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.

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.

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

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.

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.

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.

Does asymmetric correlation affect portfolio optimization?

NASA Astrophysics Data System (ADS)

Fryd, Lukas

2017-07-01

The classical portfolio optimization problem does not assume asymmetric behavior of relationship among asset returns. The existence of asymmetric response in correlation on the bad news could be important information in portfolio optimization. The paper applies Dynamic conditional correlation model (DCC) and his asymmetric version (ADCC) to propose asymmetric behavior of conditional correlation. We analyse asymmetric correlation among S&P index, bonds index and spot gold price before mortgage crisis in 2008. We evaluate forecast ability of the models during and after mortgage crisis and demonstrate the impact of asymmetric correlation on the reduction of portfolio variance.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

Modeling of Mean-VaR portfolio optimization by risk tolerance when the utility function is quadratic

NASA Astrophysics Data System (ADS)

Sukono, Sidi, Pramono; Bon, Abdul Talib bin; Supian, Sudradjat

2017-03-01

The problems of investing in financial assets are to choose a combination of weighting a portfolio can be maximized return expectations and minimizing the risk. This paper discusses the modeling of Mean-VaR portfolio optimization by risk tolerance, when square-shaped utility functions. It is assumed that the asset return has a certain distribution, and the risk of the portfolio is measured using the Value-at-Risk (VaR). So, the process of optimization of the portfolio is done based on the model of Mean-VaR portfolio optimization model for the Mean-VaR done using matrix algebra approach, and the Lagrange multiplier method, as well as Khun-Tucker. The results of the modeling portfolio optimization is in the form of a weighting vector equations depends on the vector mean return vector assets, identities, and matrix covariance between return of assets, as well as a factor in risk tolerance. As an illustration of numeric, analyzed five shares traded on the stock market in Indonesia. Based on analysis of five stocks return data gained the vector of weight composition and graphics of efficient surface of portfolio. Vector composition weighting weights and efficient surface charts can be used as a guide for investors in decisions to invest.

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.

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…

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

Risk modelling in portfolio optimization

NASA Astrophysics Data System (ADS)

Lam, W. H.; Jaaman, Saiful Hafizah Hj.; Isa, Zaidi

2013-09-01

Risk management is very important in portfolio optimization. The mean-variance model has been used in portfolio optimization to minimize the investment risk. The objective of the mean-variance model is to minimize the portfolio risk and achieve the target rate of return. Variance is used as risk measure in the mean-variance model. The purpose of this study is to compare the portfolio composition as well as performance between the optimal portfolio of mean-variance model and equally weighted portfolio. Equally weighted portfolio means the proportions that are invested in each asset are equal. The results show that the portfolio composition of the mean-variance optimal portfolio and equally weighted portfolio are different. Besides that, the mean-variance optimal portfolio gives better performance because it gives higher performance ratio than the equally weighted 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.

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

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 \

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.

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.

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.

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.

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.

Portfolio selection and asset pricing under a benchmark approach

NASA Astrophysics Data System (ADS)

Platen, Eckhard

2006-10-01

The paper presents classical and new results on portfolio optimization, as well as the fair pricing concept for derivative pricing under the benchmark approach. The growth optimal portfolio is shown to be a central object in a market model. It links asset pricing and portfolio optimization. The paper argues that the market portfolio is a proxy of the growth optimal portfolio. By choosing the drift of the discounted growth optimal portfolio as parameter process, one obtains a realistic theoretical market dynamics.

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.

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

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.

Portfolio optimization with mean-variance model

NASA Astrophysics Data System (ADS)

Hoe, Lam Weng; Siew, Lam Weng

2016-06-01

Investors wish to achieve the target rate of return at the minimum level of risk in their investment. Portfolio optimization is an investment strategy that can be used to minimize the portfolio risk and can achieve the target rate of return. The mean-variance model has been proposed in portfolio optimization. The mean-variance model is an optimization model that aims to minimize the portfolio risk which is the portfolio variance. The objective of this study is to construct the optimal portfolio using the mean-variance model. The data of this study consists of weekly returns of 20 component stocks of FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI). The results of this study show that the portfolio composition of the stocks is different. Moreover, investors can get the return at minimum level of risk with the constructed optimal mean-variance portfolio.

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.

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.

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

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.

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.

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.

Measuring Treasury Bond Portfolio Risk and Portfolio Optimization with a Non-Gaussian Multivariate Model

NASA Astrophysics Data System (ADS)

Dong, Yijun

The research about measuring the risk of a bond portfolio and the portfolio optimization was relatively rare previously, because the risk factors of bond portfolios are not very volatile. However, this condition has changed recently. The 2008 financial crisis brought high volatility to the risk factors and the related bond securities, even if the highly rated U.S. treasury bonds. Moreover, the risk factors of bond portfolios show properties of fat-tailness and asymmetry like risk factors of equity portfolios. Therefore, we need to use advanced techniques to measure and manage risk of bond portfolios. In our paper, we first apply autoregressive moving average generalized autoregressive conditional heteroscedasticity (ARMA-GARCH) model with multivariate normal tempered stable (MNTS) distribution innovations to predict risk factors of U.S. treasury bonds and statistically demonstrate that MNTS distribution has the ability to capture the properties of risk factors based on the goodness-of-fit tests. Then based on empirical evidence, we find that the VaR and AVaR estimated by assuming normal tempered stable distribution are more realistic and reliable than those estimated by assuming normal distribution, especially for the financial crisis period. Finally, we use the mean-risk portfolio optimization to minimize portfolios' potential risks. The empirical study indicates that the optimized bond portfolios have better risk-adjusted performances than the benchmark portfolios for some periods. Moreover, the optimized bond portfolios obtained by assuming normal tempered stable distribution have improved performances in comparison to the optimized bond portfolios obtained by assuming normal distribution.

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.

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.

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.

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.

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

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.

Portfolio optimization for index tracking modelling in Malaysia stock market

NASA Astrophysics Data System (ADS)

Siew, Lam Weng; Jaaman, Saiful Hafizah; Ismail, Hamizun

2016-06-01

Index tracking is an investment strategy in portfolio management which aims to construct an optimal portfolio to generate similar mean return with the stock market index mean return without purchasing all of the stocks that make up the index. The objective of this paper is to construct an optimal portfolio using the optimization model which adopts regression approach in tracking the benchmark stock market index return. In this study, the data consists of weekly price of stocks in Malaysia market index which is FTSE Bursa Malaysia Kuala Lumpur Composite Index from January 2010 until December 2013. The results of this study show that the optimal portfolio is able to track FBMKLCI Index at minimum tracking error of 1.0027% with 0.0290% excess mean return over the mean return of FBMKLCI Index. The significance of this study is to construct the optimal portfolio using optimization model which adopts regression approach in tracking the stock market index without purchasing all index components.

Static vs stochastic optimization: A case study of FTSE Bursa Malaysia sectorial indices

NASA Astrophysics Data System (ADS)

Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah@Rozita

2014-06-01

Traditional portfolio optimization methods in the likes of Markowitz' mean-variance model and semi-variance model utilize static expected return and volatility risk from historical data to generate an optimal portfolio. The optimal portfolio may not truly be optimal in reality due to the fact that maximum and minimum values from the data may largely influence the expected return and volatility risk values. This paper considers distributions of assets' return and volatility risk to determine a more realistic optimized portfolio. For illustration purposes, the sectorial indices data in FTSE Bursa Malaysia is employed. The results show that stochastic optimization provides more stable information ratio.

Vehicle routing problem and capacitated vehicle routing problem frameworks in fund allocation problem

NASA Astrophysics Data System (ADS)

Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah@Rozita

2016-11-01

Two new methods adopted from methods commonly used in the field of transportation and logistics are proposed to solve a specific issue of investment allocation problem. Vehicle routing problem and capacitated vehicle routing methods are applied to optimize the fund allocation of a portfolio of investment assets. This is done by determining the sequence of the assets. As a result, total investment risk is minimized by this sequence.

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.

Static vs stochastic optimization: A case study of FTSE Bursa Malaysia sectorial indices

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

Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah Rozita

2014-06-19

Traditional portfolio optimization methods in the likes of Markowitz' mean-variance model and semi-variance model utilize static expected return and volatility risk from historical data to generate an optimal portfolio. The optimal portfolio may not truly be optimal in reality due to the fact that maximum and minimum values from the data may largely influence the expected return and volatility risk values. This paper considers distributions of assets' return and volatility risk to determine a more realistic optimized portfolio. For illustration purposes, the sectorial indices data in FTSE Bursa Malaysia is employed. The results show that stochastic optimization provides more stablemore » information ratio.« less

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

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.

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.

A new enhanced index tracking model in portfolio optimization with sum weighted approach

NASA Astrophysics Data System (ADS)

Siew, Lam Weng; Jaaman, Saiful Hafizah; Hoe, Lam Weng

2017-04-01

Index tracking is a portfolio management which aims to construct the optimal portfolio to achieve similar return with the benchmark index return at minimum tracking error without purchasing all the stocks that make up the index. Enhanced index tracking is an improved portfolio management which aims to generate higher portfolio return than the benchmark index return besides minimizing the tracking error. The objective of this paper is to propose a new enhanced index tracking model with sum weighted approach to improve the existing index tracking model for tracking the benchmark Technology Index in Malaysia. The optimal portfolio composition and performance of both models are determined and compared in terms of portfolio mean return, tracking error and information ratio. The results of this study show that the optimal portfolio of the proposed model is able to generate higher mean return than the benchmark index at minimum tracking error. Besides that, the proposed model is able to outperform the existing model in tracking the benchmark index. The significance of this study is to propose a new enhanced index tracking model with sum weighted apporach which contributes 67% improvement on the portfolio mean return as compared to the existing model.

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 optimization with skewness and kurtosis

NASA Astrophysics Data System (ADS)

Lam, Weng Hoe; Jaaman, Saiful Hafizah Hj.; Isa, Zaidi

2013-04-01

Mean and variance of return distributions are two important parameters of the mean-variance model in portfolio optimization. However, the mean-variance model will become inadequate if the returns of assets are not normally distributed. Therefore, higher moments such as skewness and kurtosis cannot be ignored. Risk averse investors prefer portfolios with high skewness and low kurtosis so that the probability of getting negative rates of return will be reduced. The objective of this study is to compare the portfolio compositions as well as performances between the mean-variance model and mean-variance-skewness-kurtosis model by using the polynomial goal programming approach. The results show that the incorporation of skewness and kurtosis will change the optimal portfolio compositions. The mean-variance-skewness-kurtosis model outperforms the mean-variance model because the mean-variance-skewness-kurtosis model takes skewness and kurtosis into consideration. Therefore, the mean-variance-skewness-kurtosis model is more appropriate for the investors of Malaysia in portfolio optimization.

Enhanced index tracking modeling in portfolio optimization with mixed-integer programming z 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 portfolio management in stock market investment. Enhanced index tracking aims to construct an optimal portfolio to generate excess return over the return achieved by the stock market index without purchasing all of the stocks that make up the index. The objective of this paper is to construct an optimal portfolio using mixed-integer programming model which adopts regression approach in order to generate higher portfolio mean return than stock market index return. In this study, the data consists of 24 component stocks in Malaysia market index which is FTSE Bursa Malaysia Kuala Lumpur Composite Index from January 2010 until December 2012. The results of this study show that the optimal portfolio of mixed-integer programming model is able to generate higher mean return than FTSE Bursa Malaysia Kuala Lumpur Composite Index return with only selecting 30% out of the total stock market index components.

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.

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.

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.

Research on regularized mean-variance portfolio selection strategy with modified Roy safety-first principle.

PubMed

Atta Mills, Ebenezer Fiifi Emire; Yan, Dawen; Yu, Bo; Wei, Xinyuan

2016-01-01

We propose a consolidated risk measure based on variance and the safety-first principle in a mean-risk portfolio optimization framework. The safety-first principle to financial portfolio selection strategy is modified and improved. Our proposed models are subjected to norm regularization to seek near-optimal stable and sparse portfolios. We compare the cumulative wealth of our preferred proposed model to a benchmark, S&P 500 index for the same period. Our proposed portfolio strategies have better out-of-sample performance than the selected alternative portfolio rules in literature and control the downside risk of the portfolio returns.

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.

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.

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.

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.

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.

Control Improvement for Jump-Diffusion Processes with Applications to Finance

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

Baeuerle, Nicole, E-mail: nicole.baeuerle@kit.edu; Rieder, Ulrich, E-mail: ulrich.rieder@uni-ulm.de

2012-02-15

We consider stochastic control problems with jump-diffusion processes and formulate an algorithm which produces, starting from a given admissible control {pi}, a new control with a better value. If no improvement is possible, then {pi} is optimal. Such an algorithm is well-known for discrete-time Markov Decision Problems under the name Howard's policy improvement algorithm. The idea can be traced back to Bellman. Here we show with the help of martingale techniques that such an algorithm can also be formulated for stochastic control problems with jump-diffusion processes. As an application we derive some interesting results in financial portfolio optimization.

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.

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.

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.

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.

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

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.

Rational decisions, random matrices and spin glasses

NASA Astrophysics Data System (ADS)

Galluccio, Stefano; Bouchaud, Jean-Philippe; Potters, Marc

We consider the problem of rational decision making in the presence of nonlinear constraints. By using tools borrowed from spin glass and random matrix theory, we focus on the portfolio optimisation problem. We show that the number of optimal solutions is generally exponentially large, and each of them is fragile: rationality is in this case of limited use. In addition, this problem is related to spin glasses with Lévy-like (long-ranged) couplings, for which we show that the ground state is not exponentially degenerate.

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.

On the microeconomic problems studied by portfolio theory

NASA Astrophysics Data System (ADS)

Nikonov, Oleg; Medvedeva, Marina

2012-09-01

In the paper we consider economically motivated problems, which are treated with the help of methods of portfolio theory that goes back to the papers by H. Markowitz [1] and J. Tobin [2]. We show that the portfolio theory initially developed for risky securities (stocks) could be applied to other objects. In the present paper we consider several situations where such an application is reasonable and seems to be fruitful. Namely, we consider the problems of constructing the efficient portfolio of banking services and the portfolio of counteragents of a firm.

The Role of Hellinger Processes in Mathematical Finance

NASA Astrophysics Data System (ADS)

Choulli, T.; Hurd, T. R.

2001-09-01

This paper illustrates the natural role that Hellinger processes can play in solving problems from ¯nance. We propose an extension of the concept of Hellinger process applicable to entropy distance and f-divergence distances, where f is a convex logarithmic function or a convex power function with general order q, 0 6= q < 1. These concepts lead to a new approach to Merton's optimal portfolio problem and its dual in general L¶evy markets.

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.

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.

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

Computer Applications for Alternative Assessment: An Instructional and Organization Dilemma.

ERIC Educational Resources Information Center

Mills, Ed; Brown, John A.

1997-01-01

Describes the possibilities and problems that computer-generated portfolios will soon present to instructors across America. Highlights include the history of portfolio assessment, logistical problems of handling portfolios in the traditional three-ring binder format, use of the zip drive for storage, and software/hardware compatibility problems.…

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.

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.

Scheduling Future Water Supply Investments Under Uncertainty

NASA Astrophysics Data System (ADS)

Huskova, I.; Matrosov, E. S.; Harou, J. J.; Kasprzyk, J. R.; Reed, P. M.

2014-12-01

Uncertain hydrological impacts of climate change, population growth and institutional changes pose a major challenge to planning of water supply systems. Planners seek optimal portfolios of supply and demand management schemes but also when to activate assets whilst considering many system goals and plausible futures. Incorporation of scheduling into the planning under uncertainty problem strongly increases its complexity. We investigate some approaches to scheduling with many-objective heuristic search. We apply a multi-scenario many-objective scheduling approach to the Thames River basin water supply system planning problem in the UK. Decisions include which new supply and demand schemes to implement, at what capacity and when. The impact of different system uncertainties on scheme implementation schedules are explored, i.e. how the choice of future scenarios affects the search process and its outcomes. The activation of schemes is influenced by the occurrence of extreme hydrological events in the ensemble of plausible scenarios and other factors. The approach and results are compared with a previous study where only the portfolio problem is addressed (without scheduling).

Linear versus quadratic portfolio optimization model with transaction cost

NASA Astrophysics Data System (ADS)

Razak, Norhidayah Bt Ab; Kamil, Karmila Hanim; Elias, Siti Masitah

2014-06-01

Optimization model is introduced to become one of the decision making tools in investment. Hence, it is always a big challenge for investors to select the best model that could fulfill their goal in investment with respect to risk and return. In this paper we aims to discuss and compare the portfolio allocation and performance generated by quadratic and linear portfolio optimization models namely of Markowitz and Maximin model respectively. The application of these models has been proven to be significant and popular among others. However transaction cost has been debated as one of the important aspects that should be considered for portfolio reallocation as portfolio return could be significantly reduced when transaction cost is taken into consideration. Therefore, recognizing the importance to consider transaction cost value when calculating portfolio' return, we formulate this paper by using data from Shariah compliant securities listed in Bursa Malaysia. It is expected that, results from this paper will effectively justify the advantage of one model to another and shed some lights in quest to find the best decision making tools in investment for individual investors.

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.

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.

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.

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.

On the Teaching of Portfolio Theory.

ERIC Educational Resources Information Center

Biederman, Daniel K.

1992-01-01

Demonstrates how a simple portfolio problem expressed explicitly as an expected utility maximization problem can be used to instruct students in portfolio theory. Discusses risk aversion, decision making under uncertainty, and the limitations of the traditional mean variance approach. Suggests students may develop a greater appreciation of general…

Clustering of financial time series with application to index and enhanced index tracking portfolio

NASA Astrophysics Data System (ADS)

Dose, Christian; Cincotti, Silvano

2005-09-01

A stochastic-optimization technique based on time series cluster analysis is described for index tracking and enhanced index tracking problems. Our methodology solves the problem in two steps, i.e., by first selecting a subset of stocks and then setting the weight of each stock as a result of an optimization process (asset allocation). Present formulation takes into account constraints on the number of stocks and on the fraction of capital invested in each of them, whilst not including transaction costs. Computational results based on clustering selection are compared to those of random techniques and show the importance of clustering in noise reduction and robust forecasting applications, in particular for enhanced index tracking.

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.

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.

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.

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

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.

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.

HSTLBO: A hybrid algorithm based on Harmony Search and Teaching-Learning-Based Optimization for complex high-dimensional optimization problems

PubMed Central

Tuo, Shouheng; Yong, Longquan; Deng, Fang’an; Li, Yanhai; Lin, Yong; Lu, Qiuju

2017-01-01

Harmony Search (HS) and Teaching-Learning-Based Optimization (TLBO) as new swarm intelligent optimization algorithms have received much attention in recent years. Both of them have shown outstanding performance for solving NP-Hard optimization problems. However, they also suffer dramatic performance degradation for some complex high-dimensional optimization problems. Through a lot of experiments, we find that the HS and TLBO have strong complementarity each other. The HS has strong global exploration power but low convergence speed. Reversely, the TLBO has much fast convergence speed but it is easily trapped into local search. In this work, we propose a hybrid search algorithm named HSTLBO that merges the two algorithms together for synergistically solving complex optimization problems using a self-adaptive selection strategy. In the HSTLBO, both HS and TLBO are modified with the aim of balancing the global exploration and exploitation abilities, where the HS aims mainly to explore the unknown regions and the TLBO aims to rapidly exploit high-precision solutions in the known regions. Our experimental results demonstrate better performance and faster speed than five state-of-the-art HS variants and show better exploration power than five good TLBO variants with similar run time, which illustrates that our method is promising in solving complex high-dimensional optimization problems. The experiment on portfolio optimization problems also demonstrate that the HSTLBO is effective in solving complex read-world application. PMID:28403224

HSTLBO: A hybrid algorithm based on Harmony Search and Teaching-Learning-Based Optimization for complex high-dimensional optimization problems.

PubMed

Tuo, Shouheng; Yong, Longquan; Deng, Fang'an; Li, Yanhai; Lin, Yong; Lu, Qiuju

2017-01-01

Harmony Search (HS) and Teaching-Learning-Based Optimization (TLBO) as new swarm intelligent optimization algorithms have received much attention in recent years. Both of them have shown outstanding performance for solving NP-Hard optimization problems. However, they also suffer dramatic performance degradation for some complex high-dimensional optimization problems. Through a lot of experiments, we find that the HS and TLBO have strong complementarity each other. The HS has strong global exploration power but low convergence speed. Reversely, the TLBO has much fast convergence speed but it is easily trapped into local search. In this work, we propose a hybrid search algorithm named HSTLBO that merges the two algorithms together for synergistically solving complex optimization problems using a self-adaptive selection strategy. In the HSTLBO, both HS and TLBO are modified with the aim of balancing the global exploration and exploitation abilities, where the HS aims mainly to explore the unknown regions and the TLBO aims to rapidly exploit high-precision solutions in the known regions. Our experimental results demonstrate better performance and faster speed than five state-of-the-art HS variants and show better exploration power than five good TLBO variants with similar run time, which illustrates that our method is promising in solving complex high-dimensional optimization problems. The experiment on portfolio optimization problems also demonstrate that the HSTLBO is effective in solving complex read-world application.

Neural network for nonsmooth pseudoconvex optimization with general convex constraints.

PubMed

Bian, Wei; Ma, Litao; Qin, Sitian; Xue, Xiaoping

2018-05-01

In this paper, a one-layer recurrent neural network is proposed for solving a class of nonsmooth, pseudoconvex optimization problems with general convex constraints. Based on the smoothing method, we construct a new regularization function, which does not depend on any information of the feasible region. Thanks to the special structure of the regularization function, we prove the global existence, uniqueness and "slow solution" character of the state of the proposed neural network. Moreover, the state solution of the proposed network is proved to be convergent to the feasible region in finite time and to the optimal solution set of the related optimization problem subsequently. In particular, the convergence of the state to an exact optimal solution is also considered in this paper. Numerical examples with simulation results are given to show the efficiency and good characteristics of the proposed network. In addition, some preliminary theoretical analysis and application of the proposed network for a wider class of dynamic portfolio optimization are included. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

Student Engagement with E-Portfolios: Purpose, Benefits and Problems

ERIC Educational Resources Information Center

Thanaraj, Ann

2012-01-01

This paper reports on a phenomenographic study about the different ways that undergraduate law students understood and conceptualised the idea of e-portfolios as used on their programme. The aim of the study was to investigate variations in conceptions of e-portfolios, including their purpose, benefits and problems as experienced by students. The…

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.

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.

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.

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.

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.

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).

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

Problems, Pitfalls, and Benefits of Portfolios.

ERIC Educational Resources Information Center

Stone, Bernice A.

1998-01-01

Two groups of student teachers, one school-based and one university-based, were introduced to portfolio construction. School-based students received more guidance in and time for portfolio construction. Surveys and interviews indicated that the extra time and guidance helped school-based students, who benefited more from portfolios than…

Portfolio optimization and the random magnet problem

NASA Astrophysics Data System (ADS)

Rosenow, B.; Plerou, V.; Gopikrishnan, P.; Stanley, H. E.

2002-08-01

Diversification of an investment into independently fluctuating assets reduces its risk. In reality, movements of assets are mutually correlated and therefore knowledge of cross-correlations among asset price movements are of great importance. Our results support the possibility that the problem of finding an investment in stocks which exposes invested funds to a minimum level of risk is analogous to the problem of finding the magnetization of a random magnet. The interactions for this "random magnet problem" are given by the cross-correlation matrix C of stock returns. We find that random matrix theory allows us to make an estimate for C which outperforms the standard estimate in terms of constructing an investment which carries a minimum level of risk.

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

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.

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.

Validity of the Learning Portfolio: Analysis of a Portfolio Proposal for the University

ERIC Educational Resources Information Center

Gregori-Giralt, Eva; Menéndez-Varela, José Luis

2015-01-01

Validity is a central issue in portfolio-based assessment. This empirical study used a quantitative approach to analyse the validity of the inferences drawn from a disciplinary course work portfolio assessment comprising profession-specific and learning competencies. The study also examined the problems involved in the development of the…

Formal Method of Description Supporting Portfolio Assessment

ERIC Educational Resources Information Center

Morimoto, Yasuhiko; Ueno, Maomi; Kikukawa, Isao; Yokoyama, Setsuo; Miyadera, Youzou

2006-01-01

Teachers need to assess learner portfolios in the field of education. However, they need support in the process of designing and practicing what kind of portfolios are to be assessed. To solve the problem, a formal method of describing the relations between the lesson forms and portfolios that need to be collected and the relations between…

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

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.

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.

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.

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.

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.

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

Investment portfolio management from cybernetic point of view

NASA Astrophysics Data System (ADS)

Marchev, Angel, Jr.; Marchev, Angel

2013-12-01

The theory of investment portfolios is a well defined component of financial science. While sound in principle, it faces some setbacks in its real-world implementation. In this paper the authors propose a reformulation of the investment portfolio problem as a cybernetic system where the Investor is the controlling system and the portfolio is the controlled system. Also the portfolio controlling process should be dissected in several ordered phases, so that each phase is represented as a subsystem within the structure of the controlling system Investor.

Volatility forecasting for low-volatility portfolio selection in the US and the Korean equity markets

NASA Astrophysics Data System (ADS)

Kim, Saejoon

2018-01-01

We consider the problem of low-volatility portfolio selection which has been the subject of extensive research in the field of portfolio selection. To improve the currently existing techniques that rely purely on past information to select low-volatility portfolios, this paper investigates the use of time series regression techniques that make forecasts of future volatility to select the portfolios. In particular, for the first time, the utility of support vector regression and its enhancements as portfolio selection techniques is provided. It is shown that our regression-based portfolio selection provides attractive outperformances compared to the benchmark index and the portfolio defined by a well-known strategy on the data-sets of the S&P 500 and the KOSPI 200.

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

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.

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…

Electronic Portfolios.

ERIC Educational Resources Information Center

Purves, Alan C.

1996-01-01

Outlines three forms of electronic portfolio based on a student's work, a class project about a specific topic, and a class seminar on a broad topic. Discusses logistical problems of management, access, and cross-referencing; technical problems of input, access, and copying; and theoretical issues of the lack of realia, of ownership and copyright,…

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.

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.

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.

Improving the Quality of Evidence-Based Writing Entries in Electronic Portfolios

ERIC Educational Resources Information Center

Denton, David W.

2012-01-01

The problem investigated in this study was whether entries written to an electronic portfolio by preservice teachers improved in quality after an intervention was deployed. The study also compared portfolio metadata to writing quality scores to determine whether there was a relationship. Participants included a convenience sample of 11…

EFL Writers' Attitudes and Perceptions toward F-Portfolio Use

ERIC Educational Resources Information Center

Aydin, Selami

2014-01-01

Atitudes toward and perceptions of using Facebook as a portfolio-keeping tool in teaching English as a foreign language (EFL) writing. In general, existing research reveals primarily positive effects of Facebook on educational activities, and research on portfolio keeping in EFL writing shows both benefits and problem areas. Thus, the current…

Concurrent credit portfolio losses

PubMed Central

Sicking, Joachim; Schäfer, Rudi

2018-01-01

We consider the problem of concurrent portfolio losses in two non-overlapping credit portfolios. In order to explore the full statistical dependence structure of such portfolio losses, we estimate their empirical pairwise copulas. Instead of a Gaussian dependence, we typically find a strong asymmetry in the copulas. Concurrent large portfolio losses are much more likely than small ones. Studying the dependences of these losses as a function of portfolio size, we moreover reveal that not only large portfolios of thousands of contracts, but also medium-sized and small ones with only a few dozens of contracts exhibit notable portfolio loss correlations. Anticipated idiosyncratic effects turn out to be negligible. These are troublesome insights not only for investors in structured fixed-income products, but particularly for the stability of the financial sector. JEL codes: C32, F34, G21, G32, H81. PMID:29425246

Concurrent credit portfolio losses.

PubMed

Sicking, Joachim; Guhr, Thomas; Schäfer, Rudi

2018-01-01

We consider the problem of concurrent portfolio losses in two non-overlapping credit portfolios. In order to explore the full statistical dependence structure of such portfolio losses, we estimate their empirical pairwise copulas. Instead of a Gaussian dependence, we typically find a strong asymmetry in the copulas. Concurrent large portfolio losses are much more likely than small ones. Studying the dependences of these losses as a function of portfolio size, we moreover reveal that not only large portfolios of thousands of contracts, but also medium-sized and small ones with only a few dozens of contracts exhibit notable portfolio loss correlations. Anticipated idiosyncratic effects turn out to be negligible. These are troublesome insights not only for investors in structured fixed-income products, but particularly for the stability of the financial sector. JEL codes: C32, F34, G21, G32, H81.

Electronic Portfolios in Tenure and Promotion Decisions: Making a Virtual Case.

ERIC Educational Resources Information Center

Blair, Kristine

A current problem at many American universities is that tenure and promotion procedures continue to privilege print-based evidence of teaching and research productivity, or do not acknowledge the impact of technology on teaching, scholarship, and service. Despite these problems, this paper makes the case for electronic teaching portfolios as…

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.

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.

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

Portfolio Partnerships between Faculty and WAC: Lessons from Disciplinary Practice, Reflection, and Transformation

ERIC Educational Resources Information Center

Peters, Brad; Robertson, Julie Fisher

2007-01-01

In portfolio assessment, WAC helps other disciplines increase programmatic integrity and accountability. This analysis of a portfolio partnership also shows composition faculty how a dynamic culture of assessment helps us protect what we do well, improve what we need to do better, and solve problems as writing instruction keeps pace with…

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...

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.

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.

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.

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.

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.

An Application of Digital Portfolio with the Peer, Self and Instructor Assessments in Art Education

ERIC Educational Resources Information Center

Dikici, Ayhan

2009-01-01

Problem Statement: In art education, one of the most difficult tasks is to evaluate the artistic works of students. Portfolio assessment is a method of assessment that is commonly used in artistic education. The major research question investigated in the study is: "What are the advantages and disadvantages of digital portfolio in an art…

Continuous-time safety-first portfolio selection with jump-diffusion processes

NASA Astrophysics Data System (ADS)

Yan, Wei

2012-04-01

This article is concerned with continuous-time portfolio selection based on a safety-first criterion under discontinuous price processes (jump-diffusion processes). The solution of the corresponding Hamilton-Jacobi-Bellman equation of the problem is demonstrated. The analytical solutions are presented when there does not exist any riskless asset. Moreover, the problem is also discussed while there exists one riskless asset.

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.

Sensitivity-Informed De Novo Programming for Many-Objective Water Portfolio Planning Under Uncertainty

NASA Astrophysics Data System (ADS)

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

2009-12-01

Risk-based water supply management presents severe cognitive, computational, and social challenges to planning in a changing world. Decision aiding frameworks must confront the cognitive biases implicit to risk, the severe uncertainties associated with long term planning horizons, and the consequent ambiguities that shape how we define and solve water resources planning and management problems. This paper proposes and demonstrates a new interactive framework for sensitivity informed de novo programming. The theoretical focus of our many-objective de novo programming is to promote learning and evolving problem formulations to enhance risk-based decision making. We have demonstrated our proposed de novo programming framework using a case study for a single city’s water supply in the Lower Rio Grande Valley (LRGV) in Texas. Key decisions in this case study include the purchase of permanent rights to reservoir inflows and anticipatory thresholds for acquiring transfers of water through optioning and spot leases. A 10-year Monte Carlo simulation driven by historical data is used to provide performance metrics for the supply portfolios. The three major components of our methodology include Sobol globoal sensitivity analysis, many-objective evolutionary optimization and interactive tradeoff visualization. The interplay between these components allows us to evaluate alternative design metrics, their decision variable controls and the consequent system vulnerabilities. Our LRGV case study measures water supply portfolios’ efficiency, reliability, and utilization of transfers in the water supply market. The sensitivity analysis is used interactively over interannual, annual, and monthly time scales to indicate how the problem controls change as a function of the timescale of interest. These results have been used then to improve our exploration and understanding of LRGV costs, vulnerabilities, and the water portfolios’ critical reliability constraints. These results demonstrate how we can adaptively improve the value and robustness of our problem formulations by evolving our definition of optimality to discover key tradeoffs.

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.

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.

What is the Nondominated Formulation? A Demonstration of de Novo Water Supply Portfolio Planning Under Deep Uncertainty

NASA Astrophysics Data System (ADS)

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

2010-12-01

This paper proposes and demonstrates a new interactive framework for sensitivity-informed de Novo programming, in which a learning approach to formulating decision problems can confront the deep uncertainty within water management problems. The framework couples global sensitivity analysis using Sobol’ variance decomposition with multiobjective evolutionary algorithms (MOEAs) to generate planning alternatives and test their robustness to new modeling assumptions and scenarios. We explore these issues within the context of a risk-based water supply management problem, where a city seeks the most efficient use of a water market. The case study examines a single city’s water supply in the Lower Rio Grande Valley (LRGV) in Texas, using both a 10-year planning horizon and an extreme single-year drought scenario. The city’s water supply portfolio comprises a volume of permanent rights to reservoir inflows and use of a water market through anticipatory thresholds for acquiring transfers of water through optioning and spot leases. Diagnostic information from the Sobol’ variance decomposition is used to create a sensitivity-informed problem formulation testing different decision variable configurations, with tradeoffs for the formulation solved using a MOEA. Subsequent analysis uses the drought scenario to expose tradeoffs between long-term and short-term planning and illustrate the impact of deeply uncertain assumptions on water availability in droughts. The results demonstrate water supply portfolios’ efficiency, reliability, and utilization of transfers in the water supply market and show how to adaptively improve the value and robustness of our problem formulations by evolving our definition of optimality to discover key tradeoffs.

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.

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

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.

Portfolios of quantum algorithms.

PubMed

Maurer, S M; Hogg, T; Huberman, B A

2001-12-17

Quantum computation holds promise for the solution of many intractable problems. However, since many quantum algorithms are stochastic in nature they can find the solution of hard problems only probabilistically. Thus the efficiency of the algorithms has to be characterized by both the expected time to completion and the associated variance. In order to minimize both the running time and its uncertainty, we show that portfolios of quantum algorithms analogous to those of finance can outperform single algorithms when applied to the NP-complete problems such as 3-satisfiability.

Sparse Covariance Matrix Estimation by DCA-Based Algorithms.

PubMed

Phan, Duy Nhat; Le Thi, Hoai An; Dinh, Tao Pham

2017-11-01

This letter proposes a novel approach using the [Formula: see text]-norm regularization for the sparse covariance matrix estimation (SCME) problem. The objective function of SCME problem is composed of a nonconvex part and the [Formula: see text] term, which is discontinuous and difficult to tackle. Appropriate DC (difference of convex functions) approximations of [Formula: see text]-norm are used that result in approximation SCME problems that are still nonconvex. DC programming and DCA (DC algorithm), powerful tools in nonconvex programming framework, are investigated. Two DC formulations are proposed and corresponding DCA schemes developed. Two applications of the SCME problem that are considered are classification via sparse quadratic discriminant analysis and portfolio optimization. A careful empirical experiment is performed through simulated and real data sets to study the performance of the proposed algorithms. Numerical results showed their efficiency and their superiority compared with seven state-of-the-art methods.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

Physics Portfolios

ERIC Educational Resources Information Center

Whitworth, Brooke A.; Bell, Randy L.

2013-01-01

Traditionally, teachers assess students' physics understanding through lab activities, responses to open-ended word problems, and tests. But there is another way to measure student understanding, one in which students apply their learning to the world around them. This article shows how to implement student portfolios, which allow students to…

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.

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.

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 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).

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

Strife and Progress: Portfolio Strategies for Managing Urban Schools

ERIC Educational Resources Information Center

Campbell, Christine; Gross, Betheny; Hill, Paul T.

2012-01-01

Deficient urban schooling remains one of America's most pressing--and stubborn--public policy problems. This important new book details and evaluates a radical and promising new approach to K-12 education reform. "Strife and Progress" explains for a broad audience the "portfolio strategy" for providing urban education--its…

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

Solving portfolio selection problems with minimum transaction lots based on conditional-value-at-risk

NASA Astrophysics Data System (ADS)

Setiawan, E. P.; Rosadi, D.

2017-01-01

Portfolio selection problems conventionally means ‘minimizing the risk, given the certain level of returns’ from some financial assets. This problem is frequently solved with quadratic or linear programming methods, depending on the risk measure that used in the objective function. However, the solutions obtained by these method are in real numbers, which may give some problem in real application because each asset usually has its minimum transaction lots. In the classical approach considering minimum transaction lots were developed based on linear Mean Absolute Deviation (MAD), variance (like Markowitz’s model), and semi-variance as risk measure. In this paper we investigated the portfolio selection methods with minimum transaction lots with conditional value at risk (CVaR) as risk measure. The mean-CVaR methodology only involves the part of the tail of the distribution that contributed to high losses. This approach looks better when we work with non-symmetric return probability distribution. Solution of this method can be found with Genetic Algorithm (GA) methods. We provide real examples using stocks from Indonesia stocks market.

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

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.

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.

Successful Technology Transfer in Colorado: A Portfolio of Technology Transfer "Success Stories."

ERIC Educational Resources Information Center

Colorado Advanced Tech. Inst., Denver.

The examples in this portfolio demonstrate how technology transfer among universities, businesses, and federal laboratories solve real-world problems, and create new goods and services. They reveal how, through strengthening the infrastructure joining private and public sectors, Colorado can better compete in the global marketplace. All of the…

Creating Meaning through Multimodality: Multiliteracies Assessment and Photo Projects for Online Portfolios

ERIC Educational Resources Information Center

Schmerbeck, Nicola; Lucht, Felecia

2017-01-01

Actively engaged in online media, learners today are surrounded by texts overtly and covertly transmitted by visual images, sound effects, and voices as well as the written word. Language learning portfolios can engage students in the literacy-oriented learning processes of interpretation, collaboration, and problem solving as outlined by Kern…

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.

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.

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.

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

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.

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.

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

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.

Advising ePortfolios to Improve First-Generation Student Engagement in Higher Education

ERIC Educational Resources Information Center

Ambrose, G. Alex

2013-01-01

This study considers how advising ePortfolios are uniquely situated to address a current challenge in the application of educational technologies: using the right tool for the right job for the right reason at the right time. The particular problem identified for investigation lies at the intersection of two central issues: first, in the age of…

Mapping ecological risks with a portfolio-based technique: incorporating uncertainty and decision-making preferences

Treesearch

Denys Yemshanov; Frank H. Koch; Mark Ducey; Klaus Koehler

2013-01-01

Geographic mapping of risks is a useful analytical step in ecological risk assessments and in particular, in analyses aimed to estimate risks associated with introductions of invasive organisms. In this paper, we approach invasive species risk mapping as a portfolio allocation problem and apply techniques from decision theory to build an invasion risk map that combines...

Using a Portfolio of Algorithms for Planning and Scheduling

NASA Technical Reports Server (NTRS)

Sherwood, Robert; Knight, Russell; Rabideau, Gregg; Chien, Steve; Tran, Daniel; Engelhardt, Barbara

2003-01-01

The Automated Scheduling and Planning Environment (ASPEN) software system, aspects of which have been reported in several previous NASA Tech Briefs articles, includes a subsystem that utilizes a portfolio of heuristic algorithms that work synergistically to solve problems. The nature of the synergy of the specific algorithms is that their likelihoods of success are negatively correlated: that is, when a combination of them is used to solve a problem, the probability that at least one of them will succeed is greater than the sum of probabilities of success of the individual algorithms operating independently of each other. In ASPEN, the portfolio of algorithms is used in a planning process of the iterative repair type, in which conflicts are detected and addressed one at a time until either no conflicts exist or a user-defined time limit has been exceeded. At each choice point (e.g., selection of conflict; selection of method of resolution of conflict; or choice of move, addition, or deletion) ASPEN makes a stochastic choice of a combination of algorithms from the portfolio. This approach makes it possible for the search to escape from looping and from solutions that are locally but not globally optimum.

Methodology Development for Assessment of Spaceport Technology Returns and Risks

NASA Technical Reports Server (NTRS)

Joglekar, Prafulla; Zapata, Edgar

2001-01-01

As part of Kennedy Space Center's (KSC's) challenge to open the space frontier, new spaceport technologies must be developed, matured and successfully transitioned to operational systems. R&D investment decisions can be considered from multiple perspectives. Near mid and far term technology horizons must be understood. Because a multitude of technology investment opportunities are available, we must identify choices that promise the greatest likelihood of significant lifecycle At the same time, the costs and risks of any choice must be well understood and balanced against its potential returns The problem is not one of simply rank- ordering projects in terms of their desirability. KSC wants to determine a portfolio of projects that simultaneously satisfies multiple goals, such as getting the biggest bang for the buck, supporting projects that may be too risky for private funding, staying within annual budget cycles without foregoing the requirements of a long term technology vision, and ensuring the development of a diversity of technologies that, support the variety of operational functions involved in space transportation. This work aims to assist in the development of in methods and techniques that support strategic technology investment decisions and ease the process of determining an optimal portfolio of spaceport R&D investments. Available literature on risks and returns to R&D is reviewed and most useful pieces are brought to the attention of the Spaceport Technology Development Office (STDO). KSC's current project management procedures are reviewed. It is found that the "one size fits all" nature of KSC's existing procedures and project selection criteria is not conducive to prudent decision-making. Directions for improving KSC's - procedures and criteria are outlined. With help of a contractor, STDO is currently developing a tool, named Change Management Analysis Tool (CMAT)/ Portfolio Analysis Tool (PAT), to assist KSC's R&D portfolio determination. A critical review of CMAT/PAT is undertaken. Directions for the improvement of this tool are provided. STDO and KSC intend to follow up on many, if not all, of the recommendations provided.

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.

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.

What Is the Relationship Between a Preclerkship Portfolio Review and Later Performance in Clerkships?

PubMed

O'Brien, Celia Laird; Thomas, John X; Green, Marianne M

2018-01-01

Medical educators struggle to find effective ways to assess essential competencies such as communication, professionalism, and teamwork. Portfolio-based assessment provides one method of addressing this problem by allowing faculty reviewers to judge performance, as based on a longitudinal record of student behavior. At the Feinberg School of Medicine, the portfolio system measures behavioral competence using multiple assessments collected over time. This study examines whether a preclerkship portfolio review is a valid method of identifying problematic student behavior affecting later performance in clerkships. The authors divided students into two groups based on a summative preclerkship portfolio review in 2014: students who had concerning behavior in one or more competencies and students progressing satisfactorily. They compared how students in these groups later performed on two clerkship outcomes as of October 2015: final grades in required clerkships, and performance on a clerkship clinical composite score. They used Mann-Whitney tests and multiple linear regression to examine the relationship between portfolio review results and clerkship outcomes. They used USMLE Step 1 to control for knowledge acquisition. Students with concerning behavior preclerkship received significantly lower clerkship grades than students progressing satisfactorily (P = .002). They also scored significantly lower on the clinical composite score (P < .001). Regression analysis indicated concerning behavior was associated with lower clinical composite scores, even after controlling for knowledge acquisition. The results show a preclerkship portfolio review can identify behaviors that impact clerkship performance. A comprehensive portfolio system is a valid way to measure behavioral competencies.

Solving optimization problems on computational grids.

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

Wright, S. J.; Mathematics and Computer Science

2001-05-01

Multiprocessor computing platforms, which have become more and more widely available since the mid-1980s, are now heavily used by organizations that need to solve very demanding computational problems. Parallel computing is now central to the culture of many research communities. Novel parallel approaches were developed for global optimization, network optimization, and direct-search methods for nonlinear optimization. Activity was particularly widespread in parallel branch-and-bound approaches for various problems in combinatorial and network optimization. As the cost of personal computers and low-end workstations has continued to fall, while the speed and capacity of processors and networks have increased dramatically, 'cluster' platforms havemore » become popular in many settings. A somewhat different type of parallel computing platform know as a computational grid (alternatively, metacomputer) has arisen in comparatively recent times. Broadly speaking, this term refers not to a multiprocessor with identical processing nodes but rather to a heterogeneous collection of devices that are widely distributed, possibly around the globe. The advantage of such platforms is obvious: they have the potential to deliver enormous computing power. Just as obviously, however, the complexity of grids makes them very difficult to use. The Condor team, headed by Miron Livny at the University of Wisconsin, were among the pioneers in providing infrastructure for grid computations. More recently, the Globus project has developed technologies to support computations on geographically distributed platforms consisting of high-end computers, storage and visualization devices, and other scientific instruments. In 1997, we started the metaneos project as a collaborative effort between optimization specialists and the Condor and Globus groups. Our aim was to address complex, difficult optimization problems in several areas, designing and implementing the algorithms and the software infrastructure need to solve these problems on computational grids. This article describes some of the results we have obtained during the first three years of the metaneos project. Our efforts have led to development of the runtime support library MW for implementing algorithms with master-worker control structure on Condor platforms. This work is discussed here, along with work on algorithms and codes for integer linear programming, the quadratic assignment problem, and stochastic linear programmming. Our experiences in the metaneos project have shown that cheap, powerful computational grids can be used to tackle large optimization problems of various types. In an industrial or commercial setting, the results demonstrate that one may not have to buy powerful computational servers to solve many of the large problems arising in areas such as scheduling, portfolio optimization, or logistics; the idle time on employee workstations (or, at worst, an investment in a modest cluster of PCs) may do the job. For the optimization research community, our results motivate further work on parallel, grid-enabled algorithms for solving very large problems of other types. The fact that very large problems can be solved cheaply allows researchers to better understand issues of 'practical' complexity and of the role of heuristics.« less

How Do Severe Constraints Affect the Search Ability of Multiobjective Evolutionary Algorithms in Water Resources?

NASA Astrophysics Data System (ADS)

Clarkin, T. J.; Kasprzyk, J. R.; Raseman, W. J.; Herman, J. D.

2015-12-01

This study contributes a diagnostic assessment of multiobjective evolutionary algorithm (MOEA) search on a set of water resources problem formulations with different configurations of constraints. Unlike constraints in classical optimization modeling, constraints within MOEA simulation-optimization represent limits on acceptable performance that delineate whether solutions within the search problem are feasible. Constraints are relevant because of the emergent pressures on water resources systems: increasing public awareness of their sustainability, coupled with regulatory pressures on water management agencies. In this study, we test several state-of-the-art MOEAs that utilize restricted tournament selection for constraint handling on varying configurations of water resources planning problems. For example, a problem that has no constraints on performance levels will be compared with a problem with several severe constraints, and a problem with constraints that have less severe values on the constraint thresholds. One such problem, Lower Rio Grande Valley (LRGV) portfolio planning, has been solved with a suite of constraints that ensure high reliability, low cost variability, and acceptable performance in a single year severe drought. But to date, it is unclear whether or not the constraints are negatively affecting MOEAs' ability to solve the problem effectively. Two categories of results are explored. The first category uses control maps of algorithm performance to determine if the algorithm's performance is sensitive to user-defined parameters. The second category uses run-time performance metrics to determine the time required for the algorithm to reach sufficient levels of convergence and diversity on the solution sets. Our work exploring the effect of constraints will better enable practitioners to define MOEA problem formulations for real-world systems, especially when stakeholders are concerned with achieving fixed levels of performance according to one or more metrics.

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.

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.

Using KIE To Help Students Develop Shared Criteria for House Designs.

ERIC Educational Resources Information Center

Cuthbert, Alex; Hoadley, Christopher M.

How can students develop shared criteria for problems that have no "right" answer? Ill-structured problems of this sort are called design problems. Like portfolio projects, these problems are difficult to evaluate for both teachers and students. This investigation contrasts two methods for developing shared criteria for project…

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.

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.

Random Matrix Theory Approach to Indonesia Energy Portfolio Analysis

NASA Astrophysics Data System (ADS)

Mahardhika, Alifian; Purqon, Acep

2017-07-01

In a few years, Indonesia experienced difficulties in maintaining energy security, the problem is the decline in oil production from 1.6 million barrels per day to 861 thousand barrels per day in 2012. However, there is a difference condition in 2015 until the third week in 2016, world oil prices actually fell at the lowest price level since last 12 years. The decline in oil prices due to oversupply of oil by oil-producing countries of the world due to the instability of the world economy. Wave of layoffs in Indonesia is a response to the decline in oil prices, this led to the energy and mines portfolios Indonesia feared would not be more advantageous than the portfolio in other countries. In this research, portfolio analysis will be done on energy and mining in Indonesia by using stock price data of energy and mines in the period 26 November 2010 until April 1, 2016. It was found that the results have a wide effect of the market potential is high in the determination of the return on the portfolio energy and mines. Later, it was found that there are eight of the thirty stocks in the energy and mining portfolio of Indonesia which have a high probability of return relative to the average return of stocks in a portfolio of energy and mines.

The portfolio method as management support for patients with major depression.

PubMed

Nunstedt, Håkan; Nilsson, Kerstin; Skärsäter, Ingela

2014-06-01

To describe how patients with major depression in psychiatric outpatient care use the portfolio method and whether the method helps the patients to understand their depression. Major depressive disorder is an increasing problem in society. Learning about one's depression has been demonstrated to be important for recovery. If the goal is better understanding and management of depression, learning must proceed on the patient's own terms, based on the patient's previous understanding of their depression. Learning must be aligned with patient needs if it is to result in meaningful and useful understanding. Each patient's portfolio consisted of a binder. Inside the binder, there was a register with predetermined flaps and questions. The patients were asked to work with the questions in the sections that built the content in the portfolio. Individual interviews with patients (n = 5) suffering from major depression according to Diagnostic and Statistical Manual of Mental Disorders - Fourth Edition (DSM-IV) (American Psychiatric Association 1994) were repeatedly conducted between April 2008 and August 2009 in two psychiatric outpatient clinics in western Sweden. Data were analysed using latent content analysis. The results showed that the portfolio was used by patients as a management strategy for processing and analysis of their situation and that a portfolio's structure affects its usability. The patients use the portfolio for reflection on and confirmation of their progress, to create structure in their situation, as a management strategy for remembering situations and providing reminders of upcoming activities. Using a clearly structured care portfolio can enable participation and patient learning and help patients understand their depression. The portfolio method could provide a tool in psychiatric nursing that may facilitate patient understanding and increase self-efficacy. © 2013 John Wiley & Sons Ltd.

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.

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.

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.

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.

Three essays on pricing and risk management in electricity markets

NASA Astrophysics Data System (ADS)

Kotsan, Serhiy

2005-07-01

A set of three papers forms this dissertation. In the first paper I analyze an electricity market that does not clear. The system operator satisfies fixed demand at a fixed price, and attempts to minimize "cost" as indicated by independent generators' supply bids. No equilibrium exists in this situation, and the operator lacks information sufficient to minimize actual cost. As a remedy, we propose a simple efficient tax mechanism. With the tax, Nash equilibrium bids still diverge from marginal cost but nonetheless provide sufficient information to minimize actual cost, regardless of the tax rate or number of generators. The second paper examines a price mechanism with one price assigned for each level of bundled real and reactive power. Equilibrium allocation under this pricing approach raises system efficiency via better allocation of the reactive power reserves, neglected in the traditional pricing approach. Pricing reactive power should be considered in the bundle with real power since its cost is highly dependent on real power output. The efficiency of pricing approach is shown in the general case, and tested on the 30-bus IEEE network with piecewise linear cost functions of the generators. Finally the third paper addresses the problem of optimal investment in generation based on mean-variance portfolio analysis. It is assumed the investor can freely create a portfolio of shares in generation located on buses of the electrical network. Investors are risk averse, and seek to minimize the variance of the weighted average Locational Marginal Price (LMP) in their portfolio, and to maximize its expected value. I conduct simulations using a standard IEEE 68-bus network that resembles the New York - New England system and calculate LMPs in accordance with the PJM methodology for a fully optimal AC power flow solution. Results indicate that the network topology is a crucial determinant of the investment decision as line congestion makes it difficult to deliver power to certain nodes at system peak load. Determining those nodes is an important task for an investor in generation as well as the transmission system operator.

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.

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.

Building uncertainty into cost-effectiveness rankings: portfolio risk-return tradeoffs and implications for decision rules.

PubMed

O'Brien, B J; Sculpher, M J

2000-05-01

Current principles of cost-effectiveness analysis emphasize the rank ordering of programs by expected economic return (eg, quality-adjusted life-years gained per dollar expended). This criterion ignores the variance associated with the cost-effectiveness of a program, yet variance is a common measure of risk when financial investment options are appraised. Variation in health care program return is likely to be a criterion of program selection for health care managers with fixed budgets and outcome performance targets. Characterizing health care resource allocation as a risky investment problem, we show how concepts of portfolio analysis from financial economics can be adopted as a conceptual framework for presenting cost-effectiveness data from multiple programs as mean-variance data. Two specific propositions emerge: (1) the current convention of ranking programs by expected return is a special case of the portfolio selection problem in which the decision maker is assumed to be indifferent to risk, and (2) for risk-averse decision makers, the degree of joint risk or covariation in cost-effectiveness between programs will create incentives to diversify an investment portfolio. The conventional normative assumption of risk neutrality for social-level public investment decisions does not apply to a large number of health care resource allocation decisions in which health care managers seek to maximize returns subject to budget constraints and performance targets. Portfolio theory offers a useful framework for studying mean-variance tradeoffs in cost-effectiveness and offers some positive predictions (and explanations) of actual decision making in the health care sector.

Portfolios in Stochastic Local Search: Efficiently Computing Most Probable Explanations in Bayesian Networks

NASA Technical Reports Server (NTRS)

Mengshoel, Ole J.; Roth, Dan; Wilkins, David C.

2001-01-01

Portfolio methods support the combination of different algorithms and heuristics, including stochastic local search (SLS) heuristics, and have been identified as a promising approach to solve computationally hard problems. While successful in experiments, theoretical foundations and analytical results for portfolio-based SLS heuristics are less developed. This article aims to improve the understanding of the role of portfolios of heuristics in SLS. We emphasize the problem of computing most probable explanations (MPEs) in Bayesian networks (BNs). Algorithmically, we discuss a portfolio-based SLS algorithm for MPE computation, Stochastic Greedy Search (SGS). SGS supports the integration of different initialization operators (or initialization heuristics) and different search operators (greedy and noisy heuristics), thereby enabling new analytical and experimental results. Analytically, we introduce a novel Markov chain model tailored to portfolio-based SLS algorithms including SGS, thereby enabling us to analytically form expected hitting time results that explain empirical run time results. For a specific BN, we show the benefit of using a homogenous initialization portfolio. To further illustrate the portfolio approach, we consider novel additive search heuristics for handling determinism in the form of zero entries in conditional probability tables in BNs. Our additive approach adds rather than multiplies probabilities when computing the utility of an explanation. We motivate the additive measure by studying the dramatic impact of zero entries in conditional probability tables on the number of zero-probability explanations, which again complicates the search process. We consider the relationship between MAXSAT and MPE, and show that additive utility (or gain) is a generalization, to the probabilistic setting, of MAXSAT utility (or gain) used in the celebrated GSAT and WalkSAT algorithms and their descendants. Utilizing our Markov chain framework, we show that expected hitting time is a rational function - i.e. a ratio of two polynomials - of the probability of applying an additive search operator. Experimentally, we report on synthetically generated BNs as well as BNs from applications, and compare SGSs performance to that of Hugin, which performs BN inference by compilation to and propagation in clique trees. On synthetic networks, SGS speeds up computation by approximately two orders of magnitude compared to Hugin. In application networks, our approach is highly competitive in Bayesian networks with a high degree of determinism. In addition to showing that stochastic local search can be competitive with clique tree clustering, our empirical results provide an improved understanding of the circumstances under which portfolio-based SLS outperforms clique tree clustering and vice versa.

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.

Evaluation of the free, open source software WordPress as electronic portfolio system in undergraduate medical education.

PubMed

Avila, Javier; Sostmann, Kai; Breckwoldt, Jan; Peters, Harm

2016-06-03

Electronic portfolios (ePortfolios) are used to document and support learning activities. E-portfolios with mobile capabilities allow even more flexibility. However, the development or acquisition of ePortfolio software is often costly, and at the same time, commercially available systems may not sufficiently fit the institution's needs. The aim of this study was to design and evaluate an ePortfolio system with mobile capabilities using a commercially free and open source software solution. We created an online ePortfolio environment using the blogging software WordPress based on reported capability features of such software by a qualitative weight and sum method. Technical implementation and usability were evaluated by 25 medical students during their clinical training by quantitative and qualitative means using online questionnaires and focus groups. The WordPress ePortfolio environment allowed students a broad spectrum of activities - often documented via mobile devices - like collection of multimedia evidences, posting reflections, messaging, web publishing, ePortfolio searches, collaborative learning, knowledge management in a content management system including a wiki and RSS feeds, and the use of aid tools for studying. The students' experience with WordPress revealed a few technical problems, and this report provides workarounds. The WordPress ePortfolio was rated positively by the students as a content management system (67 % of the students), for exchange with other students (74 %), as a note pad for reflections (53 %) and for its potential as an information source for assessment (48 %) and exchange with a mentor (68 %). On the negative side, 74 % of the students in this pilot study did not find it easy to get started with the system, and 63 % rated the ePortfolio as not being user-friendly. Qualitative analysis indicated a need for more introductory information and training. It is possible to build an advanced ePortfolio system with mobile capabilities with the free and open source software WordPress. This allows institutions without proprietary software to build a sophisticated ePortfolio system adapted to their needs with relatively few resources. The implementation of WordPress should be accompanied by introductory courses in the use of the software and its apps in order to facilitate its usability.

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

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

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.

A Portfolio of Energy Ideas: Social Studies.

ERIC Educational Resources Information Center

Clark, Richard C., Ed.

Presented are 12 social studies units which examine current energy issues and present energy dilemmas for careful study and reflection. The activities emphasize: (1) a range of teaching strategies; (2) problem identification, problem solving, and problem analysis; (3) futures education; (4) students as active learners; and (5) consideration of the…

Generalizable open source urban water portfolio simulation framework demonstrated using a multi-objective risk-based planning benchmark problem.

NASA Astrophysics Data System (ADS)

Trindade, B. C.; Reed, P. M.

2017-12-01

The growing access and reduced cost for computing power in recent years has promoted rapid development and application of multi-objective water supply portfolio planning. As this trend continues there is a pressing need for flexible risk-based simulation frameworks and improved algorithm benchmarking for emerging classes of water supply planning and management problems. This work contributes the Water Utilities Management and Planning (WUMP) model: a generalizable and open source simulation framework designed to capture how water utilities can minimize operational and financial risks by regionally coordinating planning and management choices, i.e. making more efficient and coordinated use of restrictions, water transfers and financial hedging combined with possible construction of new infrastructure. We introduce the WUMP simulation framework as part of a new multi-objective benchmark problem for planning and management of regionally integrated water utility companies. In this problem, a group of fictitious water utilities seek to balance the use of the mentioned reliability driven actions (e.g., restrictions, water transfers and infrastructure pathways) and their inherent financial risks. Several traits of this problem make it ideal for a benchmark problem, namely the presence of (1) strong non-linearities and discontinuities in the Pareto front caused by the step-wise nature of the decision making formulation and by the abrupt addition of storage through infrastructure construction, (2) noise due to the stochastic nature of the streamflows and water demands, and (3) non-separability resulting from the cooperative formulation of the problem, in which decisions made by stakeholder may substantially impact others. Both the open source WUMP simulation framework and its demonstration in a challenging benchmarking example hold value for promoting broader advances in urban water supply portfolio planning for regions confronting change.

Performance Analysis of Continuous Black-Box Optimization Algorithms via Footprints in Instance Space.

PubMed

Muñoz, Mario A; Smith-Miles, Kate A

2017-01-01

This article presents a method for the objective assessment of an algorithm's strengths and weaknesses. Instead of examining the performance of only one or more algorithms on a benchmark set, or generating custom problems that maximize the performance difference between two algorithms, our method quantifies both the nature of the test instances and the algorithm performance. Our aim is to gather information about possible phase transitions in performance, that is, the points in which a small change in problem structure produces algorithm failure. The method is based on the accurate estimation and characterization of the algorithm footprints, that is, the regions of instance space in which good or exceptional performance is expected from an algorithm. A footprint can be estimated for each algorithm and for the overall portfolio. Therefore, we select a set of features to generate a common instance space, which we validate by constructing a sufficiently accurate prediction model. We characterize the footprints by their area and density. Our method identifies complementary performance between algorithms, quantifies the common features of hard problems, and locates regions where a phase transition may lie.

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.

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.

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.

Exploring students' perceptions on the use of significant event analysis, as part of a portfolio assessment process in general practice, as a tool for learning how to use reflection in learning

PubMed Central

Grant, Andrew J; Vermunt, Jan D; Kinnersley, Paul; Houston, Helen

2007-01-01

Background Portfolio learning enables students to collect evidence of their learning. Component tasks making up a portfolio can be devised that relate directly to intended learning outcomes. Reflective tasks can stimulate students to recognise their own learning needs. Assessment of portfolios using a rating scale relating to intended learning outcomes offers high content validity. This study evaluated a reflective portfolio used during a final-year attachment in general practice (family medicine). Students were asked to evaluate the portfolio (which used significant event analysis as a basis for reflection) as a learning tool. The validity and reliability of the portfolio as an assessment tool were also measured. Methods 81 final-year medical students completed reflective significant event analyses as part of a portfolio created during a three-week attachment (clerkship) in general practice (family medicine). As well as two reflective significant event analyses each portfolio contained an audit and a health needs assessment. Portfolios were marked three times; by the student's GP teacher, the course organiser and by another teacher in the university department of general practice. Inter-rater reliability between pairs of markers was calculated. A questionnaire enabled the students' experience of portfolio learning to be determined. Results Benefits to learning from reflective learning were limited. Students said that they thought more about the patients they wrote up in significant event analyses but information as to the nature and effect of this was not forthcoming. Moderate inter-rater reliability (Spearman's Rho .65) was found between pairs of departmental raters dealing with larger numbers (20 – 60) of portfolios. Inter-rater reliability of marking involving GP tutors who only marked 1 – 3 portfolios was very low. Students rated highly their mentoring relationship with their GP teacher but found the portfolio tasks time-consuming. Conclusion The inter-rater reliability observed in this study should be viewed alongside the high validity afforded by the authenticity of the learning tasks (compared with a sample of a student's learning taken by an exam question). Validity is enhanced by the rating scale which directly connects the grade given with intended learning outcomes. The moderate inter-rater reliability may be increased if a portfolio is completed over a longer period of time and contains more component pieces of work. The questionnaire used in this study only accessed limited information about the effect of reflection on students' learning. Qualitative methods of evaluation would determine the students experience in greater depth. It would be useful to evaluate the effects of reflective learning after students have had more time to get used to this unfamiliar method of learning and to overcome any problems in understanding the task. PMID:17397544

Exploring students' perceptions on the use of significant event analysis, as part of a portfolio assessment process in general practice, as a tool for learning how to use reflection in learning.

PubMed

Grant, Andrew J; Vermunt, Jan D; Kinnersley, Paul; Houston, Helen

2007-03-30

Portfolio learning enables students to collect evidence of their learning. Component tasks making up a portfolio can be devised that relate directly to intended learning outcomes. Reflective tasks can stimulate students to recognise their own learning needs. Assessment of portfolios using a rating scale relating to intended learning outcomes offers high content validity. This study evaluated a reflective portfolio used during a final-year attachment in general practice (family medicine). Students were asked to evaluate the portfolio (which used significant event analysis as a basis for reflection) as a learning tool. The validity and reliability of the portfolio as an assessment tool were also measured. 81 final-year medical students completed reflective significant event analyses as part of a portfolio created during a three-week attachment (clerkship) in general practice (family medicine). As well as two reflective significant event analyses each portfolio contained an audit and a health needs assessment. Portfolios were marked three times; by the student's GP teacher, the course organiser and by another teacher in the university department of general practice. Inter-rater reliability between pairs of markers was calculated. A questionnaire enabled the students' experience of portfolio learning to be determined. Benefits to learning from reflective learning were limited. Students said that they thought more about the patients they wrote up in significant event analyses but information as to the nature and effect of this was not forthcoming. Moderate inter-rater reliability (Spearman's Rho .65) was found between pairs of departmental raters dealing with larger numbers (20-60) of portfolios. Inter-rater reliability of marking involving GP tutors who only marked 1-3 portfolios was very low. Students rated highly their mentoring relationship with their GP teacher but found the portfolio tasks time-consuming. The inter-rater reliability observed in this study should be viewed alongside the high validity afforded by the authenticity of the learning tasks (compared with a sample of a student's learning taken by an exam question). Validity is enhanced by the rating scale which directly connects the grade given with intended learning outcomes. The moderate inter-rater reliability may be increased if a portfolio is completed over a longer period of time and contains more component pieces of work. The questionnaire used in this study only accessed limited information about the effect of reflection on students' learning. Qualitative methods of evaluation would determine the students experience in greater depth. It would be useful to evaluate the effects of reflective learning after students have had more time to get used to this unfamiliar method of learning and to overcome any problems in understanding the task.

Employing epigenetics to augment the expression of therapeutic proteins in mammalian cells.

PubMed

Kwaks, Ted H J; Otte, Arie P

2006-03-01

Recombinant proteins form an increasingly large part of the portfolio of biopharmaceutical companies. Production of these often complex transgenic proteins is achieved predominantly in mammalian cell lines but the process is hampered by low yields and unstable expression. Some of these problems are caused by gene silencing at the level of chromatin - so-called epigenetic gene silencing. Here, we describe approaches, which have emerged during the past few years, designed to interfere with epigenetic gene silencing with the aim of enhancing and stabilizing transgene expression. These include targeting histones, the inclusion of specific DNA elements and targeting sites of high gene-expression. We conclude that employing epigenetic gene regulation tools, in combination with further process optimization, might represent the next step forward in the production of therapeutic proteins.

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

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.

[Problem-based learning, a comparison in the acquisition of transversal competencies].

PubMed

González Pascual, Juan Luis; López Martin, Inmaculada; Toledo Gómez, David

2009-01-01

In the European Higher Education Area (EEES in Spanish reference), a change in the pedagogical model has occurred: from teaching centered on the figure of the professor to learning centered on students, from an integral perspective. This learning must bring together the full set of competencies included in the program requirements necessary to obtain a degree. The specific competencies characterize a profession and distinguish one from others. The transversal competencies surpass the limits of one particular discipline to be potentially developed in all; these are subdivided in three types: instrumental, interpersonal and systemic. The authors describe and compare the acquisition of transversal competencies connected to students' portfolios and Problem-based Learning as pedagogical methods from the perspective of second year nursing students at the European University in Madrid during the 2007-8 academic year To do so, the authors carried out a transversal descriptive study; data was collected by a purpose-made questionnaire the authors developed which they based on the transversal competencies of the Tuning Nursing Project. Variables included age, sex, pedagogical method, perception on acquisition of those 24 competencies by means of a Likert Scale. U de Mann-Whitney descriptive and analytical statistics. The authors conclude that the portfolio and Problem-based Learning are useful pedagogical methods for acquiring transversal competencies; these results coincide with those of other studies. Comparing both methods, the authors share the opinion that the Problem-based Learning method could stimulate the search for information better than the portfolio method.

Multi-objective optimization in systematic conservation planning and the representation of genetic variability among populations.

PubMed

Schlottfeldt, S; Walter, M E M T; Carvalho, A C P L F; Soares, T N; Telles, M P C; Loyola, R D; Diniz-Filho, J A F

2015-06-18

Biodiversity crises have led scientists to develop strategies for achieving conservation goals. The underlying principle of these strategies lies in systematic conservation planning (SCP), in which there are at least 2 conflicting objectives, making it a good candidate for multi-objective optimization. Although SCP is typically applied at the species level (or hierarchically higher), it can be used at lower hierarchical levels, such as using alleles as basic units for analysis, for conservation genetics. Here, we propose a method of SCP using a multi-objective approach. We used non-dominated sorting genetic algorithm II in order to identify the smallest set of local populations of Dipteryx alata (baru) (a Brazilian Cerrado species) for conservation, representing the known genetic diversity and using allele frequency information associated with heterozygosity and Hardy-Weinberg equilibrium. We worked in 3 variations for the problem. First, we reproduced a previous experiment, but using a multi-objective approach. We found that the smallest set of populations needed to represent all alleles under study was 7, corroborating the results of the previous study, but with more distinct solutions. In the 2nd and 3rd variations, we performed simultaneous optimization of 4 and 5 objectives, respectively. We found similar but refined results for 7 populations, and a larger portfolio considering intra-specific diversity and persistence with populations ranging from 8-22. This is the first study to apply multi-objective algorithms to an SCP problem using alleles at the population level as basic units for analysis.

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.

Ethical aspects of the mitigation obstruction argument against climate engineering research.

PubMed

Morrow, David R

2014-12-28

Many commentators fear that climate engineering research might lead policy-makers to reduce mitigation efforts. Most of the literature on this so-called 'moral hazard' problem focuses on the prediction that climate engineering research would reduce mitigation efforts. This paper focuses on a related ethical question: Why would it be a bad thing if climate engineering research obstructed mitigation? If climate engineering promises to be effective enough, it might justify some reduction in mitigation. Climate policy portfolios involving sufficiently large or poorly planned reductions in mitigation, however, could lead to an outcome that would be worse than the portfolio that would be chosen in the absence of further climate engineering research. This paper applies three ethical perspectives to describe the kinds of portfolios that would be worse than that 'baseline portfolio'. The literature on climate engineering identifies various mechanisms that might cause policy-makers to choose these inferior portfolios, but it is difficult to know in advance whether the existence of these mechanisms means that climate engineering research really would lead to a worse outcome. In the light of that uncertainty, a precautionary approach suggests that researchers should take measures to reduce the risk of mitigation obstruction. Several such measures are suggested. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

A Portfolio of Energy Ideas: Science.

ERIC Educational Resources Information Center

Clark, Richard C., Ed.

Presented are 10 science energy education units designed to help students learn how to turn science questions and problems about energy into experiments. Each unit focuses on subject-matter knowledge and on the logic and strategy of scientific problem solving. These teacher-oriented materials include an overview of each unit, background…

A Portfolio of Energy Ideas: Science.

ERIC Educational Resources Information Center

Clark, Richard C., Ed.

Ten units which focus on subject-matter knowledge about energy and on the logic and strategy of problem-solving within science are provided in this user's guide. Each unit includes: a detailed summary of unit problems and activities; recommended grade levels and subject areas; possible learner outcomes and general goals; teacher background…

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

Tweaking Science Education.

ERIC Educational Resources Information Center

Andersen, Hans O.

2000-01-01

Discusses problems facing science education supervisors and suggests possible solutions. Comments on the experiences of beginning teachers, portfolio compilation, mentoring, and the evaluation and selection of curricular and technological innovations. (Contains 14 references.) (WRM)

A Diagnostic Assessment of Evolutionary Multiobjective Optimization for Water Resources Systems

NASA Astrophysics Data System (ADS)

Reed, P.; Hadka, D.; Herman, J.; Kasprzyk, J.; Kollat, J.

2012-04-01

This study contributes a rigorous diagnostic assessment of state-of-the-art multiobjective evolutionary algorithms (MOEAs) and highlights key advances that the water resources field can exploit to better discover the critical tradeoffs constraining our systems. This study provides the most comprehensive diagnostic assessment of MOEAs for water resources to date, exploiting more than 100,000 MOEA runs and trillions of design evaluations. The diagnostic assessment measures the effectiveness, efficiency, reliability, and controllability of ten benchmark MOEAs for a representative suite of water resources applications addressing rainfall-runoff calibration, long-term groundwater monitoring (LTM), and risk-based water supply portfolio planning. The suite of problems encompasses a range of challenging problem properties including (1) many-objective formulations with 4 or more objectives, (2) multi-modality (or false optima), (3) nonlinearity, (4) discreteness, (5) severe constraints, (6) stochastic objectives, and (7) non-separability (also called epistasis). The applications are representative of the dominant problem classes that have shaped the history of MOEAs in water resources and that will be dominant foci in the future. Recommendations are provided for which modern MOEAs should serve as tools and benchmarks in the future water resources literature.

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

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

An Auto-Scoring Mechanism for Evaluating Problem-Solving Ability in a Web-Based Learning Environment

ERIC Educational Resources Information Center

Chiou, Chuang-Kai; Hwang, Gwo-Jen; Tseng, Judy C. R.

2009-01-01

The rapid development of computer and network technologies has attracted researchers to investigate strategies for and the effects of applying information technologies in learning activities; simultaneously, learning environments have been developed to record the learning portfolios of students seeking web information for problem-solving. Although…

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

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.

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.

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…

Student Learning and Evaluation in Analytical Chemistry Using a Problem-Oriented Approach and Portfolio Assessment

ERIC Educational Resources Information Center

Boyce, Mary C.; Singh, Kuki

2008-01-01

This paper describes a student-focused activity that promotes effective learning in analytical chemistry. Providing an environment where students were responsible for their own learning allowed them to participate at all levels from designing the problem to be addressed, planning the laboratory work to support their learning, to providing evidence…

The Rio de Janeiro Municipality's Services Portfolio and Health Actions in Primary Care in Brazil.

PubMed

Salazar, Bianca Alves; Campos, Mônica Rodrigues; Luiza, Vera Lucia

2017-03-01

This study aimed to identify the provision of actions and procedures by family health teams (FHSt), based on Rio de Janeiro Municipality's (MRJ) Health Services Portfolio (HSP) and the main factors associated with this provision, in the different population strata. Data from the National Program for Improving Access and Quality of Primary Healthcare were used and implemented at the national level into 17,202 FHSts from June to September 2012. Outcome variables were "FHSt belonging to MRJ" and "FHSt providing all nine CS-MRJ procedures". Uni-, bi- and multivariate analysis were performed. A better performance of the MRJ in relation to other major urban centers (EP6#) (p<5%) was noted in 10 of the 14 health actions analyzed. The electronic medical record showed a level of deployment in MRJ's FHSts of 96%, contrasting with 34% in the EP6# and 14% in Brazil. Both the MRJ and EP6# evidenced low supply of mental health services (about 56%). While the supply of low-complexity procedures was a major problem in large cities, the supply of health actions in the different health care lines was a larger problem in small municipalities. Overall, the MRJ showed better performance when compared to the average of large municipalities. The health service portfolio appeared to be an important management tool.

Downside Risk analysis applied to the Hedge Funds universe

NASA Astrophysics Data System (ADS)

Perelló, Josep

2007-09-01

Hedge Funds are considered as one of the portfolio management sectors which shows a fastest growing for the past decade. An optimal Hedge Fund management requires an appropriate risk metrics. The classic CAPM theory and its Ratio Sharpe fail to capture some crucial aspects due to the strong non-Gaussian character of Hedge Funds statistics. A possible way out to this problem while keeping the CAPM simplicity is the so-called Downside Risk analysis. One important benefit lies in distinguishing between good and bad returns, that is: returns greater or lower than investor's goal. We revisit most popular Downside Risk indicators and provide new analytical results on them. We compute these measures by taking the Credit Suisse/Tremont Investable Hedge Fund Index Data and with the Gaussian case as a benchmark. In this way, an unusual transversal lecture of the existing Downside Risk measures is provided.

Preanalytics in lung cancer.

PubMed

Warth, Arne; Muley, Thomas; Meister, Michael; Weichert, Wilko

2015-01-01

Preanalytic sampling techniques and preparation of tissue specimens strongly influence analytical results in lung tissue diagnostics both on the morphological but also on the molecular level. However, in contrast to analytics where tremendous achievements in the last decade have led to a whole new portfolio of test methods, developments in preanalytics have been minimal. This is specifically unfortunate in lung cancer, where usually only small amounts of tissue are at hand and optimization in all processing steps is mandatory in order to increase the diagnostic yield. In the following, we provide a comprehensive overview on some aspects of preanalytics in lung cancer from the method of sampling over tissue processing to its impact on analytical test results. We specifically discuss the role of preanalytics in novel technologies like next-generation sequencing and in the state-of the-art cytology preparations. In addition, we point out specific problems in preanalytics which hamper further developments in the field of lung tissue diagnostics.

Managing risk and expected financial return from selective expansion of operating room capacity: mean-variance analysis of a hospital's portfolio of surgeons.

PubMed

Dexter, Franklin; Ledolter, Johannes

2003-07-01

Surgeons using the same amount of operating room (OR) time differ in their achieved hospital contribution margins (revenue minus variable costs) by >1000%. Thus, to improve the financial return from perioperative facilities, OR strategic decisions should selectively focus additional OR capacity and capital purchasing on a few surgeons or subspecialties. These decisions use estimates of each surgeon's and/or subspecialty's contribution margin per OR hour. The estimates are subject to uncertainty (e.g., from outliers). We account for the uncertainties by using mean-variance portfolio analysis (i.e., quadratic programming). This method characterizes the problem of selectively expanding OR capacity based on the expected financial return and risk of different portfolios of surgeons. The assessment reveals whether the choices, of which surgeons have their OR capacity expanded, are sensitive to the uncertainties in the surgeons' contribution margins per OR hour. Thus, mean-variance analysis reduces the chance of making strategic decisions based on spurious information. We also assess the financial benefit of using mean-variance portfolio analysis when the planned expansion of OR capacity is well diversified over at least several surgeons or subspecialties. Our results show that, in such circumstances, there may be little benefit from further changing the portfolio to reduce its financial risk. Surgeon and subspecialty specific hospital financial data are uncertain, a fact that should be taken into account when making decisions about expanding operating room capacity. We show that mean-variance portfolio analysis can incorporate this uncertainty, thereby guiding operating room management decision-making and reducing the chance of a strategic decision being made based on spurious information.

Efforts Aimed To Reduce Attrition in Antimalarial Drug Discovery: A Systematic Evaluation of the Current Antimalarial Targets Portfolio.

PubMed

Chaparro, María Jesús; Calderón, Félix; Castañeda, Pablo; Fernández-Alvaro, Elena; Gabarró, Raquel; Gamo, Francisco Javier; Gómez-Lorenzo, María G; Martín, Julio; Fernández, Esther

2018-04-13

Malaria remains a major global health problem. In 2015 alone, more than 200 million cases of malaria were reported, and more than 400,000 deaths occurred. Since 2010, emerging resistance to current front-line ACTs (artemisinin combination therapies) has been detected in endemic countries. Therefore, there is an urgency for new therapies based on novel modes of action, able to relieve symptoms as fast as the artemisinins and/or block malaria transmission. During the past few years, the antimalarial community has focused their efforts on phenotypic screening as a pragmatic approach to identify new hits. Optimization efforts on several chemical series have been successful, and clinical candidates have been identified. In addition, recent advances in genetics and proteomics have led to the target deconvolution of phenotypic clinical candidates. New mechanisms of action will also be critical to overcome resistance and reduce attrition. Therefore, a complementary strategy focused on identifying well-validated targets to start hit identification programs is essential to reinforce the clinical pipeline. Leveraging published data, we have assessed the status quo of the current antimalarial target portfolio with a focus on the blood stage clinical disease. From an extensive list of reported Plasmodium targets, we have defined triage criteria. These criteria consider genetic, pharmacological, and chemical validation, as well as tractability/doability, and safety implications. These criteria have provided a quantitative score that has led us to prioritize those targets with the highest probability to deliver successful and differentiated new drugs.

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…

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

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

Smolinski, B.

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

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.

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.

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.

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.

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.

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.

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

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…

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.

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.

Single and multiple objective biomass-to-biofuel supply chain optimization considering environmental impacts

NASA Astrophysics Data System (ADS)

Valles Sosa, Claudia Evangelina

Bioenergy has become an important alternative source of energy to alleviate the reliance on petroleum energy. Bioenergy offers diminishing climate change by reducing Green House Gas Emissions, as well as providing energy security and enhancing rural development. The Energy Independence and Security Act mandate the use of 21 billion gallons of advanced biofuels including 16 billion gallons of cellulosic biofuels by the year 2022. It is clear that Biomass can make a substantial contribution to supply future energy demand in a sustainable way. However, the supply of sustainable energy is one of the main challenges that mankind will face over the coming decades. For instance, many logistical challenges will be faced in order to provide an efficient and reliable supply of quality feedstock to biorefineries. 700 million tons of biomass will be required to be sustainably delivered to biorefineries annually to meet the projected use of biofuels by the year of 2022. Approaching this complex logistic problem as a multi-commodity network flow structure, the present work proposes the use of a genetic algorithm as a single objective optimization problem that considers the maximization of profit and the present work also proposes the use of a Multiple Objective Evolutionary Algorithm to simultaneously maximize profit while minimizing global warming potential. Most transportation optimization problems available in the literature have mostly considered the maximization of profit or the minimization of total travel time as potential objectives to be optimized. However, on this research work, we take a more conscious and sustainable approach for this logistic problem. Planners are increasingly expected to adopt a multi-disciplinary approach, especially due to the rising importance of environmental stewardship. The role of a transportation planner and designer is shifting from simple economic analysis to promoting sustainability through the integration of environmental objectives. To respond to these new challenges, the Modified Multiple Objective Evolutionary Algorithm for the design optimization of a biomass to bio-refinery logistic system that considers the simultaneous maximization of the total profit and the minimization of three environmental impacts is presented. Sustainability balances economic, social and environmental goals and objectives. There exist several works in the literature that have considered economic and environmental objectives for the presented supply chain problem. However, there is a lack of research performed in the social aspect of a sustainable logistics system. This work proposes a methodology to integrate social aspect assessment, based on employment creation. Finally, most of the assessment methodologies considered in the literature only contemplate deterministic values, when in realistic situations uncertainties in the supply chain are present. In this work, Value-at-Risk, an advanced risk measure commonly used in portfolio optimization is included to consider the uncertainties in biofuel prices, among the others.

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.

Matching a Distribution by Matching Quantiles Estimation

PubMed Central

Sgouropoulos, Nikolaos; Yao, Qiwei; Yastremiz, Claudia

2015-01-01

Motivated by the problem of selecting representative portfolios for backtesting counterparty credit risks, we propose a matching quantiles estimation (MQE) method for matching a target distribution by that of a linear combination of a set of random variables. An iterative procedure based on the ordinary least-squares estimation (OLS) is proposed to compute MQE. MQE can be easily modified by adding a LASSO penalty term if a sparse representation is desired, or by restricting the matching within certain range of quantiles to match a part of the target distribution. The convergence of the algorithm and the asymptotic properties of the estimation, both with or without LASSO, are established. A measure and an associated statistical test are proposed to assess the goodness-of-match. The finite sample properties are illustrated by simulation. An application in selecting a counterparty representative portfolio with a real dataset is reported. The proposed MQE also finds applications in portfolio tracking, which demonstrates the usefulness of combining MQE with LASSO. PMID:26692592

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.

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.

Risk management in the competitive electric power industry

NASA Astrophysics Data System (ADS)

Dahlgren, Robert William

From 1990 until present day, the electric power industry has experienced dramatic changes worldwide. This recent evolution of the power industry has included creation and multiple iterations of competitive wholesale markets in many different forms. The creation of these competitive markets has resulted in increased short-term volatility of power prices. Vertically integrated utilities emerged from years of regulatory controls to now experience the need to perform risk assessment. The goal of this dissertation is to provide background and details of the evolution of market structures combined with examples of how to apply price risk assessment techniques such as Value-at-Risk (VaR). In Chapter 1, the history and evolution of three selected regional markets, PJM, California, and England and Wales is presented. A summary of the commonalities and differences is presented to provide an overview of the rate of transformation of the industry in recent years. The broad area of risk management in the power industry is also explored through a State-of-the-Art Literature Survey. In Chapter 2, an illustration of risk assessment to power trading is presented. The techniques of Value-at-Risk and Conditional Value-at-Risk are introduced and applied to a common scenario. The advantages and limitations of the techniques are compared through observation of their results against the common example. Volatility in the California Power Markets is presented in Chapter 3. This analysis explores the California markets in the summer of 2000 including the application of VaR analysis to the extreme volatility observed during this period. In Chapter 4, CVaR is applied to the same California historical data used in Chapter 3. In addition, the unique application of minimizing the risk of a power portfolio by minimizing CVaR is presented. The application relies on recent research into CVaR whereby the portfolio optimization problem can be reduced to a Linear Programming problem.

Teachers' Views on Performance-Based Assessments.

ERIC Educational Resources Information Center

King, Bruce

1991-01-01

Provides personal perspectives from teachers about the prospects and problems illuminated by Stanford University's Teacher Assessment Project. Teacher remarks address the portfolio development process, assessment centers, implications for national board certification for teachers, personal thoughts and perspectives on teaching, and the future of…

A Portfolio of the Identities of Young People of the South of Russia under the Conditions of Civilizational Choice

ERIC Educational Resources Information Center

Avksent'ev, V. A.; Aksiumov, B. V.

2012-01-01

The problem of civilizational choice is one of the most timely and relevant problems of the entire postcommunist world. Most of the states of the former Soviet Union, including Russia, still find themselves in an uncertain zone of transition. The crisis of civilizational identity, far from being overcome, has even deepened as the Soviet past…

Evaluation of the clinical process in a critical care information system using the Lean method: a case study

PubMed Central

2012-01-01

Background There are numerous applications for Health Information Systems (HIS) that support specific tasks in the clinical workflow. The Lean method has been used increasingly to optimize clinical workflows, by removing waste and shortening the delivery cycle time. There are a limited number of studies on Lean applications related to HIS. Therefore, we applied the Lean method to evaluate the clinical processes related to HIS, in order to evaluate its efficiency in removing waste and optimizing the process flow. This paper presents the evaluation findings of these clinical processes, with regards to a critical care information system (CCIS), known as IntelliVue Clinical Information Portfolio (ICIP), and recommends solutions to the problems that were identified during the study. Methods We conducted a case study under actual clinical settings, to investigate how the Lean method can be used to improve the clinical process. We used observations, interviews, and document analysis, to achieve our stated goal. We also applied two tools from the Lean methodology, namely the Value Stream Mapping and the A3 problem-solving tools. We used eVSM software to plot the Value Stream Map and A3 reports. Results We identified a number of problems related to inefficiency and waste in the clinical process, and proposed an improved process model. Conclusions The case study findings show that the Value Stream Mapping and the A3 reports can be used as tools to identify waste and integrate the process steps more efficiently. We also proposed a standardized and improved clinical process model and suggested an integrated information system that combines database and software applications to reduce waste and data redundancy. PMID:23259846

Evaluation of the clinical process in a critical care information system using the Lean method: a case study.

PubMed

Yusof, Maryati Mohd; Khodambashi, Soudabeh; Mokhtar, Ariffin Marzuki

2012-12-21

There are numerous applications for Health Information Systems (HIS) that support specific tasks in the clinical workflow. The Lean method has been used increasingly to optimize clinical workflows, by removing waste and shortening the delivery cycle time. There are a limited number of studies on Lean applications related to HIS. Therefore, we applied the Lean method to evaluate the clinical processes related to HIS, in order to evaluate its efficiency in removing waste and optimizing the process flow. This paper presents the evaluation findings of these clinical processes, with regards to a critical care information system (CCIS), known as IntelliVue Clinical Information Portfolio (ICIP), and recommends solutions to the problems that were identified during the study. We conducted a case study under actual clinical settings, to investigate how the Lean method can be used to improve the clinical process. We used observations, interviews, and document analysis, to achieve our stated goal. We also applied two tools from the Lean methodology, namely the Value Stream Mapping and the A3 problem-solving tools. We used eVSM software to plot the Value Stream Map and A3 reports. We identified a number of problems related to inefficiency and waste in the clinical process, and proposed an improved process model. The case study findings show that the Value Stream Mapping and the A3 reports can be used as tools to identify waste and integrate the process steps more efficiently. We also proposed a standardized and improved clinical process model and suggested an integrated information system that combines database and software applications to reduce waste and data redundancy.

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...

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…

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.

Secure and Efficient k-NN Queries⋆

PubMed Central

Asif, Hafiz; Vaidya, Jaideep; Shafiq, Basit; Adam, Nabil

2017-01-01

Given the morass of available data, ranking and best match queries are often used to find records of interest. As such, k-NN queries, which give the k closest matches to a query point, are of particular interest, and have many applications. We study this problem in the context of the financial sector, wherein an investment portfolio database is queried for matching portfolios. Given the sensitivity of the information involved, our key contribution is to develop a secure k-NN computation protocol that can enable the computation k-NN queries in a distributed multi-party environment while taking domain semantics into account. The experimental results show that the proposed protocols are extremely efficient. PMID:29218333

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.

Outcomes-Based Authentic Learning, Portfolio Assessment, and a Systems Approach to "Complex Problem-Solving": Related Pillars for Enhancing the Innovative Role of PBL in Future Higher Education

ERIC Educational Resources Information Center

Richards, Cameron

2015-01-01

The challenge of better reconciling individual and collective aspects of innovative problem-solving can be productively addressed to enhance the role of PBL as a key focus of the creative process in future higher education. This should involve "active learning" approaches supported by related processes of teaching, assessment and…

High Tech High.

ERIC Educational Resources Information Center

Hardy, Lawrence

2001-01-01

In an era of high-stakes testing and prescriptive teaching styles, a San Diego charter high school embraces project learning, multilevel classrooms, and video portfolios of student work. The school lacks dining, music, and athletic facilities, but features hefty teacher salaries, student freedom, and real-world problem solving. (MLH)

Postgraduate Orthodontics Students' and Mentors' Perceptions of Portfolios and Discussion as Tools for Development of Reflection.

PubMed

Tonni, Ingrid; Mora, Luca; Oliver, Richard G

2016-09-01

The aim of this study was to analyze the effects of a portfolio learning strategy designed to develop students' reflection abilities in a postgraduate orthodontic program in the UK. Nine first-year postgraduate orthodontic students and seven mentors participated in the one-year program, which included a reflective portfolio, mentorship, and discussion. After the program, the students' and mentors' perceptions were collected using focus groups and individual interviews, respectively. The data were analyzed using thematic analysis. Four categories emerged. The first, reflection, was considered a skill to learn, and time was needed for students to fully understand its meaning and achieve its outcomes. The second theme, characteristics of reflection, was descriptive at the beginning and more critical at the end of the experience. The third theme, outcomes of reflection, involved students' improved problem-solving and action-planning abilities and increased self-awareness, motivation, confidence, and communication skills. In the fourth theme, stimulation of reflection, students did not agree with mentors regarding the importance of reflective writing, but they recognized the value of the portfolio's reflective log in facilitating the reflective process. There was greater agreement between students and mentors regarding discussions with mentors and among peers as tools to achieve higher levels of reflection. Overall, these students and mentors considered the strategy an effective tool for improving students' reflection.

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.

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.

[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.

Preparation for Lifelong Learning Using ePortfolios

ERIC Educational Resources Information Center

Heinrich, E.; Bhattacharya, M.; Rayudu, R.

2007-01-01

Rapid technological change, increasing globalization and a changing world of employment with multiple roles during one's professional life are necessitating a change from knowledge to learning societies. Full participation requires lifelong learning skills, meaning the ability to solve problems, work both independently and in a team, communicate…

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.

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.

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.

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…

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…

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

Using Portfolio Assignments to Assess Students' Mathematical Thinking

ERIC Educational Resources Information Center

Fukawa-Connelly, Timothy; Buck, Stephen

2010-01-01

Writing in mathematics can improve procedural knowledge and communication skills and may also help students better understand and then remember problems. The majority of mathematics teachers know that they ought to include some writing assignments in their instructional plans, but the challenge of covering the curriculum and the time required to…

Engineering Sustainable Solutions Program: Critical Literacies for Engineers Portfolio

ERIC Educational Resources Information Center

Paten, Cheryl J. K.; Palousis, Nicholas; Hargroves, Karlson; Smith, Michael

2005-01-01

Purpose: While a number of universities in Australia have embraced concepts such as project/problem-based learning and design of innovative learning environments for engineering education, there has been a lack of national guidance on including sustainability as a "critical literacy" into all engineering streams. This paper was presented…

E-Portfolios: Making Things E-asy

ERIC Educational Resources Information Center

Waters, John K.

2007-01-01

With test scores dipping, dropout rates spiking, and disciplinary problems multiplying, student motivation was in short supply at Hope High School in East Providence, Rhode Island, when, in 2002, the state commissioner of education stepped in to stop the slide. After months of planning, the state reorganized the school into three smaller,…

Integrity-Based Budgeting

ERIC Educational Resources Information Center

Kaleba, Frank

2008-01-01

The central problem for the facility manager of large portfolios is not the accuracy of data, but rather data integrity. Data integrity means that it's (1) acceptable to the users; (2) based upon an objective source; (3) reproducible; and (4) internally consistent. Manns and Katsinas, in their January/February 2006 Facilities Manager article…

Teacher Perceptions of Electronic Portfolios as a Technology Integration Tool

ERIC Educational Resources Information Center

Blackwell, John P., III.

2013-01-01

This qualitative case study explored the problem that teachers' attitudes and perceptions about technology often serve as barriers to successful technology integration in elementary school classrooms. Trends have showed that technology teachers directly responsible for teaching students technology skills are being laid off due to budget cuts…

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…

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.

Non-native fish control below Glen Canyon Dam - Report from a structured decision-making project

USGS Publications Warehouse

Runge, Michael C.; Bean, Ellen; Smith, David; Kokos, Sonja

2011-01-01

This report describes the results of a structured decision-making project by the U.S. Geological Survey to provide substantive input to the Bureau of Reclamation (Reclamation) for use in the preparation of an Environmental Assessment concerning control of non-native fish below Glen Canyon Dam. A forum was created to allow the diverse cooperating agencies and Tribes to discuss, expand, and articulate their respective values; to develop and evaluate a broad set of potential control alternatives using the best available science; and to define individual preferences of each group on how to manage the inherent trade-offs in this non-native fish control problem. This project consisted of two face-to-face workshops, held in Mesa, Arizona, October 18-20 and November 8-10, 2010. At the first workshop, a diverse set of objectives was discussed, which represented the range of concerns of those agencies and Tribes present. A set of non-native fish control alternatives ('hybrid portfolios') was also developed. Over the 2-week period between the two workshops, four assessment teams worked to evaluate the control alternatives against the array of objectives. At the second workshop, the results of the assessment teams were presented. Multi-criteria decision analysis methods were used to examine the trade-offs inherent in the problem, and allowed the participating agencies and Tribes to express their individual judgments about how those trade-offs should best be managed in Reclamation`s selection of a preferred alternative. A broad array of objectives was identified and defined, and an effort was made to understand how these objectives are likely to be achieved by a variety of strategies. In general, the objectives reflected desired future conditions over 30 years. A rich set of alternative approaches was developed, and the complex structure of those alternatives was documented. Multi-criteria decision analysis methods allowed the evaluation of those alternatives against the array of objectives, with the values of individual agencies and tribes deliberately preserved. Trout removal strategies aimed at the Paria to Badger Rapid reach (PBR), with a variety of permutations in deference to cultural values, and with backup removal at the Little Colorado River reach (LCR) if necessary, were identified as top-ranking portfolios for all agencies and Tribes. These PBR/LCR removal portfolios outperformed LCR-only removal portfolios, for cultural reasons and for effectiveness - the probability of keeping the humpback chub population above a desired threshold was estimated to be higher under the PBR/LCR portfolios than the LCR-only portfolios. The PBR/LCR removal portfolios also outperformed portfolios based on flow manipulations, primarily because of the effect of sport fishery and wilderness recreation objectives, as well as cultural objectives. The preference for the PBR/LCR removal portfolios was quite robust to variation in the objective weights and to uncertainty about the underlying dynamics, at least over the ranges of uncertainty investigated. Examination of the effect of uncertainty on the recommended outcomes allowed us to complete a 'value of information' analysis. The results of this analysis led to an adaptive strategy that includes three possible long-term management actions (no action; LCR removal; or PBR removal) and seeks to reduce uncertainty about the following two issues: the degree to which rainbow trout limit chub populations, and the effectiveness of PBR removal to reduce trout emigration downstream into Marble and eastern Grand Canyons, where the largest population of humpback chub exist. In the face of uncertainty about the effectiveness of PBR removal, a case might be made for including flow manipulations in an adaptive strategy, but formal analysis of this case was not conducted. The full set of conclusions described above is not definitive, however. This analysis described in this report is a simplified depiction of the t

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.

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

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…

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.

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.

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.

Counselor-Mediated Contracts in Self-Management for Students in the New Start Program.

ERIC Educational Resources Information Center

Santa Rita, Emilio D., Jr.

In an effort to help students on academic suspension achieve full academic status and succeed in college, New York's Bronx Community College developed the New Start program, a portfolio-based intervention strategy utilizing personal success contracts. Students participating in the program complete guided self-assessments, identify problem areas,…

The Mindful Worker. Learning and Working into the 21st Century. The Mindful Workforce Portfolio.

ERIC Educational Resources Information Center

Miles, Curtis

This textbook contains information and activities designed to help college students develop the following generalized competencies that are critical to job success and satisfaction in the 21st century: learns; thinks reflectively; manages time; manages stress; sets goals; solves problems; demonstrates interdependence; thinks systematically; solves…

Students' Reflections Using Visualized Learning Outcomes and E-Portfolios

ERIC Educational Resources Information Center

Narumi, Takatsune; Gotoh, Yasushi

2014-01-01

How to guarantee graduate attributes has become an urgent challenge amid the increasing progress in scientific and technological development and the globalization of economic activity. In order to solve these problems, a system is required which can visualize learning outcomes in relation to attainment targets, and store and sample records of the…

Building a Learning Experience: The Implementation of a Clerkship in Geriatric Medicine.

ERIC Educational Resources Information Center

Duque, Gustavo; Bonnycastle, Michael; Nazerali, Najmi; Bailey, Robert; Ferrier, Catherine; Heilpern, Paul; Gold, Susan

2003-01-01

In a mandatory 4-week program, medical students assessed and managed the care of frail elderly with acute medical problems and disabilities. Web-based lectures with pre/posttests and electronic portfolio assessment were included. The experience was intended to promote reflection, interactive learning, and feedback. (Contains 24 references.) (SK)

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.

Condition Number Regularized Covariance Estimation*

PubMed Central

Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala

2012-01-01

Estimation of high-dimensional covariance matrices is known to be a difficult problem, has many applications, and is of current interest to the larger statistics community. In many applications including so-called the “large p small n” setting, the estimate of the covariance matrix is required to be not only invertible, but also well-conditioned. Although many regularization schemes attempt to do this, none of them address the ill-conditioning problem directly. In this paper, we propose a maximum likelihood approach, with the direct goal of obtaining a well-conditioned estimator. No sparsity assumption on either the covariance matrix or its inverse are are imposed, thus making our procedure more widely applicable. We demonstrate that the proposed regularization scheme is computationally efficient, yields a type of Steinian shrinkage estimator, and has a natural Bayesian interpretation. We investigate the theoretical properties of the regularized covariance estimator comprehensively, including its regularization path, and proceed to develop an approach that adaptively determines the level of regularization that is required. Finally, we demonstrate the performance of the regularized estimator in decision-theoretic comparisons and in the financial portfolio optimization setting. The proposed approach has desirable properties, and can serve as a competitive procedure, especially when the sample size is small and when a well-conditioned estimator is required. PMID:23730197

Condition Number Regularized Covariance Estimation.

PubMed

Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala

2013-06-01

Estimation of high-dimensional covariance matrices is known to be a difficult problem, has many applications, and is of current interest to the larger statistics community. In many applications including so-called the "large p small n " setting, the estimate of the covariance matrix is required to be not only invertible, but also well-conditioned. Although many regularization schemes attempt to do this, none of them address the ill-conditioning problem directly. In this paper, we propose a maximum likelihood approach, with the direct goal of obtaining a well-conditioned estimator. No sparsity assumption on either the covariance matrix or its inverse are are imposed, thus making our procedure more widely applicable. We demonstrate that the proposed regularization scheme is computationally efficient, yields a type of Steinian shrinkage estimator, and has a natural Bayesian interpretation. We investigate the theoretical properties of the regularized covariance estimator comprehensively, including its regularization path, and proceed to develop an approach that adaptively determines the level of regularization that is required. Finally, we demonstrate the performance of the regularized estimator in decision-theoretic comparisons and in the financial portfolio optimization setting. The proposed approach has desirable properties, and can serve as a competitive procedure, especially when the sample size is small and when a well-conditioned estimator is required.

Economic optimization of natural hazard protection - conceptual study of existing approaches

NASA Astrophysics Data System (ADS)

Spackova, Olga; Straub, Daniel

2013-04-01

Risk-based planning of protection measures against natural hazards has become a common practice in many countries. The selection procedure aims at identifying an economically efficient strategy with regard to the estimated costs and risk (i.e. expected damage). A correct setting of the evaluation methodology and decision criteria should ensure an optimal selection of the portfolio of risk protection measures under a limited state budget. To demonstrate the efficiency of investments, indicators such as Benefit-Cost Ratio (BCR), Marginal Costs (MC) or Net Present Value (NPV) are commonly used. However, the methodologies for efficiency evaluation differ amongst different countries and different hazard types (floods, earthquakes etc.). Additionally, several inconsistencies can be found in the applications of the indicators in practice. This is likely to lead to a suboptimal selection of the protection strategies. This study provides a general formulation for optimization of the natural hazard protection measures from a socio-economic perspective. It assumes that all costs and risks can be expressed in monetary values. The study regards the problem as a discrete hierarchical optimization, where the state level sets the criteria and constraints, while the actual optimization is made on the regional level (towns, catchments) when designing particular protection measures and selecting the optimal protection level. The study shows that in case of an unlimited budget, the task is quite trivial, as it is sufficient to optimize the protection measures in individual regions independently (by minimizing the sum of risk and cost). However, if the budget is limited, the need for an optimal allocation of resources amongst the regions arises. To ensure this, minimum values of BCR or MC can be required by the state, which must be achieved in each region. The study investigates the meaning of these indicators in the optimization task at the conceptual level and compares their suitability. To illustrate the theoretical findings, the indicators are tested on a hypothetical example of five regions with different risk levels. Last but not least, political and societal aspects and limitations in the use of the risk-based optimization framework are discussed.

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.

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

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.

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.

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.…

12 CFR 347.108 - Portfolio investments.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 4 2010-01-01 2010-01-01 false Portfolio investments. 347.108 Section 347.108... INTERNATIONAL BANKING § 347.108 Portfolio investments. (a) Portfolio investments. If a bank, directly or indirectly, acquires or holds an equity interest in a foreign organization as a portfolio investment and the...

12 CFR 347.108 - Portfolio investments.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 12 Banks and Banking 4 2011-01-01 2011-01-01 false Portfolio investments. 347.108 Section 347.108... INTERNATIONAL BANKING § 347.108 Portfolio investments. (a) Portfolio investments. If a bank, directly or indirectly, acquires or holds an equity interest in a foreign organization as a portfolio investment and the...

Implementation of Portfolio Assessment in a Competency-based Dental Hygiene Program.

ERIC Educational Resources Information Center

Gadbury-Amyot, Cynthia C.; Holt, Lorie P.; Overman, Pamela R.; Schmidt, Colleen R.

2000-01-01

Describes the implementation of a portfolio assessment program in the dental hygiene program at the University of Missouri School of Dentistry. Tables provide examples of program competencies and related portfolio entries, the complete scoring rubric for portfolios, and the student portfolio evaluation survey. Concludes that although portfolio…

Assessment and Assurance of Learning Using E-Portfolios

ERIC Educational Resources Information Center

Papp, Raymond

2014-01-01

Traditional paper portfolios have been used to assess student work for performance and employment purposes for decades. The advent of electronic portfolios incorporating audio, video, hyperlinked documents and scanned images takes the use of portfolios to a new level. Evaluators can use these easily accessible portfolios to gauge student…

12 CFR 1252.1 - Enterprise portfolio holding criteria.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Enterprise portfolio holding criteria. 1252.1 Section 1252.1 Banks and Banking FEDERAL HOUSING FINANCE AGENCY ENTERPRISES PORTFOLIO HOLDINGS § 1252.1 Enterprise portfolio holding criteria. The Enterprises are required to comply with the portfolio holdings...

A Mean variance analysis of arbitrage portfolios

NASA Astrophysics Data System (ADS)

Fang, Shuhong

2007-03-01

Based on the careful analysis of the definition of arbitrage portfolio and its return, the author presents a mean-variance analysis of the return of arbitrage portfolios, which implies that Korkie and Turtle's results ( B. Korkie, H.J. Turtle, A mean-variance analysis of self-financing portfolios, Manage. Sci. 48 (2002) 427-443) are misleading. A practical example is given to show the difference between the arbitrage portfolio frontier and the usual portfolio frontier.

Universal portfolios generated by the Bregman divergence

NASA Astrophysics Data System (ADS)

Tan, Choon Peng; Kuang, Kee Seng

2017-04-01

The Bregman divergence of two probability vectors is a stronger form of the f-divergence introduced by Csiszar. Two versions of the Bregman universal portfolio are presented by exploiting the mean-value theorem. The explicit form of the Bregman universal portfolio generated by a function of a convex polynomial is derived and studied empirically. This portfolio can be regarded as another generalized of the well-known Helmbold portfolio. By running the portfolios on selected stock-price data sets from the local stock exchange, it is shown that it is possible to increase the wealth of the investor by using the portfolios in investment.

Implementing portfolio in postgraduate general practice training. Benefits and recommendations.

PubMed

Alotaibi, Fawaz S

2012-10-01

This paper presents a review to explore the literature focusing on portfolio in postgraduate general practice (GP) training, and to examine the impact of implementation of portfolio on learning process, as well as proposing recommendations for its implementation in postgraduate GP training. An electronic search was carried out on several databases for studies addressing portfolio in postgraduate GP training. Six articles were included to address specifically the effectiveness of portfolio in postgraduate GP training. Five of them described successful experiences of portfolio-based learning implementation. Only one article addressed portfolio-based assessment in postgraduate GP training. The existing evidence provides various benefits of professional portfolio-based learning. It does appear to have advantages of stimulating reflective learning, promoting proactive learning, and bridging the hospital experiences of the learners to GP. Moreover, the challenges to implementation of portfolio-based learning are often based on orientation and training of stakeholders.

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.

Evaluation of an established learning portfolio.

PubMed

Vance, Gillian; Williamson, Alyson; Frearson, Richard; O'Connor, Nicole; Davison, John; Steele, Craig; Burford, Bryan

2013-02-01

The trainee-held learning portfolio is integral to the foundation programme in the UK. In the Northern Deanery, portfolio assessment is standardised through the Annual Review of Competence Progression (ARCP) process. In this study we aimed to establish how current trainees evaluate portfolio-based learning and ARCP, and how these attitudes may have changed since the foundation programme was first introduced. Deanery-wide trainee attitudes were surveyed by an electronic questionnaire in 2009 and compared with perceptions recorded during the pilot phase (2004-2005).  Many trainees continue to view the e-portfolio negatively. Indeed, significantly fewer trainees in 2009 thought that the e-portfolio was a 'good idea' or a 'worthwhile investment of time' than in 2005. Trainees remain unconvinced about the educational value of the e-portfolio: fewer trainees in 2009 regarded it as a tool that might help focus on training or recognise individual strengths and weaknesses. Issues around unnecessary bureaucracy persist. Current trainees tend to understand how to use the e-portfolio, but many did not know how much, or what evidence to collect. Few supervisors were reported to provide useful guidance on the portfolio. ARCP encouraged portfolio completion but did not give meaningful feedback to drive future learning.   Continued support is needed for both trainees and supervisors in portfolio-building skills and in using the e-portfolio as an educational tool. Trainee-tailored feedback is needed to ensure that portfolio-based assessment promotes lifelong, self-directed and reflective learners. © Blackwell Publishing Ltd 2013.

Application of portfolio theory to risk-based allocation of surveillance resources in animal populations.

PubMed

Prattley, D J; Morris, R S; Stevenson, M A; Thornton, R

2007-09-14

Distribution of finite levels of resources between multiple competing tasks can be a challenging problem. Resources need to be distributed across time periods and geographic locations to increase the probability of detection of a disease incursion or significant change in disease pattern. Efforts should focus primarily on areas and populations where risk factors for a given disease reach relatively high levels. In order to target resources into these areas, the overall risk level can be evaluated periodically across locations to create a dynamic national risk landscape. Methods are described to integrate the levels of various risk factors into an overall risk score for each area, to account for the certainty or variability around those measures and then to allocate surveillance resources across this risk landscape. In addition to targeting resources into high risk areas, surveillance continues in lower risk areas where there is a small yet positive chance of disease occurrence. In this paper we describe the application of portfolio theory concepts, routinely used in finance, to design surveillance portfolios for a series of examples. The appropriate level of resource investment is chosen for each disease or geographical area and time period given the degree of disease risk and uncertainty present.

Integrated Building Energy Systems Design Considering Storage Technologies

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

Stadler, Michael; Marnay, Chris; Siddiqui, Afzal

The addition of storage technologies such as flow batteries, conventional batteries, and heat storage can improve the economic, as well as environmental attraction of micro-generation systems (e.g., PV or fuel cells with or without CHP) and contribute to enhanced demand response. The interactions among PV, solar thermal, and storage systems can be complex, depending on the tariff structure, load profile, etc. In order to examine the impact of storage technologies on demand response and CO2 emissions, a microgrid's distributed energy resources (DER) adoption problem is formulated as a mixed-integer linear program that can pursue two strategies as its objective function.more » These two strategies are minimization of its annual energy costs or of its CO2 emissions. The problem is solved for a given test year at representative customer sites, e.g., nursing homes, to obtain not only the optimal investment portfolio, but also the optimal hourly operating schedules for the selected technologies. This paper focuses on analysis of storage technologies in micro-generation optimization on a building level, with example applications in New York State and California. It shows results from a two-year research projectperformed for the U.S. Department of Energy and ongoing work. Contrary to established expectations, our results indicate that PV and electric storage adoption compete rather than supplement each other considering the tariff structure and costs of electricity supply. The work shows that high electricity tariffs during on-peak hours are a significant driver for the adoption of electric storage technologies. To satisfy the site's objective of minimizing energy costs, the batteries have to be charged by grid power during off-peak hours instead of PV during on-peak hours. In contrast, we also show a CO2 minimization strategy where the common assumption that batteries can be charged by PV can be fulfilled at extraordinarily high energy costs for the site.« less

Advances in Optimizing Weather Driven Electric Power Systems.

NASA Astrophysics Data System (ADS)

Clack, C.; MacDonald, A. E.; Alexander, A.; Dunbar, A. D.; Xie, Y.; Wilczak, J. M.

2014-12-01

The importance of weather-driven renewable energies for the United States (and global) energy portfolio is growing. The main perceived problems with weather-driven renewable energies are their intermittent nature, low power density, and high costs. The National Energy with Weather System Simulator (NEWS) is a mathematical optimization tool that allows the construction of weather-driven energy sources that will work in harmony with the needs of the system. For example, it will match the electric load, reduce variability, decrease costs, and abate carbon emissions. One important test run included existing US carbon-free power sources, natural gas power when needed, and a High Voltage Direct Current power transmission network. This study shows that the costs and carbon emissions from an optimally designed national system decrease with geographic size. It shows that with achievable estimates of wind and solar generation costs, that the US could decrease its carbon emissions by up to 80% by the early 2030s, without an increase in electric costs. The key requirement would be a 48 state network of HVDC transmission, creating a national market for electricity not possible in the current AC grid. These results were found without the need for storage. Further, we tested the effect of changing natural gas fuel prices on the optimal configuration of the national electric power system. Another test that was carried out was an extension to global regions. The extension study shows that the same properties found in the US study extend to the most populous regions of the planet. The extra test is a simplified version of the US study, and is where much more research can be carried out. We compare our results to other model results.

Evaluating Portfolio Use as a Learning Tool for Professionals.

ERIC Educational Resources Information Center

Smith, Kari; Tillema, Harm

1998-01-01

Studies of portfolio construction and compilation involving 35 Israeli principals and 14 Dutch managers show that high-quality portfolios can only be expected after sustained use, but that the use of portfolios has an immediate impact on views toward assessment. Portfolios are time-consuming, but can provide effective feedback to the learner. (SLD)

Exploring the Role of Assessment Criteria during Teachers' Collaborative Judgement Processes of Students' Portfolios

ERIC Educational Resources Information Center

Van der Schaaf, Marieke; Baartman, Liesbeth; Prins, Frans

2012-01-01

Student portfolios are increasingly used for assessing student competences in higher education, but results about the construct validity of portfolio assessment are mixed. A prerequisite for construct validity is that the portfolio assessment is based on relevant portfolio content. Assessment criteria, are often used to enhance this condition.…

Portfolio Assessment: A Handbook for Educators. Assessment Bookshelf Series.

ERIC Educational Resources Information Center

Barton, James, Ed.; Collins, Angelo, Ed.

This guide contains practical steps for integrating portfolios into any K-12 classroom and tips for effective classroom management of portfolios. It also contains actual examples of portfolios in action in a variety of subject areas. The chapters are: (1) "Starting Out: Designing Your Portfolio" (James Barton and Angelo Collins); (2) "Preparing…

12 CFR 702.104 - Risk portfolios defined.

Code of Federal Regulations, 2011 CFR

2011-01-01

... CORRECTIVE ACTION Net Worth Classification § 702.104 Risk portfolios defined. A risk portfolio is a portfolio... 12 Banks and Banking 6 2011-01-01 2011-01-01 false Risk portfolios defined. 702.104 Section 702... or mature within the next five (5) years, and exclusive of all member business loans (as defined in...

Fellows' Perceptions of a Mandatory Reflective Electronic Portfolio in a Geriatric Medicine Fellowship Program

ERIC Educational Resources Information Center

Ruiz, Jorge G.; Qadri, Syeda S.; Karides, Marina; Castillo, Carmen; Milanez, Marcos; Roos, Bernard A.

2009-01-01

Electronic portfolios (ePortfolios) can be useful for evaluating and documenting mastery of competencies. We investigated geriatric medicine fellows' perceptions of an ePortfolio. We conducted surveys and focus groups followed by quantitative and qualitative data analysis. Our study revealed that fellows considered the ePortfolio acceptable and…

The Bottomless File Box: Electronic Portfolios for Learning and Evaluation Purposes

ERIC Educational Resources Information Center

Jarrott, Shannon; Gambrel, Laura Eubanks

2011-01-01

Portfolios have been used for the past three decades in higher education for assessment of student competency and also as a reflection tool to assist student learning. Electronic portfolios, or ePortfolios, have additional benefits compared to paper portfolios in that they are easily accessible, portable, and sharable, and they are more…

Creating a Living Portfolio: Documenting Student Growth with Electronic Portfolios.

ERIC Educational Resources Information Center

Siegle, Del

2002-01-01

This article explains how teachers can use electronic portfolios of students' work to document learner progress. It considers different file formats for storing student work, describes steps to creating an electronic portfolio, and discusses an art and literature electronic magazine created by one school featuring work from student portfolios. (CR)

17 CFR 270.17a-6 - Exemption for transactions with portfolio affiliates.

Code of Federal Regulations, 2010 CFR

2010-04-01

... with portfolio affiliates. 270.17a-6 Section 270.17a-6 Commodity and Securities Exchanges SECURITIES... Exemption for transactions with portfolio affiliates. (a) Exemption for transactions with portfolio affiliates. A transaction to which a fund, or a company controlled by a fund, and a portfolio affiliate of...

Preparedness Portfolios and Portfolio Studios: Supporting Self-Authoring Engineers

ERIC Educational Resources Information Center

Sattler, Brook; Turns, Jennifer

2015-01-01

In this work, we engaged engineering undergraduate students in constructing an ePortfolio. The purpose of the research presented here was to explore the question, "If and in what ways do students report experiencing the construction of a preparedness portfolio in a portfolio studio as an opportunity to develop into self-authoring…

Portfolio assessment during medical internships: How to obtain a reliable and feasible assessment procedure?

PubMed

Michels, Nele R M; Driessen, Erik W; Muijtjens, Arno M M; Van Gaal, Luc F; Bossaert, Leo L; De Winter, Benedicte Y

2009-12-01

A portfolio is used to mentor and assess students' clinical performance at the workplace. However, students and raters often perceive the portfolio as a time-consuming instrument. In this study, we investigated whether assessment during medical internship by a portfolio can combine reliability and feasibility. The domain-oriented reliability of 61 double-rated portfolios was measured, using a generalisability analysis with portfolio tasks and raters as sources of variation in measuring the performance of a student. We obtained reliability (Phi coefficient) of 0.87 with this internship portfolio containing 15 double-rated tasks. The generalisability analysis showed that an acceptable level of reliability (Phi = 0.80) was maintained when the amount of portfolio tasks was decreased to 13 or 9 using one and two raters, respectively. Our study shows that a portfolio can be a reliable method for the assessment of workplace learning. The possibility of reducing the amount of tasks or raters while maintaining a sufficient level of reliability suggests an increase in feasibility of portfolio use for both students and raters.

Using portfolios for clinical practice learning and assessment: the pre-registration nursing student's perspective.

PubMed

McMullan, Miriam

2008-10-01

Portfolios have been introduced to help to integrate theory and practice and thereby address the issue of the theory-practice divide. Although there has been much theoretical discussion about portfolio use in clinical placements, few studies have focused on the students' perceptions regarding their use. To obtain adult branch pre-registration nursing students' perspectives on using portfolios for their clinical practice learning and assessment, postal questionnaires were sent to 253 diploma of nursing students with a reminder to all students three weeks later. The response rate was 69% (174/253). This paper reports on the qualitative findings of the study, which employed both quantitative and qualitative methods. Although students stated that portfolios helped them in their development of self-awareness and independent learning, they indicated that portfolios do not sufficiently address the assessment of their clinical skills and the integration of theory and practice. They considered that portfolios could be greatly improved in three areas, namely in the conflict between using portfolios for both assessment and learning, the amount of support and guidance students feel they receive with their portfolio use and the portfolio design.

Application of the ultrametric distance to portfolio taxonomy. Critical approach and comparison with other methods

NASA Astrophysics Data System (ADS)

Skórnik-Pokarowska, Urszula; Orłowski, Arkadiusz

2004-12-01

We calculate the ultrametric distance between the pairs of stocks that belong to the same portfolio. The ultrametric distance allows us to distinguish groups of shares that are related. In this way, we can construct a portfolio taxonomy that can be used for constructing an efficient portfolio. We also construct a portfolio taxonomy based not only on stock prices but also on economic indices such as liquidity ratio, debt ratio and sales profitability ratio. We show that a good investment strategy can be obtained by applying to the portfolio chosen by the taxonomy method the so-called Constant Rebalanced Portfolio.

Examiner perceptions of a portfolio assessment process.

PubMed

Davis, Margery H; Ponnamperuma, Gominda G

2010-01-01

The portfolio assessment process is important for assessing learner achievement. To study examiner perceptions of Dundee Medical School's portfolio assessment process, in years 4 and 5 of the 5-year curriculum, in relation to: outcomes as a framework for the portfolio assessment process; portfolio content; portfolio assessment process; end points of the portfolio assessment process; appropriateness of the two part final exam format and examiner training. A questionnaire containing statements and open questions was used to obtain examiner feedback. Responses to each statement were compared over 3 years: 1999, 2000 and 2003. Response rates were 100%, 88% and 61% in 1999, 2002 and 2003, respectively. Examiners were positive about the ability of institutionally set learning outcomes (Dundee 12 exit learning outcomes) to provide a framework for the portfolio assessment process. They found difficulties, however, with the volume of portfolio content and the time allocated to assess it. Agreeing a grade for each learning outcome for the candidate with their co-examiner did not present difficulties. The comprehensive, holistic picture of the candidate provided by the portfolio assessment process was perceived to be one of its strengths. Examiners were supportive of the final examination format, and were satisfied with their briefing about the process. The 12 exit learning outcomes of Dundee curriculum provide an appropriate framework for the portfolio assessment process, but the content of the portfolio requires fine-tuning particularly with regard to quantity. Time allocated to examiners for the portfolio assessment process needs to be balanced against practicability. The holistic picture of the candidate provided by the process was one of its strengths.

Electronic Portfolios as Living Portals: A Narrative Inquiry into College Student Learning, Identity, and Assessment

ERIC Educational Resources Information Center

Nguyen, Celeste Fowles

2013-01-01

As universities increasingly utilize electronic portfolios, college students are asked more than ever to create ePortfolios for academics, assessment, or advising. This study shifts an analysis of ePortfolios from prior epistemological approaches, where ePortfolios have been explored as a tool to measure student progress, onto an ontological…

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…

12 CFR 225.171 - What are the limitations on managing or operating a portfolio company held as a merchant banking...

Code of Federal Regulations, 2013 CFR

2013-01-01

... banking investment? (a) May a financial holding company routinely manage or operate a portfolio company... manage or operate any portfolio company. (b) When does a financial holding company routinely manage or... portfolio company. A financial holding company routinely manages or operates a portfolio company if any...

12 CFR 225.171 - What are the limitations on managing or operating a portfolio company held as a merchant banking...

Code of Federal Regulations, 2014 CFR

2014-01-01

... banking investment? (a) May a financial holding company routinely manage or operate a portfolio company... manage or operate any portfolio company. (b) When does a financial holding company routinely manage or... portfolio company. A financial holding company routinely manages or operates a portfolio company if any...

ePortfolios and Interdisciplinary Adult Degree Programs

ERIC Educational Resources Information Center

Bryant, Layne Ray; Rust, Dianna Zeh; Fox-Horton, Julie; Johnson, Amy Denise

2017-01-01

This article discusses the use of ePortfolios in interdisciplinary online adult degree programs at two universities. Whereas one university uses the ePortfolio only in a capstone course, the other institution introduces the ePortfolio in an introductory course that focuses on goal setting and then has students add content to the ePortfolio in the…

E-Portfolio, a Valuable Job Search Tool for College Students

ERIC Educational Resources Information Center

Yu, Ti

2012-01-01

Purpose: The purpose of this paper is to find answers to the following questions: How do employers think about e-portfolios? Do employers really see e-portfolios as a suitable hiring tool? Which factors in students' e-portfolios attract potential employers? Can e-portfolios be successfully used by students in their search for a job?…

Using Facebook-Based e-Portfolio in ESL Writing Classrooms: Impact and Challenges

ERIC Educational Resources Information Center

Barrot, Jessie S.

2016-01-01

In English as a second language (ESL) writing pedagogy, much attention has been given to electronic portfolio (e-portfolio) assessment via social networking sites. However, little is known about how Facebook can be used as an e-portfolio platform. Hence, this paper describes the impact of Facebook-based e-portfolio on ESL students' writing…

Adapting to a Changing Colorado River: Making Future Water Deliveries More Reliable Through Robust Management Strategies

NASA Astrophysics Data System (ADS)

Groves, D.; Bloom, E.; Fischbach, J. R.; Knopman, D.

2013-12-01

The U.S. Bureau of Reclamation and water management agencies representing the seven Colorado River Basin States initiated the Colorado River Basin Study in January 2010 to evaluate the resiliency of the Colorado River system over the next 50 years and compare different options for ensuring successful management of the river's resources. RAND was asked to join this Basin Study Team in January 2012 to help develop an analytic approach to identify key vulnerabilities in managing the Colorado River basin over the coming decades and to evaluate different options that could reduce this vulnerability. Using a quantitative approach for planning under uncertainty called Robust Decision Making (RDM), the RAND team assisted the Basin Study by: identifying future vulnerable conditions that could lead to imbalances that could cause the basin to be unable to meet its water delivery objectives; developing a computer-based tool to define 'portfolios' of management options reflecting different strategies for reducing basin imbalances; evaluating these portfolios across thousands of future scenarios to determine how much they could improve basin outcomes; and analyzing the results from the system simulations to identify key tradeoffs among the portfolios. This talk will describe RAND's contribution to the Basin Study, focusing on the methodologies used to to identify vulnerabilities for Upper Basin and Lower Basin water supply reliability and to compare portfolios of options. Several key findings emerged from the study. Future Streamflow and Climate Conditions Are Key: - Vulnerable conditions arise in a majority of scenarios where streamflows are lower than historical averages and where drought conditions persist for eight years or more. - Depending where the shortages occur, problems will arise for delivery obligations for the upper river basin and the lower river basin. The lower river basin is vulnerable to a broader range of plausible future conditions. Additional Investments in Infrastructure and Efficiency Could Improve Performance and Reduce Risk: - Different portfolios of water-supply and demand-reduction options offer performance trade-offs. - Different types of options in the portfolios, such as conservation, desalination, or water banking, would affect future outcomes and costs of implementation. - Analysis of all the portfolios identified important near-term, high-priority options that should be implemented in the near future, including municipal, industrial, and agricultural conservation. Other Solutions May Be Required: - If future hydrologic conditions develop in a manner consistent with the more pessimistic projections, the Basin is increasingly likely to face vulnerable conditions. The region may need to consider additional management options.

Fifteen years of portfolio assessment of dental hygiene student competency: lessons learned.

PubMed

Gadbury-Amyot, Cynthia C; Bray, Kimberly Krust; Austin, Kylie J

2014-10-01

Adoption of portfolio assessment in the educational environment is gaining attention as a means to incorporate self-assessment into the curriculum and to use evidence to support learning outcomes and to demonstrate competency. Portfolios provide a medium for students to demonstrate and document their personal and professional growth across the curriculum. The purpose of this literature review is to discuss the drivers for portfolio education, the benefits to both students and program faculty/administrators, the barriers associated with portfolio use, and suggested solutions that have been determined through several years of "lessons learned." The University of Missouri Kansas City School of Dentistry, Division of Dental Hygiene department has been utilizing portfolio assessment for over 15 years and has collected data related to portfolio performance since 2001. Results from correlational statistics calculated on the 312 dental hygiene students that graduated from 2001 to 2013 demonstrate a positive and significant relationship between portfolio performance and overall GPA as well as portfolio performance and NBDHE scores. Copyright © 2014 The American Dental Hygienists’ Association.

Achieving a Prioritized Research and Technology Development Portfolio for the Dust Management Project

NASA Technical Reports Server (NTRS)

Hyatt, Mark J.; Abel, Phillip; Delaune, Paul; Fishman, Julianna; Kohli, Rajiv

2009-01-01

Mission architectures for human exploration of the lunar surface continue to advance as well as the definitions of capability needs, best practices and engineering design to mitigate the impact of lunar dust on exposed systems. The NASA DMP has been established as the agency focal point for dust characterization, technology, and simulant development. As described in this paper, the DMP has defined a process for selecting and justifying its R&T portfolio. The technology prioritization process, which is based on a ranking system according to weighted criteria, has been successfully applied to the current DMP dust mitigation technology portfolio. Several key findings emerged from this assessment. Within the dust removal and cleaning technologies group, there are critical technical challenges that must be overcome for these technologies to be implemented for lunar applications. For example, an in-situ source of CO2 on the moon is essential to the CO2 shower technology. Also, significant development effort is required to achieve technology readiness level TRL 6 for the electrostatic cleaning system for removal of particles smaller than 50 pm. The baseline materials related technologies require considerable development just to achieve TRL 6. It is also a nontrivial effort to integrate the materials in hardware for lunar application. At present, there are no terrestrial applications that are readily adaptable to lunar surface applications nor are there any obvious leading candidates. The unique requirements of dust sealing systems for lunar applications suggest an extensive development effort will be necessary to mature dust sealing systems to TRL 6 and beyond. As discussed here, several alternate materials and technologies have achieved high levels of maturity for terrestrial applications and warrant due diligence in ongoing assessment of the technology portfolio. The present assessment is the initial step in an ongoing effort to continually evaluate the DMP technology portfolio and external non-NASA relevant technology developments efforts to maintain an optimal investment profile. At the same time, there is an ongoing review of agency-wide dust-related R&T activities. The results of these ongoing assessments will be reported in future publications.

Teaching vs. Research: An Approach to Understanding Graduate Students' Roles through ePortfolio Reflection

ERIC Educational Resources Information Center

Svyantek, Martina V.; Kajfez, Rachel L.; McNair, Lisa D.

2015-01-01

In this work, we examined the problem of preparing future faculty (graduate students) regarding their development in multiple roles, focusing on students in science and engineering disciplines. The purpose of the presented research was to address the questions, "Do graduate students believe that their current experiences align with the roles…

"Send Me in, Coach!" Ruminations on the Ethics of Mentoring in Teaching and Research

ERIC Educational Resources Information Center

Shulman, Lee S.

2008-01-01

The author begins with an extended account of the manner in which popular accounts treat the topic of mentoring or coaching. This treatment is contrasted with the problems of coaching described in other articles in this issue, especially in connection to the National Board portfolio assessment. The distinction between "mediated" and "unmediated"…

A Novel Approach for Assisting Teachers in Analyzing Student Web-Searching Behaviors

ERIC Educational Resources Information Center

Hwang, G. J.; Tsai, P. S.; Tsai, C. C.; Tseng, J. C. R.

2008-01-01

Although previous research has demonstrated the benefits of applying the Internet facilities to the learning process, problems with this strategy have also been identified. One of the major difficulties is owing to the lack of an online learning environment that can record the learning portfolio of using the Internet facilities in education, such…

Who Governs Now? Takeovers, Portfolios, and School District Governance. Working Paper #52

ERIC Educational Resources Information Center

Mason, Mary L.; Reckhow, Sarah

2016-01-01

State takeovers were an infrequently applied strategy to address the problems of financially and academically troubled schools for many decades. Although 23 states had the right to take over individual schools and No Child Left Behind (NCLB) required states to address persistently low-achieving schools, only five states had exercised their power…

Statistical Forecasting of Bankruptcy of Defense Contractors. Problems and Prospects

DTIC Science & Technology

1994-01-01

investors is along the lines of the Capital Asset Pricing Model ( CAPM ). In portfolio theory generally, investors demand an expected-return premium for...Ellen Pint, Rachel Schmidt, and especially Dennis Smallwood of RAND also contributed useful insights and comments. xv Acronyms CAPM Capital Asset ...Bond Yields ............................................. 26 Bond Model Performance ................................. 27 Extensions and Limitations

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.

Validity of portfolio assessment: which qualities determine ratings?

PubMed

Driessen, Erik W; Overeem, Karlijn; van Tartwijk, Jan; van der Vleuten, Cees P M; Muijtjens, Arno M M

2006-09-01

The portfolio is becoming increasingly accepted as a valuable tool for learning and assessment. The validity of portfolio assessment, however, may suffer from bias due to irrelevant qualities, such as lay-out and writing style. We examined the possible effects of such qualities in a portfolio programme aimed at stimulating Year 1 medical students to reflect on their professional and personal development. In later curricular years, this portfolio is also used to judge clinical competence. We developed an instrument, the Portfolio Analysis Scoring Inventory, to examine the impact of form and content aspects on portfolio assessment. The Inventory consists of 15 items derived from interviews with experienced mentors, the literature, and the criteria for reflective competence used in the regular portfolio assessment procedure. Forty portfolios, selected from 231 portfolios for which ratings from the regular assessment procedure were available, were rated by 2 researchers, independently, using the Inventory. Regression analysis was used to estimate the correlation between the ratings from the regular assessment and those resulting from the Inventory items. Inter-rater agreement ranged from 0.46 to 0.87. The strongest predictor of the variance in the regular ratings was 'quality of reflection' (R 0.80; R2 66%). No further items accounted for a significant proportion of variance. Irrelevant items, such as writing style and lay-out, had negligible effects. The absence of an impact of irrelevant criteria appears to support the validity of the portfolio assessment procedure. Further studies should examine the portfolio's validity for the assessment of clinical competence.

Best evidence on the educational effects of undergraduate portfolios.

PubMed

Buckley, Sharon; Coleman, Jamie; Khan, Khalid

2010-09-01

The great variety of portfolio types and schemes used in the education of health professionals is reflected in the extensive and diverse educational literature relating to portfolio use. We have recently completed a Best Evidence Medical Education (BEME) systematic review of the literature relating to the use of portfolios in the undergraduate setting that offers clinical teachers insights into both their effects on learning and issues to consider in portfolio implementation. Using a methodology based on BEME recommendations, we searched the literature relating to a range of health professions, identifying evidence for the effects of portfolios on undergraduate student learning, and assessing the methodological quality of each study. The higher quality studies in our review report that, when implemented appropriately, portfolios can improve students' ability to integrate theory with practice, can encourage their self-awareness and reflection, and can offer support for students facing difficult emotional situations. Portfolios can also enhance student-tutor relationships and prepare students for the rigours of postgraduate training. However, the time required to complete a portfolio may detract from students' clinical learning. An analysis of methodological quality against year of publication suggests that, across a range of health professions, the quality of the literature relating to the educational effects of portfolios is improving. However, further work is still required to build the evidence base for the educational effects of portfolios, particularly comparative studies that assess effects on learning directly. Our findings have implications for the design and implementation of portfolios in the undergraduate setting. © Blackwell Publishing Ltd 2010.

Empirical performance of the multivariate normal universal portfolio

NASA Astrophysics Data System (ADS)

Tan, Choon Peng; Pang, Sook Theng

2013-09-01

Universal portfolios generated by the multivariate normal distribution are studied with emphasis on the case where variables are dependent, namely, the covariance matrix is not diagonal. The moving-order multivariate normal universal portfolio requires very long implementation time and large computer memory in its implementation. With the objective of reducing memory and implementation time, the finite-order universal portfolio is introduced. Some stock-price data sets are selected from the local stock exchange and the finite-order universal portfolio is run on the data sets, for small finite order. Empirically, it is shown that the portfolio can outperform the moving-order Dirichlet universal portfolio of Cover and Ordentlich[2] for certain parameters in the selected data sets.

Optimal Management of DoD Lands for Military Training, Ecosystem Services, and Renewable Energy Generation: Framework and Data Requirements

DTIC Science & Technology

2013-01-01

by at least 25% by 2025. To achieve this ambitious goal, DoD is considering a diverse energy portfolio that includes wind , solar, geothermal...generated power (bioenergy). wind , solar, and bioenergy sources each have significant land-management implications, so this third land-use re- quirement...production, the adverse impacts of conflicting requirements can be minimized. The regional differences in wind , solar, and bioenergy potential

The Dilemma for USSOCOM: Transitioning SOF-Peculiar to Service-Common

DTIC Science & Technology

2012-02-15

suggests a lack of “ advertising ”, i.e. the need for a clearing house of ideas. General Haase’s brief suggested the DoD did not have a defined...of debate. Still another avenue is the Capability Portfolio Management ( CPM ) system which seeks to optimize capability investments across the...defense enterprise.59 Though CPMs are charged to identify issues, priorities, and capability and resources mismatches, they have no independent decision

The Dilemma for USSOCOM: Transitioning SOF-Peculiar to Service-Common

DTIC Science & Technology

2012-02-15

Operations-peculiar (SO-peculiar or SOF-peculiar) to Service-common, while the third implication suggests a lack of “ advertising ”, i.e. the need for a...Portfolio Management ( CPM ) system which seeks to optimize capability investments across the defense enterprise.59 Though CPMs are charged to identify...capabilities as Service-common. Collectively though they do offer several avenues in which SOCOM can “ advertise ” them, and whereby through mutual

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

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.…

Remake/Remodel: Using ePortfolios and a System of Gates to Improve Student Assessment and Program Evaluation

ERIC Educational Resources Information Center

Lowenthal, Patrick; White, John W.; Cooley, Karen

2011-01-01

Electronic portfolios have become increasingly popular. The value of a portfolio, though, depends on how, when, and why students create, submit, and have their portfolios evaluated. In the following paper, we describe how we redesigned a program's assessment and evaluation plan around the use of electronic portfolios and a system of gates focusing…

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.

Students' perceptions of the use of eportfolios in nursing and midwifery education.

PubMed

Birks, Melanie; Hartin, Peter; Woods, Cindy; Emmanuel, Elizabeth; Hitchins, Marnie

2016-05-01

ePortfolios have been introduced into many higher education degrees in the past decade in an effort to help students to link theory, practice and personal experiences. This pilot study used a survey to examine ePortfolio use from the perspective of undergraduate nursing and postgraduate midwifery students. Fifty-seven students from a regional Australian university completed an online questionnaire which contained questions about the following areas of ePortfolio use: understanding of the tool; psychological perceptions; challenges around use; assessment; outcomes of use; benefits; maintenance of the ePortfolio; and enhanced learning. The majority of respondents were female, undergraduate students, aged 21-30 years. Results indicated that many students found ePortfolio use frustrating; in particular, technological and logistical challenges in using ePortfolios were highlighted. Most students, however, noted ePortfolios could be useful repositories for documents, reflections and learning experiences. Undergraduate students were more likely than postgraduate students to see the positive potential of ePortfolio use. The findings, coupled with the literature, raise questions about the effectiveness of ePortfolio use in nursing and midwifery education and, particularly, whether ePortfolios have been implemented with misguided and misinformed good intention. Further research is required to better understand the logistical and technological aspects of successful implementation of ePortfolios and fully capitalise on their benefits for nursing and midwifery education. Copyright © 2016 Elsevier Ltd. All rights reserved.

75 FR 81519 - Confirmation, Portfolio Reconciliation, and Portfolio Compression Requirements for Swap Dealers...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-28

... systemic risk, portfolio reconciliation should be a proactive process that delivers a consolidated view of... achieved by portfolio compression, in turn, may lessen systemic risk and enhance the overall stability of...

Portfolio Assessment of Multicultural Counseling Competency.

ERIC Educational Resources Information Center

Coleman, Hardin L. K.

1996-01-01

Presents portfolio assessment as an alternate approach to the measurement of multicultural counseling competency, and evaluates the strengths and weaknesses of portfolio assessment. Identifies the effectiveness of portfolio assessment in stimulating the development of further counseling competence. (SNR)

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.

The Development of E-Portfolio Evaluation Criteria and Application to the Blackboard LMS E-Portfolio

ERIC Educational Resources Information Center

McKenna, Gary F.; Stansfield, Mark H.

2012-01-01

The purpose of this paper is to develop e-portfolio evaluation criteria which will be used to review the Blackboard LMS e-portfolio being used at one Higher Education (HE) institution in the UK as evaluation criteria for reviewing e-portfolio provision does not exist in the literature. The approach taken was to initiate a wide literature search…

The extent and characteristics of United Kingdom hospital pharmacists keeping, or not keeping, a professional development portfolio.

PubMed

Kostrzewski, Andrzej J; Dhillon, Soraya; Goodsman, Danë; Taylor, Kevin M G; Weinman, John A

2009-10-01

The aim of this study was to examine the use of continuing professional development (CPD) portfolios by hospital pharmacists. The objectives were to assess the extent to which pharmacists use portfolios in CPD and to examine the attitudes/beliefs which differentiate those who do and do not keep a portfolio. Participants completed two questionnaires: (1) personality traits were examined using the Big-Five questionnaire and (2) a new Pharmacist Portfolio-Engaging Behaviour Questionnaire (PPEBQ) examined the attitudes and beliefs. What constitutes a portfolio was left to the interpretation of the participants, but it was specified that the survey was about participants' views of producing written records of their professional practice for CPD. The setting was hospital pharmacists based in the London area in December 2004. Overall, 134 pharmacists (78%) returned both questionnaires, and 80 stated that they kept a portfolio and 52 stated that they did not (two questionnaires were returned spoilt). There was no significant difference in the age or number of years qualified between those with and without a portfolio. Three personality traits were linked to keeping a portfolio (conscientiousness, agreeableness and emotional stability). Pharmacists with a portfolio scored highly on the perceived behavioural control and behavioural intention scales of the PPEBQ. The Big-Five personality questionnaire is a useful tool to investigate pharmacists' use of a portfolio. Results of the PPEBQ suggested that hospital pharmacists who had a portfolio were concerned with having control over its production. However, the PPEBQ requires further development to improve its reliability. These findings have implications for the educational support of CPD.

Developing the Maternity Portfolio to promote maternal role attainment in women who have undergone artificial reproductive treatment.

PubMed

Iwata, Hiroko; Mori, Emi; Maekawa, Tomoko; Maehara, Kunie; Sakajo, Akiko; Ozawa, Harumi; Morita, Akiko

2012-12-01

The purpose of this study was to develop the Maternity Portfolio to promote maternal role attainment in women who underwent artificial reproductive treatment. The following procedures were undertaken to develop the Maternity Portfolio: (i) a literature review was conducted to identify studies and articles related to maternal diary or portfolio usage; (ii) the research members discussed objectives and usages of the Maternity Portfolio; (iii) a trial product was developed in collaboration with two pregnant women (one following artificial reproductive treatment and one infertility patient) and seven nurses, and after feedback was completed, the product was revised; and (iv) the final product of the Maternity Portfolio was patented. The final Maternity Portfolio product consisted of a 40-page booklet; it contained an information section and a patient comments section. Following artificial reproductive treatment, this booklet can be provided to women during the first trimester. Women would then be instructed to bring the Maternity Portfolio to their prenatal checkups, where a nursing intervention program would be conducted by certified nurses. Through this program and the Maternity Portfolio, participating women are expected to obtain necessary information and maternal role attainment. The Maternity Portfolio was developed to promote maternal role attainment for women who have undergone artificial reproductive treatment. The intervention study with the Maternity Portfolio is a work in progress; therefore, a future evaluation of the study will clarify both positive and negative aspects, which should facilitate refinement of the functions and qualities of the Maternity Portfolio. © 2011 The Authors. Japan Journal of Nursing Science © 2011 Japan Academy of Nursing Science.

Mentoring portfolio use in undergraduate and postgraduate medical education.

PubMed

Dekker, Hanke; Driessen, Erik; Ter Braak, Edith; Scheele, Fedde; Slaets, Joris; Van Der Molen, Thys; Cohen-Schotanus, Janke

2009-10-01

Mentoring is widely acknowledged as being crucial for portfolio learning. The aim of this study is to examine how mentoring portfolio use has been implemented in undergraduate and postgraduate settings. The results of interviews with six key persons involved in setting up portfolio use in medical education programmes were used to develop a questionnaire, which was administered to 30 coordinators of undergraduate and postgraduate portfolio programmes in the Netherlands and Flanders. The interviews yielded four main aspects of the portfolio mentoring process--educational aims, individual meetings, small group sessions and mentor characteristics. Based on the questionnaire data, 16 undergraduate and 14 postgraduate programmes were described. Providing feedback and stimulating reflection were the main objectives of the mentoring process. Individual meetings were the favourite method for mentoring (26 programmes). Small group sessions to support the use of portfolios were held in 16 programmes, mostly in the undergraduate setting. In general, portfolio mentors were clinically qualified academic staff trained for their mentoring tasks. This study provides a variety of practical insights into implementing mentoring processes in portfolio programmes.

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.

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.

Performance of finite order distribution-generated universal portfolios

NASA Astrophysics Data System (ADS)

Pang, Sook Theng; Liew, How Hui; Chang, Yun Fah

2017-04-01

A Constant Rebalanced Portfolio (CRP) is an investment strategy which reinvests by redistributing wealth equally among a set of stocks. The empirical performance of the distribution-generated universal portfolio strategies are analysed experimentally concerning 10 higher volume stocks from different categories in Kuala Lumpur Stock Exchange. The time interval of study is from January 2000 to December 2015, which includes the credit crisis from September 2008 to March 2009. The performance of the finite-order universal portfolio strategies has been shown to be better than Constant Rebalanced Portfolio with some selected parameters of proposed universal portfolios.

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 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

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.

Electronic Portfolios. [SITE 2001 Section].

ERIC Educational Resources Information Center

Willis, Dee Anna, Ed.

This document contains the following papers on electronic portfolios from the SITE (Society for Information Technology & Teacher Education) 2001 conference: (1) "Portfolios: The Plan, the Purpose, a Preview" (Val Christensen and others); (2) "Electronic Portfolios (EP): A How To Guide" (Jerry P. Galloway); (3)…

Professionalism, Portfolios and the Development of School Leaders.

ERIC Educational Resources Information Center

Wildy, Helen; Wallace, John

1998-01-01

Describes how two reforms--portfolio culture and teacher professionalism--converge in a systemwide program for school leaders' professional development. Investigates use of portfolios to help (Australian) principals, deputy principals, and department heads improve their performance and accountability. Participants used portfolios as evidence of…

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.

Incorporating Asymmetric Dependency Patterns in the Evaluation of IS/IT projects Using Real Option Analysis

ERIC Educational Resources Information Center

Burke, John C.

2012-01-01

The objective of my dissertation is to create a general approach to evaluating IS/IT projects using Real Option Analysis (ROA). This is an important problem because an IT Project Portfolio (ITPP) can represent hundreds of projects, millions of dollars of investment and hundreds of thousands of employee hours. Therefore, any advance in the…

Enhancing the Teaching of Statistics: Portfolio Theory, an Application of Statistics in Finance

ERIC Educational Resources Information Center

Christou, Nicolas

2008-01-01

In this paper we present an application of statistics using real stock market data. Most, if not all, students have some familiarity with the stock market (or at least they have heard about it) and therefore can understand the problem easily. It is the real data analysis that students find interesting. Here we explore the building of efficient…

Student Teaching Portfolios: A Tool for Promoting Reflective Practice.

ERIC Educational Resources Information Center

Borko, Hilda; Michalec, Paul; Timmons, Maria; Siddle, Jean

1997-01-01

Examines student teaching portfolios in action within preservice teacher education, describing how the University of Colorado mandated student teaching portfolios for preservice educators. A study examined whether portfolio construction would enhance student teachers' reflection on practice. Data from interviews and students' written reflections…

Assessing Pre-Service Candidates' Web-Based Electronic Portfolios.

ERIC Educational Resources Information Center

Lamson, Sharon; Thomas, Kelli R.; Aldrich, Jennifer; King, Andy

This paper describes processes undertaken by Central Missouri State University's Department of Curriculum and Instruction to prepare teacher candidates to create Web-based professional portfolios, Central's expectations for content coverage within the electronic portfolios, and evaluation procedures. It also presents data on portfolio construction…

Portfolio Assessment and Quality Teaching

ERIC Educational Resources Information Center

Kim, Youb; Yazdian, Lisa Sensale

2014-01-01

Our article focuses on using portfolio assessment to craft quality teaching. Extant research literature on portfolio assessment suggests that the primary purpose of assessment is to serve learning, and portfolio assessments facilitate the process of making linkages among assessment, curriculum, and student learning (Asp, 2000; Bergeron, Wermuth,…

Portfolio Analysis for Vector Calculus

ERIC Educational Resources Information Center

Kaplan, Samuel R.

2015-01-01

Classic stock portfolio analysis provides an applied context for Lagrange multipliers that undergraduate students appreciate. Although modern methods of portfolio analysis are beyond the scope of vector calculus, classic methods reinforce the utility of this material. This paper discusses how to introduce classic stock portfolio analysis in a…