portion of their financial risks through a series of existing and experimental financial contracts. This work involves the formulation of these experimental contracts and the development of methods to evaluate integrated portfolios of physical and financial risk management strategies.

National Space Biomedical Research Institute (NSBRI) JSC Summer Projects

NASA Technical Reports Server (NTRS)

Dowdy, Forrest Ryan

2014-01-01

This project optimized the calorie content in a breakfast meal replacement bar for the Advanced Food Technology group. Use of multivariable optimization yielded the highest weight savings possible while simultaneously matching NASA Human Standards nutritional guidelines. The scope of this research included the study of shelf-life indicators such as water activity, moisture content, and texture analysis. Key metrics indicate higher protein content, higher caloric density, and greater mass savings as a result of the reformulation process. The optimization performed for this study demonstrated wide application to other food bars in the Advanced Food Technology portfolio. Recommendations for future work include shelf life studies on bar hardening and overall acceptability data over increased time frames and temperature fluctuation scenarios.

Drug efficiency: a new concept to guide lead optimization programs towards the selection of better clinical candidates.

PubMed

Braggio, Simone; Montanari, Dino; Rossi, Tino; Ratti, Emiliangelo

2010-07-01

As a result of their wide acceptance and conceptual simplicity, drug-like concepts are having a major influence on the drug discovery process, particularly in the selection of the 'optimal' absorption, distribution, metabolism, excretion and toxicity and physicochemical parameters space. While they have an undisputable value when assessing the potential of lead series or in evaluating inherent risk of a portfolio of drug candidates, they result much less useful in weighing up compounds for the selection of the best potential clinical candidate. We introduce the concept of drug efficiency as a new tool both to guide the drug discovery program teams during the lead optimization phase and to better assess the developability potential of a drug candidate.

Students' attitudes towards the introduction of a Personal and Professional Development portfolio: potential barriers and facilitators.

PubMed

Ross, Sarah; Maclachlan, Alison; Cleland, Jennifer

2009-12-01

Portfolios, widely used in undergraduate and postgraduate medicine, have variable purposes, formats and success. A recent systematic review summarised factors necessary for successful portfolio introduction but there are no studies investigating the views of students inexperienced in portfolio use towards portfolio learning. This study's aim was to survey student views about a prospective Professional and Personal Development (PPD) portfolio. This was a qualitative, focus group study. All focus groups were taped and transcribed verbatim, and anonymised. The transcripts were analysed inductively, using framework analysis. Four focus groups were carried out with 32 undergraduate medical students naïve in portfolio use. Three themes relevant to portfolio introduction emerged. The first theme was the need for clear information and support for portfolio introduction, and anxieties about how this could be supported effectively. The second was that students had negative views about reflective learning and whether this could be taught and assessed, believing formal assessment could foster socially acceptable content. The third was that participants revealed little understanding of reflective learning and its potential benefits. Rather portfolios were seen as useful for concrete purposes (e.g., job applications) not intrinsic benefits. Undergraduate medical students without experience of portfolios are anxious about portfolio introduction. They require support in developing reflective learning skills. Care must be taken to ensure students do not see portfolios as merely yet another assessment hurdle.

78 FR 21045 - Confirmation, Portfolio Reconciliation, Portfolio Compression, and Swap Trading Relationship...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-09

... COMMODITY FUTURES TRADING COMMISSION 17 CFR Part 23 RIN 3038-AC96 Confirmation, Portfolio Reconciliation, Portfolio Compression, and Swap Trading Relationship Documentation Requirements for Swap Dealers..., portfolio compression, and swap trading relationship documentation for Swap Dealers and Major Swap...

Operationalizing the Student Electronic Portfolio for Doctoral Nursing Education.

PubMed

Willmarth-Stec, Melissa; Beery, Teresa

2015-01-01

There is an increasing trend toward use of the electronic portfolio (e-portfolio) in Doctor of Nursing Practice programs. E-portfolios can provide documentation of competencies and achievement of program outcomes while showcasing a holistic view of the student achievement. Implementation of the e-portfolio requires careful decision making concerning software selection, set-up, portfolio components, and evaluation. The purpose of this article is to describe the implementation of an e-portfolio in a Doctor of Nursing Practice program and provide lessons learned during the implementation stage.

Evaluating Practice-Based Learning and Improvement: Efforts to Improve Acceptance of Portfolios

PubMed Central

Fragneto, Regina Y.; DiLorenzo, Amy Noel; Schell, Randall M.; Bowe, Edwin A.

2010-01-01

Introduction The Accreditation Council for Graduate Medical Education (ACGME) recommends resident portfolios as 1 method for assessing competence in practice-based learning and improvement. In July 2005, when anesthesiology residents in our department were required to start a portfolio, the residents and their faculty advisors did not readily accept this new requirement. Intensive education efforts addressing the goals and importance of portfolios were undertaken. We hypothesized that these educational efforts improved acceptance of the portfolio and retrospectively audited the portfolio evaluation forms completed by faculty advisors. Methods Intensive education about the goals and importance of portfolios began in January 2006, including presentations at departmental conferences and one-on-one education sessions. Faculty advisors were instructed to evaluate each resident's portfolio and complete a review form. We retrospectively collected data to determine the percentage of review forms completed by faculty. The portfolio reviews also assessed the percentage of 10 required portfolio components residents had completed. Results Portfolio review forms were completed by faculty advisors for 13% (5/38) of residents during the first advisor-advisee meeting in December 2005. Initiation of intensive education efforts significantly improved compliance, with review forms completed for 68% (26/38) of residents in May 2006 (P < .0001) and 95% (36/38) in December 2006 (P < .0001). Residents also significantly improved the completeness of portfolios between May and December of 2006. Discussion Portfolios are considered a best methods technique by the ACGME for evaluation of practice-based learning and improvment. We have found that intensive education about the goals and importance of portfolios can enhance acceptance of this evaluation tool, resulting in improved compliance in completion and evaluation of portfolios. PMID:22132291

Evaluating practice-based learning and improvement: efforts to improve acceptance of portfolios.

PubMed

Fragneto, Regina Y; Dilorenzo, Amy Noel; Schell, Randall M; Bowe, Edwin A

2010-12-01

The Accreditation Council for Graduate Medical Education (ACGME) recommends resident portfolios as 1 method for assessing competence in practice-based learning and improvement. In July 2005, when anesthesiology residents in our department were required to start a portfolio, the residents and their faculty advisors did not readily accept this new requirement. Intensive education efforts addressing the goals and importance of portfolios were undertaken. We hypothesized that these educational efforts improved acceptance of the portfolio and retrospectively audited the portfolio evaluation forms completed by faculty advisors. Intensive education about the goals and importance of portfolios began in January 2006, including presentations at departmental conferences and one-on-one education sessions. Faculty advisors were instructed to evaluate each resident's portfolio and complete a review form. We retrospectively collected data to determine the percentage of review forms completed by faculty. The portfolio reviews also assessed the percentage of 10 required portfolio components residents had completed. Portfolio review forms were completed by faculty advisors for 13% (5/38) of residents during the first advisor-advisee meeting in December 2005. Initiation of intensive education efforts significantly improved compliance, with review forms completed for 68% (26/38) of residents in May 2006 (P < .0001) and 95% (36/38) in December 2006 (P < .0001). Residents also significantly improved the completeness of portfolios between May and December of 2006. Portfolios are considered a best methods technique by the ACGME for evaluation of practice-based learning and improvment. We have found that intensive education about the goals and importance of portfolios can enhance acceptance of this evaluation tool, resulting in improved compliance in completion and evaluation of portfolios.

Academic portfolio in the digital era: organizing and maintaining a portfolio using reference managers.

PubMed

Bhargava, Puneet; Patel, Vatsal B; Iyer, Ramesh S; Moshiri, Mariam; Robinson, Tracy J; Lall, Chandana; Heller, Matthew T

2015-02-01

The academic portfolio has become an integral part of the promotions process. Creating and maintaining an academic portfolio in paper-based or web-based formats can be a cumbersome and time-consuming task. In this article, we describe an alternative way to efficiently organize an academic portfolio using a reference manager software, and discuss some of the afforded advantages. The reference manager software Papers (Mekentosj, Amsterdam, The Netherlands) was used to create an academic portfolio. The article outlines the key steps in creating and maintaining a digital academic portfolio. Using reference manager software (Papers), we created an academic portfolio that allows the user to digitally organize clinical, teaching, and research accomplishments in an indexed library enabling efficient updating, rapid retrieval, and easy sharing. To our knowledge, this is the first digital portfolio of its kind.

Portfolio Use and Practices in US Colleges and Schools of Pharmacy

PubMed Central

Turner, Paul D.; Jones, Rhonda M.; Tilleman, Jennifer A.; Coover, Kelli L.

2012-01-01

Objectives. To identify the prevalence of portfolio use in US pharmacy programs, common components of portfolios, and advantages of and limitations to using portfolios. Methods. A cross-sectional electronic survey instrument was sent to experiential coordinators at US colleges and schools of pharmacy to collect data on portfolio content, methods, training and resource requirements, and benefits and challenges of portfolio use. Results. Most colleges and schools of pharmacy (61.8%) use portfolios in experiential courses and the majority (67.1%) formally assess them, but there is wide variation regarding content and assessment. The majority of respondents used student portfolios as a formative evaluation primarily in the experiential curriculum. Conclusions. Although most colleges and schools of pharmacy have a portfolio system in place, few are using them to fulfill accreditation requirements. Colleges and schools need to carefully examine the intended purpose of their portfolio system and follow-through with implementation and maintenance of a system that meets their goals. PMID:22544963

[Development of a portfolio for competency-based assessment in a clinical clerkship curriculum].

PubMed

Roh, HyeRin; Lee, Jong-Tae; Yoon, Yoo Sang; Rhee, Byoung Doo

2015-12-01

The purpose of this report was to describe our experience in planning and developing a portfolio for a clinical clerkship curriculum. We have developed a portfolio for assessing student competency since 2007. During an annual workshop on clinical clerkship curricula, clerkship directors from five Paik hospitals of Inje University met to improve the assessment of the portfolio. We generated templates for students to record their activities and reflection and receive feedback. We uploaded these templates to our school's website for students to download freely. Annually, we have held a faculty development seminar and a workshop for portfolio assessment and feedback. Also, we established an orientation program on how to construct a learning portfolio for students. Future actions include creating a ubiquitous portfolio system, extending the portfolio to the entire curriculum, setting up an advisor system, and managing the quality of the portfolio. This study could be helpful for medical schools that plan to improve their portfolio assessment with an outcome-based approach.

7 CFR 4290.760 - How a change in size or activity of a Portfolio Concern affects the RBIC and the Portfolio Concern.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 15 2010-01-01 2010-01-01 false How a change in size or activity of a Portfolio Concern affects the RBIC and the Portfolio Concern. 4290.760 Section 4290.760 Agriculture Regulations of... size or activity of a Portfolio Concern affects the RBIC and the Portfolio Concern. (a) Effect on RBIC...

Qualitative study of the impact of an authentic electronic portfolio in undergraduate medical education.

PubMed

Belcher, Rosie; Jones, Anna; Smith, Laura-Jane; Vincent, Tim; Naidu, Sindhu Bhaarrati; Montgomery, Julia; Haq, Inam; Gill, Deborah

2014-12-17

Portfolios are increasingly used in undergraduate and postgraduate medical education. Four medical schools have collaborated with an established NHS electronic portfolio provider to develop and implement an authentic professional electronic portfolio for undergraduate students. We hypothesized that using an authentic portfolio would have significant advantages for students, particularly in familiarizing them with the tool many will continue to use for years after graduation. This paper describes the early evaluation of this undergraduate portfolio at two participating medical schools. To gather data, a questionnaire survey with extensive free text comments was used at School 1, and three focus groups were held at School 2. This paper reports thematic analysis of students' opinions expressed in the free text comments and focus groups. Five main themes, common across both schools were identified. These concerned the purpose, use and acceptability of the portfolio, advantages of and barriers to the use of the portfolio, and the impacts on both learning and professional identity. An authentic portfolio mitigated some of the negative aspects of using a portfolio, and had a positive effect on students' perception of themselves as becoming past of the profession. However, significant barriers to portfolio use remained, including a lack of understanding of the purpose of a portfolio and a perceived damaging effect on feedback.

Student portfolios and the hidden curriculum on gender: mapping exclusion.

PubMed

Phillips, Christine B

2009-09-01

The hidden curriculum - the norms, values and practices that are transmitted to students through modelling by preceptors and teachers, and decisions about curricular exclusions and inclusions - can be profoundly important in the socialising of trainee doctors. However, tracking the hidden curriculum as it evolves can be challenging for medical schools. This study aimed to explore the content of student e-portfolios on gender issues, a key perspective often taught through a hidden curriculum. Online posts for a gender and medicine e-portfolio task completed by two cohorts of students in Year 3 of a 4-year medical course (n = 167, 66% female) were analysed using a grounded theory approach. A process of gendered 'othering' was applied to both men and women in the medical school using different pedagogical strategies. Curricular emphases on women's health and lack of support for male students to acquire gynaecological examination skills were seen as explicit ways of excluding males. For female medical students, exclusion tended to be implicit, operating through modelling and aphoristic comments about so-called 'female-friendly' career choices and the negative impact of motherhood on career. E-portfolios can be a useful way of tracking the hidden curriculum as it evolves. Responses to gendered exclusion may be developed more readily for the explicit processes impacting on male students than for the implicit processes impacting on female students, which often reflect structural issues related to training and employment.

Downside Risk Optimization of the Thrift Savings Plan Lifecycle Fund Portfolios

DTIC Science & Technology

2010-03-01

ETF funds follow indices like the TSP individual funds but are valued by investors due to their “ stock -like” features and low administrative costs...investors worldwide. According to US News and World Report, actively managed stock funds lost nearly 41% on average in 2008 (Mardquardt, 2009...TSP funds: the Government Securities Investment (G) Fund, Fixed Income Index Investment (F) Fund, Common Stock Index Investment (C) Fund, Small

Regional allocation of biomass to U.S. energy demands under a portfolio of policy scenarios.

PubMed

Mullins, Kimberley A; Venkatesh, Aranya; Nagengast, Amy L; Kocoloski, Matt

2014-01-01

The potential for widespread use of domestically available energy resources, in conjunction with climate change concerns, suggest that biomass may be an essential component of U.S. energy systems in the near future. Cellulosic biomass in particular is anticipated to be used in increasing quantities because of policy efforts, such as federal renewable fuel standards and state renewable portfolio standards. Unfortunately, these independently designed biomass policies do not account for the fact that cellulosic biomass can equally be used for different, competing energy demands. An integrated assessment of multiple feedstocks, energy demands, and system costs is critical for making optimal decisions about a unified biomass energy strategy. This study develops a spatially explicit, best-use framework to optimally allocate cellulosic biomass feedstocks to energy demands in transportation, electricity, and residential heating sectors, while minimizing total system costs and tracking greenhouse gas emissions. Comparing biomass usage across three climate policy scenarios suggests that biomass used for space heating is a low cost emissions reduction option, while biomass for liquid fuel or for electricity becomes attractive only as emissions reduction targets or carbon prices increase. Regardless of the policy approach, study results make a strong case for national and regional coordination in policy design and compliance pathways.

The Use of Portfolios for Teacher Evaluation.

ERIC Educational Resources Information Center

Lengeling, M. Martha

A discussion of the use of portfolios for teacher evaluation reviews common uses of portfolios in higher education and offers suggestions for portfolio construction. It is noted that portfolios are frequently used for evaluation of both learner and teacher performance, as a means of documenting an individual's capabilities and skills. Some…

Challenges in Producing a Portfolio for Assessment: In Search of Underpinning Educational Theories

ERIC Educational Resources Information Center

Tisani, Nomathamsanqa

2008-01-01

The use of portfolios for assessment is gaining popularity in higher education. Despite acknowledged difficulties and flaws associated with this assessment method, portfolios have advantages over traditional methods. Handbooks on methods of constructing portfolios often emphasise the mechanics of the "process" of building portfolios.…