Sample records for mean-variance portfolio optimization

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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.

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

    PubMed

    Bacanin, Nebojsa; Tuba, Milan

    2014-01-01

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

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

    PubMed Central

    2014-01-01

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

  11. 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.

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

    PubMed

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

    2017-08-01

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

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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

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

    PubMed

    Shinzato, Takashi

    2016-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Shinzato, Takashi

    2016-12-01

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

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Belief Propagation Algorithm for Portfolio Optimization Problems

    PubMed Central

    2015-01-01

    The typical behavior of optimal solutions to portfolio optimization problems with absolute deviation and expected shortfall models using replica analysis was pioneeringly estimated by S. Ciliberti et al. [Eur. Phys. B. 57, 175 (2007)]; however, they have not yet developed an approximate derivation method for finding the optimal portfolio with respect to a given return set. In this study, an approximation algorithm based on belief propagation for the portfolio optimization problem is presented using the Bethe free energy formalism, and the consistency of the numerical experimental results of the proposed algorithm with those of replica analysis is confirmed. Furthermore, the conjecture of H. Konno and H. Yamazaki, that the optimal solutions with the absolute deviation model and with the mean-variance model have the same typical behavior, is verified using replica analysis and the belief propagation algorithm. PMID:26305462

  10. Belief Propagation Algorithm for Portfolio Optimization Problems.

    PubMed

    Shinzato, Takashi; Yasuda, Muneki

    2015-01-01

    The typical behavior of optimal solutions to portfolio optimization problems with absolute deviation and expected shortfall models using replica analysis was pioneeringly estimated by S. Ciliberti et al. [Eur. Phys. B. 57, 175 (2007)]; however, they have not yet developed an approximate derivation method for finding the optimal portfolio with respect to a given return set. In this study, an approximation algorithm based on belief propagation for the portfolio optimization problem is presented using the Bethe free energy formalism, and the consistency of the numerical experimental results of the proposed algorithm with those of replica analysis is confirmed. Furthermore, the conjecture of H. Konno and H. Yamazaki, that the optimal solutions with the absolute deviation model and with the mean-variance model have the same typical behavior, is verified using replica analysis and the belief propagation algorithm.

  11. 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.

  12. 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.

  13. On the Endogeneity of the Mean-Variance Efficient Frontier.

    ERIC Educational Resources Information Center

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

    2002-01-01

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

  14. 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 \

  15. 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.

  16. 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.

  17. 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.

  18. Swarm based mean-variance mapping optimization (MVMOS) for solving economic dispatch

    NASA Astrophysics Data System (ADS)

    Khoa, T. H.; Vasant, P. M.; Singh, M. S. Balbir; Dieu, V. N.

    2014-10-01

    The economic dispatch (ED) is an essential optimization task in the power generation system. It is defined as the process of allocating the real power output of generation units to meet required load demand so as their total operating cost is minimized while satisfying all physical and operational constraints. This paper introduces a novel optimization which named as Swarm based Mean-variance mapping optimization (MVMOS). The technique is the extension of the original single particle mean-variance mapping optimization (MVMO). Its features make it potentially attractive algorithm for solving optimization problems. The proposed method is implemented for three test power systems, including 3, 13 and 20 thermal generation units with quadratic cost function and the obtained results are compared with many other methods available in the literature. Test results have indicated that the proposed method can efficiently implement for solving economic dispatch.

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

    NASA Astrophysics Data System (ADS)

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

    2012-10-01

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

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Optimal control of LQG problem with an explicit trade-off between mean and variance

    NASA Astrophysics Data System (ADS)

    Qian, Fucai; Xie, Guo; Liu, Ding; Xie, Wenfang

    2011-12-01

    For discrete-time linear-quadratic Gaussian (LQG) control problems, a utility function on the expectation and the variance of the conventional performance index is considered. The utility function is viewed as an overall objective of the system and can perform the optimal trade-off between the mean and the variance of performance index. The nonlinear utility function is first converted into an auxiliary parameters optimisation problem about the expectation and the variance. Then an optimal closed-loop feedback controller for the nonseparable mean-variance minimisation problem is designed by nonlinear mathematical programming. Finally, simulation results are given to verify the algorithm's effectiveness obtained in this article.

  6. 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.

  7. 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.

  8. Random Matrix Approach for Primal-Dual Portfolio Optimization Problems

    NASA Astrophysics Data System (ADS)

    Tada, Daichi; Yamamoto, Hisashi; Shinzato, Takashi

    2017-12-01

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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Asset Allocation and Optimal Contract for Delegated Portfolio Management

    NASA Astrophysics Data System (ADS)

    Liu, Jingjun; Liang, Jianfeng

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

  13. A One-Layer Recurrent Neural Network for Real-Time Portfolio Optimization With Probability Criterion.

    PubMed

    Liu, Qingshan; Dang, Chuangyin; Huang, Tingwen

    2013-02-01

    This paper presents a decision-making model described by a recurrent neural network for dynamic portfolio optimization. The portfolio-optimization problem is first converted into a constrained fractional programming problem. Since the objective function in the programming problem is not convex, the traditional optimization techniques are no longer applicable for solving this problem. Fortunately, the objective function in the fractional programming is pseudoconvex on the feasible region. It leads to a one-layer recurrent neural network modeled by means of a discontinuous dynamic system. To ensure the optimal solutions for portfolio optimization, the convergence of the proposed neural network is analyzed and proved. In fact, the neural network guarantees to get the optimal solutions for portfolio-investment advice if some mild conditions are satisfied. A numerical example with simulation results substantiates the effectiveness and illustrates the characteristics of the proposed neural network.

  14. 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.

  15. Portfolio optimization by using linear programing models based on genetic algorithm

    NASA Astrophysics Data System (ADS)

    Sukono; Hidayat, Y.; Lesmana, E.; Putra, A. S.; Napitupulu, H.; Supian, S.

    2018-01-01

    In this paper, we discussed the investment portfolio optimization using linear programming model based on genetic algorithms. It is assumed that the portfolio risk is measured by absolute standard deviation, and each investor has a risk tolerance on the investment portfolio. To complete the investment portfolio optimization problem, the issue is arranged into a linear programming model. Furthermore, determination of the optimum solution for linear programming is done by using a genetic algorithm. As a numerical illustration, we analyze some of the stocks traded on the capital market in Indonesia. Based on the analysis, it is shown that the portfolio optimization performed by genetic algorithm approach produces more optimal efficient portfolio, compared to the portfolio optimization performed by a linear programming algorithm approach. Therefore, genetic algorithms can be considered as an alternative on determining the investment portfolio optimization, particularly using linear programming models.

  16. Contract portfolio optimization for a gasoline supply chain

    NASA Astrophysics Data System (ADS)

    Wang, Shanshan

    Major oil companies sell gasoline through three channels of trade: branded (associated with long-term contracts), unbranded (associated with short-term contracts), and spot market. The branded channel provides them with a long-term secured and sustainable demand source, but requires an inflexible long-term commitment with demand and price risks. The unbranded channel provides a medium level of allocation flexibility. The spot market provides them with the greatest allocation flexibility to the changing market conditions, but the spot market's illiquidity mitigates this benefit. In order to sell the product in a profitable and sustainable way, they need an optimal contract portfolio. This dissertation addresses the contract portfolio optimization problem from different perspectives (retrospective view and forward-looking view) at different levels (strategic level, tactical level and operational level). The objective of the retrospective operational model is to develop a financial case to estimate the business value of having a dynamic optimization model and quantify the opportunity values missed in the past. This model proves the financial significance of the problem and provides top management valuable insights into the business. BP has applied the insights and principles gained from this work and implemented the model to the entire Midwest gasoline supply chain to retrospectively review optimization opportunities. The strategic model is the most parsimonious model that captures the essential economic tradeoffs among different contract types, to demonstrate the need for a contract portfolio and what drives the portfolio. We examine the properties of the optimal contract portfolio and provide a comparative statics analysis by changing the model parameters. As the strategic model encapsulates the business problem at the macroscopic level, the tactical model resolves lower level issues. It considers the time dynamics, the information flow and contracting flow. Using

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. Portfolio optimization using fuzzy linear programming

    NASA Astrophysics Data System (ADS)

    Pandit, Purnima K.

    2013-09-01

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

  2. 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.

  3. 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.

  4. 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

  5. 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

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

    DTIC Science & Technology

    2012-04-30

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

  7. 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.

  8. On long-only information-based portfolio diversification framework

    NASA Astrophysics Data System (ADS)

    Santos, Raphael A.; Takada, Hellinton H.

    2014-12-01

    Using the concepts from information theory, it is possible to improve the traditional frameworks for long-only asset allocation. In modern portfolio theory, the investor has two basic procedures: the choice of a portfolio that maximizes its risk-adjusted excess return or the mixed allocation between the maximum Sharpe portfolio and the risk-free asset. In the literature, the first procedure was already addressed using information theory. One contribution of this paper is the consideration of the second procedure in the information theory context. The performance of these approaches was compared with three traditional asset allocation methodologies: the Markowitz's mean-variance, the resampled mean-variance and the equally weighted portfolio. Using simulated and real data, the information theory-based methodologies were verified to be more robust when dealing with the estimation errors.

  9. 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…

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. Robust Active Portfolio Management

    DTIC Science & Technology

    2006-11-27

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

  15. 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.

  16. 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.

  17. 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.

  18. A VaR Algorithm for Warrants Portfolio

    NASA Astrophysics Data System (ADS)

    Dai, Jun; Ni, Liyun; Wang, Xiangrong; Chen, Weizhong

    Based on Gamma Vega-Cornish Fish methodology, this paper propose the algorithm for calculating VaR via adjusting the quantile under the given confidence level using the four moments (e.g. mean, variance, skewness and kurtosis) of the warrants portfolio return and estimating the variance of portfolio by EWMA methodology. Meanwhile, the proposed algorithm considers the attenuation of the effect of history return on portfolio return of future days. Empirical study shows that, comparing with Gamma-Cornish Fish method and standard normal method, the VaR calculated by Gamma Vega-Cornish Fish can improve the effectiveness of forecasting the portfolio risk by virture of considering the Gamma risk and the Vega risk of the warrants. The significance test is conducted on the calculation results by employing two-tailed test developed by Kupiec. Test results show that the calculated VaRs of the warrants portfolio all pass the significance test under the significance level of 5%.

  19. 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.

  20. 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.

  1. R package MVR for Joint Adaptive Mean-Variance Regularization and Variance Stabilization

    PubMed Central

    Dazard, Jean-Eudes; Xu, Hua; Rao, J. Sunil

    2015-01-01

    We present an implementation in the R language for statistical computing of our recent non-parametric joint adaptive mean-variance regularization and variance stabilization procedure. The method is specifically suited for handling difficult problems posed by high-dimensional multivariate datasets (p ≫ n paradigm), such as in ‘omics’-type data, among which are that the variance is often a function of the mean, variable-specific estimators of variances are not reliable, and tests statistics have low powers due to a lack of degrees of freedom. The implementation offers a complete set of features including: (i) normalization and/or variance stabilization function, (ii) computation of mean-variance-regularized t and F statistics, (iii) generation of diverse diagnostic plots, (iv) synthetic and real ‘omics’ test datasets, (v) computationally efficient implementation, using C interfacing, and an option for parallel computing, (vi) manual and documentation on how to setup a cluster. To make each feature as user-friendly as possible, only one subroutine per functionality is to be handled by the end-user. It is available as an R package, called MVR (‘Mean-Variance Regularization’), downloadable from the CRAN. PMID:26819572

  2. Portfolio of automated trading systems: complexity and learning set size issues.

    PubMed

    Raudys, Sarunas

    2013-03-01

    In this paper, we consider using profit/loss histories of multiple automated trading systems (ATSs) as N input variables in portfolio management. By means of multivariate statistical analysis and simulation studies, we analyze the influences of sample size (L) and input dimensionality on the accuracy of determining the portfolio weights. We find that degradation in portfolio performance due to inexact estimation of N means and N(N - 1)/2 correlations is proportional to N/L; however, estimation of N variances does not worsen the result. To reduce unhelpful sample size/dimensionality effects, we perform a clustering of N time series and split them into a small number of blocks. Each block is composed of mutually correlated ATSs. It generates an expert trading agent based on a nontrainable 1/N portfolio rule. To increase the diversity of the expert agents, we use training sets of different lengths for clustering. In the output of the portfolio management system, the regularized mean-variance framework-based fusion agent is developed in each walk-forward step of an out-of-sample portfolio validation experiment. Experiments with the real financial data (2003-2012) confirm the effectiveness of the suggested approach.

  3. 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

  4. 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

  5. Divergent estimation error in portfolio optimization and in linear regression

    NASA Astrophysics Data System (ADS)

    Kondor, I.; Varga-Haszonits, I.

    2008-08-01

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

  6. Portfolio Optimization with Stochastic Dividends and Stochastic Volatility

    ERIC Educational Resources Information Center

    Varga, Katherine Yvonne

    2015-01-01

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

  7. Mean-Variance Hedging on Uncertain Time Horizon in a Market with a Jump

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

    Kharroubi, Idris, E-mail: kharroubi@ceremade.dauphine.fr; Lim, Thomas, E-mail: lim@ensiie.fr; Ngoupeyou, Armand, E-mail: armand.ngoupeyou@univ-paris-diderot.fr

    2013-12-15

    In this work, we study the problem of mean-variance hedging with a random horizon T∧τ, where T is a deterministic constant and τ is a jump time of the underlying asset price process. We first formulate this problem as a stochastic control problem and relate it to a system of BSDEs with a jump. We then provide a verification theorem which gives the optimal strategy for the mean-variance hedging using the solution of the previous system of BSDEs. Finally, we prove that this system of BSDEs admits a solution via a decomposition approach coming from filtration enlargement theory.

  8. Means and Variances without Calculus

    ERIC Educational Resources Information Center

    Kinney, John J.

    2005-01-01

    This article gives a method of finding discrete approximations to continuous probability density functions and shows examples of its use, allowing students without calculus access to the calculation of means and variances.

  9. The stability of portfolio investment in stock crashes

    NASA Astrophysics Data System (ADS)

    Li, Yun-Xian; Qian, Zhen-Wei; Li, Jiang-Cheng; Tang, Nian-Sheng; Mei, Dong-Cheng

    2016-08-01

    The stability of portfolio investment in stock market crashes with Markowitz portfolio is investigated by the method of theoretical and empirical simulation. From numerical simulation of the mean escape time (MET), we conclude that: (i) The increasing number (Np) of stocks in Markowitz portfolio induces a maximum in the curve of MET versus the initial position; (ii) A critical value of Np in the behavior of MET versus the long-run variance or amplitude of volatility fluctuations maximumlly enhances the stability of portfolio investment. When Np takes value below the critical value, the increasing Np enhances the stability of portfolio investment, but restrains it when Np takes value above the critical value. In addition, a good agreement of both the MET and probability density functions of returns is found between real data and theoretical results.

  10. Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data.

    PubMed

    Dazard, Jean-Eudes; Rao, J Sunil

    2012-07-01

    The paper addresses a common problem in the analysis of high-dimensional high-throughput "omics" data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel "similarity statistic"-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called 'MVR' ('Mean-Variance Regularization'), downloadable from the CRAN website.

  11. 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

  12. Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data

    PubMed Central

    Dazard, Jean-Eudes; Rao, J. Sunil

    2012-01-01

    The paper addresses a common problem in the analysis of high-dimensional high-throughput “omics” data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel “similarity statistic”-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called ‘MVR’ (‘Mean-Variance Regularization’), downloadable from the CRAN website. PMID:22711950

  13. Integrating mean and variance heterogeneities to identify differentially expressed genes.

    PubMed

    Ouyang, Weiwei; An, Qiang; Zhao, Jinying; Qin, Huaizhen

    2016-12-06

    In functional genomics studies, tests on mean heterogeneity have been widely employed to identify differentially expressed genes with distinct mean expression levels under different experimental conditions. Variance heterogeneity (aka, the difference between condition-specific variances) of gene expression levels is simply neglected or calibrated for as an impediment. The mean heterogeneity in the expression level of a gene reflects one aspect of its distribution alteration; and variance heterogeneity induced by condition change may reflect another aspect. Change in condition may alter both mean and some higher-order characteristics of the distributions of expression levels of susceptible genes. In this report, we put forth a conception of mean-variance differentially expressed (MVDE) genes, whose expression means and variances are sensitive to the change in experimental condition. We mathematically proved the null independence of existent mean heterogeneity tests and variance heterogeneity tests. Based on the independence, we proposed an integrative mean-variance test (IMVT) to combine gene-wise mean heterogeneity and variance heterogeneity induced by condition change. The IMVT outperformed its competitors under comprehensive simulations of normality and Laplace settings. For moderate samples, the IMVT well controlled type I error rates, and so did existent mean heterogeneity test (i.e., the Welch t test (WT), the moderated Welch t test (MWT)) and the procedure of separate tests on mean and variance heterogeneities (SMVT), but the likelihood ratio test (LRT) severely inflated type I error rates. In presence of variance heterogeneity, the IMVT appeared noticeably more powerful than all the valid mean heterogeneity tests. Application to the gene profiles of peripheral circulating B raised solid evidence of informative variance heterogeneity. After adjusting for background data structure, the IMVT replicated previous discoveries and identified novel experiment

  14. Evaluation of Mean and Variance Integrals without Integration

    ERIC Educational Resources Information Center

    Joarder, A. H.; Omar, M. H.

    2007-01-01

    The mean and variance of some continuous distributions, in particular the exponentially decreasing probability distribution and the normal distribution, are considered. Since they involve integration by parts, many students do not feel comfortable. In this note, a technique is demonstrated for deriving mean and variance through differential…

  15. One Idea of Portfolio Risk Control Focusing on States of Correlation

    NASA Astrophysics Data System (ADS)

    Nishiyama, Noboru

    2004-04-01

    In the modern portfolio theory there are 2 major risk parameters that mean and variance. Correlations should be playing important role as well but variance is thought to be most important risk parameter for risk control in the theory. I focused on states of correlation to calculate eigen values as risk control parameter.

  16. 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

  17. Why risk is not variance: an expository note.

    PubMed

    Cox, Louis Anthony Tony

    2008-08-01

    Variance (or standard deviation) of return is widely used as a measure of risk in financial investment risk analysis applications, where mean-variance analysis is applied to calculate efficient frontiers and undominated portfolios. Why, then, do health, safety, and environmental (HS&E) and reliability engineering risk analysts insist on defining risk more flexibly, as being determined by probabilities and consequences, rather than simply by variances? This note suggests an answer by providing a simple proof that mean-variance decision making violates the principle that a rational decisionmaker should prefer higher to lower probabilities of receiving a fixed gain, all else being equal. Indeed, simply hypothesizing a continuous increasing indifference curve for mean-variance combinations at the origin is enough to imply that a decisionmaker must find unacceptable some prospects that offer a positive probability of gain and zero probability of loss. Unlike some previous analyses of limitations of variance as a risk metric, this expository note uses only simple mathematics and does not require the additional framework of von Neumann Morgenstern utility theory.

  18. 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

    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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. Risk-sensitivity and the mean-variance trade-off: decision making in sensorimotor control

    PubMed Central

    Nagengast, Arne J.; Braun, Daniel A.; Wolpert, Daniel M.

    2011-01-01

    Numerous psychophysical studies suggest that the sensorimotor system chooses actions that optimize the average cost associated with a movement. Recently, however, violations of this hypothesis have been reported in line with economic theories of decision-making that not only consider the mean payoff, but are also sensitive to risk, that is the variability of the payoff. Here, we examine the hypothesis that risk-sensitivity in sensorimotor control arises as a mean-variance trade-off in movement costs. We designed a motor task in which participants could choose between a sure motor action that resulted in a fixed amount of effort and a risky motor action that resulted in a variable amount of effort that could be either lower or higher than the fixed effort. By changing the mean effort of the risky action while experimentally fixing its variance, we determined indifference points at which participants chose equiprobably between the sure, fixed amount of effort option and the risky, variable effort option. Depending on whether participants accepted a variable effort with a mean that was higher, lower or equal to the fixed effort, they could be classified as risk-seeking, risk-averse or risk-neutral. Most subjects were risk-sensitive in our task consistent with a mean-variance trade-off in effort, thereby, underlining the importance of risk-sensitivity in computational models of sensorimotor control. PMID:21208966

  6. The mean and variance of phylogenetic diversity under rarefaction

    PubMed Central

    Matsen, Frederick A.

    2013-01-01

    Summary Phylogenetic diversity (PD) depends on sampling depth, which complicates the comparison of PD between samples of different depth. One approach to dealing with differing sample depth for a given diversity statistic is to rarefy, which means to take a random subset of a given size of the original sample. Exact analytical formulae for the mean and variance of species richness under rarefaction have existed for some time but no such solution exists for PD.We have derived exact formulae for the mean and variance of PD under rarefaction. We confirm that these formulae are correct by comparing exact solution mean and variance to that calculated by repeated random (Monte Carlo) subsampling of a dataset of stem counts of woody shrubs of Toohey Forest, Queensland, Australia. We also demonstrate the application of the method using two examples: identifying hotspots of mammalian diversity in Australasian ecoregions, and characterising the human vaginal microbiome.There is a very high degree of correspondence between the analytical and random subsampling methods for calculating mean and variance of PD under rarefaction, although the Monte Carlo method requires a large number of random draws to converge on the exact solution for the variance.Rarefaction of mammalian PD of ecoregions in Australasia to a common standard of 25 species reveals very different rank orderings of ecoregions, indicating quite different hotspots of diversity than those obtained for unrarefied PD. The application of these methods to the vaginal microbiome shows that a classical score used to quantify bacterial vaginosis is correlated with the shape of the rarefaction curve.The analytical formulae for the mean and variance of PD under rarefaction are both exact and more efficient than repeated subsampling. Rarefaction of PD allows for many applications where comparisons of samples of different depth is required. PMID:23833701

  7. The mean and variance of phylogenetic diversity under rarefaction.

    PubMed

    Nipperess, David A; Matsen, Frederick A

    2013-06-01

    Phylogenetic diversity (PD) depends on sampling depth, which complicates the comparison of PD between samples of different depth. One approach to dealing with differing sample depth for a given diversity statistic is to rarefy, which means to take a random subset of a given size of the original sample. Exact analytical formulae for the mean and variance of species richness under rarefaction have existed for some time but no such solution exists for PD.We have derived exact formulae for the mean and variance of PD under rarefaction. We confirm that these formulae are correct by comparing exact solution mean and variance to that calculated by repeated random (Monte Carlo) subsampling of a dataset of stem counts of woody shrubs of Toohey Forest, Queensland, Australia. We also demonstrate the application of the method using two examples: identifying hotspots of mammalian diversity in Australasian ecoregions, and characterising the human vaginal microbiome.There is a very high degree of correspondence between the analytical and random subsampling methods for calculating mean and variance of PD under rarefaction, although the Monte Carlo method requires a large number of random draws to converge on the exact solution for the variance.Rarefaction of mammalian PD of ecoregions in Australasia to a common standard of 25 species reveals very different rank orderings of ecoregions, indicating quite different hotspots of diversity than those obtained for unrarefied PD. The application of these methods to the vaginal microbiome shows that a classical score used to quantify bacterial vaginosis is correlated with the shape of the rarefaction curve.The analytical formulae for the mean and variance of PD under rarefaction are both exact and more efficient than repeated subsampling. Rarefaction of PD allows for many applications where comparisons of samples of different depth is required.

  8. 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.

  9. 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

  10. 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.

  11. 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

  12. A Versatile Omnibus Test for Detecting Mean and Variance Heterogeneity

    PubMed Central

    Bailey, Matthew; Kauwe, John S. K.; Maxwell, Taylor J.

    2014-01-01

    Recent research has revealed loci that display variance heterogeneity through various means such as biological disruption, linkage disequilibrium (LD), gene-by-gene (GxG), or gene-by-environment (GxE) interaction. We propose a versatile likelihood ratio test that allows joint testing for mean and variance heterogeneity (LRTMV) or either effect alone (LRTM or LRTV) in the presence of covariates. Using extensive simulations for our method and others we found that all parametric tests were sensitive to non-normality regardless of any trait transformations. Coupling our test with the parametric bootstrap solves this issue. Using simulations and empirical data from a known mean-only functional variant we demonstrate how linkage disequilibrium (LD) can produce variance-heterogeneity loci (vQTL) in a predictable fashion based on differential allele frequencies, high D’ and relatively low r2 values. We propose that a joint test for mean and variance heterogeneity is more powerful than a variance only test for detecting vQTL. This takes advantage of loci that also have mean effects without sacrificing much power to detect variance only effects. We discuss using vQTL as an approach to detect gene-by-gene interactions and also how vQTL are related to relationship loci (rQTL) and how both can create prior hypothesis for each other and reveal the relationships between traits and possibly between components of a composite trait. PMID:24482837

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. On the Likely Utility of Hybrid Weights Optimized for Variances in Hybrid Error Covariance Models

    NASA Astrophysics Data System (ADS)

    Satterfield, E.; Hodyss, D.; Kuhl, D.; Bishop, C. H.

    2017-12-01

    Because of imperfections in ensemble data assimilation schemes, one cannot assume that the ensemble covariance is equal to the true error covariance of a forecast. Previous work demonstrated how information about the distribution of true error variances given an ensemble sample variance can be revealed from an archive of (observation-minus-forecast, ensemble-variance) data pairs. Here, we derive a simple and intuitively compelling formula to obtain the mean of this distribution of true error variances given an ensemble sample variance from (observation-minus-forecast, ensemble-variance) data pairs produced by a single run of a data assimilation system. This formula takes the form of a Hybrid weighted average of the climatological forecast error variance and the ensemble sample variance. Here, we test the extent to which these readily obtainable weights can be used to rapidly optimize the covariance weights used in Hybrid data assimilation systems that employ weighted averages of static covariance models and flow-dependent ensemble based covariance models. Univariate data assimilation and multi-variate cycling ensemble data assimilation are considered. In both cases, it is found that our computationally efficient formula gives Hybrid weights that closely approximate the optimal weights found through the simple but computationally expensive process of testing every plausible combination of weights.

  19. 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.

  20. 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.

  1. 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).

  2. 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.

  3. 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.

  4. 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.

  5. Robust Means Modeling: An Alternative for Hypothesis Testing of Independent Means under Variance Heterogeneity and Nonnormality

    ERIC Educational Resources Information Center

    Fan, Weihua; Hancock, Gregory R.

    2012-01-01

    This study proposes robust means modeling (RMM) approaches for hypothesis testing of mean differences for between-subjects designs in order to control the biasing effects of nonnormality and variance inequality. Drawing from structural equation modeling (SEM), the RMM approaches make no assumption of variance homogeneity and employ robust…

  6. Variance-Stable R-Estimators.

    DTIC Science & Technology

    1984-05-01

    By means of the concept of change-of variance function we investigate the stability properties of the asymptotic variance of R-estimators. This allows us to construct the optimal V-robust R-estimator that minimizes the asymptotic variance at the model, under the side condition of a bounded change-of variance function. Finally, we discuss the connection between this function and an influence function for two-sample rank tests introduced by Eplett (1980). (Author)

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

    NASA Astrophysics Data System (ADS)

    Shinzato, Takashi

    2017-02-01

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

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. Validity and reliability of portfolio assessment of competency in a baccalaureate dental hygiene program

    NASA Astrophysics Data System (ADS)

    Gadbury-Amyot, Cynthia C.

    This study examined validity and reliability of portfolio assessment using Messick's (1996, 1995) unified framework of construct validity. Theoretical and empirical evidence was sought for six aspects of construct validity. The sample included twenty student portfolios. Each portfolio were evaluated by seven faculty raters using a primary trait analysis scoring rubric. There was a significant relationship (r = .81--.95; p < .01) between the seven subscales in the scoring rubric demonstrating measurement of a common construct. Item analysis was conducted to examine convergent and discriminant empirical relationships of the 35 items in the scoring rubric. There was a significant relationship between all items ( p < .01), and all but one item was more strongly correlated with its own subscale than with other subscales. However, correlations of items across subscales were predominantly moderate in strength indicating that items did not strongly discriminate between subscales. A fully crossed, two facet generalizability (G) study design was used to examine reliability. Analysis of variance demonstrated that the greatest source of variance was the scoring rubric itself, accounting for 78% of the total variance. The smallest source of variance was the interaction between portfolio and rubric (1.15%) indicating that while the seven subscales varied in difficulty level, the relative standing of individual portfolios was maintained across subscales. Faculty rater variance accounted for only 1.28% of total variance. A phi coefficient of .86, analogous to a reliability coefficient in classical test theory, was obtained in the Decision study by increasing the subscales to fourteen and decreasing faculty raters to three. There was a significant relationship between portfolios and grade point average (r = .70; p < .01), and the National Dental Hygiene Board Examination (r = .60; p < .01). The relationship between portfolios and the Central Regional Dental Testing Service

  14. 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.

  15. Origin and Consequences of the Relationship between Protein Mean and Variance

    PubMed Central

    Vallania, Francesco Luigi Massimo; Sherman, Marc; Goodwin, Zane; Mogno, Ilaria; Cohen, Barak Alon; Mitra, Robi David

    2014-01-01

    Cell-to-cell variance in protein levels (noise) is a ubiquitous phenomenon that can increase fitness by generating phenotypic differences within clonal populations of cells. An important challenge is to identify the specific molecular events that control noise. This task is complicated by the strong dependence of a protein's cell-to-cell variance on its mean expression level through a power-law like relationship (σ2∝μ1.69). Here, we dissect the nature of this relationship using a stochastic model parameterized with experimentally measured values. This framework naturally recapitulates the power-law like relationship (σ2∝μ1.6) and accurately predicts protein variance across the yeast proteome (r2 = 0.935). Using this model we identified two distinct mechanisms by which protein variance can be increased. Variables that affect promoter activation, such as nucleosome positioning, increase protein variance by changing the exponent of the power-law relationship. In contrast, variables that affect processes downstream of promoter activation, such as mRNA and protein synthesis, increase protein variance in a mean-dependent manner following the power-law. We verified our findings experimentally using an inducible gene expression system in yeast. We conclude that the power-law-like relationship between noise and protein mean is due to the kinetics of promoter activation. Our results provide a framework for understanding how molecular processes shape stochastic variation across the genome. PMID:25062021

  16. 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

  17. 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.

  18. Computation of mean and variance of the radiotherapy dose for PCA-modeled random shape and position variations of the target.

    PubMed

    Budiarto, E; Keijzer, M; Storchi, P R M; Heemink, A W; Breedveld, S; Heijmen, B J M

    2014-01-20

    Radiotherapy dose delivery in the tumor and surrounding healthy tissues is affected by movements and deformations of the corresponding organs between fractions. The random variations may be characterized by non-rigid, anisotropic principal component analysis (PCA) modes. In this article new dynamic dose deposition matrices, based on established PCA modes, are introduced as a tool to evaluate the mean and the variance of the dose at each target point resulting from any given set of fluence profiles. The method is tested for a simple cubic geometry and for a prostate case. The movements spread out the distributions of the mean dose and cause the variance of the dose to be highest near the edges of the beams. The non-rigidity and anisotropy of the movements are reflected in both quantities. The dynamic dose deposition matrices facilitate the inclusion of the mean and the variance of the dose in the existing fluence-profile optimizer for radiotherapy planning, to ensure robust plans with respect to the movements.

  19. 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.

  20. 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.

  1. Estimating means and variances: The comparative efficiency of composite and grab samples.

    PubMed

    Brumelle, S; Nemetz, P; Casey, D

    1984-03-01

    This paper compares the efficiencies of two sampling techniques for estimating a population mean and variance. One procedure, called grab sampling, consists of collecting and analyzing one sample per period. The second procedure, called composite sampling, collectsn samples per period which are then pooled and analyzed as a single sample. We review the well known fact that composite sampling provides a superior estimate of the mean. However, it is somewhat surprising that composite sampling does not always generate a more efficient estimate of the variance. For populations with platykurtic distributions, grab sampling gives a more efficient estimate of the variance, whereas composite sampling is better for leptokurtic distributions. These conditions on kurtosis can be related to peakedness and skewness. For example, a necessary condition for composite sampling to provide a more efficient estimate of the variance is that the population density function evaluated at the mean (i.e.f(μ)) be greater than[Formula: see text]. If[Formula: see text], then a grab sample is more efficient. In spite of this result, however, composite sampling does provide a smaller estimate of standard error than does grab sampling in the context of estimating population means.

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. 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

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. Measuring kinetics of complex single ion channel data using mean-variance histograms.

    PubMed

    Patlak, J B

    1993-07-01

    The measurement of single ion channel kinetics is difficult when those channels exhibit subconductance events. When the kinetics are fast, and when the current magnitudes are small, as is the case for Na+, Ca2+, and some K+ channels, these difficulties can lead to serious errors in the estimation of channel kinetics. I present here a method, based on the construction and analysis of mean-variance histograms, that can overcome these problems. A mean-variance histogram is constructed by calculating the mean current and the current variance within a brief "window" (a set of N consecutive data samples) superimposed on the digitized raw channel data. Systematic movement of this window over the data produces large numbers of mean-variance pairs which can be assembled into a two-dimensional histogram. Defined current levels (open, closed, or sublevel) appear in such plots as low variance regions. The total number of events in such low variance regions is estimated by curve fitting and plotted as a function of window width. This function decreases with the same time constants as the original dwell time probability distribution for each of the regions. The method can therefore be used: 1) to present a qualitative summary of the single channel data from which the signal-to-noise ratio, open channel noise, steadiness of the baseline, and number of conductance levels can be quickly determined; 2) to quantify the dwell time distribution in each of the levels exhibited. In this paper I present the analysis of a Na+ channel recording that had a number of complexities. The signal-to-noise ratio was only about 8 for the main open state, open channel noise, and fast flickers to other states were present, as were a substantial number of subconductance states. "Standard" half-amplitude threshold analysis of these data produce open and closed time histograms that were well fitted by the sum of two exponentials, but with apparently erroneous time constants, whereas the mean-variance

  12. Measuring kinetics of complex single ion channel data using mean-variance histograms.

    PubMed Central

    Patlak, J B

    1993-01-01

    The measurement of single ion channel kinetics is difficult when those channels exhibit subconductance events. When the kinetics are fast, and when the current magnitudes are small, as is the case for Na+, Ca2+, and some K+ channels, these difficulties can lead to serious errors in the estimation of channel kinetics. I present here a method, based on the construction and analysis of mean-variance histograms, that can overcome these problems. A mean-variance histogram is constructed by calculating the mean current and the current variance within a brief "window" (a set of N consecutive data samples) superimposed on the digitized raw channel data. Systematic movement of this window over the data produces large numbers of mean-variance pairs which can be assembled into a two-dimensional histogram. Defined current levels (open, closed, or sublevel) appear in such plots as low variance regions. The total number of events in such low variance regions is estimated by curve fitting and plotted as a function of window width. This function decreases with the same time constants as the original dwell time probability distribution for each of the regions. The method can therefore be used: 1) to present a qualitative summary of the single channel data from which the signal-to-noise ratio, open channel noise, steadiness of the baseline, and number of conductance levels can be quickly determined; 2) to quantify the dwell time distribution in each of the levels exhibited. In this paper I present the analysis of a Na+ channel recording that had a number of complexities. The signal-to-noise ratio was only about 8 for the main open state, open channel noise, and fast flickers to other states were present, as were a substantial number of subconductance states. "Standard" half-amplitude threshold analysis of these data produce open and closed time histograms that were well fitted by the sum of two exponentials, but with apparently erroneous time constants, whereas the mean-variance

  13. 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.

  14. A nonparametric mean-variance smoothing method to assess Arabidopsis cold stress transcriptional regulator CBF2 overexpression microarray data.

    PubMed

    Hu, Pingsha; Maiti, Tapabrata

    2011-01-01

    Microarray is a powerful tool for genome-wide gene expression analysis. In microarray expression data, often mean and variance have certain relationships. We present a non-parametric mean-variance smoothing method (NPMVS) to analyze differentially expressed genes. In this method, a nonlinear smoothing curve is fitted to estimate the relationship between mean and variance. Inference is then made upon shrinkage estimation of posterior means assuming variances are known. Different methods have been applied to simulated datasets, in which a variety of mean and variance relationships were imposed. The simulation study showed that NPMVS outperformed the other two popular shrinkage estimation methods in some mean-variance relationships; and NPMVS was competitive with the two methods in other relationships. A real biological dataset, in which a cold stress transcription factor gene, CBF2, was overexpressed, has also been analyzed with the three methods. Gene ontology and cis-element analysis showed that NPMVS identified more cold and stress responsive genes than the other two methods did. The good performance of NPMVS is mainly due to its shrinkage estimation for both means and variances. In addition, NPMVS exploits a non-parametric regression between mean and variance, instead of assuming a specific parametric relationship between mean and variance. The source code written in R is available from the authors on request.

  15. A Nonparametric Mean-Variance Smoothing Method to Assess Arabidopsis Cold Stress Transcriptional Regulator CBF2 Overexpression Microarray Data

    PubMed Central

    Hu, Pingsha; Maiti, Tapabrata

    2011-01-01

    Microarray is a powerful tool for genome-wide gene expression analysis. In microarray expression data, often mean and variance have certain relationships. We present a non-parametric mean-variance smoothing method (NPMVS) to analyze differentially expressed genes. In this method, a nonlinear smoothing curve is fitted to estimate the relationship between mean and variance. Inference is then made upon shrinkage estimation of posterior means assuming variances are known. Different methods have been applied to simulated datasets, in which a variety of mean and variance relationships were imposed. The simulation study showed that NPMVS outperformed the other two popular shrinkage estimation methods in some mean-variance relationships; and NPMVS was competitive with the two methods in other relationships. A real biological dataset, in which a cold stress transcription factor gene, CBF2, was overexpressed, has also been analyzed with the three methods. Gene ontology and cis-element analysis showed that NPMVS identified more cold and stress responsive genes than the other two methods did. The good performance of NPMVS is mainly due to its shrinkage estimation for both means and variances. In addition, NPMVS exploits a non-parametric regression between mean and variance, instead of assuming a specific parametric relationship between mean and variance. The source code written in R is available from the authors on request. PMID:21611181

  16. 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.

  17. 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…

  18. Electronic Teaching Portfolios: Technology Skills + Portfolio Development = Powerful Preservice Teachers.

    ERIC Educational Resources Information Center

    Capraro, Mary Margaret

    An electronic portfolio is a collection of work captured by electronic means that serves as an exhibit of individual efforts, progress, and achievements in one or more areas. Due to rapid growth and updates in technology, keeping electronic portfolios is becoming increasingly common in a variety of educational settings. In fall 2002 at one large…

  19. LMI-Based Fuzzy Optimal Variance Control of Airfoil Model Subject to Input Constraints

    NASA Technical Reports Server (NTRS)

    Swei, Sean S.M.; Ayoubi, Mohammad A.

    2017-01-01

    This paper presents a study of fuzzy optimal variance control problem for dynamical systems subject to actuator amplitude and rate constraints. Using Takagi-Sugeno fuzzy modeling and dynamic Parallel Distributed Compensation technique, the stability and the constraints can be cast as a multi-objective optimization problem in the form of Linear Matrix Inequalities. By utilizing the formulations and solutions for the input and output variance constraint problems, we develop a fuzzy full-state feedback controller. The stability and performance of the proposed controller is demonstrated through its application to the airfoil flutter suppression.

  20. Portfolios and ICT as Means of Professional Learning in Teacher Education

    ERIC Educational Resources Information Center

    Hauge, Trond Eiliv

    2006-01-01

    Teaching portfolios supported by new learning technologies have increased in importance in Norwegian schools and teacher education. However, the learning potentials of integrated e-portfolios have still to be researched and further developed. This article focuses on professional learning in a teacher education programme reorganised by use of…

  1. 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

  2. On the mean and variance of the writhe of random polygons.

    PubMed

    Portillo, J; Diao, Y; Scharein, R; Arsuaga, J; Vazquez, M

    We here address two problems concerning the writhe of random polygons. First, we study the behavior of the mean writhe as a function length. Second, we study the variance of the writhe. Suppose that we are dealing with a set of random polygons with the same length and knot type, which could be the model of some circular DNA with the same topological property. In general, a simple way of detecting chirality of this knot type is to compute the mean writhe of the polygons; if the mean writhe is non-zero then the knot is chiral. How accurate is this method? For example, if for a specific knot type K the mean writhe decreased to zero as the length of the polygons increased, then this method would be limited in the case of long polygons. Furthermore, we conjecture that the sign of the mean writhe is a topological invariant of chiral knots. This sign appears to be the same as that of an "ideal" conformation of the knot. We provide numerical evidence to support these claims, and we propose a new nomenclature of knots based on the sign of their expected writhes. This nomenclature can be of particular interest to applied scientists. The second part of our study focuses on the variance of the writhe, a problem that has not received much attention in the past. In this case, we focused on the equilateral random polygons. We give numerical as well as analytical evidence to show that the variance of the writhe of equilateral random polygons (of length n ) behaves as a linear function of the length of the equilateral random polygon.

  3. On the mean and variance of the writhe of random polygons

    PubMed Central

    Portillo, J.; Diao, Y.; Scharein, R.; Arsuaga, J.; Vazquez, M.

    2013-01-01

    We here address two problems concerning the writhe of random polygons. First, we study the behavior of the mean writhe as a function length. Second, we study the variance of the writhe. Suppose that we are dealing with a set of random polygons with the same length and knot type, which could be the model of some circular DNA with the same topological property. In general, a simple way of detecting chirality of this knot type is to compute the mean writhe of the polygons; if the mean writhe is non-zero then the knot is chiral. How accurate is this method? For example, if for a specific knot type K the mean writhe decreased to zero as the length of the polygons increased, then this method would be limited in the case of long polygons. Furthermore, we conjecture that the sign of the mean writhe is a topological invariant of chiral knots. This sign appears to be the same as that of an “ideal” conformation of the knot. We provide numerical evidence to support these claims, and we propose a new nomenclature of knots based on the sign of their expected writhes. This nomenclature can be of particular interest to applied scientists. The second part of our study focuses on the variance of the writhe, a problem that has not received much attention in the past. In this case, we focused on the equilateral random polygons. We give numerical as well as analytical evidence to show that the variance of the writhe of equilateral random polygons (of length n) behaves as a linear function of the length of the equilateral random polygon. PMID:25685182

  4. 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

  5. TARGETED SEQUENTIAL DESIGN FOR TARGETED LEARNING INFERENCE OF THE OPTIMAL TREATMENT RULE AND ITS MEAN REWARD.

    PubMed

    Chambaz, Antoine; Zheng, Wenjing; van der Laan, Mark J

    2017-01-01

    This article studies the targeted sequential inference of an optimal treatment rule (TR) and its mean reward in the non-exceptional case, i.e. , assuming that there is no stratum of the baseline covariates where treatment is neither beneficial nor harmful, and under a companion margin assumption. Our pivotal estimator, whose definition hinges on the targeted minimum loss estimation (TMLE) principle, actually infers the mean reward under the current estimate of the optimal TR. This data-adaptive statistical parameter is worthy of interest on its own. Our main result is a central limit theorem which enables the construction of confidence intervals on both mean rewards under the current estimate of the optimal TR and under the optimal TR itself. The asymptotic variance of the estimator takes the form of the variance of an efficient influence curve at a limiting distribution, allowing to discuss the efficiency of inference. As a by product, we also derive confidence intervals on two cumulated pseudo-regrets, a key notion in the study of bandits problems. A simulation study illustrates the procedure. One of the corner-stones of the theoretical study is a new maximal inequality for martingales with respect to the uniform entropy integral.

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

    PubMed

    Powell, Mark R

    2015-12-01

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

  7. 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.

  8. Neurobiological studies of risk assessment: a comparison of expected utility and mean-variance approaches.

    PubMed

    D'Acremont, Mathieu; Bossaerts, Peter

    2008-12-01

    When modeling valuation under uncertainty, economists generally prefer expected utility because it has an axiomatic foundation, meaning that the resulting choices will satisfy a number of rationality requirements. In expected utility theory, values are computed by multiplying probabilities of each possible state of nature by the payoff in that state and summing the results. The drawback of this approach is that all state probabilities need to be dealt with separately, which becomes extremely cumbersome when it comes to learning. Finance academics and professionals, however, prefer to value risky prospects in terms of a trade-off between expected reward and risk, where the latter is usually measured in terms of reward variance. This mean-variance approach is fast and simple and greatly facilitates learning, but it impedes assigning values to new gambles on the basis of those of known ones. To date, it is unclear whether the human brain computes values in accordance with expected utility theory or with mean-variance analysis. In this article, we discuss the theoretical and empirical arguments that favor one or the other theory. We also propose a new experimental paradigm that could determine whether the human brain follows the expected utility or the mean-variance approach. Behavioral results of implementation of the paradigm are discussed.

  9. 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.

  10. 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…

  11. Electronic Teaching Portfolios: Technology Skills + Portfolio Development--Do They = Powerful Preservice Teachers?

    ERIC Educational Resources Information Center

    Capraro, Mary Margaret

    2006-01-01

    Electronic portfolios are a "collection of work captured by electronic means, that serves as an exhibit of individual efforts, progress, and achievements in one or more areas" (Weidmer, 1998, p. 586). Because of the rapid growth and updates in technology, keeping electronic portfolios is becoming increasingly common in a variety of educational…

  12. 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.

  13. Intelligent ensemble T-S fuzzy neural networks with RCDPSO_DM optimization for effective handling of complex clinical pathway variances.

    PubMed

    Du, Gang; Jiang, Zhibin; Diao, Xiaodi; Yao, Yang

    2013-07-01

    Takagi-Sugeno (T-S) fuzzy neural networks (FNNs) can be used to handle complex, fuzzy, uncertain clinical pathway (CP) variances. However, there are many drawbacks, such as slow training rate, propensity to become trapped in a local minimum and poor ability to perform a global search. In order to improve overall performance of variance handling by T-S FNNs, a new CP variance handling method is proposed in this study. It is based on random cooperative decomposing particle swarm optimization with double mutation mechanism (RCDPSO_DM) for T-S FNNs. Moreover, the proposed integrated learning algorithm, combining the RCDPSO_DM algorithm with a Kalman filtering algorithm, is applied to optimize antecedent and consequent parameters of constructed T-S FNNs. Then, a multi-swarm cooperative immigrating particle swarm algorithm ensemble method is used for intelligent ensemble T-S FNNs with RCDPSO_DM optimization to further improve stability and accuracy of CP variance handling. Finally, two case studies on liver and kidney poisoning variances in osteosarcoma preoperative chemotherapy are used to validate the proposed method. The result demonstrates that intelligent ensemble T-S FNNs based on the RCDPSO_DM achieves superior performances, in terms of stability, efficiency, precision and generalizability, over PSO ensemble of all T-S FNNs with RCDPSO_DM optimization, single T-S FNNs with RCDPSO_DM optimization, standard T-S FNNs, standard Mamdani FNNs and T-S FNNs based on other algorithms (cooperative particle swarm optimization and particle swarm optimization) for CP variance handling. Therefore, it makes CP variance handling more effective. Copyright © 2013 Elsevier Ltd. All rights reserved.

  14. 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.

  15. 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.

  16. 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.

  17. Image Enhancement via Subimage Histogram Equalization Based on Mean and Variance

    PubMed Central

    2017-01-01

    This paper puts forward a novel image enhancement method via Mean and Variance based Subimage Histogram Equalization (MVSIHE), which effectively increases the contrast of the input image with brightness and details well preserved compared with some other methods based on histogram equalization (HE). Firstly, the histogram of input image is divided into four segments based on the mean and variance of luminance component, and the histogram bins of each segment are modified and equalized, respectively. Secondly, the result is obtained via the concatenation of the processed subhistograms. Lastly, the normalization method is deployed on intensity levels, and the integration of the processed image with the input image is performed. 100 benchmark images from a public image database named CVG-UGR-Database are used for comparison with other state-of-the-art methods. The experiment results show that the algorithm can not only enhance image information effectively but also well preserve brightness and details of the original image. PMID:29403529

  18. 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.

  19. 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…

  20. Meta-analysis with missing study-level sample variance data.

    PubMed

    Chowdhry, Amit K; Dworkin, Robert H; McDermott, Michael P

    2016-07-30

    We consider a study-level meta-analysis with a normally distributed outcome variable and possibly unequal study-level variances, where the object of inference is the difference in means between a treatment and control group. A common complication in such an analysis is missing sample variances for some studies. A frequently used approach is to impute the weighted (by sample size) mean of the observed variances (mean imputation). Another approach is to include only those studies with variances reported (complete case analysis). Both mean imputation and complete case analysis are only valid under the missing-completely-at-random assumption, and even then the inverse variance weights produced are not necessarily optimal. We propose a multiple imputation method employing gamma meta-regression to impute the missing sample variances. Our method takes advantage of study-level covariates that may be used to provide information about the missing data. Through simulation studies, we show that multiple imputation, when the imputation model is correctly specified, is superior to competing methods in terms of confidence interval coverage probability and type I error probability when testing a specified group difference. Finally, we describe a similar approach to handling missing variances in cross-over studies. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  1. 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.

  2. 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.

  3. 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

  4. On the Spike Train Variability Characterized by Variance-to-Mean Power Relationship.

    PubMed

    Koyama, Shinsuke

    2015-07-01

    We propose a statistical method for modeling the non-Poisson variability of spike trains observed in a wide range of brain regions. Central to our approach is the assumption that the variance and the mean of interspike intervals are related by a power function characterized by two parameters: the scale factor and exponent. It is shown that this single assumption allows the variability of spike trains to have an arbitrary scale and various dependencies on the firing rate in the spike count statistics, as well as in the interval statistics, depending on the two parameters of the power function. We also propose a statistical model for spike trains that exhibits the variance-to-mean power relationship. Based on this, a maximum likelihood method is developed for inferring the parameters from rate-modulated spike trains. The proposed method is illustrated on simulated and experimental spike trains.

  5. 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.

  6. flowVS: channel-specific variance stabilization in flow cytometry.

    PubMed

    Azad, Ariful; Rajwa, Bartek; Pothen, Alex

    2016-07-28

    Comparing phenotypes of heterogeneous cell populations from multiple biological conditions is at the heart of scientific discovery based on flow cytometry (FC). When the biological signal is measured by the average expression of a biomarker, standard statistical methods require that variance be approximately stabilized in populations to be compared. Since the mean and variance of a cell population are often correlated in fluorescence-based FC measurements, a preprocessing step is needed to stabilize the within-population variances. We present a variance-stabilization algorithm, called flowVS, that removes the mean-variance correlations from cell populations identified in each fluorescence channel. flowVS transforms each channel from all samples of a data set by the inverse hyperbolic sine (asinh) transformation. For each channel, the parameters of the transformation are optimally selected by Bartlett's likelihood-ratio test so that the populations attain homogeneous variances. The optimum parameters are then used to transform the corresponding channels in every sample. flowVS is therefore an explicit variance-stabilization method that stabilizes within-population variances in each channel by evaluating the homoskedasticity of clusters with a likelihood-ratio test. With two publicly available datasets, we show that flowVS removes the mean-variance dependence from raw FC data and makes the within-population variance relatively homogeneous. We demonstrate that alternative transformation techniques such as flowTrans, flowScape, logicle, and FCSTrans might not stabilize variance. Besides flow cytometry, flowVS can also be applied to stabilize variance in microarray data. With a publicly available data set we demonstrate that flowVS performs as well as the VSN software, a state-of-the-art approach developed for microarrays. The homogeneity of variance in cell populations across FC samples is desirable when extracting features uniformly and comparing cell populations with

  7. 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

  8. Twelve tips for successful e-tutoring using electronic portfolios.

    PubMed

    Deketelaere, Ann; Degryse, Jan; De Munter, Agnes; De Leyn, Paul

    2009-06-01

    E-tutoring by means of a digital portfolio offers personal guidance in a context in which regular face-to-face contact between supervisor and student is difficult. However, implementing e-tutoring in practice is not always straightforward. This article investigates the conditions for successful e-tutoring of electronic portfolios. A combination of three methods is used: our own experience with e-tutoring, interviews with 14 tutors using an e-portfolio and the answers on questionnaires by 107 students. We present 12 tips to increase the chances of successful e-tutoring when using electronic portfolios. E-tutoring by means of electronic portfolios can be a feasible alternative in contexts in which face-to-face tutoring is difficult.

  9. 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.

  10. Is There a Common Summary Statistical Process for Representing the Mean and Variance? A Study Using Illustrations of Familiar Items.

    PubMed

    Yang, Yi; Tokita, Midori; Ishiguchi, Akira

    2018-01-01

    A number of studies revealed that our visual system can extract different types of summary statistics, such as the mean and variance, from sets of items. Although the extraction of such summary statistics has been studied well in isolation, the relationship between these statistics remains unclear. In this study, we explored this issue using an individual differences approach. Observers viewed illustrations of strawberries and lollypops varying in size or orientation and performed four tasks in a within-subject design, namely mean and variance discrimination tasks with size and orientation domains. We found that the performances in the mean and variance discrimination tasks were not correlated with each other and demonstrated that extractions of the mean and variance are mediated by different representation mechanisms. In addition, we tested the relationship between performances in size and orientation domains for each summary statistic (i.e. mean and variance) and examined whether each summary statistic has distinct processes across perceptual domains. The results illustrated that statistical summary representations of size and orientation may share a common mechanism for representing the mean and possibly for representing variance. Introspections for each observer performing the tasks were also examined and discussed.

  11. Is There a Common Summary Statistical Process for Representing the Mean and Variance? A Study Using Illustrations of Familiar Items

    PubMed Central

    Yang, Yi; Tokita, Midori; Ishiguchi, Akira

    2018-01-01

    A number of studies revealed that our visual system can extract different types of summary statistics, such as the mean and variance, from sets of items. Although the extraction of such summary statistics has been studied well in isolation, the relationship between these statistics remains unclear. In this study, we explored this issue using an individual differences approach. Observers viewed illustrations of strawberries and lollypops varying in size or orientation and performed four tasks in a within-subject design, namely mean and variance discrimination tasks with size and orientation domains. We found that the performances in the mean and variance discrimination tasks were not correlated with each other and demonstrated that extractions of the mean and variance are mediated by different representation mechanisms. In addition, we tested the relationship between performances in size and orientation domains for each summary statistic (i.e. mean and variance) and examined whether each summary statistic has distinct processes across perceptual domains. The results illustrated that statistical summary representations of size and orientation may share a common mechanism for representing the mean and possibly for representing variance. Introspections for each observer performing the tasks were also examined and discussed. PMID:29399318

  12. A nonlinear bi-level programming approach for product portfolio management.

    PubMed

    Ma, Shuang

    2016-01-01

    Product portfolio management (PPM) is a critical decision-making for companies across various industries in today's competitive environment. Traditional studies on PPM problem have been motivated toward engineering feasibilities and marketing which relatively pay less attention to other competitors' actions and the competitive relations, especially in mathematical optimization domain. The key challenge lies in that how to construct a mathematical optimization model to describe this Stackelberg game-based leader-follower PPM problem and the competitive relations between them. The primary work of this paper is the representation of a decision framework and the optimization model to leverage the PPM problem of leader and follower. A nonlinear, integer bi-level programming model is developed based on the decision framework. Furthermore, a bi-level nested genetic algorithm is put forward to solve this nonlinear bi-level programming model for leader-follower PPM problem. A case study of notebook computer product portfolio optimization is reported. Results and analyses reveal that the leader-follower bi-level optimization model is robust and can empower product portfolio optimization.

  13. 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

  14. 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.

  15. 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.

  16. A simple and exploratory way to determine the mean-variance relationship in generalized linear models.

    PubMed

    Tsou, Tsung-Shan

    2007-03-30

    This paper introduces an exploratory way to determine how variance relates to the mean in generalized linear models. This novel method employs the robust likelihood technique introduced by Royall and Tsou.A urinary data set collected by Ginsberg et al. and the fabric data set analysed by Lee and Nelder are considered to demonstrate the applicability and simplicity of the proposed technique. Application of the proposed method could easily reveal a mean-variance relationship that would generally be left unnoticed, or that would require more complex modelling to detect. Copyright (c) 2006 John Wiley & Sons, Ltd.

  17. 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

  18. Robust Programming Problems Based on the Mean-Variance Model Including Uncertainty Factors

    NASA Astrophysics Data System (ADS)

    Hasuike, Takashi; Ishii, Hiroaki

    2009-01-01

    This paper considers robust programming problems based on the mean-variance model including uncertainty sets and fuzzy factors. Since these problems are not well-defined problems due to fuzzy factors, it is hard to solve them directly. Therefore, introducing chance constraints, fuzzy goals and possibility measures, the proposed models are transformed into the deterministic equivalent problems. Furthermore, in order to solve these equivalent problems efficiently, the solution method is constructed introducing the mean-absolute deviation and doing the equivalent transformations.

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

    NASA Astrophysics Data System (ADS)

    Chen, Wei; Zhang, Wei-Guo

    2010-05-01

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

  20. Estimating synaptic parameters from mean, variance, and covariance in trains of synaptic responses.

    PubMed

    Scheuss, V; Neher, E

    2001-10-01

    Fluctuation analysis of synaptic transmission using the variance-mean approach has been restricted in the past to steady-state responses. Here we extend this method to short repetitive trains of synaptic responses, during which the response amplitudes are not stationary. We consider intervals between trains, long enough so that the system is in the same average state at the beginning of each train. This allows analysis of ensemble means and variances for each response in a train separately. Thus, modifications in synaptic efficacy during short-term plasticity can be attributed to changes in synaptic parameters. In addition, we provide practical guidelines for the analysis of the covariance between successive responses in trains. Explicit algorithms to estimate synaptic parameters are derived and tested by Monte Carlo simulations on the basis of a binomial model of synaptic transmission, allowing for quantal variability, heterogeneity in the release probability, and postsynaptic receptor saturation and desensitization. We find that the combined analysis of variance and covariance is advantageous in yielding an estimate for the number of release sites, which is independent of heterogeneity in the release probability under certain conditions. Furthermore, it allows one to calculate the apparent quantal size for each response in a sequence of stimuli.

  1. Optimizing cost-efficiency in mean exposure assessment - cost functions reconsidered

    PubMed Central

    2011-01-01

    Background Reliable exposure data is a vital concern in medical epidemiology and intervention studies. The present study addresses the needs of the medical researcher to spend monetary resources devoted to exposure assessment with an optimal cost-efficiency, i.e. obtain the best possible statistical performance at a specified budget. A few previous studies have suggested mathematical optimization procedures based on very simple cost models; this study extends the methodology to cover even non-linear cost scenarios. Methods Statistical performance, i.e. efficiency, was assessed in terms of the precision of an exposure mean value, as determined in a hierarchical, nested measurement model with three stages. Total costs were assessed using a corresponding three-stage cost model, allowing costs at each stage to vary non-linearly with the number of measurements according to a power function. Using these models, procedures for identifying the optimally cost-efficient allocation of measurements under a constrained budget were developed, and applied on 225 scenarios combining different sizes of unit costs, cost function exponents, and exposure variance components. Results Explicit mathematical rules for identifying optimal allocation could be developed when cost functions were linear, while non-linear cost functions implied that parts of or the entire optimization procedure had to be carried out using numerical methods. For many of the 225 scenarios, the optimal strategy consisted in measuring on only one occasion from each of as many subjects as allowed by the budget. Significant deviations from this principle occurred if costs for recruiting subjects were large compared to costs for setting up measurement occasions, and, at the same time, the between-subjects to within-subject variance ratio was small. In these cases, non-linearities had a profound influence on the optimal allocation and on the eventual size of the exposure data set. Conclusions The analysis procedures

  2. Optimizing cost-efficiency in mean exposure assessment--cost functions reconsidered.

    PubMed

    Mathiassen, Svend Erik; Bolin, Kristian

    2011-05-21

    Reliable exposure data is a vital concern in medical epidemiology and intervention studies. The present study addresses the needs of the medical researcher to spend monetary resources devoted to exposure assessment with an optimal cost-efficiency, i.e. obtain the best possible statistical performance at a specified budget. A few previous studies have suggested mathematical optimization procedures based on very simple cost models; this study extends the methodology to cover even non-linear cost scenarios. Statistical performance, i.e. efficiency, was assessed in terms of the precision of an exposure mean value, as determined in a hierarchical, nested measurement model with three stages. Total costs were assessed using a corresponding three-stage cost model, allowing costs at each stage to vary non-linearly with the number of measurements according to a power function. Using these models, procedures for identifying the optimally cost-efficient allocation of measurements under a constrained budget were developed, and applied on 225 scenarios combining different sizes of unit costs, cost function exponents, and exposure variance components. Explicit mathematical rules for identifying optimal allocation could be developed when cost functions were linear, while non-linear cost functions implied that parts of or the entire optimization procedure had to be carried out using numerical methods.For many of the 225 scenarios, the optimal strategy consisted in measuring on only one occasion from each of as many subjects as allowed by the budget. Significant deviations from this principle occurred if costs for recruiting subjects were large compared to costs for setting up measurement occasions, and, at the same time, the between-subjects to within-subject variance ratio was small. In these cases, non-linearities had a profound influence on the optimal allocation and on the eventual size of the exposure data set. The analysis procedures developed in the present study can be used

  3. Read-noise characterization of focal plane array detectors via mean-variance analysis.

    PubMed

    Sperline, R P; Knight, A K; Gresham, C A; Koppenaal, D W; Hieftje, G M; Denton, M B

    2005-11-01

    Mean-variance analysis is described as a method for characterization of the read-noise and gain of focal plane array (FPA) detectors, including charge-coupled devices (CCDs), charge-injection devices (CIDs), and complementary metal-oxide-semiconductor (CMOS) multiplexers (infrared arrays). Practical FPA detector characterization is outlined. The nondestructive readout capability available in some CIDs and FPA devices is discussed as a means for signal-to-noise ratio improvement. Derivations of the equations are fully presented to unify understanding of this method by the spectroscopic community.

  4. The dynamics of integrate-and-fire: mean versus variance modulations and dependence on baseline parameters.

    PubMed

    Pressley, Joanna; Troyer, Todd W

    2011-05-01

    The leaky integrate-and-fire (LIF) is the simplest neuron model that captures the essential properties of neuronal signaling. Yet common intuitions are inadequate to explain basic properties of LIF responses to sinusoidal modulations of the input. Here we examine responses to low and moderate frequency modulations of both the mean and variance of the input current and quantify how these responses depend on baseline parameters. Across parameters, responses to modulations in the mean current are low pass, approaching zero in the limit of high frequencies. For very low baseline firing rates, the response cutoff frequency matches that expected from membrane integration. However, the cutoff shows a rapid, supralinear increase with firing rate, with a steeper increase in the case of lower noise. For modulations of the input variance, the gain at high frequency remains finite. Here, we show that the low-frequency responses depend strongly on baseline parameters and derive an analytic condition specifying the parameters at which responses switch from being dominated by low versus high frequencies. Additionally, we show that the resonant responses for variance modulations have properties not expected for common oscillatory resonances: they peak at frequencies higher than the baseline firing rate and persist when oscillatory spiking is disrupted by high noise. Finally, the responses to mean and variance modulations are shown to have a complementary dependence on baseline parameters at higher frequencies, resulting in responses to modulations of Poisson input rates that are independent of baseline input statistics.

  5. Comparison of particle swarm optimization and simulated annealing for locating additional boreholes considering combined variance minimization

    NASA Astrophysics Data System (ADS)

    Soltani-Mohammadi, Saeed; Safa, Mohammad; Mokhtari, Hadi

    2016-10-01

    One of the most important stages in complementary exploration is optimal designing the additional drilling pattern or defining the optimum number and location of additional boreholes. Quite a lot research has been carried out in this regard in which for most of the proposed algorithms, kriging variance minimization as a criterion for uncertainty assessment is defined as objective function and the problem could be solved through optimization methods. Although kriging variance implementation is known to have many advantages in objective function definition, it is not sensitive to local variability. As a result, the only factors evaluated for locating the additional boreholes are initial data configuration and variogram model parameters and the effects of local variability are omitted. In this paper, with the goal of considering the local variability in boundaries uncertainty assessment, the application of combined variance is investigated to define the objective function. Thus in order to verify the applicability of the proposed objective function, it is used to locate the additional boreholes in Esfordi phosphate mine through the implementation of metaheuristic optimization methods such as simulated annealing and particle swarm optimization. Comparison of results from the proposed objective function and conventional methods indicates that the new changes imposed on the objective function has caused the algorithm output to be sensitive to the variations of grade, domain's boundaries and the thickness of mineralization domain. The comparison between the results of different optimization algorithms proved that for the presented case the application of particle swarm optimization is more appropriate than simulated annealing.

  6. 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.

  7. 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

  8. Spatiotemporal characterization of Ensemble Prediction Systems - the Mean-Variance of Logarithms (MVL) diagram

    NASA Astrophysics Data System (ADS)

    Gutiérrez, J. M.; Primo, C.; Rodríguez, M. A.; Fernández, J.

    2008-02-01

    We present a novel approach to characterize and graphically represent the spatiotemporal evolution of ensembles using a simple diagram. To this aim we analyze the fluctuations obtained as differences between each member of the ensemble and the control. The lognormal character of these fluctuations suggests a characterization in terms of the first two moments of the logarithmic transformed values. On one hand, the mean is associated with the exponential growth in time. On the other hand, the variance accounts for the spatial correlation and localization of fluctuations. In this paper we introduce the MVL (Mean-Variance of Logarithms) diagram to intuitively represent the interplay and evolution of these two quantities. We show that this diagram uncovers useful information about the spatiotemporal dynamics of the ensemble. Some universal features of the diagram are also described, associated either with the nonlinear system or with the ensemble method and illustrated using both toy models and numerical weather prediction systems.

  9. 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.

  10. 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.

  11. How Authors and Readers of ePortfolios Make Collaborative Meaning

    ERIC Educational Resources Information Center

    Benander, Ruth; Refaei, Brenda

    2016-01-01

    This article reports on a case study, using a think-aloud approach (Boren & Ramey, 2000; Jaspers, Steen, van den Bos & Geenen, 2004; Kilsdonk et al., 2016), to investigate how different types of audiences interpret ePortfolios. During recorded viewing, students, instructors, and business professionals narrated their experience of reading…

  12. 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.

  13. Gender differences in variance and means on the Naglieri Non-verbal Ability Test: data from the Philippines.

    PubMed

    Vista, Alvin; Care, Esther

    2011-06-01

    Research on gender differences in intelligence has focused mostly on samples from Western countries and empirical evidence on gender differences from Southeast Asia is relatively sparse. This article presents results on gender differences in variance and means on a non-verbal intelligence test using a national sample of public school students from the Philippines. More than 2,700 sixth graders from public schools across the country were tested with the Naglieri Non-verbal Ability Test (NNAT). Variance ratios (VRs) and log-transformed VRs were computed. Proportion ratios for each of the ability levels were also calculated and a chi-square goodness-of-fit test was performed. An analysis of variance was performed to determine the overall gender difference in mean scores as well as within each of three age subgroups. Our data show non-existent or trivial gender difference in mean scores. However, the tails of the distributions show differences between the males and females, with greater variability among males in the upper half of the distribution and greater variability among females in the lower half of the distribution. Descriptions of the results and their implications are discussed. Results on mean score differences support the hypothesis that there are no significant gender differences in cognitive ability. The unusual results regarding differences in variance and the male-female proportion in the tails require more complex investigations. ©2010 The British Psychological Society.

  14. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  16. 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).

  17. Career Portfolios. Practice Application Brief No. 13.

    ERIC Educational Resources Information Center

    Wonacott, Michael E.

    Career portfolios contain evidence of individuals' knowledge and skills and are useful tools in job search and career change, especially now that employers want generalizable workplace skills not well portrayed by traditional means and students are often inept at communicating their skills and knowledge to employers. Career portfolios contain and…

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

    NASA Astrophysics Data System (ADS)

    Scheingraber, Christoph; Käser, Martin; Allmann, Alexander

    2017-04-01

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

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. Applications of polynomial optimization in financial risk investment

    NASA Astrophysics Data System (ADS)

    Zeng, Meilan; Fu, Hongwei

    2017-09-01

    Recently, polynomial optimization has many important applications in optimization, financial economics and eigenvalues of tensor, etc. This paper studies the applications of polynomial optimization in financial risk investment. We consider the standard mean-variance risk measurement model and the mean-variance risk measurement model with transaction costs. We use Lasserre's hierarchy of semidefinite programming (SDP) relaxations to solve the specific cases. The results show that polynomial optimization is effective for some financial optimization problems.

  4. The Expected Sample Variance of Uncorrelated Random Variables with a Common Mean and Some Applications in Unbalanced Random Effects Models

    ERIC Educational Resources Information Center

    Vardeman, Stephen B.; Wendelberger, Joanne R.

    2005-01-01

    There is a little-known but very simple generalization of the standard result that for uncorrelated random variables with common mean [mu] and variance [sigma][superscript 2], the expected value of the sample variance is [sigma][superscript 2]. The generalization justifies the use of the usual standard error of the sample mean in possibly…

  5. Risk of portfolio with simulated returns based on copula model

    NASA Astrophysics Data System (ADS)

    Razak, Ruzanna Ab; Ismail, Noriszura

    2015-02-01

    The commonly used tool for measuring risk of a portfolio with equally weighted stocks is variance-covariance method. Under extreme circumstances, this method leads to significant underestimation of actual risk due to its multivariate normality assumption of the joint distribution of stocks. The purpose of this research is to compare the actual risk of portfolio with the simulated risk of portfolio in which the joint distribution of two return series is predetermined. The data used is daily stock prices from the ASEAN market for the period January 2000 to December 2012. The copula approach is applied to capture the time varying dependence among the return series. The results shows that the chosen copula families are not suitable to present the dependence structures of each bivariate returns. Exception for the Philippines-Thailand pair where by t copula distribution appears to be the appropriate choice to depict its dependence. Assuming that the t copula distribution is the joint distribution of each paired series, simulated returns is generated and value-at-risk (VaR) is then applied to evaluate the risk of each portfolio consisting of two simulated return series. The VaR estimates was found to be symmetrical due to the simulation of returns via elliptical copula-GARCH approach. By comparison, it is found that the actual risks are underestimated for all pairs of portfolios except for Philippines-Thailand. This study was able to show that disregard of the non-normal dependence structure of two series will result underestimation of actual risk of the portfolio.

  6. Statistical methodology for estimating the mean difference in a meta-analysis without study-specific variance information.

    PubMed

    Sangnawakij, Patarawan; Böhning, Dankmar; Adams, Stephen; Stanton, Michael; Holling, Heinz

    2017-04-30

    Statistical inference for analyzing the results from several independent studies on the same quantity of interest has been investigated frequently in recent decades. Typically, any meta-analytic inference requires that the quantity of interest is available from each study together with an estimate of its variability. The current work is motivated by a meta-analysis on comparing two treatments (thoracoscopic and open) of congenital lung malformations in young children. Quantities of interest include continuous end-points such as length of operation or number of chest tube days. As studies only report mean values (and no standard errors or confidence intervals), the question arises how meta-analytic inference can be developed. We suggest two methods to estimate study-specific variances in such a meta-analysis, where only sample means and sample sizes are available in the treatment arms. A general likelihood ratio test is derived for testing equality of variances in two groups. By means of simulation studies, the bias and estimated standard error of the overall mean difference from both methodologies are evaluated and compared with two existing approaches: complete study analysis only and partial variance information. The performance of the test is evaluated in terms of type I error. Additionally, we illustrate these methods in the meta-analysis on comparing thoracoscopic and open surgery for congenital lung malformations and in a meta-analysis on the change in renal function after kidney donation. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  7. Approximate sample size formulas for the two-sample trimmed mean test with unequal variances.

    PubMed

    Luh, Wei-Ming; Guo, Jiin-Huarng

    2007-05-01

    Yuen's two-sample trimmed mean test statistic is one of the most robust methods to apply when variances are heterogeneous. The present study develops formulas for the sample size required for the test. The formulas are applicable for the cases of unequal variances, non-normality and unequal sample sizes. Given the specified alpha and the power (1-beta), the minimum sample size needed by the proposed formulas under various conditions is less than is given by the conventional formulas. Moreover, given a specified size of sample calculated by the proposed formulas, simulation results show that Yuen's test can achieve statistical power which is generally superior to that of the approximate t test. A numerical example is provided.

  8. Variance adaptation in navigational decision making

    NASA Astrophysics Data System (ADS)

    Gershow, Marc; Gepner, Ruben; Wolk, Jason; Wadekar, Digvijay

    Drosophila larvae navigate their environments using a biased random walk strategy. A key component of this strategy is the decision to initiate a turn (change direction) in response to declining conditions. We modeled this decision as the output of a Linear-Nonlinear-Poisson cascade and used reverse correlation with visual and fictive olfactory stimuli to find the parameters of this model. Because the larva responds to changes in stimulus intensity, we used stimuli with uncorrelated normally distributed intensity derivatives, i.e. Brownian processes, and took the stimulus derivative as the input to our LNP cascade. In this way, we were able to present stimuli with 0 mean and controlled variance. We found that the nonlinear rate function depended on the variance in the stimulus input, allowing larvae to respond more strongly to small changes in low-noise compared to high-noise environments. We measured the rate at which the larva adapted its behavior following changes in stimulus variance, and found that larvae adapted more quickly to increases in variance than to decreases, consistent with the behavior of an optimal Bayes estimator. Supported by NIH Grant 1DP2EB022359 and NSF Grant PHY-1455015.

  9. Contrast discrimination: Second responses reveal the relationship between the mean and variance of visual signals

    PubMed Central

    Solomon, Joshua A.

    2007-01-01

    To explain the relationship between first- and second-response accuracies in a detection experiment, Swets, Tanner, and Birdsall [Swets, J., Tanner, W. P., Jr., & Birdsall, T. G. (1961). Decision processes in perception. Psychological Review, 68, 301–340] proposed that the variance of visual signals increased with their means. However, both a low threshold and intrinsic uncertainty produce similar relationships. I measured the relationship between first- and second-response accuracies for suprathreshold contrast discrimination, which is thought to be unaffected by sensory thresholds and intrinsic uncertainty. The results are consistent with a slowly increasing variance. PMID:17961625

  10. Optimizing occupational exposure measurement strategies when estimating the log-scale arithmetic mean value--an example from the reinforced plastics industry.

    PubMed

    Lampa, Erik G; Nilsson, Leif; Liljelind, Ingrid E; Bergdahl, Ingvar A

    2006-06-01

    When assessing occupational exposures, repeated measurements are in most cases required. Repeated measurements are more resource intensive than a single measurement, so careful planning of the measurement strategy is necessary to assure that resources are spent wisely. The optimal strategy depends on the objectives of the measurements. Here, two different models of random effects analysis of variance (ANOVA) are proposed for the optimization of measurement strategies by the minimization of the variance of the estimated log-transformed arithmetic mean value of a worker group, i.e. the strategies are optimized for precise estimation of that value. The first model is a one-way random effects ANOVA model. For that model it is shown that the best precision in the estimated mean value is always obtained by including as many workers as possible in the sample while restricting the number of replicates to two or at most three regardless of the size of the variance components. The second model introduces the 'shared temporal variation' which accounts for those random temporal fluctuations of the exposure that the workers have in common. It is shown for that model that the optimal sample allocation depends on the relative sizes of the between-worker component and the shared temporal component, so that if the between-worker component is larger than the shared temporal component more workers should be included in the sample and vice versa. The results are illustrated graphically with an example from the reinforced plastics industry. If there exists a shared temporal variation at a workplace, that variability needs to be accounted for in the sampling design and the more complex model is recommended.

  11. The mean-variance relationship reveals two possible strategies for dynamic brain connectivity analysis in fMRI.

    PubMed

    Thompson, William H; Fransson, Peter

    2015-01-01

    When studying brain connectivity using fMRI, signal intensity time-series are typically correlated with each other in time to compute estimates of the degree of interaction between different brain regions and/or networks. In the static connectivity case, the problem of defining which connections that should be considered significant in the analysis can be addressed in a rather straightforward manner by a statistical thresholding that is based on the magnitude of the correlation coefficients. More recently, interest has come to focus on the dynamical aspects of brain connectivity and the problem of deciding which brain connections that are to be considered relevant in the context of dynamical changes in connectivity provides further options. Since we, in the dynamical case, are interested in changes in connectivity over time, the variance of the correlation time-series becomes a relevant parameter. In this study, we discuss the relationship between the mean and variance of brain connectivity time-series and show that by studying the relation between them, two conceptually different strategies to analyze dynamic functional brain connectivity become available. Using resting-state fMRI data from a cohort of 46 subjects, we show that the mean of fMRI connectivity time-series scales negatively with its variance. This finding leads to the suggestion that magnitude- versus variance-based thresholding strategies will induce different results in studies of dynamic functional brain connectivity. Our assertion is exemplified by showing that the magnitude-based strategy is more sensitive to within-resting-state network (RSN) connectivity compared to between-RSN connectivity whereas the opposite holds true for a variance-based analysis strategy. The implications of our findings for dynamical functional brain connectivity studies are discussed.

  12. Robust Least-Squares Support Vector Machine With Minimization of Mean and Variance of Modeling Error.

    PubMed

    Lu, Xinjiang; Liu, Wenbo; Zhou, Chuang; Huang, Minghui

    2017-06-13

    The least-squares support vector machine (LS-SVM) is a popular data-driven modeling method and has been successfully applied to a wide range of applications. However, it has some disadvantages, including being ineffective at handling non-Gaussian noise as well as being sensitive to outliers. In this paper, a robust LS-SVM method is proposed and is shown to have more reliable performance when modeling a nonlinear system under conditions where Gaussian or non-Gaussian noise is present. The construction of a new objective function allows for a reduction of the mean of the modeling error as well as the minimization of its variance, and it does not constrain the mean of the modeling error to zero. This differs from the traditional LS-SVM, which uses a worst-case scenario approach in order to minimize the modeling error and constrains the mean of the modeling error to zero. In doing so, the proposed method takes the modeling error distribution information into consideration and is thus less conservative and more robust in regards to random noise. A solving method is then developed in order to determine the optimal parameters for the proposed robust LS-SVM. An additional analysis indicates that the proposed LS-SVM gives a smaller weight to a large-error training sample and a larger weight to a small-error training sample, and is thus more robust than the traditional LS-SVM. The effectiveness of the proposed robust LS-SVM is demonstrated using both artificial and real life cases.

  13. The neutron-gamma Feynman variance to mean approach: Gamma detection and total neutron-gamma detection (theory and practice)

    NASA Astrophysics Data System (ADS)

    Chernikova, Dina; Axell, Kåre; Avdic, Senada; Pázsit, Imre; Nordlund, Anders; Allard, Stefan

    2015-05-01

    Two versions of the neutron-gamma variance to mean (Feynman-alpha method or Feynman-Y function) formula for either gamma detection only or total neutron-gamma detection, respectively, are derived and compared in this paper. The new formulas have particular importance for detectors of either gamma photons or detectors sensitive to both neutron and gamma radiation. If applied to a plastic or liquid scintillation detector, the total neutron-gamma detection Feynman-Y expression corresponds to a situation where no discrimination is made between neutrons and gamma particles. The gamma variance to mean formulas are useful when a detector of only gamma radiation is used or when working with a combined neutron-gamma detector at high count rates. The theoretical derivation is based on the Chapman-Kolmogorov equation with the inclusion of general reactions and corresponding intensities for neutrons and gammas, but with the inclusion of prompt reactions only. A one energy group approximation is considered. The comparison of the two different theories is made by using reaction intensities obtained in MCNPX simulations with a simplified geometry for two scintillation detectors and a 252Cf-source. In addition, the variance to mean ratios, neutron, gamma and total neutron-gamma are evaluated experimentally for a weak 252Cf neutron-gamma source, a 137Cs random gamma source and a 22Na correlated gamma source. Due to the focus being on the possibility of using neutron-gamma variance to mean theories for both reactor and safeguards applications, we limited the present study to the general analytical expressions for Feynman-alpha formulas.

  14. 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.

  15. Optimal Auxiliary-Covariate Based Two-Phase Sampling Design for Semiparametric Efficient Estimation of a Mean or Mean Difference, with Application to Clinical Trials

    PubMed Central

    Gilbert, Peter B.; Yu, Xuesong; Rotnitzky, Andrea

    2014-01-01

    To address the objective in a clinical trial to estimate the mean or mean difference of an expensive endpoint Y, one approach employs a two-phase sampling design, wherein inexpensive auxiliary variables W predictive of Y are measured in everyone, Y is measured in a random sample, and the semi-parametric efficient estimator is applied. This approach is made efficient by specifying the phase-two selection probabilities as optimal functions of the auxiliary variables and measurement costs. While this approach is familiar to survey samplers, it apparently has seldom been used in clinical trials, and several novel results practicable for clinical trials are developed. Simulations are performed to identify settings where the optimal approach significantly improves efficiency compared to approaches in current practice. Proofs and R code are provided. The optimality results are developed to design an HIV vaccine trial, with objective to compare the mean “importance-weighted” breadth (Y) of the T cell response between randomized vaccine groups. The trial collects an auxiliary response (W) highly predictive of Y, and measures Y in the optimal subset. We show that the optimal design-estimation approach can confer anywhere between absent and large efficiency gain (up to 24% in the examples) compared to the approach with the same efficient estimator but simple random sampling, where greater variability in the cost-standardized conditional variance of Y given W yields greater efficiency gains. Accurate estimation of E[Y∣W] is important for realizing the efficiency gain, which is aided by an ample phase-two sample and by using a robust fitting method. PMID:24123289

  16. 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.

  17. 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.

  18. Portfolio Dietary Pattern and Cardiovascular Disease: A Systematic Review and Meta-Analysis of Controlled Trials.

    PubMed

    Chiavaroli, Laura; Nishi, Stephanie K; Khan, Tauseef A; Braunstein, Catherine R; Glenn, Andrea J; Mejia, Sonia Blanco; Rahelić, Dario; Kahleová, Hana; Salas-Salvadó, Jordi; Jenkins, David J A; Kendall, Cyril W C; Sievenpiper, John L

    2018-05-25

    The evidence for the Portfolio dietary pattern, a plant-based dietary pattern that combines recognized cholesterol-lowering foods (nuts, plant protein, viscous fibre, plant sterols), has not been summarized. To update the European Association for the Study of Diabetes clinical practice guidelines for nutrition therapy, we conducted a systematic review and meta-analysis of controlled trials using GRADE of the effect of the Portfolio dietary pattern on the primary therapeutic lipid target for cardiovascular disease prevention, low-density lipoprotein cholesterol (LDL-C), and other established cardiometabolic risk factors. We searched MEDLINE, EMBASE, and The Cochrane Library through April 19, 2018. We included controlled trials ≥ 3-weeks assessing the effect of the Portfolio dietary pattern on cardiometabolic risk factors compared with an energy-matched control diet free of Portfolio dietary pattern components. Two independent reviewers extracted data and assessed risk of bias. The primary outcome was LDL-C. Data were pooled using the generic inverse-variance method and expressed as mean differences (MDs) with 95% confidence intervals (CIs). Heterogeneity was assessed (Cochran Q statistic) and quantified (I 2 -statistic). GRADE assessed the certainty of the evidence. Eligibility criteria were met by 7 trial comparisons in 439 participants with hyperlipidemia, in which the Portfolio dietary pattern was given on a background of a National Cholesterol Education Program (NCEP) Step II diet. The combination of a portfolio dietary pattern and NCEP Step II diet significantly reduced the primary outcome LDL-C by ~17% (MD, -0.73mmol/L, [95% CI, -0.89 to -0.56 mmol/L]) as well as non-high-density lipoprotein cholesterol, apolipoprotein B, total cholesterol, triglycerides, systolic and diastolic blood pressure, C-reactive protein, and estimated 10-year coronary heart disease (CHD) risk, compared with an NCEP Step 2 diet alone (P<0.05). There was no effect on high

  19. 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…

  20. 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.

  1. 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

  2. The variance of length of stay and the optimal DRG outlier payments.

    PubMed

    Felder, Stefan

    2009-09-01

    Prospective payment schemes in health care often include supply-side insurance for cost outliers. In hospital reimbursement, prospective payments for patient discharges, based on their classification into diagnosis related group (DRGs), are complemented by outlier payments for long stay patients. The outlier scheme fixes the length of stay (LOS) threshold, constraining the profit risk of the hospitals. In most DRG systems, this threshold increases with the standard deviation of the LOS distribution. The present paper addresses the adequacy of this DRG outlier threshold rule for risk-averse hospitals with preferences depending on the expected value and the variance of profits. It first shows that the optimal threshold solves the hospital's tradeoff between higher profit risk and lower premium loading payments. It then demonstrates for normally distributed truncated LOS that the optimal outlier threshold indeed decreases with an increase in the standard deviation.

  3. 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.

  4. Assessing differential gene expression with small sample sizes in oligonucleotide arrays using a mean-variance model.

    PubMed

    Hu, Jianhua; Wright, Fred A

    2007-03-01

    The identification of the genes that are differentially expressed in two-sample microarray experiments remains a difficult problem when the number of arrays is very small. We discuss the implications of using ordinary t-statistics and examine other commonly used variants. For oligonucleotide arrays with multiple probes per gene, we introduce a simple model relating the mean and variance of expression, possibly with gene-specific random effects. Parameter estimates from the model have natural shrinkage properties that guard against inappropriately small variance estimates, and the model is used to obtain a differential expression statistic. A limiting value to the positive false discovery rate (pFDR) for ordinary t-tests provides motivation for our use of the data structure to improve variance estimates. Our approach performs well compared to other proposed approaches in terms of the false discovery rate.

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

    ERIC Educational Resources Information Center

    Buzzetto-More, Nicole; Alade, Ayodele

    2008-01-01

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

  6. Optimal auxiliary-covariate-based two-phase sampling design for semiparametric efficient estimation of a mean or mean difference, with application to clinical trials.

    PubMed

    Gilbert, Peter B; Yu, Xuesong; Rotnitzky, Andrea

    2014-03-15

    To address the objective in a clinical trial to estimate the mean or mean difference of an expensive endpoint Y, one approach employs a two-phase sampling design, wherein inexpensive auxiliary variables W predictive of Y are measured in everyone, Y is measured in a random sample, and the semiparametric efficient estimator is applied. This approach is made efficient by specifying the phase two selection probabilities as optimal functions of the auxiliary variables and measurement costs. While this approach is familiar to survey samplers, it apparently has seldom been used in clinical trials, and several novel results practicable for clinical trials are developed. We perform simulations to identify settings where the optimal approach significantly improves efficiency compared to approaches in current practice. We provide proofs and R code. The optimality results are developed to design an HIV vaccine trial, with objective to compare the mean 'importance-weighted' breadth (Y) of the T-cell response between randomized vaccine groups. The trial collects an auxiliary response (W) highly predictive of Y and measures Y in the optimal subset. We show that the optimal design-estimation approach can confer anywhere between absent and large efficiency gain (up to 24 % in the examples) compared to the approach with the same efficient estimator but simple random sampling, where greater variability in the cost-standardized conditional variance of Y given W yields greater efficiency gains. Accurate estimation of E[Y | W] is important for realizing the efficiency gain, which is aided by an ample phase two sample and by using a robust fitting method. Copyright © 2013 John Wiley & Sons, Ltd.

  7. 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.

  8. 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…

  9. 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)

  10. Scale-dependent portfolio effects explain growth inflation and volatility reduction in landscape demography

    PubMed Central

    2017-01-01

    Population demography is central to fundamental ecology and for predicting range shifts, decline of threatened species, and spread of invasive organisms. There is a mismatch between most demographic work, carried out on few populations and at local scales, and the need to predict dynamics at landscape and regional scales. Inspired by concepts from landscape ecology and Markowitz’s portfolio theory, we develop a landscape portfolio platform to quantify and predict the behavior of multiple populations, scaling up the expectation and variance of the dynamics of an ensemble of populations. We illustrate this framework using a 35-y time series on gypsy moth populations. We demonstrate the demography accumulation curve in which the collective growth of the ensemble depends on the number of local populations included, highlighting a minimum but adequate number of populations for both regional-scale persistence and cross-scale inference. The attainable set of landscape portfolios further suggests tools for regional population management for both threatened and invasive species. PMID:29109261

  11. 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.

  12. Portfolios in Practice: What Is a Portfolio?

    ERIC Educational Resources Information Center

    Arter, Judith A.

    A consortium effort sponsored by the Northwest Regional Evaluation Association has arrived at a workable definition of a portfolio that takes into account the viewpoints of teachers and those interested in large-scale assessment. The modified definition states that: "A student portfolio is a purposeful collection of student work that tells…

  13. Application of E-Portfolio System to Enhance Teacher Professional Development

    ERIC Educational Resources Information Center

    Liao, Chin-Wen

    2011-01-01

    This study focuses on the meaning, applications and future development of e-teaching portfolios as an attempt to highlight the important role it plays in the "post-modern teaching practice mode". For the purpose of enhancing teacher professional development, application of the teaching portfolio system in the post-modern teacher qualification…

  14. Calibrating nadir striped artifacts in a multibeam backscatter image using the equal mean-variance fitting model

    NASA Astrophysics Data System (ADS)

    Yang, Fanlin; Zhao, Chunxia; Zhang, Kai; Feng, Chengkai; Ma, Yue

    2017-07-01

    Acoustic seafloor classification with multibeam backscatter measurements is an attractive approach for mapping seafloor properties over a large area. However, artifacts in the multibeam backscatter measurements prevent accurate characterization of the seafloor. In particular, the backscatter level is extremely strong and highly variable in the near-nadir region due to the specular echo phenomenon. Consequently, striped artifacts emerge in the backscatter image, which can degrade the classification accuracy. This study focuses on the striped artifacts in multibeam backscatter images. To this end, a calibration algorithm based on equal mean-variance fitting is developed. By fitting the local shape of the angular response curve, the striped artifacts are compressed and moved according to the relations between the mean and variance in the near-nadir and off-nadir region. The algorithm utilized the measured data of near-nadir region and retained the basic shape of the response curve. The experimental results verify the high performance of the proposed method.

  15. 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.

  16. 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.

  17. Optimal design of minimum mean-square error noise reduction algorithms using the simulated annealing technique.

    PubMed

    Bai, Mingsian R; Hsieh, Ping-Ju; Hur, Kur-Nan

    2009-02-01

    The performance of the minimum mean-square error noise reduction (MMSE-NR) algorithm in conjunction with time-recursive averaging (TRA) for noise estimation is found to be very sensitive to the choice of two recursion parameters. To address this problem in a more systematic manner, this paper proposes an optimization method to efficiently search the optimal parameters of the MMSE-TRA-NR algorithms. The objective function is based on a regression model, whereas the optimization process is carried out with the simulated annealing algorithm that is well suited for problems with many local optima. Another NR algorithm proposed in the paper employs linear prediction coding as a preprocessor for extracting the correlated portion of human speech. Objective and subjective tests were undertaken to compare the optimized MMSE-TRA-NR algorithm with several conventional NR algorithms. The results of subjective tests were processed by using analysis of variance to justify the statistic significance. A post hoc test, Tukey's Honestly Significant Difference, was conducted to further assess the pairwise difference between the NR algorithms.

  18. Improving Workplace-Based Assessment and Feedback by an E-Portfolio Enhanced with Learning Analytics

    ERIC Educational Resources Information Center

    van der Schaaf, Marieke; Donkers, Jeroen; Slof, Bert; Moonen-van Loon, Joyce; van Tartwijk, Jan; Driessen, Eric; Badii, Atta; Serban, Ovidiu; Ten Cate, Olle

    2017-01-01

    Electronic portfolios (E-portfolios) are crucial means for workplace-based assessment and feedback. Although E-portfolios provide a useful approach to view each learner's progress, so far options for personalized feedback and potential data about a learner's performances at the workplace often remain unexploited. This paper advocates that…

  19. 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.

  20. 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

  1. Heteroscedastic Tests Statistics for One-Way Analysis of Variance: The Trimmed Means and Hall's Transformation Conjunction

    ERIC Educational Resources Information Center

    Luh, Wei-Ming; Guo, Jiin-Huarng

    2005-01-01

    To deal with nonnormal and heterogeneous data for the one-way fixed effect analysis of variance model, the authors adopted a trimmed means method in conjunction with Hall's invertible transformation into a heteroscedastic test statistic (Alexander-Govern test or Welch test). The results of simulation experiments showed that the proposed technique…

  2. 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

  3. 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.

  4. 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.

  5. Quantifying Systemic Risk by Solutions of the Mean-Variance Risk Model.

    PubMed

    Jurczyk, Jan; Eckrot, Alexander; Morgenstern, Ingo

    2016-01-01

    The world is still recovering from the financial crisis peaking in September 2008. The triggering event was the bankruptcy of Lehman Brothers. To detect such turmoils, one can investigate the time-dependent behaviour of correlations between assets or indices. These cross-correlations have been connected to the systemic risks within markets by several studies in the aftermath of this crisis. We study 37 different US indices which cover almost all aspects of the US economy and show that monitoring an average investor's behaviour can be used to quantify times of increased risk. In this paper the overall investing strategy is approximated by the ground-states of the mean-variance model along the efficient frontier bound to real world constraints. Changes in the behaviour of the average investor is utlilized as a early warning sign.

  6. The Inheritance of Metabolic Flux: Expressions for the within-Sibship Mean and Variance Given the Parental Genotypes

    PubMed Central

    Ward, P. J.

    1990-01-01

    Recent developments have related quantitative trait expression to metabolic flux. The present paper investigates some implications of this for statistical aspects of polygenic inheritance. Expressions are derived for the within-sibship genetic mean and genetic variance of metabolic flux given a pair of parental, diploid, n-locus genotypes. These are exact and hold for arbitrary numbers of gene loci, arbitrary allelic values at each locus, and for arbitrary recombination fractions between adjacent gene loci. The within-sibship, genetic variance is seen to be simply a measure of parental heterozygosity plus a measure of the degree of linkage coupling within the parental genotypes. Approximations are given for the within-sibship phenotypic mean and variance of metabolic flux. These results are applied to the problem of attaining adequate statistical power in a test of association between allozymic variation and inter-individual variation in metabolic flux. Simulations indicate that statistical power can be greatly increased by augmenting the data with predictions and observations on progeny statistics in relation to parental allozyme genotypes. Adequate power may thus be attainable at small sample sizes, and when allozymic variation is scored at a only small fraction of the total set of loci whose catalytic products determine the flux. PMID:2379825

  7. 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

  8. VARIANCE ANISOTROPY IN KINETIC PLASMAS

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

    Parashar, Tulasi N.; Matthaeus, William H.; Oughton, Sean

    Solar wind fluctuations admit well-documented anisotropies of the variance matrix, or polarization, related to the mean magnetic field direction. Typically, one finds a ratio of perpendicular variance to parallel variance of the order of 9:1 for the magnetic field. Here we study the question of whether a kinetic plasma spontaneously generates and sustains parallel variances when initiated with only perpendicular variance. We find that parallel variance grows and saturates at about 5% of the perpendicular variance in a few nonlinear times irrespective of the Reynolds number. For sufficiently large systems (Reynolds numbers) the variance approaches values consistent with the solarmore » wind observations.« less

  9. 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...

  10. Exploring the meteorological potential for planning a high performance European electricity super-grid: optimal power capacity distribution among countries

    NASA Astrophysics Data System (ADS)

    Santos-Alamillos, Francisco J.; Brayshaw, David J.; Methven, John; Thomaidis, Nikolaos S.; Ruiz-Arias, José A.; Pozo-Vázquez, David

    2017-11-01

    The concept of a European super-grid for electricity presents clear advantages for a reliable and affordable renewable power production (photovoltaics and wind). Based on the mean-variance portfolio optimization analysis, we explore optimal scenarios for the allocation of new renewable capacity at national level in order to provide to energy decision-makers guidance about which regions should be mostly targeted to either maximize total production or reduce its day-to-day variability. The results show that the existing distribution of renewable generation capacity across Europe is far from optimal: i.e. a ‘better’ spatial distribution of resources could have been achieved with either a ~31% increase in mean power supply (for the same level of day-to-day variability) or a ~37.5% reduction in day-to-day variability (for the same level of mean productivity). Careful planning of additional increments in renewable capacity at the European level could, however, act to significantly ameliorate this deficiency. The choice of where to deploy resources depends, however, on the objective being pursued—if the goal is to maximize average output, then new capacity is best allocated in the countries with highest resources, whereas investment in additional capacity in a north/south dipole pattern across Europe would act to most reduce daily variations and thus decrease the day-to-day volatility of renewable power supply.

  11. Minimum variance optimal rate allocation for multiplexed H.264/AVC bitstreams.

    PubMed

    Tagliasacchi, Marco; Valenzise, Giuseppe; Tubaro, Stefano

    2008-07-01

    Consider the problem of transmitting multiple video streams to fulfill a constant bandwidth constraint. The available bit budget needs to be distributed across the sequences in order to meet some optimality criteria. For example, one might want to minimize the average distortion or, alternatively, minimize the distortion variance, in order to keep almost constant quality among the encoded sequences. By working in the rho-domain, we propose a low-delay rate allocation scheme that, at each time instant, provides a closed form solution for either the aforementioned problems. We show that minimizing the distortion variance instead of the average distortion leads, for each of the multiplexed sequences, to a coding penalty less than 0.5 dB, in terms of average PSNR. In addition, our analysis provides an explicit relationship between model parameters and this loss. In order to smooth the distortion also along time, we accommodate a shared encoder buffer to compensate for rate fluctuations. Although the proposed scheme is general, and it can be adopted for any video and image coding standard, we provide experimental evidence by transcoding bitstreams encoded using the state-of-the-art H.264/AVC standard. The results of our simulations reveal that is it possible to achieve distortion smoothing both in time and across the sequences, without sacrificing coding efficiency.

  12. Alternatives: the right medicine for your portfolio?

    PubMed

    Doody, Dennis

    2006-01-01

    Because they often play an active role in developing their portfolio companies' strategies, private capital investment managers can add significant value to companies in their portfolio. The relative inefficiency of private capital markets can give savvy investors an edge that they can not so easily gain in the more efficient public markets. Originally created as a means to reduce volatility, hedge funds should not be seen as the high-risk bets that they are widely perceived to be. Most hedge funds actually are concerned with protecting downside risk.

  13. 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.

  14. Longitudinal design considerations to optimize power to detect variances and covariances among rates of change: Simulation results based on actual longitudinal studies

    PubMed Central

    Rast, Philippe; Hofer, Scott M.

    2014-01-01

    We investigated the power to detect variances and covariances in rates of change in the context of existing longitudinal studies using linear bivariate growth curve models. Power was estimated by means of Monte Carlo simulations. Our findings show that typical longitudinal study designs have substantial power to detect both variances and covariances among rates of change in a variety of cognitive, physical functioning, and mental health outcomes. We performed simulations to investigate the interplay among number and spacing of occasions, total duration of the study, effect size, and error variance on power and required sample size. The relation between growth rate reliability (GRR) and effect size to the sample size required to detect power ≥ .80 was non-linear, with rapidly decreasing sample sizes needed as GRR increases. The results presented here stand in contrast to previous simulation results and recommendations (Hertzog, Lindenberger, Ghisletta, & von Oertzen, 2006; Hertzog, von Oertzen, Ghisletta, & Lindenberger, 2008; von Oertzen, Ghisletta, & Lindenberger, 2010), which are limited due to confounds between study length and number of waves, error variance with GCR, and parameter values which are largely out of bounds of actual study values. Power to detect change is generally low in the early phases (i.e. first years) of longitudinal studies but can substantially increase if the design is optimized. We recommend additional assessments, including embedded intensive measurement designs, to improve power in the early phases of long-term longitudinal studies. PMID:24219544

  15. 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.

  16. 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.

  17. Validity and reliability of portfolio assessment of student competence in two dental school populations: a four-year study.

    PubMed

    Gadbury-Amyot, Cynthia C; McCracken, Michael S; Woldt, Janet L; Brennan, Robert L

    2014-05-01

    The purpose of this study was to empirically investigate the validity and reliability of portfolio assessment in two U.S. dental schools using a unified framework for validity. In the process of validation, it is not the test that is validated but rather the claims (interpretations and uses) about test scores that are validated. Kane's argument-based validation framework provided the structure for reporting results where validity claims are followed by evidence to support the argument. This multivariate generalizability theory study found that the greatest source of variance was attributable to faculty raters, suggesting that portfolio assessment would benefit from two raters' evaluating each portfolio independently. The results are generally supportive of holistic scoring, but analytical scoring deserves further research. Correlational analyses between student portfolios and traditional measures of student competence and readiness for licensure resulted in significant correlations between portfolios and National Board Dental Examination Part I (r=0.323, p<0.01) and Part II scores (r=0.268, p<0.05) and small and non-significant correlations with grade point average and scores on the Western Regional Examining Board (WREB) exam. It is incumbent upon the users of portfolio assessment to determine if the claims and evidence arguments set forth in this study support the proposed claims for and decisions about portfolio assessment in their respective institutions.

  18. 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…

  19. 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.

  20. Quantifying Systemic Risk by Solutions of the Mean-Variance Risk Model

    PubMed Central

    Morgenstern, Ingo

    2016-01-01

    The world is still recovering from the financial crisis peaking in September 2008. The triggering event was the bankruptcy of Lehman Brothers. To detect such turmoils, one can investigate the time-dependent behaviour of correlations between assets or indices. These cross-correlations have been connected to the systemic risks within markets by several studies in the aftermath of this crisis. We study 37 different US indices which cover almost all aspects of the US economy and show that monitoring an average investor’s behaviour can be used to quantify times of increased risk. In this paper the overall investing strategy is approximated by the ground-states of the mean-variance model along the efficient frontier bound to real world constraints. Changes in the behaviour of the average investor is utlilized as a early warning sign. PMID:27351482

  1. Switching portfolios.

    PubMed

    Singer, Y

    1997-08-01

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

  2. Portfolio langagier en francais (Language Portfolios in French).

    ERIC Educational Resources Information Center

    Laplante, Bernard; Christiansen, Helen

    2001-01-01

    Suggests that first-year college students learning French should create a language portfolio that contains documents that illustrate what they have learned in French, along with a brief statement of what linguistic skill the document demonstrates. The goal of the portfolio is to make students more aware of their own learning, their strengths, and…

  3. 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

  4. 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

  5. Multilevel covariance regression with correlated random effects in the mean and variance structure.

    PubMed

    Quintero, Adrian; Lesaffre, Emmanuel

    2017-09-01

    Multivariate regression methods generally assume a constant covariance matrix for the observations. In case a heteroscedastic model is needed, the parametric and nonparametric covariance regression approaches can be restrictive in the literature. We propose a multilevel regression model for the mean and covariance structure, including random intercepts in both components and allowing for correlation between them. The implied conditional covariance function can be different across clusters as a result of the random effect in the variance structure. In addition, allowing for correlation between the random intercepts in the mean and covariance makes the model convenient for skewedly distributed responses. Furthermore, it permits us to analyse directly the relation between the mean response level and the variability in each cluster. Parameter estimation is carried out via Gibbs sampling. We compare the performance of our model to other covariance modelling approaches in a simulation study. Finally, the proposed model is applied to the RN4CAST dataset to identify the variables that impact burnout of nurses in Belgium. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. 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

  7. Validation by simulation of a clinical trial model using the standardized mean and variance criteria.

    PubMed

    Abbas, Ismail; Rovira, Joan; Casanovas, Josep

    2006-12-01

    To develop and validate a model of a clinical trial that evaluates the changes in cholesterol level as a surrogate marker for lipodystrophy in HIV subjects under alternative antiretroviral regimes, i.e., treatment with Protease Inhibitors vs. a combination of nevirapine and other antiretroviral drugs. Five simulation models were developed based on different assumptions, on treatment variability and pattern of cholesterol reduction over time. The last recorded cholesterol level, the difference from the baseline, the average difference from the baseline and level evolution, are the considered endpoints. Specific validation criteria based on a 10% minus or plus standardized distance in means and variances were used to compare the real and the simulated data. The validity criterion was met by all models for considered endpoints. However, only two models met the validity criterion when all endpoints were considered. The model based on the assumption that within-subjects variability of cholesterol levels changes over time is the one that minimizes the validity criterion, standardized distance equal to or less than 1% minus or plus. Simulation is a useful technique for calibration, estimation, and evaluation of models, which allows us to relax the often overly restrictive assumptions regarding parameters required by analytical approaches. The validity criterion can also be used to select the preferred model for design optimization, until additional data are obtained allowing an external validation of the model.

  8. Portfolio Assessment.

    ERIC Educational Resources Information Center

    Dagavarian, Debra A.

    The portfolio assessment process at Thomas A. Edison State College is described in this report. Through portfolio assessment, the school helps students identify and gain credit for college-level skills and knowledge acquired through work, volunteer activities, independent reading, military or corporate training, and life experiences that may be…

  9. Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance.

    PubMed

    Poplová, Michaela; Sovka, Pavel; Cifra, Michal

    2017-01-01

    Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal.

  10. Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance

    PubMed Central

    Poplová, Michaela; Sovka, Pavel

    2017-01-01

    Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal. PMID:29216207

  11. Gender Differences in Variance and Means on the Naglieri Non-Verbal Ability Test: Data from the Philippines

    ERIC Educational Resources Information Center

    Vista, Alvin; Care, Esther

    2011-01-01

    Background: Research on gender differences in intelligence has focused mostly on samples from Western countries and empirical evidence on gender differences from Southeast Asia is relatively sparse. Aims: This article presents results on gender differences in variance and means on a non-verbal intelligence test using a national sample of public…

  12. Power and Sample Size Calculations for Testing Linear Combinations of Group Means under Variance Heterogeneity with Applications to Meta and Moderation Analyses

    ERIC Educational Resources Information Center

    Shieh, Gwowen; Jan, Show-Li

    2015-01-01

    The general formulation of a linear combination of population means permits a wide range of research questions to be tested within the context of ANOVA. However, it has been stressed in many research areas that the homogeneous variances assumption is frequently violated. To accommodate the heterogeneity of variance structure, the…

  13. 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.

  14. Optimal design criteria - prediction vs. parameter estimation

    NASA Astrophysics Data System (ADS)

    Waldl, Helmut

    2014-05-01

    G-optimality is a popular design criterion for optimal prediction, it tries to minimize the kriging variance over the whole design region. A G-optimal design minimizes the maximum variance of all predicted values. If we use kriging methods for prediction it is self-evident to use the kriging variance as a measure of uncertainty for the estimates. Though the computation of the kriging variance and even more the computation of the empirical kriging variance is computationally very costly and finding the maximum kriging variance in high-dimensional regions can be time demanding such that we cannot really find the G-optimal design with nowadays available computer equipment in practice. We cannot always avoid this problem by using space-filling designs because small designs that minimize the empirical kriging variance are often non-space-filling. D-optimality is the design criterion related to parameter estimation. A D-optimal design maximizes the determinant of the information matrix of the estimates. D-optimality in terms of trend parameter estimation and D-optimality in terms of covariance parameter estimation yield basically different designs. The Pareto frontier of these two competing determinant criteria corresponds with designs that perform well under both criteria. Under certain conditions searching the G-optimal design on the above Pareto frontier yields almost as good results as searching the G-optimal design in the whole design region. In doing so the maximum of the empirical kriging variance has to be computed only a few times though. The method is demonstrated by means of a computer simulation experiment based on data provided by the Belgian institute Management Unit of the North Sea Mathematical Models (MUMM) that describe the evolution of inorganic and organic carbon and nutrients, phytoplankton, bacteria and zooplankton in the Southern Bight of the North Sea.

  15. Electronic portfolios in nursing education: a review of the literature.

    PubMed

    Green, Janet; Wyllie, Aileen; Jackson, Debra

    2014-01-01

    As health professionals, nurses are responsible for staying abreast of current professional knowledge and managing their own career, professional growth and development, and ideally, practices to support these activities should start during their student years. Interest in electronic or eportfolios is gathering momentum as educationalists explore their potential as a strategy for fostering lifelong learning and enhancing on-going personal and professional development. In this paper, we present an overview of e-portfolios and their application to nurse education, highlighting potential benefits and considerations of useage. We argue that the e-portfolio can represent an authentic means of assessing cognitive, reflective and affective skills. Furthermore, the e-portfolio provides a means through which nurses can record and provide evidence of skills, achievements, experience, professional development and on-going learning, not only for themselves, but for the information and scrutiny of registration boards, employers, managers and peers. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

  16. 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.

  17. Heritable Environmental Variance Causes Nonlinear Relationships Between Traits: Application to Birth Weight and Stillbirth of Pigs

    PubMed Central

    Mulder, Herman A.; Hill, William G.; Knol, Egbert F.

    2015-01-01

    There is recent evidence from laboratory experiments and analysis of livestock populations that not only the phenotype itself, but also its environmental variance, is under genetic control. Little is known about the relationships between the environmental variance of one trait and mean levels of other traits, however. A genetic covariance between these is expected to lead to nonlinearity between them, for example between birth weight and survival of piglets, where animals of extreme weights have lower survival. The objectives were to derive this nonlinear relationship analytically using multiple regression and apply it to data on piglet birth weight and survival. This study provides a framework to study such nonlinear relationships caused by genetic covariance of environmental variance of one trait and the mean of the other. It is shown that positions of phenotypic and genetic optima may differ and that genetic relationships are likely to be more curvilinear than phenotypic relationships, dependent mainly on the environmental correlation between these traits. Genetic correlations may change if the population means change relative to the optimal phenotypes. Data of piglet birth weight and survival show that the presence of nonlinearity can be partly explained by the genetic covariance between environmental variance of birth weight and survival. The framework developed can be used to assess effects of artificial and natural selection on means and variances of traits and the statistical method presented can be used to estimate trade-offs between environmental variance of one trait and mean levels of others. PMID:25631318

  18. 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.

  19. The influence of reflection on portfolio learning in undergraduate dental education.

    PubMed

    Koole, S; Vanobbergen, J; De Visschere, L; Aper, L; Dornan, T; Derese, A

    2013-02-01

    Disparity exists between the growing consensus about the positive effects of reflection on performance and the scarcity of empirical evidence demonstrating this effect. Portfolios are considered a useful instrument to assess and supervise competence-based education and to stimulate reflection. The present study describes the introduction of a portfolio in a social dentistry and oral health promotion course and investigates student reflection as a predictor for the acquisition of the other competences in the course. Fourth year undergraduate dental students (n = 110) in the course 'Society and Health' between 2008 and 2011 collected evidence in their portfolios, demonstrating the acquisition of five competences: the ability to (1) assess the oral health profile of a target group; (2) integrate theoretical models in health promotion; (3) search for and apply scientific evidence; (4) work trans-, multi- and/or trans-disciplinarily; (5) reflect on personal development. Linear regression analysis was used to investigate the predictive value of reflection on the other course related competences. Reflection scores proved to significantly predict other course-related competences, when analysing all students between 2008 and 2011 and for each year separately, explaining between 10.7% and 25.5% of the variance in the other competences. Undergraduate dental students' competences related to social dentistry and oral health promotion were significantly predicted by the reflection scores obtained in a portfolio-based context. In line with the growing consensus about the benefits of reflection for dental students and professionals, results suggest the value to further develop the integration of reflection in dental education and practice. © 2012 John Wiley & Sons A/S.

  20. Risks of Large Portfolios

    PubMed Central

    Fan, Jianqing; Liao, Yuan; Shi, Xiaofeng

    2014-01-01

    The risk of a large portfolio is often estimated by substituting a good estimator of the volatility matrix. However, the accuracy of such a risk estimator is largely unknown. We study factor-based risk estimators under a large amount of assets, and introduce a high-confidence level upper bound (H-CLUB) to assess the estimation. The H-CLUB is constructed using the confidence interval of risk estimators with either known or unknown factors. We derive the limiting distribution of the estimated risks in high dimensionality. We find that when the dimension is large, the factor-based risk estimators have the same asymptotic variance no matter whether the factors are known or not, which is slightly smaller than that of the sample covariance-based estimator. Numerically, H-CLUB outperforms the traditional crude bounds, and provides an insightful risk assessment. In addition, our simulated results quantify the relative error in the risk estimation, which is usually negligible using 3-month daily data. PMID:26195851

  1. Beyond optimality: Multistakeholder robustness tradeoffs for regional water portfolio planning under deep uncertainty

    NASA Astrophysics Data System (ADS)

    Herman, Jonathan D.; Zeff, Harrison B.; Reed, Patrick M.; Characklis, Gregory W.

    2014-10-01

    While optimality is a foundational mathematical concept in water resources planning and management, "optimal" solutions may be vulnerable to failure if deeply uncertain future conditions deviate from those assumed during optimization. These vulnerabilities may produce severely asymmetric impacts across a region, making it vital to evaluate the robustness of management strategies as well as their impacts for regional stakeholders. In this study, we contribute a multistakeholder many-objective robust decision making (MORDM) framework that blends many-objective search and uncertainty analysis tools to discover key tradeoffs between water supply alternatives and their robustness to deep uncertainties (e.g., population pressures, climate change, and financial risks). The proposed framework is demonstrated for four interconnected water utilities representing major stakeholders in the "Research Triangle" region of North Carolina, U.S. The utilities supply well over one million customers and have the ability to collectively manage drought via transfer agreements and shared infrastructure. We show that water portfolios for this region that compose optimal tradeoffs (i.e., Pareto-approximate solutions) under expected future conditions may suffer significantly degraded performance with only modest changes in deeply uncertain hydrologic and economic factors. We then use the Patient Rule Induction Method (PRIM) to identify which uncertain factors drive the individual and collective vulnerabilities for the four cooperating utilities. Our framework identifies key stakeholder dependencies and robustness tradeoffs associated with cooperative regional planning, which are critical to understanding the tensions between individual versus regional water supply goals. Cooperative demand management was found to be the key factor controlling the robustness of regional water supply planning, dominating other hydroclimatic and economic uncertainties through the 2025 planning horizon. Results

  2. Approximate Sample Size Formulas for Testing Group Mean Differences when Variances Are Unequal in One-Way ANOVA

    ERIC Educational Resources Information Center

    Guo, Jiin-Huarng; Luh, Wei-Ming

    2008-01-01

    This study proposes an approach for determining appropriate sample size for Welch's F test when unequal variances are expected. Given a certain maximum deviation in population means and using the quantile of F and t distributions, there is no need to specify a noncentrality parameter and it is easy to estimate the approximate sample size needed…

  3. A Cosmic Variance Cookbook

    NASA Astrophysics Data System (ADS)

    Moster, Benjamin P.; Somerville, Rachel S.; Newman, Jeffrey A.; Rix, Hans-Walter

    2011-04-01

    Deep pencil beam surveys (<1 deg2) are of fundamental importance for studying the high-redshift universe. However, inferences about galaxy population properties (e.g., the abundance of objects) are in practice limited by "cosmic variance." This is the uncertainty in observational estimates of the number density of galaxies arising from the underlying large-scale density fluctuations. This source of uncertainty can be significant, especially for surveys which cover only small areas and for massive high-redshift galaxies. Cosmic variance for a given galaxy population can be determined using predictions from cold dark matter theory and the galaxy bias. In this paper, we provide tools for experiment design and interpretation. For a given survey geometry, we present the cosmic variance of dark matter as a function of mean redshift \\bar{z} and redshift bin size Δz. Using a halo occupation model to predict galaxy clustering, we derive the galaxy bias as a function of mean redshift for galaxy samples of a given stellar mass range. In the linear regime, the cosmic variance of these galaxy samples is the product of the galaxy bias and the dark matter cosmic variance. We present a simple recipe using a fitting function to compute cosmic variance as a function of the angular dimensions of the field, \\bar{z}, Δz, and stellar mass m *. We also provide tabulated values and a software tool. The accuracy of the resulting cosmic variance estimates (δσ v /σ v ) is shown to be better than 20%. We find that for GOODS at \\bar{z}=2 and with Δz = 0.5, the relative cosmic variance of galaxies with m *>1011 M sun is ~38%, while it is ~27% for GEMS and ~12% for COSMOS. For galaxies of m * ~ 1010 M sun, the relative cosmic variance is ~19% for GOODS, ~13% for GEMS, and ~6% for COSMOS. This implies that cosmic variance is a significant source of uncertainty at \\bar{z}=2 for small fields and massive galaxies, while for larger fields and intermediate mass galaxies, cosmic variance is

  4. 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.

  5. 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.

  6. The Use of Web-Based Portfolios in College Physical Education Activity Courses

    ERIC Educational Resources Information Center

    Hastie, Peter A.; Sinelnikov, Oleg A.

    2007-01-01

    This paper describes the introduction of web-based portfolios as a means of authentic assessment in collegiate physical education classes. Students in three volleyball classes were required to contribute to web-based team portfolios, and at the end of the semester, were able to make comment upon this process. A six-item on-line survey used to…

  7. Learning from Portfolios: Differential Use of Feedback in Portfolio Construction.

    ERIC Educational Resources Information Center

    Tillema, Harm H.; Smith, Kari

    2000-01-01

    Studied how students used feedback information provided them in distinctly framed portfolios of dossier, reflective, and learning-oriented types. Results with 137 college students support a view of portfolio construction in which the individual benefits from feedback were closely linked to the intentions present during collection of the portfolio…

  8. Portfolio theory and cost-effectiveness analysis: a further discussion.

    PubMed

    Sendi, Pedram; Al, Maiwenn J; Rutten, Frans F H

    2004-01-01

    Portfolio theory has been suggested as a means to improve the risk-return characteristics of investments in health-care programs through diversification when costs and effects are uncertain. This approach is based on the assumption that the investment proportions are not subject to uncertainty and that the budget can be invested in toto in health-care programs. In the present paper we develop an algorithm that accounts for the fact that investment proportions in health-care programs may be uncertain (due to the uncertainty associated with costs) and limited (due to the size of the programs). The initial budget allocation across programs may therefore be revised at the end of the investment period to cover the extra costs of some programs with the leftover budget of other programs in the portfolio. Once the total budget is equivalent to or exceeds the expected costs of the programs in the portfolio, the initial budget allocation policy does not impact the risk-return characteristics of the combined portfolio, i.e., there is no benefit from diversification anymore. The applicability of portfolio methods to improve the risk-return characteristics of investments in health care is limited to situations where the available budget is much smaller than the expected costs of the programs to be funded.

  9. A flexible model for the mean and variance functions, with application to medical cost data.

    PubMed

    Chen, Jinsong; Liu, Lei; Zhang, Daowen; Shih, Ya-Chen T

    2013-10-30

    Medical cost data are often skewed to the right and heteroscedastic, having a nonlinear relation with covariates. To tackle these issues, we consider an extension to generalized linear models by assuming nonlinear associations of covariates in the mean function and allowing the variance to be an unknown but smooth function of the mean. We make no further assumption on the distributional form. The unknown functions are described by penalized splines, and the estimation is carried out using nonparametric quasi-likelihood. Simulation studies show the flexibility and advantages of our approach. We apply the model to the annual medical costs of heart failure patients in the clinical data repository at the University of Virginia Hospital System. Copyright © 2013 John Wiley & Sons, Ltd.

  10. Developing a decision support system for R&D project portfolio selection with interdependencies

    NASA Astrophysics Data System (ADS)

    Ashrafi, Maryam; Davoudpour, Hamid; Abbassi, Mohammad

    2012-11-01

    Although investment in research and technology is a promising tool for technology centered organizations through obtaining their objectives, resource constraints make organizations select between their pool of research and technology projects through means of R&D project portfolio selection techniques mitigating corresponding risks and enhancing the overall value of project portfolio.

  11. 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.

  12. On the Performance of Maximum Likelihood versus Means and Variance Adjusted Weighted Least Squares Estimation in CFA

    ERIC Educational Resources Information Center

    Beauducel, Andre; Herzberg, Philipp Yorck

    2006-01-01

    This simulation study compared maximum likelihood (ML) estimation with weighted least squares means and variance adjusted (WLSMV) estimation. The study was based on confirmatory factor analyses with 1, 2, 4, and 8 factors, based on 250, 500, 750, and 1,000 cases, and on 5, 10, 20, and 40 variables with 2, 3, 4, 5, and 6 categories. There was no…

  13. Going beyond the Mean: Using Variances to Enhance Understanding of the Impact of Educational Interventions for Multilevel Models

    ERIC Educational Resources Information Center

    Peralta, Yadira; Moreno, Mario; Harwell, Michael; Guzey, S. Selcen; Moore, Tamara J.

    2018-01-01

    Variance heterogeneity is a common feature of educational data when treatment differences expressed through means are present, and often reflects a treatment by subject interaction with respect to an outcome variable. Identifying variables that account for this interaction can enhance understanding of whom a treatment does and does not benefit in…

  14. The reliability and validity of a portfolio designed as a programmatic assessment of performance in an integrated clinical placement.

    PubMed

    Roberts, Chris; Shadbolt, Narelle; Clark, Tyler; Simpson, Phillip

    2014-09-20

    Little is known about the technical adequacy of portfolios in reporting multiple complex academic and performance-based assessments. We explored, first, the influencing factors on the precision of scoring within a programmatic assessment of student learning outcomes within an integrated clinical placement. Second, the degree to which validity evidence supported interpretation of student scores. Within generalisability theory, we estimated the contribution that each wanted factor (i.e. student capability) and unwanted factors (e.g. the impact of assessors) made to the variation in portfolio task scores. Relative and absolute standard errors of measurement provided a confidence interval around a pre-determined pass/fail standard for all six tasks. Validity evidence was sought through demonstrating the internal consistency of the portfolio and exploring the relationship of student scores with clinical experience. The mean portfolio mark for 257 students, across 372 raters, based on six tasks, was 75.56 (SD, 6.68). For a single student on one assessment task, 11% of the variance in scores was due to true differences in student capability. The most significant interaction was context specificity (49%), the tendency for one student to engage with one task and not engage with another task. Rater subjectivity was 29%. An absolute standard error of measurement of 4.74%, gave a 95% CI of +/- 9.30%, and a 68% CI of +/- 4.74% around a pass/fail score of 57%. Construct validity was supported by demonstration of an assessment framework, the internal consistency of the portfolio tasks, and higher scores for students who did the clinical placement later in the academic year. A portfolio designed as a programmatic assessment of an integrated clinical placement has sufficient evidence of validity to support a specific interpretation of student scores around passing a clinical placement. It has modest precision in assessing students' achievement of a competency standard. There were

  15. 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.

  16. 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)…

  17. 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...

  18. 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...

  19. Mass fluctuation kinetics: Capturing stochastic effects in systems of chemical reactions through coupled mean-variance computations

    NASA Astrophysics Data System (ADS)

    Gómez-Uribe, Carlos A.; Verghese, George C.

    2007-01-01

    The intrinsic stochastic effects in chemical reactions, and particularly in biochemical networks, may result in behaviors significantly different from those predicted by deterministic mass action kinetics (MAK). Analyzing stochastic effects, however, is often computationally taxing and complex. The authors describe here the derivation and application of what they term the mass fluctuation kinetics (MFK), a set of deterministic equations to track the means, variances, and covariances of the concentrations of the chemical species in the system. These equations are obtained by approximating the dynamics of the first and second moments of the chemical master equation. Apart from needing knowledge of the system volume, the MFK description requires only the same information used to specify the MAK model, and is not significantly harder to write down or apply. When the effects of fluctuations are negligible, the MFK description typically reduces to MAK. The MFK equations are capable of describing the average behavior of the network substantially better than MAK, because they incorporate the effects of fluctuations on the evolution of the means. They also account for the effects of the means on the evolution of the variances and covariances, to produce quite accurate uncertainty bands around the average behavior. The MFK computations, although approximate, are significantly faster than Monte Carlo methods for computing first and second moments in systems of chemical reactions. They may therefore be used, perhaps along with a few Monte Carlo simulations of sample state trajectories, to efficiently provide a detailed picture of the behavior of a chemical system.

  20. Portfolios in Saudi medical colleges

    PubMed Central

    Fida, Nadia M.; Shamim, Muhammad S.

    2016-01-01

    Over recent decades, the use of portfolios in medical education has evolved, and is being applied in undergraduate and postgraduate programs worldwide. Portfolios, as a learning process and method of documenting and assessing learning, is supported as a valuable tool by adult learning theories that stress the need for learners to be self-directed and to engage in experiential learning. Thoughtfully implemented, a portfolio provides learning experiences unequaled by any single learning tool. The credibility (validity) and dependability (reliability) of assessment through portfolios have been questioned owing to its subjective nature; however, methods to safeguard these features have been described in the literature. This paper discusses some of this literature, with particular attention to the role of portfolios in relation to self-reflective learning, provides an overview of current use of portfolios in undergraduate medical education in Saudi Arabia, and proposes research-based guidelines for its implementation and other similar contexts. PMID:26905344

  1. A systematic review protocol on the use of teaching portfolios for educators in further and higher education.

    PubMed

    McColgan, Karen; Blackwood, Bronagh

    2009-12-01

    This paper is a review protocol that will be used to identify, critically appraise and synthesize the best current evidence relating to the use of teaching portfolios for educators in further and higher education. While portfolio use as a means to assist students in further and higher education has undergone extensive research and review, their use as a tool to assist educators has yet to receive systematic attention. Reviews conducted on studies related to portfolio use and undergraduate students have suggested that a teaching portfolio may have a benefit for educators in higher education as a means to provide relevancy and focus to their teaching. The objectives of the review are to evaluate how a teaching portfolio assists educators in teaching and learning; to evaluate the effects of maintaining a teaching portfolio for educators in relation to personal development; to explore the type of portfolio used; to determine whether a teaching portfolio is perceived more beneficial for various grades and professional types; and to determine any motivating factors or workplace incentives behind its implementation and completion. A search of the following databases will be made: MEDLINE, CINAHL, BREI, ERIC and AUEI. The review will follow the Joanna Briggs Institute guidance for systematic reviews of quantitative and qualitative research. The review will offer clarity and direction on the use of teaching portfolios for educators, policymakers, supervisory managers and researchers involved in further and higher education.

  2. 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,…

  3. 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…

  4. Portfolio as a tool to evaluate clinical competences of traumatology in medical students.

    PubMed

    Santonja-Medina, Fernando; García-Sanz, M Paz; Martínez-Martínez, Francisco; Bó, David; García-Estañ, Joaquín

    2016-01-01

    This article investigates whether a reflexive portfolio is instrumental in determining the level of acquisition of clinical competences in traumatology, a subject in the 5th year of the degree of medicine. A total of 131 students used the portfolio during their clinical rotation of traumatology. The students' portfolios were blind evaluated by four professors who annotated the existence (yes/no) of 23 learning outcomes. The reliability of the portfolio was moderate, according to the kappa index (0.48), but the evaluation scores between evaluators were very similar. Considering the mean percentage, 59.8% of the students obtained all the competences established and only 13 of the 23 learning outcomes (56.5%) were fulfilled by >50% of the students. Our study suggests that the portfolio may be an important tool to quantitatively analyze the acquisition of traumatology competences of medical students, thus allowing the implementation of methods to improve its teaching.

  5. Using Electronic Portfolios

    ERIC Educational Resources Information Center

    Page, Deb

    2012-01-01

    The digitized collections of artifacts known as electronic portfolios are creating solutions to a variety of performance improvement needs in ways that are cost-effective and improve both individual and group learning and performance. When social media functionality is embedded in e-portfolios, the tools support collaboration, social learning,…

  6. Digital Portfolios: Fact or Fashion?

    ERIC Educational Resources Information Center

    Woodward, Helen; Nanlohy, Phil

    2004-01-01

    The value of portfolios as an assessment tool is thoroughly researched and their use in education is well documented ( Woodward, 2000). Research on the introduction of digital portfolios is substantially based on general portfolio research; however, additional specific factors and features need to be considered. One of the inherent dangers with…

  7. 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.

  8. Portfolio Management

    NASA Technical Reports Server (NTRS)

    Duncan, Sharon L.

    2011-01-01

    Enterprise Business Information Services Division (EBIS) supports the Laboratory and its functions through the implementation and support of business information systems on behalf of its business community. EBIS Five Strategic Focus Areas: (1) Improve project estimating, planning and delivery capability (2) Improve maintainability and sustainability of EBIS Application Portfolio (3) Leap forward in IT Leadership (4) Comprehensive Talent Management (5) Continuous IT Security Program. Portfolio Management is a strategy in which software applications are managed as assets

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

    ERIC Educational Resources Information Center

    Michelson, Elana; Mandell, Alan

    2004-01-01

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

  10. The effect of model uncertainty on some optimal routing problems

    NASA Technical Reports Server (NTRS)

    Mohanty, Bibhu; Cassandras, Christos G.

    1991-01-01

    The effect of model uncertainties on optimal routing in a system of parallel queues is examined. The uncertainty arises in modeling the service time distribution for the customers (jobs, packets) to be served. For a Poisson arrival process and Bernoulli routing, the optimal mean system delay generally depends on the variance of this distribution. However, as the input traffic load approaches the system capacity the optimal routing assignment and corresponding mean system delay are shown to converge to a variance-invariant point. The implications of these results are examined in the context of gradient-based routing algorithms. An example of a model-independent algorithm using online gradient estimation is also included.

  11. E-Portfolios Come of Age

    ERIC Educational Resources Information Center

    Waters, John K.

    2009-01-01

    Industry analysts say the systems have reached a mature adolescence, having grown from mere electronic filing cabinets into multimedia platforms that can operate with a variety of e-learning tools. Their fullest potential still lies ahead. This article talks about electronic portfolios--better known as e-portfolios, and how e-portfolios are taking…

  12. 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...

  13. Portfolio Preparation Tips for Teachers

    ERIC Educational Resources Information Center

    Hunter-Lombardi, Brooke

    2008-01-01

    As college deadlines loom, teachers may wonder if there is a magic portfolio formula for their students to follow. After twenty years of thought on portfolio development and the opportunity to review over 10,000 individual portfolios, the author is convinced that there is no single formula for success. With hard work, careful planning, and…

  14. Portfolio Based Management

    ERIC Educational Resources Information Center

    Daigneau, William A.

    2010-01-01

    In this article, the author talks about Portfolio Management, a concept used to make allocation decisions in the world of financial investments. While much has been written about Portfolio theory, and the term is widely used in the facilities management industry, little is really understood about the concept and its real-world application. The…

  15. 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.

  16. Mean-variance analysis of block-iterative reconstruction algorithms modeling 3D detector response in SPECT

    NASA Astrophysics Data System (ADS)

    Lalush, D. S.; Tsui, B. M. W.

    1998-06-01

    We study the statistical convergence properties of two fast iterative reconstruction algorithms, the rescaled block-iterative (RBI) and ordered subset (OS) EM algorithms, in the context of cardiac SPECT with 3D detector response modeling. The Monte Carlo method was used to generate nearly noise-free projection data modeling the effects of attenuation, detector response, and scatter from the MCAT phantom. One thousand noise realizations were generated with an average count level approximating a typical T1-201 cardiac study. Each noise realization was reconstructed using the RBI and OS algorithms for cases with and without detector response modeling. For each iteration up to twenty, we generated mean and variance images, as well as covariance images for six specific locations. Both OS and RBI converged in the mean to results that were close to the noise-free ML-EM result using the same projection model. When detector response was not modeled in the reconstruction, RBI exhibited considerably lower noise variance than OS for the same resolution. When 3D detector response was modeled, the RBI-EM provided a small improvement in the tradeoff between noise level and resolution recovery, primarily in the axial direction, while OS required about half the number of iterations of RBI to reach the same resolution. We conclude that OS is faster than RBI, but may be sensitive to errors in the projection model. Both OS-EM and RBI-EM are effective alternatives to the EVIL-EM algorithm, but noise level and speed of convergence depend on the projection model used.

  17. Variance to mean ratio, R(t), for poisson processes on phylogenetic trees.

    PubMed

    Goldman, N

    1994-09-01

    The ratio of expected variance to mean, R(t), of numbers of DNA base substitutions for contemporary sequences related by a "star" phylogeny is widely seen as a measure of the adherence of the sequences' evolution to a Poisson process with a molecular clock, as predicted by the "neutral theory" of molecular evolution under certain conditions. A number of estimators of R(t) have been proposed, all predicted to have mean 1 and distributions based on the chi 2. Various genes have previously been analyzed and found to have values of R(t) far in excess of 1, calling into question important aspects of the neutral theory. In this paper, I use Monte Carlo simulation to show that the previously suggested means and distributions of estimators of R(t) are highly inaccurate. The analysis is applied to star phylogenies and to general phylogenetic trees, and well-known gene sequences are reanalyzed. For star phylogenies the results show that Kimura's estimators ("The Neutral Theory of Molecular Evolution," Cambridge Univ. Press, Cambridge, 1983) are unsatisfactory for statistical testing of R(t), but confirm the accuracy of Bulmer's correction factor (Genetics 123: 615-619, 1989). For all three nonstar phylogenies studied, attained values of all three estimators of R(t), although larger than 1, are within their true confidence limits under simple Poisson process models. This shows that lineage effects can be responsible for high estimates of R(t), restoring some limited confidence in the molecular clock and showing that the distinction between lineage and molecular clock effects is vital.(ABSTRACT TRUNCATED AT 250 WORDS)

  18. Portfolio as a tool to evaluate clinical competences of traumatology in medical students

    PubMed Central

    Santonja-Medina, Fernando; García-Sanz, M Paz; Martínez-Martínez, Francisco; Bó, David; García-Estañ, Joaquín

    2016-01-01

    This article investigates whether a reflexive portfolio is instrumental in determining the level of acquisition of clinical competences in traumatology, a subject in the 5th year of the degree of medicine. A total of 131 students used the portfolio during their clinical rotation of traumatology. The students’ portfolios were blind evaluated by four professors who annotated the existence (yes/no) of 23 learning outcomes. The reliability of the portfolio was moderate, according to the kappa index (0.48), but the evaluation scores between evaluators were very similar. Considering the mean percentage, 59.8% of the students obtained all the competences established and only 13 of the 23 learning outcomes (56.5%) were fulfilled by >50% of the students. Our study suggests that the portfolio may be an important tool to quantitatively analyze the acquisition of traumatology competences of medical students, thus allowing the implementation of methods to improve its teaching. PMID:26929675

  19. 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…

  20. 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...

  1. 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)

  2. Using portfolios to assess learning in chemistry: One school's story of evolving assessment practice

    NASA Astrophysics Data System (ADS)

    Weaver, Starlin Dawn

    The purpose of this study was to investigate the process of implementing an alternative form of assessment in chemistry classrooms. The current reform of science education involves the implementation of varied forms of instruction; it stands to reason that assessment will evolve with the curriculum (Baxter, Shavelson, Goldman & Pine, 1992). In an era for which the exclusive use of multiple-choice and similar tests i.e., fill-in the-blank, matching, and true/false are inappropriate measures of student abilities (Hamm & Adams, 1991), portfolios can offer a suitable alternative assessment, as well as a means for evaluation (Paulson, Paulson & Meyer, 1991). This study was conducted in a small math, science and technology high school and focused on three individual teachers and twelve of their students. The research focused on how teachers defined portfolios and implemented this assessment tool in their classrooms and how students and teachers perceived the use and value of the process. This study employed qualitative methodology using individual interviews, document analyses, and classroom observations. Data sources included documents, transcripts of interviews and fieldnotes. The primary research questions were: How do the teachers define and implement portfolios? How do the teachers' definitions of portfolios change during implementation? What are the students' understandings of portfolios and how they are used and do the students' understandings change? What do teachers and students believe portfolios represent regarding the learning that occurs in the science classroom? and What do the data collected via this study demonstrate about portfolios as a valid means of assessing student progress? The teachers' and students' definitions addressed four of the six components of portfolios identified in the literature. Both groups recognized a defined use, evidence, student and teacher made decisions, and reflection as key portfolio elements. Each group failed to identify

  3. 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…

  4. 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.

  5. 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.

  6. Quality Issues in Judging Portfolios: Implications for Organizing Teaching Portfolio Assessment Procedures

    ERIC Educational Resources Information Center

    Tigelaar, Dineke E. H.; Dolmans, Diana H. J. M.; Wolfhagen, Ineke H. A. P.; van der Vleuten, Cees P. M.

    2005-01-01

    This article addresses the choice of the most appropriate procedure for the assessment of portfolios used in teacher and lecturer assessment. A characteristic of modern assessment modes, including portfolios, is that the information they provide is often qualitative and derived from different contexts. Unambiguous, objective rating of portfolios…

  7. 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.

  8. Mean-deviation analysis in the theory of choice.

    PubMed

    Grechuk, Bogdan; Molyboha, Anton; Zabarankin, Michael

    2012-08-01

    Mean-deviation analysis, along with the existing theories of coherent risk measures and dual utility, is examined in the context of the theory of choice under uncertainty, which studies rational preference relations for random outcomes based on different sets of axioms such as transitivity, monotonicity, continuity, etc. An axiomatic foundation of the theory of coherent risk measures is obtained as a relaxation of the axioms of the dual utility theory, and a further relaxation of the axioms are shown to lead to the mean-deviation analysis. Paradoxes arising from the sets of axioms corresponding to these theories and their possible resolutions are discussed, and application of the mean-deviation analysis to optimal risk sharing and portfolio selection in the context of rational choice is considered. © 2012 Society for Risk Analysis.

  9. Increasing selection response by Bayesian modeling of heterogeneous environmental variances

    USDA-ARS?s Scientific Manuscript database

    Heterogeneity of environmental variance among genotypes reduces selection response because genotypes with higher variance are more likely to be selected than low-variance genotypes. Modeling heterogeneous variances to obtain weighted means corrected for heterogeneous variances is difficult in likel...

  10. 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.

  11. Diversified models for portfolio selection based on uncertain semivariance

    NASA Astrophysics Data System (ADS)

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

    2017-02-01

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

  12. Developing a sustainable electronic portfolio (ePortfolio) program that fosters reflective practice and incorporates CanMEDS competencies into the undergraduate medical curriculum.

    PubMed

    Hall, Pippa; Byszewski, Anna; Sutherland, Stephanie; Stodel, Emma J

    2012-06-01

    The University of Ottawa (uOttawa) Faculty of Medicine in 2008 launched a revised undergraduate medical education (UGME) curriculum that was based on the seven CanMEDS roles (medical expert, communicator, collaborator, health advocate, manager, scholar, and professional) and added an eighth role of person to incorporate the dimension of mindfulness and personal well-being. In this article, the authors describe the development of an electronic Portfolio (ePortfolio) program that enables uOttawa medical students to document their activities and to demonstrate their development of competence in each of the eight roles. The ePortfolio program supports reflective practice, an important component of professional competence, and provides a means for addressing the "hidden curriculum." It is bilingual, mandatory, and spans the four years of UGME. It includes both an online component for students to document their personal development and for student-coach dialogue, as well as twice-yearly, small-group meetings in which students engage in reflective discussions and learn to give and receive feedback.The authors reflect on the challenges they faced in the development and implementation of the ePortfolio program and share the lessons they have learned along the way to a successful and sustainable program. These lessons include switching from a complex information technology system to a user-friendly, Web-based blog platform; rethinking orientation sessions to ensure that faculty and students understand the value of the ePortfolio program; soliciting student input to improve the program and increase student buy-in; and providing faculty development opportunities and recognition.

  13. Multi-objective Optimization of Solar Irradiance and Variance at Pertinent Inclination Angles

    NASA Astrophysics Data System (ADS)

    Jain, Dhanesh; Lalwani, Mahendra

    2018-05-01

    The performance of photovoltaic panel gets highly affected bychange in atmospheric conditions and angle of inclination. This article evaluates the optimum tilt angle and orientation angle (surface azimuth angle) for solar photovoltaic array in order to get maximum solar irradiance and to reduce variance of radiation at different sets or subsets of time periods. Non-linear regression and adaptive neural fuzzy interference system (ANFIS) methods are used for predicting the solar radiation. The results of ANFIS are more accurate in comparison to non-linear regression. These results are further used for evaluating the correlation and applied for estimating the optimum combination of tilt angle and orientation angle with the help of general algebraic modelling system and multi-objective genetic algorithm. The hourly average solar irradiation is calculated at different combinations of tilt angle and orientation angle with the help of horizontal surface radiation data of Jodhpur (Rajasthan, India). The hourly average solar irradiance is calculated for three cases: zero variance, with actual variance and with double variance at different time scenarios. It is concluded that monthly collected solar radiation produces better result as compared to bimonthly, seasonally, half-yearly and yearly collected solar radiation. The profit obtained for monthly varying angle has 4.6% more with zero variance and 3.8% more with actual variance, than the annually fixed angle.

  14. 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...

  15. 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.

  16. 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…

  17. Portfolios, Power, and Ethics

    ERIC Educational Resources Information Center

    Lynch, Brian; Shaw, Peter

    2005-01-01

    Portfolios have been used in a variety of ways for assessing student work. In education, generally, and more specifically in second language education, portfolios have been associated with alternative assessment (Darling-Hammond, 1994; Hamayan, 1995; Shohamy, 1996; Wolf, Bixby, Glenn, & Gardener, 1991). This article defines "alternative…

  18. Portfolio-based Teacher Assessment.

    ERIC Educational Resources Information Center

    Curry, Stacie; Cruz, John

    2000-01-01

    Educators in the Fowler (California) Unified School District have found that teacher evaluation portfolios help link improvement and accountability concerns in the peer review process. Portfolios that are structured around professional standards and the school's accountability goals are a good way to measure teacher effectiveness. Implementation…

  19. 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…

  20. Modeling stock prices in a portfolio using multidimensional geometric brownian motion

    NASA Astrophysics Data System (ADS)

    Maruddani, Di Asih I.; Trimono

    2018-05-01

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

  1. Teaching Portfolios and the Beginning Teacher.

    ERIC Educational Resources Information Center

    Zubizarreta, John

    1994-01-01

    Teaching portfolios are becoming the most effective tool to improve new and seasoned teachers' instruction via a supportive, convincing evaluation method. In taking a concentrated three days to write a creditable portfolio, a new teacher feels more competent to think about teaching. The portfolio's process of written reflection invokes the power…

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

    PubMed

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

    2007-08-01

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

  3. Technology for Online Portfolio Assessment Programs

    ERIC Educational Resources Information Center

    Ferrara, Victoria M.

    2010-01-01

    Portfolio assessment is a valid and reliable method to assess experiential learning. Developing a fully online portfolio assessment program is neither easy nor inexpensive. The institution seeking to take its portfolio assessment program online must make a commitment to its students by offering the technologies most suited to meet students' needs.…

  4. Build Better ePortfolios

    ERIC Educational Resources Information Center

    Zuger, Sascha

    2008-01-01

    Tech-using educators know the many benefits of ePortfolios. They help get a handle on kids' interests, difficulties, and strengths. Techno-loving student thrive on the real-time interaction. Administrators like that ePortfolios record student progress digitally, making a convenient shared resource between students, parents, and other teachers.…

  5. Layering Networked and Symphonic Selves: A Critical Role for e-Portfolios in Employability through Integrative Learning

    ERIC Educational Resources Information Center

    Cambridge, Darren

    2008-01-01

    Purpose: E-portfolios, which document and facilitate learning and performance, have recently attracted interest in the USA, UK, and Europe as means to increase employability and support lifelong learning. This article aims to critically examine these objectives in order to guide the future e-portfolio practice. Design/methodology/approach: Social…

  6. 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…

  7. Robust optimization of supersonic ORC nozzle guide vanes

    NASA Astrophysics Data System (ADS)

    Bufi, Elio A.; Cinnella, Paola

    2017-03-01

    An efficient Robust Optimization (RO) strategy is developed for the design of 2D supersonic Organic Rankine Cycle turbine expanders. The dense gas effects are not-negligible for this application and they are taken into account describing the thermodynamics by means of the Peng-Robinson-Stryjek-Vera equation of state. The design methodology combines an Uncertainty Quantification (UQ) loop based on a Bayesian kriging model of the system response to the uncertain parameters, used to approximate statistics (mean and variance) of the uncertain system output, a CFD solver, and a multi-objective non-dominated sorting algorithm (NSGA), also based on a Kriging surrogate of the multi-objective fitness function, along with an adaptive infill strategy for surrogate enrichment at each generation of the NSGA. The objective functions are the average and variance of the isentropic efficiency. The blade shape is parametrized by means of a Free Form Deformation (FFD) approach. The robust optimal blades are compared to the baseline design (based on the Method of Characteristics) and to a blade obtained by means of a deterministic CFD-based optimization.

  8. Handbook of Research on ePortfolios

    ERIC Educational Resources Information Center

    Jafari, Ali, Ed.; Kaufman, Catherine, Ed.

    2006-01-01

    The "Handbook of Research on ePortfolios" is the single source for comprehensive coverage of the major themes of ePortfolios, addressing all of the major issues, from concept to technology to implementation. It is the first reference publication to provide a complete investigation on a variety of ePortfolio uses through case studies and…

  9. 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.

  10. Information Technology Portfolio Management Proof of Concept: Modern Portfolio Theory With KVA and ROI Analysis

    DTIC Science & Technology

    2010-09-01

    approach” that provides analysis for “program managers to attain the right knowledge [e.g., portfolio values] at critical junctures so they can make...portfolio, it is critical to create a credible beta (β) for the presumed “market volatility” of the IT asset class. The KVA methodology may be used...for this critical task. Establishing a beta (β) for DoD wide IT portfolio management uses the work conducted at the Naval Postgraduate School (NPS

  11. Hybrid computer optimization of systems with random parameters

    NASA Technical Reports Server (NTRS)

    White, R. C., Jr.

    1972-01-01

    A hybrid computer Monte Carlo technique for the simulation and optimization of systems with random parameters is presented. The method is applied to the simultaneous optimization of the means and variances of two parameters in the radar-homing missile problem treated by McGhee and Levine.

  12. Development of the Electronic Portfolio Student Perspective Instrument: An ePortfolio Integration Initiative

    ERIC Educational Resources Information Center

    Ritzhaupt, Albert Dieter; Singh, Oma; Seyferth, Thelma; Dedrick, Robert F.

    2008-01-01

    With the proliferation of eportfolios and their organizational uses in higher education, it is important for educators and other relevant stakeholders to understand the student perspective. The way students view and use ePortfolios are revealing elements to aid educators in the successful integration of ePortfolio systems. This research describes…

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

    ERIC Educational Resources Information Center

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

    2008-01-01

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

  14. 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.

  15. The importance of personality and parental styles on optimism in adolescents.

    PubMed

    Zanon, Cristian; Bastianello, Micheline Roat; Pacico, Juliana Cerentini; Hutz, Claudio Simon

    2014-01-01

    Some studies have suggested that personality factors are important to optimism development. Others have emphasized that family relations are relevant variables to optimism. This study aimed to evaluate the importance of parenting styles to optimism controlling for the variance accounted for by personality factors. Participants were 344 Brazilian high school students (44% male) with mean age of 16.2 years (SD = 1) who answered personality, optimism, responsiveness and demandingness scales. Hierarchical regression analyses were conducted having personality factors (in the first step) and maternal and paternal parenting styles, and demandingness and responsiveness (in the second step) as predictive variables and optimism as the criterion. Personality factors, especially neuroticism (β = -.34, p < .01), extraversion (β = .26, p < .01) and agreeableness (β = .16, p < .01), accounted for 34% of the optimism variance and insignificant variance was predicted exclusively by parental styles (1%). These findings suggest that personality is more important to optimism development than parental styles.

  16. An Electronic Portfolio to Support Learning

    ERIC Educational Resources Information Center

    Wade, Anne; Abrami, Philip C.; Sclater, Jennifer

    2005-01-01

    In this paper, we provide a description of a CSLP research project that looked at portfolio use within a middle school, the web-based e-portfolio software we have developed within the context of the Quebec educational system, our plans for further development of the tool, and our research plans related to the use of portfolios to support learning.…

  17. Advanced Variance Reduction Strategies for Optimizing Mesh Tallies in MAVRIC

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

    Peplow, Douglas E.; Blakeman, Edward D; Wagner, John C

    2007-01-01

    More often than in the past, Monte Carlo methods are being used to compute fluxes or doses over large areas using mesh tallies (a set of region tallies defined on a mesh that overlays the geometry). For problems that demand that the uncertainty in each mesh cell be less than some set maximum, computation time is controlled by the cell with the largest uncertainty. This issue becomes quite troublesome in deep-penetration problems, and advanced variance reduction techniques are required to obtain reasonable uncertainties over large areas. The CADIS (Consistent Adjoint Driven Importance Sampling) methodology has been shown to very efficientlymore » optimize the calculation of a response (flux or dose) for a single point or a small region using weight windows and a biased source based on the adjoint of that response. This has been incorporated into codes such as ADVANTG (based on MCNP) and the new sequence MAVRIC, which will be available in the next release of SCALE. In an effort to compute lower uncertainties everywhere in the problem, Larsen's group has also developed several methods to help distribute particles more evenly, based on forward estimates of flux. This paper focuses on the use of a forward estimate to weight the placement of the source in the adjoint calculation used by CADIS, which we refer to as a forward-weighted CADIS (FW-CADIS).« less

  18. Variance-Based Cluster Selection Criteria in a K-Means Framework for One-Mode Dissimilarity Data.

    PubMed

    Vera, J Fernando; Macías, Rodrigo

    2017-06-01

    One of the main problems in cluster analysis is that of determining the number of groups in the data. In general, the approach taken depends on the cluster method used. For K-means, some of the most widely employed criteria are formulated in terms of the decomposition of the total point scatter, regarding a two-mode data set of N points in p dimensions, which are optimally arranged into K classes. This paper addresses the formulation of criteria to determine the number of clusters, in the general situation in which the available information for clustering is a one-mode [Formula: see text] dissimilarity matrix describing the objects. In this framework, p and the coordinates of points are usually unknown, and the application of criteria originally formulated for two-mode data sets is dependent on their possible reformulation in the one-mode situation. The decomposition of the variability of the clustered objects is proposed in terms of the corresponding block-shaped partition of the dissimilarity matrix. Within-block and between-block dispersion values for the partitioned dissimilarity matrix are derived, and variance-based criteria are subsequently formulated in order to determine the number of groups in the data. A Monte Carlo experiment was carried out to study the performance of the proposed criteria. For simulated clustered points in p dimensions, greater efficiency in recovering the number of clusters is obtained when the criteria are calculated from the related Euclidean distances instead of the known two-mode data set, in general, for unequal-sized clusters and for low dimensionality situations. For simulated dissimilarity data sets, the proposed criteria always outperform the results obtained when these criteria are calculated from their original formulation, using dissimilarities instead of distances.

  19. 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…

  20. 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...

  1. The Role of Document Captions in Student Portfolios as a Link between Teacher and Student Assessment.

    ERIC Educational Resources Information Center

    Evans, Karen S.; Vavrus, Linda G.

    A follow-up study to Stanford University's Teacher Assessment Project (TAP) investigated captioning as a means of making sense of portfolios and explored how the captioning process might provide a way to use student portfolios to link student assessment and teacher assessment. Each of four teachers (three third grade and one fourth grade) from the…

  2. The Web-based CanMEDS Resident Learning Portfolio Project (WEBCAM): how we got started.

    PubMed

    Glen, Peter; Balaa, Fady; Momoli, Franco; Martin, Louise; Found, Dorothy; Arnaout, Angel

    2016-12-01

    The CanMEDS framework is ubiquitous in Canadian postgraduate medical education; however, training programs do not have a universal method of assessing competence. We set out to develop a novel portfolio that allowed trainees to generate a longitudinal record of their training and development within the framework. The portfolio provided an objective means for the residency program director to document and evaluate resident progress within the CanMEDS roles.

  3. On the Computation of the RMSEA and CFI from the Mean-And-Variance Corrected Test Statistic with Nonnormal Data in SEM.

    PubMed

    Savalei, Victoria

    2018-01-01

    A new type of nonnormality correction to the RMSEA has recently been developed, which has several advantages over existing corrections. In particular, the new correction adjusts the sample estimate of the RMSEA for the inflation due to nonnormality, while leaving its population value unchanged, so that established cutoff criteria can still be used to judge the degree of approximate fit. A confidence interval (CI) for the new robust RMSEA based on the mean-corrected ("Satorra-Bentler") test statistic has also been proposed. Follow up work has provided the same type of nonnormality correction for the CFI (Brosseau-Liard & Savalei, 2014). These developments have recently been implemented in lavaan. This note has three goals: a) to show how to compute the new robust RMSEA and CFI from the mean-and-variance corrected test statistic; b) to offer a new CI for the robust RMSEA based on the mean-and-variance corrected test statistic; and c) to caution that the logic of the new nonnormality corrections to RMSEA and CFI is most appropriate for the maximum likelihood (ML) estimator, and cannot easily be generalized to the most commonly used categorical data estimators.

  4. Repeat sample intraocular pressure variance in induced and naturally ocular hypertensive monkeys.

    PubMed

    Dawson, William W; Dawson, Judyth C; Hope, George M; Brooks, Dennis E; Percicot, Christine L

    2005-12-01

    To compare repeat-sample means variance of laser induced ocular hypertension (OH) in rhesus monkeys with the repeat-sample mean variance of natural OH in age-range matched monkeys of similar and dissimilar pedigrees. Multiple monocular, retrospective, intraocular pressure (IOP) measures were recorded repeatedly during a short sampling interval (SSI, 1-5 months) and a long sampling interval (LSI, 6-36 months). There were 5-13 eyes in each SSI and LSI subgroup. Each interval contained subgroups from the Florida with natural hypertension (NHT), induced hypertension (IHT1) Florida monkeys, unrelated (Strasbourg, France) induced hypertensives (IHT2), and Florida age-range matched controls (C). Repeat-sample individual variance means and related IOPs were analyzed by a parametric analysis of variance (ANOV) and results compared to non-parametric Kruskal-Wallis ANOV. As designed, all group intraocular pressure distributions were significantly different (P < or = 0.009) except for the two (Florida/Strasbourg) induced OH groups. A parametric 2 x 4 design ANOV for mean variance showed large significant effects due to treatment group and sampling interval. Similar results were produced by the nonparametric ANOV. Induced OH sample variance (LSI) was 43x the natural OH sample variance-mean. The same relationship for the SSI was 12x. Laser induced ocular hypertension in rhesus monkeys produces large IOP repeat-sample variance mean results compared to controls and natural OH.

  5. 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…

  6. Trends in Gender Differences in Academic Achievement from 1960 to 1994: An Analysis of Differences in Mean, Variance, and Extreme Scores.

    ERIC Educational Resources Information Center

    Nowell, Amy; Hedges, Larry V.

    1998-01-01

    Uses evidence from seven surveys of the U.S. 12th-grade population and the National Assessment of Educational Progress to show that gender differences in mean and variance in academic achievement are small from 1960 to 1994 but that differences in extreme scores are often substantial. (SLD)

  7. 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.

  8. An electronic portfolio for quantitative assessment of surgical skills in undergraduate medical education.

    PubMed

    Sánchez Gómez, Serafín; Ostos, Elisa María Cabot; Solano, Juan Manuel Maza; Salado, Tomás Francisco Herrero

    2013-05-06

    We evaluated a newly designed electronic portfolio (e-Portfolio) that provided quantitative evaluation of surgical skills. Medical students at the University of Seville used the e-Portfolio on a voluntary basis for evaluation of their performance in undergraduate surgical subjects. Our new web-based e-Portfolio was designed to evaluate surgical practical knowledge and skills targets. Students recorded each activity on a form, attached evidence, and added their reflections. Students self-assessed their practical knowledge using qualitative criteria (yes/no), and graded their skills according to complexity (basic/advanced) and participation (observer/assistant/independent). A numerical value was assigned to each activity, and the values of all activities were summated to obtain the total score. The application automatically displayed quantitative feedback. We performed qualitative evaluation of the perceived usefulness of the e-Portfolio and quantitative evaluation of the targets achieved. Thirty-seven of 112 students (33%) used the e-Portfolio, of which 87% reported that they understood the methodology of the portfolio. All students reported an improved understanding of their learning objectives resulting from the numerical visualization of progress, all students reported that the quantitative feedback encouraged their learning, and 79% of students felt that their teachers were more available because they were using the e-Portfolio. Only 51.3% of students reported that the reflective aspects of learning were useful. Individual students achieved a maximum of 65% of the total targets and 87% of the skills targets. The mean total score was 345 ± 38 points. For basic skills, 92% of students achieved the maximum score for participation as an independent operator, and all achieved the maximum scores for participation as an observer and assistant. For complex skills, 62% of students achieved the maximum score for participation as an independent operator, and 98% achieved

  9. Student Evaluations of the Portfolio Process

    PubMed Central

    Airey, Tatum C.; Bisso, Andrea M.; Slack, Marion K.

    2011-01-01

    Objective. To evaluate pharmacy students’ perceived benefits of the portfolio process and to gather suggestions for improving the process. Methods. A questionnaire was designed and administered to 250 first-, second-, and third-year pharmacy students at the University of Arizona College of Pharmacy. Results. Although the objectives of the portfolio process were for students to understand the expected outcomes, understand the impact of extracurricular activities on attaining competencies, identify what should be learned, identify their strengths and weaknesses, and modify their approach to learning, overall students perceived the portfolio process as having less than moderate benefit. First-year students wanted more examples of portfolios while second- and third-year students suggested that more time with their advisor would be beneficial. Conclusions. The portfolio process will continue to be refined and efforts made to improve students’ perceptions of the process as it is intended to develop the self-assessments skills they will need to improve their knowledge and professional skills throughout their pharmacy careers. PMID:21969718

  10. Student evaluations of the portfolio process.

    PubMed

    Murphy, John E; Airey, Tatum C; Bisso, Andrea M; Slack, Marion K

    2011-09-10

    To evaluate pharmacy students' perceived benefits of the portfolio process and to gather suggestions for improving the process. A questionnaire was designed and administered to 250 first-, second-, and third-year pharmacy students at the University of Arizona College of Pharmacy. Although the objectives of the portfolio process were for students to understand the expected outcomes, understand the impact of extracurricular activities on attaining competencies, identify what should be learned, identify their strengths and weaknesses, and modify their approach to learning, overall students perceived the portfolio process as having less than moderate benefit. First-year students wanted more examples of portfolios while second- and third-year students suggested that more time with their advisor would be beneficial. The portfolio process will continue to be refined and efforts made to improve students' perceptions of the process as it is intended to develop the self-assessments skills they will need to improve their knowledge and professional skills throughout their pharmacy careers.

  11. Effective Implementation of ePortfolios: The Development of ePortfolios to Support Online Learning

    ERIC Educational Resources Information Center

    Cote, Kyle; Emmett, Tara

    2015-01-01

    This article discusses the ePortfolio system for grades 9-12 at the Virtual Learning Academy Charter School (VLACS). ePortfolio implementation at VLACS developed from an Advisory course curriculum that supports students' journey toward becoming college, career, and citizenship ready. We provide a unique perspective for implementation in that VLACS…

  12. Why ePortfolios? Student Perceptions of ePortfolio Use in Continuing Education Learning Environments

    ERIC Educational Resources Information Center

    Wuetherick, Brad; Dickinson, John

    2015-01-01

    Over the past decade, there has been an increased exploration of ePortfolios in higher education across disciplines at both the undergraduate and graduate level. ePortfolios have been significantly under-explored, however, in the context of non-traditional continuing education environments within higher education. This paper explores students'…

  13. 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

  14. The effect of a dietary portfolio compared to a DASH-type diet on blood pressure.

    PubMed

    Jenkins, D J A; Jones, P J; Frohlich, J; Lamarche, B; Ireland, C; Nishi, S K; Srichaikul, K; Galange, P; Pellini, C; Faulkner, D; de Souza, R J; Sievenpiper, J L; Mirrahimi, A; Jayalath, V H; Augustin, L S; Bashyam, B; Leiter, L A; Josse, R; Couture, P; Ramprasath, V; Kendall, C W C

    2015-12-01

    Compared to a DASH-type diet, an intensively applied dietary portfolio reduced diastolic blood pressure at 24 weeks as a secondary outcome in a previous study. Due to the importance of strategies to reduce blood pressure, we performed an exploratory analysis pooling data from intensively and routinely applied portfolio treatments from the same study to assess the effect over time on systolic, diastolic and mean arterial pressure (MAP), and the relation to sodium (Na(+)), potassium (K(+)), and portfolio components. 241 participants with hyperlipidemia, from four academic centers across Canada were randomized and completed either a DASH-type diet (control n = 82) or a dietary portfolio that included, soy protein, viscous fibers and nuts (n = 159) for 24 weeks. Fasting measures and 7-day food records were obtained at weeks 0, 12 and 24, with 24-h urines at weeks 0 and 24. The dietary portfolio reduced systolic, diastolic and mean arterial blood pressure compared to the control by 2.1 mm Hg (95% CI, 4.2 to -0.1 mm Hg) (p = 0.056), 1.8 mm Hg (CI, 3.2 to 0.4 mm Hg) (p = 0.013) and 1.9 mm Hg (CI, 3.4 to 0.4 mm Hg) (p = 0.015), respectively. Blood pressure reductions were small at 12 weeks and only reached significance at 24 weeks. Nuts, soy and viscous fiber all related negatively to change in mean arterial pressure (ρ = -0.15 to -0.17, p ≤ 0.016) as did urinary potassium (ρ = -0.25, p = 0.001), while the Na(+)/K(+) ratio was positively associated (ρ = 0.20, p = 0.010). Consumption of a cholesterol-lowering dietary portfolio also decreased blood pressure by comparison with a healthy DASH-type diet. CLINICAL TRIAL REG. NO.: NCT00438425, clinicaltrials.gov. Copyright © 2015 The Italian Society of Diabetology, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition, and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.

  15. 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.

  16. 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

  17. Electronic Portfolios. [SITE 2002 Section].

    ERIC Educational Resources Information Center

    Barrett, Helen C., Ed.

    This document contains the following papers on electronic portfolios from the SITE (Society for Information Technology & Teacher Education) 2002 conference: (1) "What Is the Perceived Value of Creating Electronic Portfolios to Teacher Credential Candidates?" (Valerie Amber and Brenda Czech); (2) "Development and Use of…

  18. 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.…

  19. Assessment Portfolios as Opportunities for Teacher Learning

    ERIC Educational Resources Information Center

    Gearhart, Maryl; Osmundson, Ellen

    2009-01-01

    This article is an analysis of the role of assessment portfolios in teacher learning. Over 18 months, 23 science teachers developed, implemented, and evaluated assessments to track student learning, supported by portfolio tasks and resources, grade-level colleagues, and team facilitators. Evidence of teacher learning included (a) portfolios of a…

  20. Using Electronic Portfolios for Second Language Assessment

    ERIC Educational Resources Information Center

    Cummins, Patricia W.; Davesne, Celine

    2009-01-01

    Portfolio assessment as developed in Europe presents a learner-empowering alternative to computer-based testing. The authors present the European Language Portfolio (ELP) and its American adaptations, LinguaFolio and the Global Language Portfolio, as tools to be used with the Common European Framework of Reference for languages and the American…

  1. The Use of Portfolios in US Pharmacy Schools

    PubMed Central

    Cumberland, Denise M.

    2018-01-01

    Objective. To conduct a review of the pharmacy literature on the use of portfolios in US pharmacy schools. Findings. This study provides examples of how pharmacy schools are using portfolios in various parts and across their curricula, however, assessment/outcome data is lacking. These examples can be used as a starting point for schools as they begin to design their own use of portfolios. Overall, students indicated that the use of portfolios is important in their professional development, but significant time is needed to complete. Summary. Things to consider when implementing a portfolio system include how it will be used, who will review it, and what resources will be needed to sustain the project. It is important for schools to consider these items at the start of the process to ensure the portfolio process that is created is useful for assessing the overall programmatic or course outcomes being proposed by their use. More scholarly work needs to be published on the use of portfolios. PMID:29692438

  2. 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.

  3. Does health affect portfolio choice?

    PubMed

    Love, David A; Smith, Paul A

    2010-12-01

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

  4. Culture Portfolios Revisited: Feedback from Students and Instructors

    ERIC Educational Resources Information Center

    Abrams, Zsuzsanna I.; Byrd, David R.; Boovy, Bradley; Mohring, Anja

    2006-01-01

    Teaching culture in the foreign language (L2) classroom can be a real dilemma for instructors: What culture do we teach? What does it mean to learn about a culture? How can students learn culture? In order to answer these questions, we evaluated the strengths and weaknesses of two types of culture portfolios: a traditional one that used on-line…

  5. Universal portfolios generated by weakly stationary processes

    NASA Astrophysics Data System (ADS)

    Tan, Choon Peng; Pang, Sook Theng

    2014-12-01

    Recently, a universal portfolio generated by a set of independent Brownian motions where a finite number of past stock prices are weighted by the moments of the multivariate normal distribution is introduced and studied. The multivariate normal moments as polynomials in time consequently lead to a constant rebalanced portfolio depending on the drift coefficients of the Brownian motions. For a weakly stationary process, a different type of universal portfolio is proposed where the weights on the stock prices depend only on the time differences of the stock prices. An empirical study is conducted on the returns achieved by the universal portfolios generated by the Ornstein-Uhlenbeck process on selected stock-price data sets. Promising results are demonstrated for increasing the wealth of the investor by using the weakly-stationary-process-generated universal portfolios.

  6. 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.

  7. 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.

  8. Academic Misconduct in Teaching Portfolios

    ERIC Educational Resources Information Center

    Erikson, Martin G.; Erlandson, Peter; Erikson, Malgorzata

    2015-01-01

    Within academia, clear and standardised communication is vital. From this point of departure, we discuss the trustworthiness of teaching portfolios when used in assessment. Here, misconduct and fraud are discussed in terms of fabrication, falsification, and plagiarism, following the literature on research fraud. We argue that the portfolio's…

  9. Do Portfolios Have a Future?

    ERIC Educational Resources Information Center

    Driessen, Erik

    2017-01-01

    While portfolios have seen an unprecedented surge in popularity, they have also become the subject of controversy: learners often perceive little gain from writing reflections as part of their portfolios; scholars question the ethics of such obligatory reflection; and students, residents, teachers and scholars alike condemn the bureaucracy…

  10. Reflection during Portfolio-Based Conversations

    ERIC Educational Resources Information Center

    Oosterbaan, Anne E.; van der Schaaf, Marieke F.; Baartman, Liesbeth K. J.; Stokking, Karel M.

    2010-01-01

    This study aims to explore the relationship between the occurrence of reflection (and non-reflection) and thinking activities (e.g., orientating, selecting, analysing) during portfolio-based conversations. Analysis of 21 transcripts of portfolio-based conversations revealed that 20% of the segments were made up of reflection (content reflection…

  11. E-Portfolio for Enhancing Graduate Research Supervision

    ERIC Educational Resources Information Center

    Le, Quynh

    2012-01-01

    Purpose: E-Portfolio is a powerful tool for demonstrating evidence of learning and achievements in graduate research. The purpose of this paper is to examine the concept, structure and functions of e-Portfolio in graduate research and discuss the significance of the role of e-Portfolio in enhancing the quality of graduate research students and…

  12. Minimum variance geographic sampling

    NASA Technical Reports Server (NTRS)

    Terrell, G. R. (Principal Investigator)

    1980-01-01

    Resource inventories require samples with geographical scatter, sometimes not as widely spaced as would be hoped. A simple model of correlation over distances is used to create a minimum variance unbiased estimate population means. The fitting procedure is illustrated from data used to estimate Missouri corn acreage.

  13. Host nutrition alters the variance in parasite transmission potential

    PubMed Central

    Vale, Pedro F.; Choisy, Marc; Little, Tom J.

    2013-01-01

    The environmental conditions experienced by hosts are known to affect their mean parasite transmission potential. How different conditions may affect the variance of transmission potential has received less attention, but is an important question for disease management, especially if specific ecological contexts are more likely to foster a few extremely infectious hosts. Using the obligate-killing bacterium Pasteuria ramosa and its crustacean host Daphnia magna, we analysed how host nutrition affected the variance of individual parasite loads, and, therefore, transmission potential. Under low food, individual parasite loads showed similar mean and variance, following a Poisson distribution. By contrast, among well-nourished hosts, parasite loads were right-skewed and overdispersed, following a negative binomial distribution. Abundant food may, therefore, yield individuals causing potentially more transmission than the population average. Measuring both the mean and variance of individual parasite loads in controlled experimental infections may offer a useful way of revealing risk factors for potential highly infectious hosts. PMID:23407498

  14. Host nutrition alters the variance in parasite transmission potential.

    PubMed

    Vale, Pedro F; Choisy, Marc; Little, Tom J

    2013-04-23

    The environmental conditions experienced by hosts are known to affect their mean parasite transmission potential. How different conditions may affect the variance of transmission potential has received less attention, but is an important question for disease management, especially if specific ecological contexts are more likely to foster a few extremely infectious hosts. Using the obligate-killing bacterium Pasteuria ramosa and its crustacean host Daphnia magna, we analysed how host nutrition affected the variance of individual parasite loads, and, therefore, transmission potential. Under low food, individual parasite loads showed similar mean and variance, following a Poisson distribution. By contrast, among well-nourished hosts, parasite loads were right-skewed and overdispersed, following a negative binomial distribution. Abundant food may, therefore, yield individuals causing potentially more transmission than the population average. Measuring both the mean and variance of individual parasite loads in controlled experimental infections may offer a useful way of revealing risk factors for potential highly infectious hosts.

  15. Genetic basis of between-individual and within-individual variance of docility.

    PubMed

    Martin, J G A; Pirotta, E; Petelle, M B; Blumstein, D T

    2017-04-01

    Between-individual variation in phenotypes within a population is the basis of evolution. However, evolutionary and behavioural ecologists have mainly focused on estimating between-individual variance in mean trait and neglected variation in within-individual variance, or predictability of a trait. In fact, an important assumption of mixed-effects models used to estimate between-individual variance in mean traits is that within-individual residual variance (predictability) is identical across individuals. Individual heterogeneity in the predictability of behaviours is a potentially important effect but rarely estimated and accounted for. We used 11 389 measures of docility behaviour from 1576 yellow-bellied marmots (Marmota flaviventris) to estimate between-individual variation in both mean docility and its predictability. We then implemented a double hierarchical animal model to decompose the variances of both mean trait and predictability into their environmental and genetic components. We found that individuals differed both in their docility and in their predictability of docility with a negative phenotypic covariance. We also found significant genetic variance for both mean docility and its predictability but no genetic covariance between the two. This analysis is one of the first to estimate the genetic basis of both mean trait and within-individual variance in a wild population. Our results indicate that equal within-individual variance should not be assumed. We demonstrate the evolutionary importance of the variation in the predictability of docility and illustrate potential bias in models ignoring variation in predictability. We conclude that the variability in the predictability of a trait should not be ignored, and present a coherent approach for its quantification. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

  16. Individual and collective bodies: using measures of variance and association in contextual epidemiology.

    PubMed

    Merlo, J; Ohlsson, H; Lynch, K F; Chaix, B; Subramanian, S V

    2009-12-01

    Social epidemiology investigates both individuals and their collectives. Although the limits that define the individual bodies are very apparent, the collective body's geographical or cultural limits (eg "neighbourhood") are more difficult to discern. Also, epidemiologists normally investigate causation as changes in group means. However, many variables of interest in epidemiology may cause a change in the variance of the distribution of the dependent variable. In spite of that, variance is normally considered a measure of uncertainty or a nuisance rather than a source of substantive information. This reasoning is also true in many multilevel investigations, whereas understanding the distribution of variance across levels should be fundamental. This means-centric reductionism is mostly concerned with risk factors and creates a paradoxical situation, as social medicine is not only interested in increasing the (mean) health of the population, but also in understanding and decreasing inappropriate health and health care inequalities (variance). Critical essay and literature review. The present study promotes (a) the application of measures of variance and clustering to evaluate the boundaries one uses in defining collective levels of analysis (eg neighbourhoods), (b) the combined use of measures of variance and means-centric measures of association, and (c) the investigation of causes of health variation (variance-altering causation). Both measures of variance and means-centric measures of association need to be included when performing contextual analyses. The variance approach, a new aspect of contextual analysis that cannot be interpreted in means-centric terms, allows perspectives to be expanded.

  17. 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…

  18. 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...

  19. Making practice transparent through e-portfolio.

    PubMed

    Stewart, Sarah M

    2013-12-01

    Midwives are required to maintain a professional portfolio as part of their statutory requirements. Some midwives are using open social networking tools and processes to develop an e-portfolio. However, confidentiality of patient and client data and professional reputation have to be taken into consideration when using online public spaces for reflection. There is little evidence about how midwives use social networking tools for ongoing learning. It is uncertain how reflecting in an e-portfolio with an audience impacts on learning outcomes. This paper investigates ways in which reflective midwifery practice be carried out using e-portfolio in open, social networking platforms using collaborative processes. Using an auto-ethnographic approach I explored my e-portfolio and selected posts that had attracted six or more comments. I used thematic analysis to identify themes within the textual conversations in the posts and responses posted by readers. The analysis identified that my collaborative e-portfolio had four themes: to provide commentary and discuss issues; to reflect and process learning; to seek advice, brainstorm and process ideas for practice, projects and research, and provide evidence of professional development. E-portfolio using open social networking tools and processes is a viable option for midwives because it facilitates collaborative reflection and shared learning. However, my experience shows that concerns about what people think, and client confidentiality does impact on the nature of open reflection and learning outcomes. I conclude this paper with a framework for managing midwifery statutory obligations using online public spaces and social networking tools. Copyright © 2013 Australian College of Midwives. Published by Elsevier Ltd. All rights reserved.

  20. Optimal allocation of testing resources for statistical simulations

    NASA Astrophysics Data System (ADS)

    Quintana, Carolina; Millwater, Harry R.; Singh, Gulshan; Golden, Patrick

    2015-07-01

    Statistical estimates from simulation involve uncertainty caused by the variability in the input random variables due to limited data. Allocating resources to obtain more experimental data of the input variables to better characterize their probability distributions can reduce the variance of statistical estimates. The methodology proposed determines the optimal number of additional experiments required to minimize the variance of the output moments given single or multiple constraints. The method uses multivariate t-distribution and Wishart distribution to generate realizations of the population mean and covariance of the input variables, respectively, given an amount of available data. This method handles independent and correlated random variables. A particle swarm method is used for the optimization. The optimal number of additional experiments per variable depends on the number and variance of the initial data, the influence of the variable in the output function and the cost of each additional experiment. The methodology is demonstrated using a fretting fatigue example.

  1. ePortfolios Meet Social Software

    ERIC Educational Resources Information Center

    Waters, John K.

    2007-01-01

    Although a seemingly good idea, electronic portfolios have to date failed to gain significant traction in higher education. Institutions with ePortfolio implementations routinely report high numbers of accounts on their campuses, but few believe that those numbers are a meaningful reflection of actual usage. Change is in the air for the…

  2. Using Courthouse Portfolios to Establish Rapport and Motivate College Students

    ERIC Educational Resources Information Center

    Gentry, Ruben

    2013-01-01

    Motivation enhances student learning (Wang, 2012). One means for an instructor to stimulate students and get them actively involved is to establish good rapport with them (Cottringer & Sloan, 2003). For this study, county courthouse portfolios were developed and used to build relationships and motivate college students. The strategy was…

  3. [Development and validation of a questionnaire on perception of portfolio by undergraduate medical students].

    PubMed

    Riquelme, Arnoldo; Méndez, Benjamín; de la Fuente, Paloma; Padilla, Oslando; Benaglio, Carla; Sirhan, Marisol; Labarca, Jaime

    2011-01-01

    Portfolio is an innovative instrument that promotes reflection, creativity and professionalism among students. To describe the development and validation process of a questionnaire to evaluate the use of portfolio in undergraduate medical students. Focus groups with students and teachers were employed to identify aspects related with portfolio in undergraduate teaching. The Delphi technique was used to prioritize relevant aspects and construct the questionnaire. The validated questionnaire, consisting of 43 items and 6 factors, was applied to 97 students (response rote of 99.9%) in 2007 and 100 students (99.2%) in 2008. Each question had to be answered using a Likert scale, from 0 (completely disagree) to 4 (completely agree) The validity and reliability of the questionnaire was evaluated. The questionnaire showed a high reliability (Cronbach alpha = 0.9). The mean total scores obtained in 2007 and 2008 were 106.2 ± 21.2 (61.7% of the maximal obtainable score) and 104.6 ± 34.0 (60.8% of the maximal obtainable score), respectively No significant differences were seen in the analysis by factors. Changes in portfolio during 2008 showed differences in items related with organization, evaluation and regulation. The questionnaire is a valid and highly reliable instrument, measuring perceptions about the portfolio by undergraduate medical students. The students perceived an improvement in their creativity and professionalism as one of the strengths of portfolio. The weaknesses identified during the implementation process helped us to focus changes in organization and evaluation to improve the portfolio as a dynamic process.

  4. 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)

  5. 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…

  6. 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…

  7. Portfolio Assessment Handbook. 1990-91.

    ERIC Educational Resources Information Center

    Thomas A. Edison State Coll., Trenton, NJ.

    This handbook gives the adult student information to complete portfolios that are designed to help adult students earn college credits for outside experience. Portfolio assessment is a flexible and efficient way to earn college credit. Nearly any area of learning can be converted into credits as long as it is taught at a regionally accredited…

  8. A Guide to Writing Academic Portfolios for Radiologists.

    PubMed

    Thomas, John V; Sanyal, Rupan; O'Malley, Janis P; Singh, Satinder P; Morgan, Desiree E; Canon, Cheri L

    2016-12-01

    The academic educator's portfolio is a collection of materials that document academic performance and achievements, supplementing the curriculum vitae, in order to showcase a faculty member's most significant accomplishments. A decade ago, a survey of medical schools revealed frustration in the nonuniform methods of measuring faculty's medical education productivity. A proposed solution was the use of an academic educator's portfolio. In the academic medical community, compiling an academic portfolio is always a challenge because teaching has never been confined to the traditional classroom setting and often involves active participation of the medical student, resident, or fellow in the ongoing care of the patient. Diagnostic radiology in addition requires a knowledge base that encompasses basic sciences, imaging physics, technology, and traditional and molecular medicine. Teaching and performing research that involves this complex mix, while providing patient care that is often behind the scenes, provides unique challenges in the documentation of teaching, research, and clinical service for diagnostic radiology faculty. An academic portfolio is seen as a way to explain why relevant academic activities are significant to promotions committee members who may have backgrounds in unrelated academic areas and may not be familiar with a faculty member's work. The academic portfolio consists of teaching, research, and service portfolios. The teaching portfolio is a collection of materials that document teaching performance and documents the educator's transition to a more effective educator. A research portfolio showcases the most significant research accomplishments. The service portfolio documents service responsibilities and highlight any service excellence. All portfolios should briefly discuss the educator's philosophy, activities, methods used to implement activities, leadership, mentoring, or committee roles in these respective areas. Recognizing that academic

  9. 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.

  10. Junior doctors' guide to portfolio learning and building.

    PubMed

    Kitchen, Mark

    2012-10-01

    A portfolio is a collection of evidence supporting an individual's achievement of competencies and learning outcomes. The material included in the portfolio must be reflected upon, as reflection provides the evidence that learning has taken place. Portfolio learning is important for two principal reasons: assessment of the trainee, and for lifelong learning and reflection. The ability of a portfolio to be used for both summative and formative assessment makes it a flexible and robust assessment method. A portfolio also demonstrates reflection and lifelong learning abilities. Reflective learning is key to postgraduate medical education: it is part of both the Foundation Programme curriculum and General Medical Council guidance on best practice. To ensure correct learning outcomes are identified and evidenced, the curriculum programme must be referred to and an educational supervisor should be consulted. Once identified, it is necessary to: identify how these outcomes can be met (learning needs); decide what needs to be done to meet these needs; reflect on what has been done; and evidence what has been done in the portfolio. Evidence could include written feedback, certificates of course completion, online learning modules, etc. A learning portfolio is a necessary tool for every postgraduate medical trainee. The portfolio serves to record and evidence all learning that has taken place, and thereon acts as a guide for future learning needs. The key process to portfolio building and learning is the provision of evidence by reflecting upon the learning that has taken place. © Blackwell Publishing Ltd 2012.

  11. 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.

  12. 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…

  13. Digital Portfolios: Documenting Student Growth

    ERIC Educational Resources Information Center

    Cramer, Matthew

    2009-01-01

    The digital portfolio process at Camino Nuevo High School (CNHS) offers an essential 21st century skill to students. All students are trained in basic web design to build and maintain their digital portfolios. These skills equip them with tools they will likely use in their future endeavors in college and the professional world. Teachers at CNHS…

  14. Guidance for ePortfolio Researchers: A Case Study with Implications for the ePortfolio Domain

    ERIC Educational Resources Information Center

    Kennelly, Emily; Osborn, Debra; Reardon, Robert; Shetty, Becka

    2016-01-01

    This study examined whether or not students using a career ePortfolio, including a matrix for identifying and reflecting on transferrable skills, enabled them to rate their skills more confidently and positively after a simulated (mock) job interview. Three groups were studied: those completing the skills matrix in the ePortfolio; those using the…

  15. Portfolio as Practice: The Narratives of Emerging Teachers.

    ERIC Educational Resources Information Center

    Darling, L. Farr

    2001-01-01

    Portfolio construction is a complex social practice with intentions, rules, and standards. This definition is not typically found in teacher education literature and has implications for evaluating students' portfolios. The paper examines teacher education students' recollections of creating portfolios in one Canadian program and argues that…

  16. Automatic Trading Agent. RMT Based Portfolio Theory and Portfolio Selection

    NASA Astrophysics Data System (ADS)

    Snarska, M.; Krzych, J.

    2006-11-01

    Portfolio theory is a very powerful tool in the modern investment theory. It is helpful in estimating risk of an investor's portfolio, arosen from lack of information, uncertainty and incomplete knowledge of reality, which forbids a perfect prediction of future price changes. Despite of many advantages this tool is not known and not widely used among investors on Warsaw Stock Exchange. The main reason for abandoning this method is a high level of complexity and immense calculations. The aim of this paper is to introduce an automatic decision-making system, which allows a single investor to use complex methods of Modern Portfolio Theory (MPT). The key tool in MPT is an analysis of an empirical covariance matrix. This matrix, obtained from historical data, biased by such a high amount of statistical uncertainty, that it can be seen as random. By bringing into practice the ideas of Random Matrix Theory (RMT), the noise is removed or significantly reduced, so the future risk and return are better estimated and controlled. These concepts are applied to the Warsaw Stock Exchange Simulator {http://gra.onet.pl}. The result of the simulation is 18% level of gains in comparison with respective 10% loss of the Warsaw Stock Exchange main index WIG.

  17. 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.

  18. Portfolio Development in Teacher Education and Educational Leadership.

    ERIC Educational Resources Information Center

    Biddle, James

    The Ohio Consortium for Portfolio Development was established in 1988 as an interinstitutional research effort to integrate portfolio development into teacher education. A subphase focused on portfolio use by entry year teachers in a metropolitan school system. Personnel at Wright State University, Central State University, and the University of…

  19. 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.

  20. The true invariant of an arbitrage free portfolio

    NASA Astrophysics Data System (ADS)

    Schmidt, Anatoly B.

    2003-03-01

    It is shown that the arbitrage free portfolio paradigm being applied to a portfolio with an arbitrary number of shares N allows for the extended solution in which the option price F depends on N. However the resulting stock hedging expense Q= MF (where M is the number of options in the portfolio) does not depend on whether N is treated as an independent variable or as a parameter. Therefore the stock hedging expense is the true invariant of the arbitrage free portfolio paradigm.

  1. 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.

  2. Understanding the multifractality in portfolio excess returns

    NASA Astrophysics Data System (ADS)

    Chen, Cheng; Wang, Yudong

    2017-01-01

    The multifractality in stock returns have been investigated extensively. However, whether the autocorrelations in portfolio returns are multifractal have not been considered in the literature. In this paper, we detect multifractal behavior of returns of portfolios constructed based on two popular trading rules, size and book-to-market (BM) ratio. Using the multifractal detrended fluctuation analysis, we find that the portfolio returns are significantly multifractal and the multifractality is mainly attributed to long-range dependence. We also investigate the multifractal cross-correlation between portfolio return and market average return using the detrended cross-correlation analysis. Our results show that the cross-correlations of small fluctuations are persistent, while those of large fluctuations are anti-persistent.

  3. Gender Variance and Educational Psychology: Implications for Practice

    ERIC Educational Resources Information Center

    Yavuz, Carrie

    2016-01-01

    The area of gender variance appears to be more visible in both the media and everyday life. Within educational psychology literature gender variance remains underrepresented. The positioning of educational psychologists working across the three levels of child and family, school or establishment and education authority/council, means that they are…

  4. Portfolio on a Shoestring

    NASA Astrophysics Data System (ADS)

    Mitchell, S. E.; Barbier, S. B.; Krishnamurthi, A.; Lochner, J. C.

    2008-06-01

    Many education and outreach programs face two daunting shortages: time and money. EPO professionals are frequently challenged to develop quality efforts for a variety of audiences and settings, all on a shoestring budget. How do you create a broad and cohesive education and outreach portfolio with limited resources? In this session, we discussed several effective strategies to make the most of your assets, such as adaptation of existing programs and materials, mutually beneficial partnerships, and innovative (and inexpensive) dissemination techniques. These approaches can fill in the gaps in your portfolio, increasing the scope and impact of your EPO efforts. There are a variety of cost-effective tools and techniques that can bring your EPO endeavors to a wide range of audiences and settings. Turn your program's EPO wish list into reality through savvy leveraging of existing personnel, funding, and materials... or find a partner that can help you fill any gaps in your portfolio.

  5. 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.

  6. 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.

  7. 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

  8. Random matrix theory filters and currency portfolio optimisation

    NASA Astrophysics Data System (ADS)

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

    2010-04-01

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

  9. A Note on Using Portfolios To Assess Learning.

    ERIC Educational Resources Information Center

    Fenwick, Tara J.; Parsons, Jim

    1999-01-01

    Explains that a portfolio is a collection of student work that reflects the course content and is assembled by the student in a folder or binder over a specified period of time. Discusses how to use portfolios, the benefits of using portfolios as assessment tools, and potential concerns teachers need to address. (CMK)

  10. Portfolio analysis of layered security measures.

    PubMed

    Chatterjee, Samrat; Hora, Stephen C; Rosoff, Heather

    2015-03-01

    Layered defenses are necessary for protecting the public from terrorist attacks. Designing a system of such defensive measures requires consideration of the interaction of these countermeasures. In this article, we present an analysis of a layered security system within the lower Manhattan area. It shows how portfolios of security measures can be evaluated through portfolio decision analysis. Consideration is given to the total benefits and costs of the system. Portfolio diagrams are created that help communicate alternatives among stakeholders who have differing views on the tradeoffs between security and economic activity. © 2014 Society for Risk Analysis.

  11. 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.

  12. An Analysis of Variance Framework for Matrix Sampling.

    ERIC Educational Resources Information Center

    Sirotnik, Kenneth

    Significant cost savings can be achieved with the use of matrix sampling in estimating population parameters from psychometric data. The statistical design is intuitively simple, using the framework of the two-way classification analysis of variance technique. For example, the mean and variance are derived from the performance of a certain grade…

  13. [Reflective portfolio: a proposal for teaching and learning geared on competencies].

    PubMed

    Cotta, Rosângela Minardi Mitre; da Costa, Glauce Dias; Mendonça, Erica Toledo

    2013-06-01

    This article seeks to analyze the experience of collective construction of portfolios as a teaching-learning method in the discipline of Health Policy, identifying the competencies developed by students. Qualitative research, whose collection and data processing were conducted by means of documental and thematic analysis of 34 portfolios. The "Learning to be" and "Learning to live and work together" competencies were considered according to the proposals of the UNESCO report for Education. The training of critical-reflexive individuals, provided by the portfolio, was particularly observed when students reported the transformation of the negative views that they had about the health care system - an inefficient and precarious policy - to a positive vision - policy which deals with the principles of equity, integrity and universality. This process of critical transformation is the result of the practice and use of communication skills, information management (search, selection, analysis and evaluation of information), leadership, cooperation and human relationships (teamwork, ethics and recognition of diversity), and personal competencies (time management, responsibility and planning), namely important skills in the training of professionals committed to the national health policy.

  14. Principal component of explained variance: An efficient and optimal data dimension reduction framework for association studies.

    PubMed

    Turgeon, Maxime; Oualkacha, Karim; Ciampi, Antonio; Miftah, Hanane; Dehghan, Golsa; Zanke, Brent W; Benedet, Andréa L; Rosa-Neto, Pedro; Greenwood, Celia Mt; Labbe, Aurélie

    2018-05-01

    The genomics era has led to an increase in the dimensionality of data collected in the investigation of biological questions. In this context, dimension-reduction techniques can be used to summarise high-dimensional signals into low-dimensional ones, to further test for association with one or more covariates of interest. This paper revisits one such approach, previously known as principal component of heritability and renamed here as principal component of explained variance (PCEV). As its name suggests, the PCEV seeks a linear combination of outcomes in an optimal manner, by maximising the proportion of variance explained by one or several covariates of interest. By construction, this method optimises power; however, due to its computational complexity, it has unfortunately received little attention in the past. Here, we propose a general analytical PCEV framework that builds on the assets of the original method, i.e. conceptually simple and free of tuning parameters. Moreover, our framework extends the range of applications of the original procedure by providing a computationally simple strategy for high-dimensional outcomes, along with exact and asymptotic testing procedures that drastically reduce its computational cost. We investigate the merits of the PCEV using an extensive set of simulations. Furthermore, the use of the PCEV approach is illustrated using three examples taken from the fields of epigenetics and brain imaging.

  15. Student Portfolios: A Collection of Articles.

    ERIC Educational Resources Information Center

    Fogarty, Robin, Ed.

    More and more, schools are looking to student portfolios as a valid, reliable, and authentic form of assessment. This collection offers practical, well-researched answers to a variety of philosophical, organizational, and implementational questions surrounding portfolio assessment. Articles in the first section provide a rationale for student…

  16. Portfolios for Majors in Professional Communication.

    ERIC Educational Resources Information Center

    Killingsworth, M. Jimmie; Sanders, Scott P.

    1987-01-01

    Suggests general principles for developing assignments where students prepare portfolios that reveal their overall communication skills in addition to the usual job search tools. Emphasizes that students should concentrate on including works in the portfolio with the criteria of quality, variety, professionalism, and maturity in mind. (SKC)

  17. Portfolio Assessment: Increasing Reliability and Validity.

    ERIC Educational Resources Information Center

    Griffee, Dale

    2002-01-01

    Addresses the traditional understanding of reliability as it pertains to writing portfolio assessments. Offers a list of practical actions that can be taken to increase assessment reliability, including explicit definitions of what a portfolio holds, rater training, rater burnout, and consistent rating procedures. (Contains 26 references.) (NB)

  18. Unlocking ePortfolio Practice: Teaching Beliefs

    ERIC Educational Resources Information Center

    Henscheid, Jean M.; Brown, Gary; Gordon, Aifang; Chen, Helen L.

    2014-01-01

    The Association for Authentic, Experiential, and Evidence-Based Learning (AAEEBL) annual ePortfolio survey focuses on understanding ePortfolio practitioners' teaching beliefs and practices. The action research reported here extends that survey research to a population of emerging educators (i.e., graduate students in education). In addition to…

  19. Splashy Portfolios Kids Can Make Themselves.

    ERIC Educational Resources Information Center

    Booth, Virginia Humphreys

    1994-01-01

    A children's art project lets students create artistic portfolios in a Jackson Pollock style. The activity takes 60 minutes and requires posterboard, adhesive tape, spray paint, tempera paints, eyedroppers, newspapers, colored markers, and stencil letters. By inviting students to make their own portfolios, teachers are cultivating students'…

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

    PubMed

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

    2017-01-01

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

  1. 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.

  2. Impact of Damping Uncertainty on SEA Model Response Variance

    NASA Technical Reports Server (NTRS)

    Schiller, Noah; Cabell, Randolph; Grosveld, Ferdinand

    2010-01-01

    Statistical Energy Analysis (SEA) is commonly used to predict high-frequency vibroacoustic levels. This statistical approach provides the mean response over an ensemble of random subsystems that share the same gross system properties such as density, size, and damping. Recently, techniques have been developed to predict the ensemble variance as well as the mean response. However these techniques do not account for uncertainties in the system properties. In the present paper uncertainty in the damping loss factor is propagated through SEA to obtain more realistic prediction bounds that account for both ensemble and damping variance. The analysis is performed on a floor-equipped cylindrical test article that resembles an aircraft fuselage. Realistic bounds on the damping loss factor are determined from measurements acquired on the sidewall of the test article. The analysis demonstrates that uncertainties in damping have the potential to significantly impact the mean and variance of the predicted response.

  3. IT Portfolio Selection and IT Synergy

    ERIC Educational Resources Information Center

    Cho, Woo Je

    2010-01-01

    This dissertation consists of three chapters. The primary objectives of this dissertation are: (1) to provide a methodological framework of IT (Information Technology) portfolio management, and (2) to identify the effect of IT synergy on IT portfolio selection of a firm. The first chapter presents a methodological framework for IT project…

  4. Classroom-Based Measurement and Portfolio Assessment.

    ERIC Educational Resources Information Center

    Nolet, Victor

    1992-01-01

    Portfolio assessment involves collecting multiple forms of data to support inferences about student performance in skill or content areas that cannot be sampled directly by a single measure. Portfolio assessment can help to clarify and individualize instructional goals for regular and special education students as well as suggest research and…

  5. The Audiovisual Portfolio.

    ERIC Educational Resources Information Center

    Williams, Eugene

    1979-01-01

    Describes the development of an audiovisual portfolio, consisting of a student teaching notebook, slide narrative presentation, audiotapes, and a videotape-- valuable for prospective teachers in job interviews. (CMV)

  6. Student Chemical Engineering Reflective ePortfolios--ChE Student Perceptions of Learning from Reflective ePortfolio Creation

    ERIC Educational Resources Information Center

    Cherrstrom, Catherine A.; Raisor, Cindy; Fowler, Debra

    2015-01-01

    Engineering educators and employers value and prioritize communication skills, but developing and assessing such skills in engineering programs is challenging. Reflective ePortfolios provide opportunities to enhance communication skills. The purpose of this three-­year qualitative case study was to investigate the use of reflective ePortfolios in…

  7. 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…

  8. 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.

  9. 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

  10. 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.

  11. 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?…

  12. SunShot Initiative Portfolio Book 2014

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

    Solar Energy Technologies Office

    2014-05-01

    The 2014 SunShot Initiative Portfolio Book outlines the progress towards the goals outlined in the SunShot Vision Study. Contents include overviews of each of SunShot’s five subprogram areas, as well as a description of every active project in the SunShot’s project portfolio as of May 2014.

  13. Writing Portfolios in the Classroom: Policy and Practice, Promise and Peril. Evaluating Writing through Portfolios. Final Report.

    ERIC Educational Resources Information Center

    Calfee, Robert C., Ed.; Perfumo, Pamela, Ed.

    This book presents essays by researchers, practitioners, and policy makers who study the impact of classroom portfolios in the assessment of writing achievement by elementary and middle-grade students. Essays in the book report on a national survey of exemplary projects and presents contributions to a Portfolio Conference held at Stanford…

  14. Linking Assessment to Undergraduate Student Capabilities through Portfolio Examination

    ERIC Educational Resources Information Center

    O'Sullivan, Anthony J.; Harris, Peter; Hughes, Chris S.; Toohey, Susan M.; Balasooriya, Chinthaka; Velan, Gary; Kumar, Rakesh K.; McNeil, H. Patrick

    2012-01-01

    Portfolios are an established method of assessment, although concerns do exist around their validity for capabilities such as reflection and self-direction. This article describes an e-portfolio which closely aligns learning and reflection to graduate capabilities, incorporating features that address concerns about portfolios. Students are…

  15. With Portfolio in Hand. Validating the New Teacher Professionalism.

    ERIC Educational Resources Information Center

    Lyons, Nona, Ed.

    This book suggests that portfolios can become a new kind of credential of competent and effective teachers. The book includes 5 parts with 16 chapters. Part 1, "Prologue," offers: (1) "Portfolio Possibilities: Validating a New Teacher Professionalism" (Nona Lyons) and (2) "Teacher Portfolios: A Theoretical Activity"…

  16. 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

  17. 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

  18. Troubleshooting Portfolios

    ERIC Educational Resources Information Center

    Crismond, David; Peterie, Matthew

    2017-01-01

    The Troubleshooting Portfolios approach was developed at the Olathe Northwest High School in Olathe, Kansas. This approach supports integrated STEM and "informed design" thinking and learning, in which students: (1) use design strategies effectively; (2) work creatively and collaboratively in teams; (3) make knowledge-driven decisions;…

  19. Using E-Portfolios and ESL Learners

    ERIC Educational Resources Information Center

    Alawdat, Maha

    2013-01-01

    This study examines the use of e-portfolios for ESL (English as a second language) learners. The data were collected by reviewing 11 empirical studies from 2010-2012 in order to synthesize meaningful information about e-portfolios for ESL/EFL (English as a foreign language) acquisition. The studies were coded into two main categories: learning…

  20. 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.