Behavioral optimization models for multicriteria portfolio selection
Mehlawat Mukesh Kumar
2013-01-01
Full Text Available In this paper, behavioral construct of suitability is used to develop a multicriteria decision making framework for portfolio selection. To achieve this purpose, we rely on multiple methodologies. Analytical hierarchy process technique is used to model the suitability considerations with a view to obtaining the suitability performance score in respect of each asset. A fuzzy multiple criteria decision making method is used to obtain the financial quality score of each asset based upon investor's rating on the financial criteria. Two optimization models are developed for optimal asset allocation considering simultaneously financial and suitability criteria. An empirical study is conducted on randomly selected assets from National Stock Exchange, Mumbai, India to demonstrate the effectiveness of the proposed methodology.
Fuzzy Investment Portfolio Selection Models Based on Interval Analysis Approach
Haifeng Guo
2012-01-01
Full Text Available This paper employs fuzzy set theory to solve the unintuitive problem of the Markowitz mean-variance (MV portfolio model and extend it to a fuzzy investment portfolio selection model. Our model establishes intervals for expected returns and risk preference, which can take into account investors' different investment appetite and thus can find the optimal resolution for each interval. In the empirical part, we test this model in Chinese stocks investment and find that this model can fulfill different kinds of investors’ objectives. Finally, investment risk can be decreased when we add investment limit to each stock in the portfolio, which indicates our model is useful in practice.
Li, Zejing
2012-01-01
This dissertation is mainly devoted to the research of two problems - the continuous-time portfolio optimization in different Wishart models and the effects of discrete rebalancing on portfolio wealth distribution and optimal portfolio strategy.
Diversified models for portfolio selection based on uncertain semivariance
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.
Uncertain programming models for portfolio selection with uncertain returns
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.
José Claudio Isaias
2015-01-01
Full Text Available In the selecting of stock portfolios, one type of analysis that has shown good results is Data Envelopment Analysis (DEA. It, however, has been shown to have gaps regarding its estimates of monthly time horizons of data collection for the selection of stock portfolios and of monthly time horizons for the maintenance of a selected portfolio. To better estimate these horizons, this study proposes a model of mathematical programming binary of minimization of square errors. This model is the paper’s main contribution. The model’s results are validated by simulating the estimated annual return indexes of a portfolio that uses both horizons estimated and of other portfolios that do not use these horizons. The simulation shows that portfolios with both horizons estimated have higher indexes, on average 6.99% per year. The hypothesis tests confirm the statistically significant superiority of the results of the proposed mathematical model’s indexes. The model’s indexes are also compared with portfolios that use just one of the horizons estimated; here the indexes of the dual-horizon portfolios outperform the single-horizon portfolios, though with a decrease in percentage of statistically significant superiority.
The Optimal Portfolio Selection Model under g-Expectation
Li Li
2014-01-01
complicated and sophisticated, the optimal solution turns out to be surprisingly simple, the payoff of a portfolio of two binary claims. Also I give the economic meaning of my model and the comparison with that one in the work of Jin and Zhou, 2008.
Branka Marasović
2009-03-01
Full Text Available In this paper we select an optimal portfolio on the Croatian capital market by using the multicriterial programming. In accordance with the modern portfolio theory maximisation of returns at minimal risk should be the investment goal of any successful investor. However, contrary to the expectations of the modern portfolio theory, the tests carried out on a number of financial markets reveal the existence of other indicators important in portfolio selection. Considering the importance of variables other than return and risk, selection of the optimal portfolio becomes a multicriterial problem which should be solved by using the appropriate techniques.In order to select an optimal portfolio, absolute values of criteria, like return, risk, price to earning value ratio (P/E, price to book value ratio (P/B and price to sale value ratio (P/S are included in our multicriterial model. However the problem might occur as the mean values of some criteria are significantly different for different sectors and because financial managers emphasize that comparison of the same criteria for different sectors could lead us to wrong conclusions. In the second part of the paper, relative values of previously stated criteria (in relation to mean value of sector are included in model for selecting optimal portfolio. Furthermore, the paper shows that if relative values of criteria are included in multicriterial model for selecting optimal portfolio, return in subsequent period is considerably higher than if absolute values of the same criteria were used.
Wei Yue
2015-01-01
Full Text Available The major issues for mean-variance-skewness models are the errors in estimations that cause corner solutions and low diversity in the portfolio. In this paper, a multiobjective fuzzy portfolio selection model with transaction cost and liquidity is proposed to maintain the diversity of portfolio. In addition, we have designed a multiobjective evolutionary algorithm based on decomposition of the objective space to maintain the diversity of obtained solutions. The algorithm is used to obtain a set of Pareto-optimal portfolios with good diversity and convergence. To demonstrate the effectiveness of the proposed model and algorithm, the performance of the proposed algorithm is compared with the classic MOEA/D and NSGA-II through some numerical examples based on the data of the Shanghai Stock Exchange Market. Simulation results show that our proposed algorithm is able to obtain better diversity and more evenly distributed Pareto front than the other two algorithms and the proposed model can maintain quite well the diversity of portfolio. The purpose of this paper is to deal with portfolio problems in the weighted possibilistic mean-variance-skewness (MVS and possibilistic mean-variance-skewness-entropy (MVS-E frameworks with transaction cost and liquidity and to provide different Pareto-optimal investment strategies as diversified as possible for investors at a time, rather than one strategy for investors at a time.
Stock Selection for Portfolios Using Expected Utility-Entropy Decision Model
Jiping Yang
2017-09-01
Full Text Available Yang and Qiu proposed and then recently improved an expected utility-entropy (EU-E measure of risk and decision model. When segregation holds, Luce et al. derived an expected utility term, plus a constant multiplies the Shannon entropy as the representation of risky choices, further demonstrating the reasonability of the EU-E decision model. In this paper, we apply the EU-E decision model to selecting the set of stocks to be included in the portfolios. We first select 7 and 10 stocks from the 30 component stocks of Dow Jones Industrial Average index, and then derive and compare the efficient portfolios in the mean-variance framework. The conclusions imply that efficient portfolios composed of 7(10 stocks selected using the EU-E model with intermediate intervals of the tradeoff coefficients are more efficient than that composed of the sets of stocks selected using the expected utility model. Furthermore, the efficient portfolio of 7(10 stocks selected by the EU-E decision model have almost the same efficient frontier as that of the sample of all stocks. This suggests the necessity of incorporating both the expected utility and Shannon entropy together when taking risky decisions, further demonstrating the importance of Shannon entropy as the measure of uncertainty, as well as the applicability of the EU-E model as a decision-making model.
Deformed exponentials and portfolio selection
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.
On market timing and portfolio selectivity: modifying the Henriksson-Merton model
Goś, Krzysztof
2011-01-01
This paper evaluates selected functionalities of the parametrical Henriksson-Merton test, a tool designed for measuring the market timing and portfolio selectivity capabilities. It also provides a solution to two significant disadvantages of the model: relatively indirect interpretation and vulnerability to parameter insignificance. The model has been put to test on a group of Polish mutual funds in a period of 63 months (January 2004 – March 2009), providing unsatisfa...
Multi-objective possibilistic model for portfolio selection with transaction cost
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.
Portfolio Selection with Jumps under Regime Switching
Lin Zhao
2010-01-01
Full Text Available We investigate a continuous-time version of the mean-variance portfolio selection model with jumps under regime switching. The portfolio selection is proposed and analyzed for a market consisting of one bank account and multiple stocks. The random regime switching is assumed to be independent of the underlying Brownian motion and jump processes. A Markov chain modulated diffusion formulation is employed to model the problem.
Noise sensitivity of portfolio selection in constant conditional correlation GARCH models
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.
Risk modelling in portfolio optimization
Lam, W. H.; Jaaman, Saiful Hafizah Hj.; Isa, Zaidi
2013-09-01
Risk management is very important in portfolio optimization. The mean-variance model has been used in portfolio optimization to minimize the investment risk. The objective of the mean-variance model is to minimize the portfolio risk and achieve the target rate of return. Variance is used as risk measure in the mean-variance model. The purpose of this study is to compare the portfolio composition as well as performance between the optimal portfolio of mean-variance model and equally weighted portfolio. Equally weighted portfolio means the proportions that are invested in each asset are equal. The results show that the portfolio composition of the mean-variance optimal portfolio and equally weighted portfolio are different. Besides that, the mean-variance optimal portfolio gives better performance because it gives higher performance ratio than the equally weighted portfolio.
A comparison of portfolio selection models via application on ISE 100 index data
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.
Feature selection for portfolio optimization
Bjerring, Thomas Trier; Ross, Omri; Weissensteiner, Alex
2016-01-01
Most portfolio selection rules based on the sample mean and covariance matrix perform poorly out-of-sample. Moreover, there is a growing body of evidence that such optimization rules are not able to beat simple rules of thumb, such as 1/N. Parameter uncertainty has been identified as one major....... While most of the diversification benefits are preserved, the parameter estimation problem is alleviated. We conduct out-of-sample back-tests to show that in most cases different well-established portfolio selection rules applied on the reduced asset universe are able to improve alpha relative...
Portfolio selection with heavy tails
Hyung, N.; Vries, de C.G.
2007-01-01
Consider the portfolio problem of choosing the mix between stocks and bonds under a downside risk constraint. Typically stock returns exhibit fatter tails than bonds corresponding to their greater downside risk. Downside risk criteria like the safety first criterion therefore often select corner
Portfolio Selection Using Level Crossing Analysis
Bolgorian, Meysam; Shirazi, A. H.; Jafari, G. R.
Asset allocation is one of the most important and also challenging issues in finance. In this paper using level crossing analysis we introduce a new approach for portfolio selection. We introduce a portfolio index that is obtained based on minimizing the waiting time to receive known return and risk values. By the waiting time, we mean time that a special level is observed in average. The advantage of this approach is that the investors are able to set their goals based on gaining return and knowing the average waiting time and risk value at the same time. As an example we use our model for forming portfolio of stocks in Tehran Stock Exchange (TSE).
Vanderley Herrero Sola, Antonio; Mota, Caroline Maria de Miranda
2012-01-01
Highlights: ► We propose a multicriteria decision model for technology replacement. ► We prioritize induction motors in order to improve the energy efficiency. ► The best portfolio of options is selected based on decision maker’s utilities. ► The model contribute to surpass some organizational barriers. - Abstract: The energy efficient technologies offered by the market are in constant evolution, but their insertion in the productive sector comes up against organizational barriers, which obstruct decision making in firms. This paper proposes a multicriteria decision model in order to replace technologies in industrial energy systems, regarding organizational barriers for energy efficiency. The proposed model is applied in industrial motor systems, using Multi-Attribute Utility Theory (MAUT), in order to select the best portfolio of options based on the decision maker’s utilities. Portfolios of options from the prioritized set of motors compiled by the operational area of the studied industry are analyzed, including diverse suppliers and different classes of motors. The results show that it is essential to structure the proposed model in two steps, beginning with the operational level, to ensure that important technologies for the production system are prioritized, thus preserving the interests of the organization and improving the efficiency of industrial energy systems.
An Artificial Bee Colony Algorithm for Uncertain Portfolio Selection
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 ...
Parametric Portfolio Selection: Evaluating and Comparing to Markowitz Portfolios
Marcelo C. Medeiros
2014-10-01
Full Text Available In this paper we exploit the parametric portfolio optimization in the Brazilian market. Our data consists of monthly returns of 306 Brazilian stocks in the period between 2001 and 2013. We tested the model both in and out of sample and compared the results with the value and equal weighted portfolios and with a Markowitz based portfolio. We performed statistical inference in the parametric optimization using bootstrap techniques in order to build the parameters empirical distributions. Our results showed that the parametric optimization is a very efficient technique out of sample. It consistently showed superior results when compared with the VW, EW and Markowitz portfolios even when transaction costs were included. Finally, we consider the parametric approach to be very flexible to the inclusion of constraints in weights, transaction costs and listing and delisting of stocks.
A fuzzy compromise programming approach for the Black-Litterman portfolio selection model
Mohsen Gharakhani
2013-01-01
Full Text Available In this paper, we examine advanced optimization approach for portfolio problem introduced by Black and Litterman to consider the shortcomings of Markowitz standard Mean-Variance optimization. Black and Litterman propose a new approach to estimate asset return. They present a way to incorporate the investor’s views into asset pricing process. Since the investor’s view about future asset return is always subjective and imprecise, we can represent it by using fuzzy numbers and the resulting model is multi-objective linear programming. Therefore, the proposed model is analyzed through fuzzy compromise programming approach using appropriate membership function. For this purpose, we introduce the fuzzy ideal solution concept based on investor preference and indifference relationships using canonical representation of proposed fuzzy numbers by means of their correspondingα-cuts. A real world numerical example is presented in which MSCI (Morgan Stanley Capital International Index is chosen as the target index. The results are reported for a portfolio consisting of the six national indices. The performance of the proposed models is compared using several financial criteria.
Robust portfolio selection under norm uncertainty
Lei Wang
2016-06-01
Full Text Available Abstract In this paper, we consider the robust portfolio selection problem which has a data uncertainty described by the ( p , w $(p,w$ -norm in the objective function. We show that the robust formulation of this problem is equivalent to a linear optimization problem. Moreover, we present some numerical results concerning our robust portfolio selection problem.
Uncertain Portfolio Selection with Background Risk and Liquidity Constraint
Jia Zhai
2017-01-01
Full Text Available This paper discusses an uncertain portfolio selection problem with consideration of background risk and asset liquidity. In addition, the transaction costs are also considered. The security returns, background asset return, and asset liquidity are estimated by experienced experts instead of historical data. Regarding them as uncertain variables, a mean-risk model with background risk, liquidity, and transaction costs is proposed for portfolio selection and the crisp forms of the model are provided when security returns obey different uncertainty distributions. Moreover, for better understanding of the impact of background risk and liquidity on portfolio selection, some important theorems are proved. Finally, numerical experiments are presented to illustrate the modeling idea.
Learning to Select Supplier Portfolios for Service Supply Chain.
Zhang, Rui; Li, Jingfei; Wu, Shaoyu; Meng, Dabin
2016-01-01
The research on service supply chain has attracted more and more focus from both academia and industrial community. In a service supply chain, the selection of supplier portfolio is an important and difficult problem due to the fact that a supplier portfolio may include multiple suppliers from a variety of fields. To address this problem, we propose a novel supplier portfolio selection method based on a well known machine learning approach, i.e., Ranking Neural Network (RankNet). In the proposed method, we regard the problem of supplier portfolio selection as a ranking problem, which integrates a large scale of decision making features into a ranking neural network. Extensive simulation experiments are conducted, which demonstrate the feasibility and effectiveness of the proposed method. The proposed supplier portfolio selection model can be applied in a real corporation easily in the future.
Portfolio Manager Selection – A Case Study
Christensen, Michael
2017-01-01
Within a delegated portfolio management setting, this paper presents a case study of how the manager selection process can be operationalized in practice. Investors have to pursue a thorough screening of potential portfolio managers in order to discover their quality, and this paper discusses how...
IT Portfolio Selection and IT Synergy
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…
Jianwei Gao
2017-02-01
Full Text Available This paper aims to develop a risk-free protection index model for portfolio selection based on the uncertain theory. First, the returns of risk assets are assumed as uncertain variables and subject to reputable experts’ evaluations. Second, under this assumption, combining with the risk-free interest rate we define a risk-free protection index (RFPI, which can measure the protection degree when the loss of risk assets happens. Third, note that the proportion entropy serves as a complementary means to reduce the risk by the preset diversification requirement. We put forward a risk-free protection index model with an entropy constraint under an uncertainty framework by applying the RFPI, Huang’s risk index model (RIM, and mean-variance-entropy model (MVEM. Furthermore, to solve our portfolio model, an algorithm is given to estimate the uncertain expected return and standard deviation of different risk assets by applying the Delphi method. Finally, an example is provided to show that the risk-free protection index model performs better than the traditional MVEM and RIM.
Two-Stage Fuzzy Portfolio Selection Problem with Transaction Costs
Chen, Yanju; Wang, Ye
2015-01-01
This paper studies a two-period portfolio selection problem. The problem is formulated as a two-stage fuzzy portfolio selection model with transaction costs, in which the future returns of risky security are characterized by possibility distributions. The objective of the proposed model is to achieve the maximum utility in terms of the expected value and variance of the final wealth. Given the first-stage decision vector and a realization of fuzzy return, the optimal value expression of the s...
Markowitz portfolio optimization model employing fuzzy measure
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.
Portfolio Selection with Heavy Tails
N. Hyung (Namwon); C.G. de Vries (Casper)
2004-01-01
textabstractConsider the portfolio problem of choosing the mix between stocks and bonds under a downside risk constraint. Typically stock returns exhibit fatter tails than bonds corresponding to their greater downside risk. Downside risk criteria like the safety first criterion therefore of ten
M. Jasemi
2012-01-01
Full Text Available
ENGLISH ABSTRACT: In an effort to model stock markets, many researchers have developed portfolio selection models to maximise investor satisfaction. However, this field still needs more accurate and comprehensive models. Development of these models is difficult because of unpredictable economic, social, and political variables that affect stock market behaviour. In this paper, a new model with three modules for portfolio optimisation is presented. The first module derives the efficient frontier through a new approach; the second presents an intelligent mechanism for emitting trading signals; while the third module integrates the outputs of the first two modules. Some important features of the model in comparison with others are: 1 consideration of investors’ emotions – the psychology of the market – that arises from the three above-mentioned factors; 2 significant loosening of simplifying assumptions about markets and stocks; and 3 greater sensitivity to new data.
AFRIKAANSE OPSOMMING: In ‘n poging om aandelemarkte te modelleer het verskeie navorsers portefeulje-seleksiemodelle ontwikkel om beleggers se tevredenheid te maksimiseer. Desnieteenstaande word meer akkurate en omvattende modelle benodig. Die ontwikkeling van hierdie modelle word bemoeilik deur die onvoorspelbare ekonomiese, sosiale en politiese veranderlikes wat aandelemarkte se gedrag raak. In hierdie artikel word ‘n nuwe model voorgehou wat bestaan uit drie modules vir portefeulje-optimisering. Die eerste module bepaal die doelmatigheidsgrens op ‘n nuwe metode; die tweede hou ‘n intelligente meganisme voor om transaksieseine te lewer terwyl die derde module die uitsette van die eerste twee modules integreer. Sommige van die belangrike eienskappe van die model wat dit van ander onderskei is: 1 konsiderasie van die beleggers se emosies – die sielkunde van die mark – wat ontstaan vanweë die genoemde faktore; 2 betekenisvolle verslapping van die
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.
Developing a framework for energy technology portfolio selection
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.
Fuzzy Portfolio Selection Problem with Different Borrowing and Lending Rates
Chen, Wei; Yang, Yiping; Ma, Hui
2011-01-01
As we know, borrowing and lending risk-free assets arise extensively in the theory and practice of finance. However, little study has ever investigated them in fuzzy portfolio problem. In this paper, the returns of each assets are assumed to be fuzzy variables, then following the mean-variance approach, a new possibilistic portfolio selection model with different interest rates for borrowing and lending is proposed, in which the possibilistic semiabsolute deviation of the return is used to...
An artificial bee colony algorithm for uncertain portfolio selection.
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.
Continuous-Time Mean-Variance Portfolio Selection under the CEV Process
Ma, Hui-qiang
2014-01-01
We consider a continuous-time mean-variance portfolio selection model when stock price follows the constant elasticity of variance (CEV) process. The aim of this paper is to derive an optimal portfolio strategy and the efficient frontier. The mean-variance portfolio selection problem is formulated as a linearly constrained convex program problem. By employing the Lagrange multiplier method and stochastic optimal control theory, we obtain the optimal portfolio strategy and mean-variance effici...
Optimal Portfolio Selection Under Concave Price Impact
Ma Jin; Song Qingshuo; Xu Jing; Zhang Jianfeng
2013-01-01
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 solution 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.
Optimal Portfolio Selection Under Concave Price Impact
Ma Jin, E-mail: jinma@usc.edu [University of Southern California, Department of Mathematics (United States); Song Qingshuo, E-mail: songe.qingshuo@cityu.edu.hk [City University of Hong Kong, Department of Mathematics (Hong Kong); Xu Jing, E-mail: xujing8023@yahoo.com.cn [Chongqing University, School of Economics and Business Administration (China); Zhang Jianfeng, E-mail: jianfenz@usc.edu [University of Southern California, Department of Mathematics (United States)
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 solution 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.
Applying the partitioned multiobjective risk method (PMRM) to portfolio selection.
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
Portfolio selection using genetic algorithms | Yahaya | International ...
In this paper, one of the nature-inspired evolutionary algorithms – a Genetic Algorithms (GA) was used in solving the portfolio selection problem (PSP). Based on a real dataset from a popular stock market, the performance of the algorithm in relation to those obtained from one of the popular quadratic programming (QP) ...
Stock portfolio selection using Dempster–Shafer evidence theory
Gour Sundar Mitra Thakur
2018-04-01
Full Text Available Markowitz’s return–risk model for stock portfolio selection is based on the historical return data of assets. In addition to the effect of historical return, there are many other critical factors which directly or indirectly influence the stock market. We use the fuzzy Delphi method to identify the critical factors initially. Factors having lower correlation coefficients are finally considered for further consideration. The critical factors and historical data are used to apply Dempster–Shafer evidence theory to rank the stocks. Then, a portfolio selection model that prefers stocks with higher rank is proposed. Illustration is done using stocks under Bombay Stock Exchange (BSE. Simulation is done by Ant Colony Optimization. The performance of the outcome is found satisfactory when compared with recent performance of the assets. Keywords: Stock portfolio selection, Ranking, Dempster–Shafer evidence theory, Ant Colony Optimization, Fuzzy Delphi method
Mehmet Asutay
2015-04-01
Full Text Available This study examines the effect of Islamic screening criteria on Shari’ah-compliant portfolio selection and performance compared to Socially Responsible Investment (SRI portfolio. Each portfolio constructed from 15 stocks based on FTSE 100 using data from year 1997. Mean-variance portfolio optimization is employed with some financial ratios added as constraints for the Shari’ah portfolio. Annual expected return of each portfolio from 2008 to 2013 is used to calculate Sharpe’s ratio, Treynor ratio and Jensen’s alpha as the performance measurement tools. Macroeconomic variables are assessed using ordinary least square to examine whether they influence the portfolios’ expected returns or not. The result finds that Shari’ah portfolio has a better performance than SRI from year 2008 to 2010 shown by higher value of the measurement tools. However, from 2011 to 2013, SRI portfolio has better performance than Shari’ah portfolio.
Portfolio optimization with mean-variance model
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.
Selection of a portfolio of R & D projects
Casault, Sébastien; Groen, Arend J.; Linton, J.D.; Linton, Jonathan; Link, A.N.; Vonortas, N.S.
2013-01-01
While portfolios of research are increasingly discussed, a portfolio perspective is infrequently taken when selecting two or more projects. Consequently, this chapter considers the current state of knowledge in project and portfolio selection, identifies why we can and cannot apply knowledge from
Model Risk in Portfolio Optimization
David Stefanovits
2014-08-01
Full Text Available We consider a one-period portfolio optimization problem under model uncertainty. For this purpose, we introduce a measure of model risk. We derive analytical results for this measure of model risk in the mean-variance problem assuming we have observations drawn from a normal variance mixture model. This model allows for heavy tails, tail dependence and leptokurtosis of marginals. The results show that mean-variance optimization is seriously compromised by model uncertainty, in particular, for non-Gaussian data and small sample sizes. To mitigate these shortcomings, we propose a method to adjust the sample covariance matrix in order to reduce model risk.
Portfolio selection theory and wildlife management
JW Hearne
2008-12-01
Full Text Available With a strong commercial incentive driving the increase in game ranching in Southern Africa the need has come for more advanced management tools. In this paper the potential of Portfolio Selection Theory to determine the optimal mix of species on game ranches is explored. Land, or the food it produces, is a resource available to invest. We consider species as investment choices. Each species has its own return and risk profile. The question arises as to what proportion of the resource available should be invested in each species. We show that if the objective is to minimise risk for a given return, then the problem is analogous to the Portfolio Selection Problem. The method is then implemented for a typical game ranch. We show that besides risk and return objectives, it is necessary to include an additional objective so as to ensure sufficient species to maintain the character of a game ranch. Some other points of difference from the classical Portfolio Selection problem are also highlighted and discussed.
Log-Optimal Portfolio Selection Using the Blackwell Approachability Theorem
V'yugin, Vladimir
2014-01-01
We present a method for constructing the log-optimal portfolio using the well-calibrated forecasts of market values. Dawid's notion of calibration and the Blackwell approachability theorem are used for computing well-calibrated forecasts. We select a portfolio using this "artificial" probability distribution of market values. Our portfolio performs asymptotically at least as well as any stationary portfolio that redistributes the investment at each round using a continuous function of side in...
The admissible portfolio selection problem with transaction costs and an improved PSO algorithm
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.
Selecting Large Portfolios of Social Projects in Public Organizations
Igor Litvinchev
2014-01-01
Full Text Available We address the portfolio selection of social projects in public organizations considering interdependencies (synergies affecting project funds requirements and tasks. A mixed integer linear programming model is proposed incorporating the most relevant aspects of the problem found in the literature. The model supports both complete (all or nothing and partial (a certain amount from a given interval of funding resource allocation policies. Numerical results for large-scale problem instances are presented.
Automatic Trading Agent. RMT Based Portfolio Theory and Portfolio Selection
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.
Stock portfolio selection using Dempster–Shafer evidence theory
Mitra Thakur, Gour Sundar; Bhattacharyya, Rupak; Sarkar (Mondal), Seema
2016-01-01
Markowitz’s return–risk model for stock portfolio selection is based on the historical return data of assets. In addition to the effect of historical return, there are many other critical factors which directly or indirectly influence the stock market. We use the fuzzy Delphi method to identify the critical factors initially. Factors having lower correlation coefficients are finally considered for further consideration. The critical factors and historical data are used to apply Dempster–Shafe...
Portfolio selection using ELECTRE III: Evidence from Tehran Stock Exchange
Aazam Shabani Vezmelai
2015-04-01
Full Text Available Ranking the companies can be a useful guide for investors to select an optimum portfolio. Tehran stock exchange (TSE uses liquidity criterion to rank the companies; however, this study shows that preferences of investors, the criteria they use to evaluate companies’ performances, and the extent to which ranking of companies based on investors’ criteria are in line with the ranking announced by the stock exchange. Since the criteria used for ranking the companies are various and often conflicting and because each multiple criteria technique has its own specific characteristics, various rankings are offered. Therefore, it is required to utilize multiple criteria decision making models to avoid confusion of investors. For this purpose, some companies were selected from 50 top companies listed in 2011 in TSE, which maintained the reliability of their ranks and finally, 20 companies were selected and were ranked based on investors’ criteria using EECTRE III Technique. The obtained ranking was then compared with the ranking offered by stock exchange. Research results indicate that ELECTRE III technique was a useful and efficient method to select a portfolio. Moreover, value-based criteria as well as accounting criteria are suitable and useful bases for investors to select a portfolio.
Purchasing portfolio models: a critique and update
Gelderman, C.J.; Weele, van A.J.
2005-01-01
Purchasing portfolio models have spawned considerable discussion in the literature. Many advantages and disadvantages have been put forward, revealing considerable divergence in opinion on the merits of portfolio models. This study addresses the question of whether or not the use of purchasing
Portfolio selection theory and wildlife management | Hearne | ORiON
Portfolio selection theory and wildlife management. ... Abstract. With a strong commercial incentive driving the increase in game ranching in Southern Africa the need has come for more advanced management tools. ... Keywords: Portfolio selection, multi-objective optimisation, game ranching, wildlife management.
Portfolios with fuzzy returns: Selection strategies based on semi-infinite programming
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.
Vast Portfolio Selection with Gross-exposure Constraints().
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.
Vast Portfolio Selection with Gross-exposure Constraints*
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
Fuzzy Portfolio Selection Problem with Different Borrowing and Lending Rates
Wei Chen
2011-01-01
the returns of each assets are assumed to be fuzzy variables, then following the mean-variance approach, a new possibilistic portfolio selection model with different interest rates for borrowing and lending is proposed, in which the possibilistic semiabsolute deviation of the return is used to measure investment risk. The conventional probabilistic mean variance model can be transformed to a linear programming problem under possibility distributions. Finally, a numerical example is given to illustrate the modeling idea and the impact of borrowing and lending on optimal decision making.
Maximizing Consensus in Portfolio Selection in Multicriteria Group Decision Making
Michael, Emmerich T. M.; Deutz, A.H.; Li, L.; Asep, Maulana A.; Yevseyeva, I.
2016-01-01
This paper deals with a scenario of decision making where a moderator selects a (sub)set (aka portfolio) of decision alternatives from a larger set. The larger the number of decision makers who agree on a solution in the portfolio the more successful the moderator is. We assume that decision makers
Two-Stage Fuzzy Portfolio Selection Problem with Transaction Costs
Yanju Chen
2015-01-01
Full Text Available This paper studies a two-period portfolio selection problem. The problem is formulated as a two-stage fuzzy portfolio selection model with transaction costs, in which the future returns of risky security are characterized by possibility distributions. The objective of the proposed model is to achieve the maximum utility in terms of the expected value and variance of the final wealth. Given the first-stage decision vector and a realization of fuzzy return, the optimal value expression of the second-stage programming problem is derived. As a result, the proposed two-stage model is equivalent to a single-stage model, and the analytical optimal solution of the two-stage model is obtained, which helps us to discuss the properties of the optimal solution. Finally, some numerical experiments are performed to demonstrate the new modeling idea and the effectiveness. The computational results provided by the proposed model show that the more risk-averse investor will invest more wealth in the risk-free security. They also show that the optimal invested amount in risky security increases as the risk-free return decreases and the optimal utility increases as the risk-free return increases, whereas the optimal utility increases as the transaction costs decrease. In most instances the utilities provided by the proposed two-stage model are larger than those provided by the single-stage model.
Portfolio Selection Based on Distance between Fuzzy Variables
Weiyi Qian
2014-01-01
Full Text Available This paper researches portfolio selection problem in fuzzy environment. We introduce a new simple method in which the distance between fuzzy variables is used to measure the divergence of fuzzy investment return from a prior one. Firstly, two new mathematical models are proposed by expressing divergence as distance, investment return as expected value, and risk as variance and semivariance, respectively. Secondly, the crisp forms of the new models are also provided for different types of fuzzy variables. Finally, several numerical examples are given to illustrate the effectiveness of the proposed approach.
A proposed selection process in Over-The-Top project portfolio management
Jemy Vestius Confido
2018-05-01
Full Text Available Purpose: The purpose of this paper is to propose an Over-The-Top (OTT initiative selection process for communication service providers (CSPs entering an OTT business. Design/methodology/approach: To achieve this objective, a literature review was conducted to comprehend the past and current practices of the project (or initiative selection process as mainly suggested in project portfolio management (PPM. This literature was compared with specific situations and the needs of CSPs when constructing an OTT portfolio. Based on the contrast between the conventional project selection process and specific OTT characteristics, a different selection process is developed and tested using group model-building (GMB, which involved an in-depth interview, a questionnaire and a focus group discussion (FGD. Findings: The paper recommends five distinct steps for CSPs to construct an OTT initiative portfolio: candidate list of OTT initiatives, interdependency diagram, evaluation of all interdependent OTT initiatives, evaluation of all non-interdependent OTT initiatives and optimal portfolio of OTT initiatives. Research limitations/implications: The research is empirical, and various OTT services are implemented; the conclusion is derived only from one CSP, which operates as a group. Generalization of this approach will require further empirical tests on different CSPs, OTT players or any firms performing portfolio selection with a degree of interdependency among the projects. Practical implications: Having considered interdependency, the proposed OTT initiative selection steps can be further implemented by portfolio managers for more effective OTT initiative portfolio construction. Originality/value: While the previous literature and common practices suggest ensuring the benefits (mainly financial of individual projects, this research accords higher priority to the success of the overall OTT initiative portfolio and recommends that an evaluation of the overall
Javed Bin Kamal
2012-09-01
Full Text Available The paper aims at constructing an optimal portfolio by applying Sharpe’s single index model of capital asset pricing in different scenarios, one is ex ante stock price bubble scenario and stock price bubble and bubble burst is second scenario. Here we considered beginning of year 2010 as rise of stock price bubble in Dhaka Stock Exchange. Hence period from 2005 -2009 is considered as ex ante stock price bubble period. Using DSI (All share price index in Dhaka Stock Exchange as market index and considering daily indices for the March 2005 to December 2009 period, the proposed method formulates a unique cut off point (cut off rate of return and selects stocks having excess of their expected return over risk-free rate of return surpassing this cut-off point. Here, risk free rate considered to be 8.5% per annum (Treasury bill rate in 2009. Percentage of an investment in each of the selected stocks is then decided on the basis of respective weights assigned to each stock depending on respective ‘β’ value, stock movement variance representing unsystematic risk, return on stock and risk free return vis-à-vis the cut off rate of return. Interestingly, most of the stocks selected turned out to be bank stocks. Again we went for single index model applied to same stocks those made to the optimum portfolio in ex ante stock price bubble scenario considering data for the period of January 2010 to June 2012. We found that all stocks failed to make the pass Single Index Model criteria i.e. excess return over beta must be higher than the risk free rate. Here for the period of 2010 to 2012, the risk free rate considered to be 11.5 % per annum (Treasury bill rate during 2012.
The electricity portfolio simulation model (EPSim) technical description.
Drennen, Thomas E.; Klotz, Richard (Hobart and William Smith Colleges, Geneva, NY)
2005-09-01
Stakeholders often have competing interests when selecting or planning new power plants. The purpose of developing this preliminary Electricity Portfolio Simulation Model (EPSim) is to provide a first cut, dynamic methodology and approach to this problem, that can subsequently be refined and validated, that may help energy planners, policy makers, and energy students better understand the tradeoffs associated with competing electricity portfolios. EPSim allows the user to explore competing electricity portfolios annually from 2002 to 2025 in terms of five different criteria: cost, environmental impacts, energy dependence, health and safety, and sustainability. Four additional criteria (infrastructure vulnerability, service limitations, policy needs and science and technology needs) may be added in future versions of the model. Using an analytic hierarchy process (AHP) approach, users or groups of users apply weights to each of the criteria. The default energy assumptions of the model mimic Department of Energy's (DOE) electricity portfolio to 2025 (EIA, 2005). At any time, the user can compare alternative portfolios to this reference case portfolio.
Applying Portfolio Selection: A Case of Indonesia Stock Exchange
Maria Praptiningsih
2012-01-01
Full Text Available This study has three objectives. First, we investigate whether Modern Portfolio Theory can be applied on the financial decisions that made by investors or individual in order to increase their wealth through investment activities. Second, we examine the real behavior of each asset in terms of capital assets pricing models. Third, we determine whether our portfolio is the best model to produce a higher return in a given level of risk or a lowest risk in a particular level of return. It is found that three different stocks listed in the Indonesia Stock Exchange have a positive relationship with market returns. The reactions of the investor regarding these stocks are not influenced by each other. Lastly, the minimum variance portfolio (MVP point which represents the single portfolio with the lowest possible level of standard deviation, occurs when the expected return of portfolio is approximately 2.2 percent at a standard deviation of 8.8 percent.
Properties of Risk Measures of Generalized Entropy in Portfolio Selection
Rongxi Zhou
2017-12-01
Full Text Available This paper systematically investigates the properties of six kinds of entropy-based risk measures: Information Entropy and Cumulative Residual Entropy in the probability space, Fuzzy Entropy, Credibility Entropy and Sine Entropy in the fuzzy space, and Hybrid Entropy in the hybridized uncertainty of both fuzziness and randomness. We discover that none of the risk measures satisfy all six of the following properties, which various scholars have associated with effective risk measures: Monotonicity, Translation Invariance, Sub-additivity, Positive Homogeneity, Consistency and Convexity. Measures based on Fuzzy Entropy, Credibility Entropy, and Sine Entropy all exhibit the same properties: Sub-additivity, Positive Homogeneity, Consistency, and Convexity. These measures based on Information Entropy and Hybrid Entropy, meanwhile, only exhibit Sub-additivity and Consistency. Cumulative Residual Entropy satisfies just Sub-additivity, Positive Homogeneity, and Convexity. After identifying these properties, we develop seven portfolio models based on different risk measures and made empirical comparisons using samples from both the Shenzhen Stock Exchange of China and the New York Stock Exchange of America. The comparisons show that the Mean Fuzzy Entropy Model performs the best among the seven models with respect to both daily returns and relative cumulative returns. Overall, these results could provide an important reference for both constructing effective risk measures and rationally selecting the appropriate risk measure under different portfolio selection conditions.
Selection of risk reduction portfolios under interval-valued probabilities
Toppila, Antti; Salo, Ahti
2017-01-01
A central problem in risk management is that of identifying the optimal combination (or portfolio) of improvements that enhance the reliability of the system most through reducing failure event probabilities, subject to the availability of resources. This optimal portfolio can be sensitive with regard to epistemic uncertainties about the failure events' probabilities. In this paper, we develop an optimization model to support the allocation of resources to improvements that mitigate risks in coherent systems in which interval-valued probabilities defined by lower and upper bounds are employed to capture epistemic uncertainties. Decision recommendations are based on portfolio dominance: a resource allocation portfolio is dominated if there exists another portfolio that improves system reliability (i) at least as much for all feasible failure probabilities and (ii) strictly more for some feasible probabilities. Based on non-dominated portfolios, recommendations about improvements to implement are derived by inspecting in how many non-dominated portfolios a given improvement is contained. We present an exact method for computing the non-dominated portfolios. We also present an approximate method that simplifies the reliability function using total order interactions so that larger problem instances can be solved with reasonable computational effort. - Highlights: • Reliability allocation under epistemic uncertainty about probabilities. • Comparison of alternatives using dominance. • Computational methods for generating the non-dominated alternatives. • Deriving decision recommendations that are robust with respect to epistemic uncertainty.
Credit Portfolio Selection According to Sectors in Risky Environments: Markowitz Practice
Halim Kazan; Kültigin Uludag
2014-01-01
In this study, it was researched that how the rate of repayment of loans will be increased and how the credit risk will be minimized in banking sector, by using Markowitz Portfolio Theory. Construction, textile and wholesale and retail sectors were examined under the central bank data. Portfolio groups were selected and risks( variances of Portfolio groups) were evaluated according to Markowitz portfolio theory. Markowitz portfolio theory is effective than the other portfolio selection instru...
Maslow Portfolio Selection for Individuals with Low Financial Sustainability
Zongxin Li
2018-04-01
Full Text Available In this paper, we extend Maslow’s need hierarchy theory and the two-level optimization approach by developing the framework of the Maslow portfolio selection model (MPSM by solving the two optimization problems to meet the need of individuals with low financial sustainability who prefer to satisfy their lower-level (safety need first, and, thereafter, look for higher-level (self-actualization need to maximize the optimal return. We illustrate our proposed model with real American stock data from the S&P index and conduct the out-of-sample analysis to compare the performance of our proposed Variance-CVaR (conditional value-at-risk MPSM with both traditional mean-variance and mean-CVaR models. Our empirical analysis shows that our proposed Variance-CVaR MPSM is not only sustainable, but also obtains the best out-of-sample performance in the sense that the optimal portfolios obtained by using our proposed Variance-CVaR MPSM obtain the highest cumulative returns in the out-of-sample period among the models used in our paper. We note that our proposed model is not only suitable to individuals with low financial sustainability, but also suitable to institutions or investors with high financial sustainability.
A behavioural approach to financial portfolio selection problem: an empirical study using heuristics
Grishina, Nina
2014-01-01
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University The behaviourally based portfolio selection problem with investor's loss aversion and risk aversion biases in portfolio choice under uncertainty are studied. The main results of this work are developed heuristic approaches for the prospect theory and cumulative prospect theory models proposed by Kahneman and Tversky in 1979 and 1992 as well as an empirical comparative analysis of these models ...
Linear versus quadratic portfolio optimization model with transaction cost
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.
Portfolio selection theory and wildlife management
Theron and Van den Honert (2003) dealt with issues of risk and return in an agricultural context. ... By repeatedly solving (1) with different specified values of R an efficient frontier of portfolio .... the built–in solver of Microsoft® Excel [2].
Patent portfolio management: literature review and a proposed model.
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.
Land-Use Portfolio Modeler, Version 1.0
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
NPD project portfolio selection using reinvestment strategy in competitive environment
Alireza Ghassemi
2018-01-01
Full Text Available This study aims to design a new model for selecting most fitting new product development projects in a pool of projects. To catch the best model, we assume new products will be introduced to the competitive markets. Also, we suppose the revenue yielded by completed projects can be reinvested on implementation of other projects. Other sources of financing are borrowing loans from banks and initial capital of the firm. These limited resources determine most evaluated projects to be performed. Several types of interactions among different projects are considered to make the chosen projects more like a portfolio. In addition, some numerical examples from the real world are provided to demonstrate the applicability of the proposed model. These examples show how the particular considerations in the suggested model affect the results.
Enhanced index tracking modelling in portfolio optimization
Lam, W. S.; Hj. Jaaman, Saiful Hafizah; Ismail, Hamizun bin
2013-09-01
Enhanced index tracking is a popular form of passive fund management in stock market. It is a dual-objective optimization problem, a trade-off between maximizing the mean return and minimizing the risk. Enhanced index tracking aims to generate excess return over the return achieved by the index without purchasing all of the stocks that make up the index by establishing an optimal portfolio. The objective of this study is to determine the optimal portfolio composition and performance by using weighted model in enhanced index tracking. Weighted model focuses on the trade-off between the excess return and the risk. The results of this study show that the optimal portfolio for the weighted model is able to outperform the Malaysia market index which is Kuala Lumpur Composite Index because of higher mean return and lower risk without purchasing all the stocks in the market index.
A diversified portfolio model of adaptability.
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).
Declarative Modeling for Production Order Portfolio Scheduling
Banaszak Zbigniew
2014-12-01
Full Text Available A declarative framework enabling to determine conditions as well as to develop decision-making software supporting small- and medium-sized enterprises aimed at unique, multi-project-like and mass customized oriented production is discussed. A set of unique production orders grouped into portfolio orders is considered. Operations executed along different production orders share available resources following a mutual exclusion protocol. A unique product or production batch is completed while following a given activity’s network order. The problem concerns scheduling a newly inserted project portfolio subject to constraints imposed by a multi-project environment The answers sought are: Can a given project portfolio specified by its cost and completion time be completed within the assumed time period in a manufacturing system in hand? Which manufacturing system capability guarantees the completion of a given project portfolio ordered under assumed cost and time constraints? The considered problems regard finding a computationally effective approach aimed at simultaneous routing and allocation as well as batching and scheduling of a newly ordered project portfolio subject to constraints imposed by a multi-project environment. The main objective is to provide a declarative model enabling to state a constraint satisfaction problem aimed at multi-project-like and mass customized oriented production scheduling. Multiple illustrative examples are discussed.
Continuous-Time Mean-Variance Portfolio Selection under the CEV Process
Hui-qiang Ma
2014-01-01
Full Text Available We consider a continuous-time mean-variance portfolio selection model when stock price follows the constant elasticity of variance (CEV process. The aim of this paper is to derive an optimal portfolio strategy and the efficient frontier. The mean-variance portfolio selection problem is formulated as a linearly constrained convex program problem. By employing the Lagrange multiplier method and stochastic optimal control theory, we obtain the optimal portfolio strategy and mean-variance efficient frontier analytically. The results show that the mean-variance efficient frontier is still a parabola in the mean-variance plane, and the optimal strategies depend not only on the total wealth but also on the stock price. Moreover, some numerical examples are given to analyze the sensitivity of the efficient frontier with respect to the elasticity parameter and to illustrate the results presented in this paper. The numerical results show that the price of risk decreases as the elasticity coefficient increases.
Portfolio Effects of Renewable Energies - Basics, Models, Exemplary Results
Wiese, Andreas; Herrmann, Matthias
2007-07-01
The combination of sites and technologies to so-called renewable energy portfolios, which are being developed and implemented under the same financing umbrella, is currently the subject of intense discussion in the finance world. The resulting portfolio effect may allow the prediction of a higher return with the same risk or the same return with a lower risk - always in comparison with the investment in a single project. Models are currently being developed to analyse this subject and derive the portfolio effect. In particular, the effect of the spatial distribution, as well as the effects of using different technologies, suppliers and cost assumptions with different level of uncertainties, are of importance. Wind parks, photovoltaic, biomass, biogas and hydropower are being considered. The status of the model development and first results are being presented in the current paper. In a first example, the portfolio effect has been calculated and analysed using selected parameters for a wind energy portfolio of 39 sites distributed over Europe. Consequently it has been shown that the predicted yield, with the predetermined probabilities between 75 to 90%, is 3 - 8% higher than the sum of the yields for the individual wind parks using the same probabilities. (auth)
Discrete Analysis of Portfolio Selection with Optimal Stopping Time
Jianfeng Liang
2009-01-01
Full Text Available Most of the investments in practice are carried out without certain horizons. There are many factors to drive investment to a stop. In this paper, we consider a portfolio selection policy with market-related stopping time. Particularly, we assume that the investor exits the market once his wealth reaches a given investment target or falls below a bankruptcy threshold. Our objective is to minimize the expected time when the investment target is obtained, at the same time, we guarantee the probability that bankruptcy happens is no larger than a given level. We formulate the problem as a mix integer linear programming model and make analysis of the model by using a numerical example.
PROJECT PORTFOLIO SELECTION COMPETENCES RESEARCH INUNIVERSITIES OF LITHUANIA
R #363;ta #268;iutien #279;; Evelina Meilien #279;; Bronius Neverauskas
2011-01-01
As a result of the theoretical findings, the paperdemonstrates that projectportfolio selection is crucial project management problem. Successful ProjectPortfolio management requires specific competences.Every project of projectportfolio must be evaluated according to the basedcriteria and parameters.Empirical study was based on framework matrix withfour parameters of projectportfolio selection and only two phases of projectportfolio formation. The r...
A General Framework for Portfolio Theory. Part I: theory and various models
Maier-Paape, Stanislaus; Zhu, Qiji Jim
2017-01-01
Utility and risk are two often competing measurements on the investment success. We show that efficient trade-off between these two measurements for investment portfolios happens, in general, on a convex curve in the two dimensional space of utility and risk. This is a rather general pattern. The modern portfolio theory of Markowitz [H. Markowitz, Portfolio Selection, 1959] and its natural generalization, the capital market pricing model, [W. F. Sharpe, Mutual fund performance , 1966] are spe...
Fuzzy portfolio model with fuzzy-input return rates and fuzzy-output proportions
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.
Fuzzy Random λ-Mean SAD Portfolio Selection Problem: An Ant Colony Optimization Approach
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.
Portfolio selection problem with liquidity constraints under non-extensive statistical mechanics
Zhao, Pan; Xiao, Qingxian
2016-01-01
In this study, we consider the optimal portfolio selection problem with liquidity limits. A portfolio selection model is proposed in which the risky asset price is driven by the process based on non-extensive statistical mechanics instead of the classic Wiener process. Using dynamic programming and Lagrange multiplier methods, we obtain the optimal policy and value function. Moreover, the numerical results indicate that this model is considerably different from the model based on the classic Wiener process, the optimal strategy is affected by the non-extensive parameter q, the increase in the investment in the risky asset is faster at a larger parameter q and the increase in wealth is similar.
Mean-Coherent Risk and Mean-Variance Approaches in Portfolio Selection : An Empirical Comparison
Polbennikov, S.Y.; Melenberg, B.
2005-01-01
We empirically analyze the implementation of coherent risk measures in portfolio selection.First, we compare optimal portfolios obtained through mean-coherent risk optimization with corresponding mean-variance portfolios.We find that, even for a typical portfolio of equities, the outcomes can be
Reliable Portfolio Selection Problem in Fuzzy Environment: An mλ Measure Based Approach
Yuan Feng
2017-04-01
Full Text Available This paper investigates a fuzzy portfolio selection problem with guaranteed reliability, in which the fuzzy variables are used to capture the uncertain returns of different securities. To effectively handle the fuzziness in a mathematical way, a new expected value operator and variance of fuzzy variables are defined based on the m λ measure that is a linear combination of the possibility measure and necessity measure to balance the pessimism and optimism in the decision-making process. To formulate the reliable portfolio selection problem, we particularly adopt the expected total return and standard variance of the total return to evaluate the reliability of the investment strategies, producing three risk-guaranteed reliable portfolio selection models. To solve the proposed models, an effective genetic algorithm is designed to generate the approximate optimal solution to the considered problem. Finally, the numerical examples are given to show the performance of the proposed models and algorithm.
Nonparametric correlation models for portfolio allocation
Aslanidis, Nektarios; Casas, Isabel
2013-01-01
This article proposes time-varying nonparametric and semiparametric estimators of the conditional cross-correlation matrix in the context of portfolio allocation. Simulations results show that the nonparametric and semiparametric models are best in DGPs with substantial variability or structural ...... currencies. Results show the nonparametric model generally dominates the others when evaluating in-sample. However, the semiparametric model is best for out-of-sample analysis....
Optimal portfolio selection for general provisioning and terminal wealth problems
van Weert, K.; Dhaene, J.; Goovaerts, M.
2010-01-01
In Dhaene et al. (2005), multiperiod portfolio selection problems are discussed, using an analytical approach to find optimal constant mix investment strategies in a provisioning or a savings context. In this paper we extend some of these results, investigating some specific, real-life situations.
Optimal portfolio selection for general provisioning and terminal wealth problems
van Weert, K.; Dhaene, J.; Goovaerts, M.
2009-01-01
In Dhaene et al. (2005), multiperiod portfolio selection problems are discussed, using an analytical approach to find optimal constant mix investment strategies in a provisioning or savings context. In this paper we extend some of these results, investigating some specific, real-life situations. The
MARKOV CHAIN PORTFOLIO LIQUIDITY OPTIMIZATION MODEL
Eder Oliveira Abensur
2014-05-01
Full Text Available The international financial crisis of September 2008 and May 2010 showed the importance of liquidity as an attribute to be considered in portfolio decisions. This study proposes an optimization model based on available public data, using Markov chain and Genetic Algorithms concepts as it considers the classic duality of risk versus return and incorporating liquidity costs. The work intends to propose a multi-criterion non-linear optimization model using liquidity based on a Markov chain. The non-linear model was tested using Genetic Algorithms with twenty five Brazilian stocks from 2007 to 2009. The results suggest that this is an innovative development methodology and useful for developing an efficient and realistic financial portfolio, as it considers many attributes such as risk, return and liquidity.
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.
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
A dynamic decision model for portfolio investment and assets management
QIAN Edward Y.; FENG Ying; HIGGISION James
2005-01-01
This paper addresses a dynamic portfolio investment problem. It discusses how we can dynamically choose candidate assets, achieve the possible maximum revenue and reduce the risk to the minimum level. The paper generalizes Markowitz's portfolio selection theory and Sharpe's rule for investment decision. An analytical solution is presented to show how an institutional or individual investor can combine Markowitz's portfolio selection theory, generalized Sharpe's rule and Value-at-Risk(VaR) to find candidate assets and optimal level of position sizes for investment (dis-investment). The result shows that the generalized Markowitz's portfolio selection theory and generalized Sharpe's rule improve decision making for investment.
New Method of Selecting Efficient Project Portfolios in the Presence of Hybrid Uncertainty
Bogdan Rębiasz
2016-01-01
Full Text Available A new methods of selecting efficient project portfolios in the presence of hybrid uncertainty has been presented. Pareto optimal solutions have been defined by an algorithm for generating project portfolios. The method presented allows us to select efficient project portfolios taking into account statistical and economic dependencies between projects when some of the parameters used in the calculation of effectiveness can be expressed in the form of an interactive possibility distribution and some in the form of a probability distribution. The procedure for processing such hybrid data combines stochastic simulation with nonlinear programming. The interaction between data are modeled by correlation matrices and the interval regression. Economic dependences are taken into account by the equations balancing the production capacity of the company. The practical example presented indicates that an interaction between projects has a significant impact on the results of calculations. (original abstract
Effective Stock Selection and Portfolio Construction Within US, International, and Emerging Markets
Bijan Beheshti
2018-05-01
Full Text Available In this paper, we explore the ex-post attributes of 120 simulated portfolios across the U.S., International, and Emerging Markets. We estimate expected returns using a given global stock selection model employing Global Equity Rating (GLER and Consensus Temporary Earnings Forecasting (CTEF signals. Our portfolios are constructed under the Markowitz optimization framework and constrained at various tracking error levels. Further, an alpha alignment factor is applied to aid in portfolio construction. As a result of our research, we present the reader with three key findings. First, GLER and CTEF signals employed as the primary inputs to security selection result in portfolios with superior risk adjusted returns relative to the Russell 3000, MSCI AC World ex. US, and MSCI Emerging Markets benchmarks which they are measured against. Second, expanding the investment universe outside the U.S. increases the opportunity set yielding higher risk adjusted performance. Third, the incorporation of an alpha alignment factor within the portfolio construction process improves risk forecasts resulting in ex-post tracking error aligning more closely to ex-ante, and ultimately improving information ratios.
Towards a reference model for portfolio management for product development
Larsson, Flemming
2006-01-01
The aim of this paper is to explore the concept of portfolio management for product development at company level. Departing from a combination of explorative interviews with industry professionals and a literature review a proposal for a reference model for portfolio management is developed....... The model consists of a set of defined and interrelated concepts which forms a coherent and consistent reference model that explicate the totality of the portfolio management concept at company level in terms of structure, processes and elements. The model simultaneously pinpoints, positions and integrates...... several central dimensions of portfolio management....
Kim, Saejoon
2018-01-01
We consider the problem of low-volatility portfolio selection which has been the subject of extensive research in the field of portfolio selection. To improve the currently existing techniques that rely purely on past information to select low-volatility portfolios, this paper investigates the use of time series regression techniques that make forecasts of future volatility to select the portfolios. In particular, for the first time, the utility of support vector regression and its enhancements as portfolio selection techniques is provided. It is shown that our regression-based portfolio selection provides attractive outperformances compared to the benchmark index and the portfolio defined by a well-known strategy on the data-sets of the S&P 500 and the KOSPI 200.
Enhanced index tracking modeling in portfolio optimization with mixed-integer programming z approach
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.
PORTFOLIO SELECTION OF INFORMATION SYSTEMS PROJECTS USING PROMETHEE V WITH C-OPTIMAL CONCEPT
Jonatas A. de Almeida
2014-05-01
Full Text Available This paper presents a multicriteria decision model for selecting a portfolio of information system (IS projects, which integrates strategic and organizational view within a multicriteria decision structure. The PROMETHEE V method, based on outranking relations is applied, considering the c-optimal concept in order to overcome some scaling problems found in the classical PROMETHEE V approach. Then, a procedure is proposed in order to make a final analysis of the c-optimal portfolios found as a result of using PROMETHEE V. Also, the organizational view is discussed, including some factors that may influence decision making on IS projects to be included in the portfolio, such as adding the company's strategic vision and technical aspects that demonstrate how IS contributes value to a company's business.
A hybrid intelligent algorithm for portfolio selection problem with fuzzy returns
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.
Dynamic Portfolio Selection on Croatian Financial Markets: MGARCH Approach
Škrinjarić, Tihana; Šego, Boško
2016-01-01
Background: Investors on financial markets are interested in finding trading strategies which could enable them to beat the market. They always look for best possibilities to achieve above-average returns and manage risks successfully. MGARCH methodology (Multivariate Generalized Autoregressive Conditional Heteroskedasticity) makes it possible to model changing risks and return dynamics on financial markets on a daily basis. The results could be used in order to enhance portfolio formation an...
Dynamic Portfolio Selection on Croatian Financial Markets: MGARCH Approach
Škrinjarić Tihana
2016-09-01
Full Text Available Background: Investors on financial markets are interested in finding trading strategies which could enable them to beat the market. They always look for best possibilities to achieve above-average returns and manage risks successfully. MGARCH methodology (Multivariate Generalized Autoregressive Conditional Heteroskedasticity makes it possible to model changing risks and return dynamics on financial markets on a daily basis. The results could be used in order to enhance portfolio formation and restructuring over time.
The Effect of Exit Strategy on Optimal Portfolio Selection with Birandom Returns
Cao, Guohua; Shan, Dan
2013-01-01
The aims of this paper are to use a birandom variable to denote the stock return selected by some recurring technical patterns and to study the effect of exit strategy on optimal portfolio selection with birandom returns. Firstly, we propose a new method to estimate the stock return and use birandom distribution to denote the final stock return which can reflect the features of technical patterns and investors' heterogeneity simultaneously; secondly, we build a birandom safety-first model and...
Mean-variance model for portfolio optimization with background risk based on uncertainty theory
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.
Yongyi Shou
2014-01-01
Full Text Available A multiagent evolutionary algorithm is proposed to solve the resource-constrained project portfolio selection and scheduling problem. The proposed algorithm has a dual level structure. In the upper level a set of agents make decisions to select appropriate project portfolios. Each agent selects its project portfolio independently. The neighborhood competition operator and self-learning operator are designed to improve the agent’s energy, that is, the portfolio profit. In the lower level the selected projects are scheduled simultaneously and completion times are computed to estimate the expected portfolio profit. A priority rule-based heuristic is used by each agent to solve the multiproject scheduling problem. A set of instances were generated systematically from the widely used Patterson set. Computational experiments confirmed that the proposed evolutionary algorithm is effective for the resource-constrained project portfolio selection and scheduling problem.
Construction of uncertainty sets for portfolio selection problems
Wiechers, Christof
2011-01-01
While modern portfolio theory grounds on the trade-off between portfolio return and portfolio variance to determine the optimal investment decision, postmodern portfolio theory uses downside risk measures instead of the variance. Prominent examples are given by the risk measures Value-at-Risk and its coherent extension, Conditional Value-at-Risk. When avoiding distributional assumptions on the process that generates the risky assets' returns, historical return data or expert knowledge remain ...
Portfolio optimization for index tracking modelling in Malaysia stock market
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.
Continuous-Time Mean-Variance Portfolio Selection: A Stochastic LQ Framework
Zhou, X.Y.; Li, D.
2000-01-01
This paper is concerned with a continuous-time mean-variance portfolio selection model that is formulated as a bicriteria optimization problem. The objective is to maximize the expected terminal return and minimize the variance of the terminal wealth. By putting weights on the two criteria one obtains a single objective stochastic control problem which is however not in the standard form due to the variance term involved. It is shown that this nonstandard problem can be 'embedded' into a class of auxiliary stochastic linear-quadratic (LQ) problems. The stochastic LQ control model proves to be an appropriate and effective framework to study the mean-variance problem in light of the recent development on general stochastic LQ problems with indefinite control weighting matrices. This gives rise to the efficient frontier in a closed form for the original portfolio selection problem
Comparative evaluation of fuzzy logic and genetic algorithms models for portfolio optimization
Heidar Masoumi Soureh
2017-03-01
Full Text Available Selection of optimum methods which have appropriate speed and precision for planning and de-cision-making has always been a challenge for investors and managers. One the most important concerns for them is investment planning and optimization for acquisition of desirable wealth under controlled risk with the best return. This paper proposes a model based on Markowitz the-orem by considering the aforementioned limitations in order to help effective decisions-making for portfolio selection. Then, the model is investigated by fuzzy logic and genetic algorithms, for the optimization of the portfolio in selected active companies listed in Tehran Stock Exchange over the period 2012-2016 and the results of the above models are discussed. The results show that the two studied models had functional differences in portfolio optimization, its tools and the possibility of supplementing each other and their selection.
Mean-Variance Portfolio Selection with Margin Requirements
Yuan Zhou
2013-01-01
Full Text Available We study the continuous-time mean-variance portfolio selection problem in the situation when investors must pay margin for short selling. The problem is essentially a nonlinear stochastic optimal control problem because the coefficients of positive and negative parts of control variables are different. We can not apply the results of stochastic linearquadratic (LQ problem. Also the solution of corresponding Hamilton-Jacobi-Bellman (HJB equation is not smooth. Li et al. (2002 studied the case when short selling is prohibited; therefore they only need to consider the positive part of control variables, whereas we need to handle both the positive part and the negative part of control variables. The main difficulty is that the positive part and the negative part are not independent. The previous results are not directly applicable. By decomposing the problem into several subproblems we figure out the solutions of HJB equation in two disjoint regions and then prove it is the viscosity solution of HJB equation. Finally we formulate solution of optimal portfolio and the efficient frontier. We also present two examples showing how different margin rates affect the optimal solutions and the efficient frontier.
Allan, Grant; Eromenko, Igor; McGregor, Peter; Swales, Kim
2011-01-01
Standalone levelised cost assessments of electricity supply options miss an important contribution that renewable and non-fossil fuel technologies can make to the electricity portfolio: that of reducing the variability of electricity costs, and their potentially damaging impact upon economic activity. Portfolio theory applications to the electricity generation mix have shown that renewable technologies, their costs being largely uncorrelated with non-renewable technologies, can offer such benefits. We look at the existing Scottish generation mix and examine drivers of changes out to 2020. We assess recent scenarios for the Scottish generation mix in 2020 against mean-variance efficient portfolios of electricity-generating technologies. Each of the scenarios studied implies a portfolio cost of electricity that is between 22% and 38% higher than the portfolio cost of electricity in 2007. These scenarios prove to be mean-variance 'inefficient' in the sense that, for example, lower variance portfolios can be obtained without increasing portfolio costs, typically by expanding the share of renewables. As part of extensive sensitivity analysis, we find that Wave and Tidal technologies can contribute to lower risk electricity portfolios, while not increasing portfolio cost. - Research Highlights: → Portfolio analysis of scenarios for Scotland's electricity generating mix in 2020. → Reveals potential inefficiencies of selecting mixes based on levelised cost alone. → Portfolio risk-reducing contribution of Wave and Tidal technologies assessed.
Allan, Grant, E-mail: grant.j.allan@strath.ac.u [Fraser of Allander Institute, Department of Economics, University of Strathclyde, Sir William Duncan Building, 130 Rottenrow, Glasgow G4 0GE (United Kingdom); Eromenko, Igor; McGregor, Peter [Fraser of Allander Institute, Department of Economics, University of Strathclyde, Sir William Duncan Building, 130 Rottenrow, Glasgow G4 0GE (United Kingdom); Swales, Kim [Department of Economics, University of Strathclyde, Sir William Duncan Building, 130 Rottenrow, Glasgow G4 0GE (United Kingdom)
2011-01-15
Standalone levelised cost assessments of electricity supply options miss an important contribution that renewable and non-fossil fuel technologies can make to the electricity portfolio: that of reducing the variability of electricity costs, and their potentially damaging impact upon economic activity. Portfolio theory applications to the electricity generation mix have shown that renewable technologies, their costs being largely uncorrelated with non-renewable technologies, can offer such benefits. We look at the existing Scottish generation mix and examine drivers of changes out to 2020. We assess recent scenarios for the Scottish generation mix in 2020 against mean-variance efficient portfolios of electricity-generating technologies. Each of the scenarios studied implies a portfolio cost of electricity that is between 22% and 38% higher than the portfolio cost of electricity in 2007. These scenarios prove to be mean-variance 'inefficient' in the sense that, for example, lower variance portfolios can be obtained without increasing portfolio costs, typically by expanding the share of renewables. As part of extensive sensitivity analysis, we find that Wave and Tidal technologies can contribute to lower risk electricity portfolios, while not increasing portfolio cost. - Research Highlights: {yields} Portfolio analysis of scenarios for Scotland's electricity generating mix in 2020. {yields} Reveals potential inefficiencies of selecting mixes based on levelised cost alone. {yields} Portfolio risk-reducing contribution of Wave and Tidal technologies assessed.
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.
Mean-Variance stochastic goal programming for sustainable mutual funds' portfolio selection.
García-Bernabeu, Ana
2015-11-01
Full Text Available Mean-Variance Stochastic Goal Programming models (MV-SGP provide satisficing investment solutions in uncertain contexts. In this work, an MV-SGP model is proposed for portfolio selection which includes goals with regards to traditional and sustainable assets. The proposed approach is based on a two-step procedure. In the first step, sustainability and/or financial screens are applied to a set of assets (mutual funds previously evaluated with TOPSIS to determine the opportunity set. In a second step, satisficing portfolios of assets are obtained using a Goal Programming approach. Two different goals are considered. The first goal reflects only the purely financial side of the target while the second goal is referred to the sustainable side. Aversion to Risk Absolute (ARA coefficients are estimated and incorporated in our investment decision making approach using two different approaches.
A portfolio analysis model of the demand for nuclear power plants
Sutherland, R.J.
1986-01-01
Electric utilities are characterized as timid risk averters that select coal or nuclear plants or both, where the levellized cost of each is characterized by considerable risk. A portfolio selection model is developed to explain the historical demand for nuclear reactors by region. Some qualitative policy implications are derived with respect to the DOE's objective of reviving the nuclear power market. (author)
Xu, Guo; Wing-Keung, Wong; Lixing, Zhu
2013-01-01
This paper investigates the impact of background risk on an investor’s portfolio choice in a mean-VaR, mean-CVaR and mean-variance framework, and analyzes the characterizations of the mean-variance boundary and mean-VaR efficient frontier in the presence of background risk. We also consider the case with a risk-free security.
Portfolio Sensitivity Model for Analyzing Credit Risk Caused by Structural and Macroeconomic Changes
Goran Klepac
2008-12-01
Full Text Available This paper proposes a new model for portfolio sensitivity analysis. The model is suitable for decision support in financial institutions, specifically for portfolio planning and portfolio management. The basic advantage of the model is the ability to create simulations for credit risk predictions in cases when we virtually change portfolio structure and/or macroeconomic factors. The model takes a holistic approach to portfolio management consolidating all organizational segments in the process such as marketing, retail and risk.
Development of an Electronic Portfolio System Success Model: An Information Systems Approach
Balaban, Igor; Mu, Enrique; Divjak, Blazenka
2013-01-01
This research has two main goals: to develop an instrument for assessing Electronic Portfolio (ePortfolio) success and to build a corresponding ePortfolio success model using DeLone and McLean's information systems success model as the theoretical framework. For this purpose, we developed an ePortfolio success measurement instrument and structural…
Portfolio selection between rational and behavioral theories emergent markets case
Bouri Abdelfatteh
2012-08-01
Full Text Available The aim of this paper is to explore the determinants of Portfolio Choice under the investors, professionals and academics’ perception. We introduce an approach based on cognitive mapping technique with a series of semi-directive interviews. Among a sample of 30 Tunisian individuals, we propose tow different frameworks: a mean-variance framework and a behavioral framework. Each framework is oriented to capture the effect of some concepts as proposed by the mean-variance portfolio theory and the behavioral portfolio theory on the portfolio choice decision. The originality of this research paper is guaranteed since it traits the behavioral portfolio choice in emergent markets. In the best of our knowledge this is the first study in the Tunisian context that explores such area of research. Ours results show that the Tunisian investors behave as it prescribed by the behavioral portfolio theory. They use some concepts proposed by the rational mean-variance theory of portfolio choice but they are affected by their emotions and some others cognitive bias when constructing and managing they portfolio of assets.
Portfolio optimization for seed selection in diverse weather scenarios.
Marko, Oskar; Brdar, Sanja; Panić, Marko; Šašić, Isidora; Despotović, Danica; Knežević, Milivoje; Crnojević, Vladimir
2017-01-01
The aim of this work was to develop a method for selection of optimal soybean varieties for the American Midwest using data analytics. We extracted the knowledge about 174 varieties from the dataset, which contained information about weather, soil, yield and regional statistical parameters. Next, we predicted the yield of each variety in each of 6,490 observed subregions of the Midwest. Furthermore, yield was predicted for all the possible weather scenarios approximated by 15 historical weather instances contained in the dataset. Using predicted yields and covariance between varieties through different weather scenarios, we performed portfolio optimisation. In this way, for each subregion, we obtained a selection of varieties, that proved superior to others in terms of the amount and stability of yield. According to the rules of Syngenta Crop Challenge, for which this research was conducted, we aggregated the results across all subregions and selected up to five soybean varieties that should be distributed across the network of seed retailers. The work presented in this paper was the winning solution for Syngenta Crop Challenge 2017.
Portfolio optimization for seed selection in diverse weather scenarios.
Oskar Marko
Full Text Available 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.
System for selecting a postponement strategy portfolio for supply chains
Luiz Eduardo Simão
2015-03-01
Full Text Available The stagnation of the economy has increased competition and uncertainty in the industrial sector. Trends such as the increase in the proliferation of the variety of products and the requirement for customization of products has contributed to difficulties in forecasting demand, due to increased uncertainty of demand for final products. In this new competitive environment, it is no longer possible to use the traditional “one size fits all” supply chain process, with unique policies for all products because this practice can lead to significant profitability losses due to the increase in stock levels and lost sales. However, research on supply chains has given relatively little attention to the need to use different, segmented supply chain strategies as well as to develop and manage these multiple supply chains strategies simultaneously. Thus, this paper aims to present an approach for selecting a portfolio of postponement strategies based on segmentation of supply chain, based on analysis of the demand profile (volume-variety analysis and a tool to assist in the selection of postponement strategies driven by the customer-product sector and their respective propositions of value.
Semantic modeling of portfolio assessment in e-learning environment
Lucila Romero
2017-01-01
Full Text Available In learning environment, portfolio is used as a tool to keep track of learner’s progress. Particularly, when it comes to e-learning, continuous assessment allows greater customization and efficiency in learning process and prevents students lost interest in their study. Also, each student has his own characteristics and learning skills that must be taken into account in order to keep learner`s interest. So, personalized monitoring is the key to guarantee the success of technology-based education. In this context, portfolio assessment emerge as the solution because is an easy way to allow teacher organize and personalize assessment according to students characteristic and need. A portfolio assessment can contain various types of assessment like formative assessment, summative assessment, hetero or self-assessment and use different instruments like multiple choice questions, conceptual maps, and essay among others. So, a portfolio assessment represents a compilation of all assessments must be solved by a student in a course, it documents progress and set targets. In previous work, it has been proposed a conceptual framework that consist of an ontology network named AOnet which is a semantic tool conceptualizing different types of assessments. Continuing that work, this paper presents a proposal to implement portfolios assessment in e-learning environments. The proposal consists of a semantic model that describes key components and relations of this domain to set the bases to develop a tool to generate, manage and perform portfolios assessment.
Bozhalkina, Yana
2017-12-01
Mathematical model of the loan portfolio structure change in the form of Markov chain is explored. This model considers in one scheme both the process of customers attraction, their selection based on the credit score, and loans repayment. The model describes the structure and volume of the loan portfolio dynamics, which allows to make medium-term forecasts of profitability and risk. Within the model corrective actions of bank management in order to increase lending volumes or to reduce the risk are formalized.
Continuous-time mean-variance portfolio selection with value-at-risk and no-shorting constraints
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.
Continuous Time Portfolio Selection under Conditional Capital at Risk
Gordana Dmitrasinovic-Vidovic
2010-01-01
Full Text Available Portfolio optimization with respect to different risk measures is of interest to both practitioners and academics. For there to be a well-defined optimal portfolio, it is important that the risk measure be coherent and quasiconvex with respect to the proportion invested in risky assets. In this paper we investigate one such measure—conditional capital at risk—and find the optimal strategies under this measure, in the Black-Scholes continuous time setting, with time dependent coefficients.
RISK LOAN PORTFOLIO OPTIMIZATION MODEL BASED ON CVAR RISK MEASURE
Ming-Chang LEE
2015-07-01
Full Text Available In order to achieve commercial banks liquidity, safety and profitability objective requirements, loan portfolio risk analysis based optimization decisions are rational allocation of assets. The risk analysis and asset allocation are the key technology of banking and risk management. The aim of this paper, build a loan portfolio optimization model based on risk analysis. Loan portfolio rate of return by using Value-at-Risk (VaR and Conditional Value-at-Risk (CVaR constraint optimization decision model reflects the bank's risk tolerance, and the potential loss of direct control of the bank. In this paper, it analyze a general risk management model applied to portfolio problems with VaR and CVaR risk measures by using Using the Lagrangian Algorithm. This paper solves the highly difficult problem by matrix operation method. Therefore, the combination of this paper is easy understanding the portfolio problems with VaR and CVaR risk model is a hyperbola in mean-standard deviation space. It is easy calculation in proposed method.
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.
Robust Markowitz mean-variance portfolio selection under ambiguous covariance matrix *
Ismail, Amine; Pham, Huyên
2016-01-01
This paper studies a robust continuous-time Markowitz portfolio selection pro\\-blem where the model uncertainty carries on the covariance matrix of multiple risky assets. This problem is formulated into a min-max mean-variance problem over a set of non-dominated probability measures that is solved by a McKean-Vlasov dynamic programming approach, which allows us to characterize the solution in terms of a Bellman-Isaacs equation in the Wasserstein space of probability measures. We provide expli...
Application of Markowitz Portfolio Theory by Building Optimal Portfolio on the US Stock Market
Martin Širůček
2015-01-01
Full Text Available This paper is focused on building investment portfolios by using the Markowitz Portfolio Theory (MPT. Derivation based on the Capital Asset Pricing Model (CAPM is used to calculate the weights of individual securities in portfolios. The calculated portfolios include a portfolio copying the benchmark made using the CAPM model, portfolio with low and high beta coefficients, and a random portfolio. Only stocks were selected for the examined sample from all the asset classes. Stocks in each portfolio are put together according to predefined criteria. All stocks were selected from Dow Jones Industrial Average (DJIA index which serves as a benchmark, too. Portfolios were compared based on their risk and return profiles. The results of this work will provide general recommendations on the optimal approach to choose securities for an investor’s portfolio.
PENGGUNAAN ALGORITMA GENETIKA UNTUK PEMILIHAN PORTFOLIO SAHAM DALAM MODEL MARKOWITZ
Silvia Rostianingsih
2005-01-01
Full Text Available Modern portfolio theory is based on asumption that investor can choose his proportion asset in portfolio, so they can minimize the risk and maximize the return. This paper presents the use of genetic algorithm (GA to optimize the choice of share portfolio in markowitz model by representing the efficient set portfolio. GA represent the efficient set using undirect representation to avoid infeasible solution and penalty function. From the implementation, it can be concluded that GA is one of methods which is able to obtain optimum point from portfolio. Abstract in Bahasa Indonesia : Teori portofolio modern mendasarkan teorinya pada asumsi bahwa investor bertindak secara rasional dengan memilih proporsi asetnya dalam sebuah portofolio sedemikian rupa sehingga dapat meminimalkan resiko dan memaksimalkan return. Dalam paper ini penulis mencoba menyajikan penggunaan algoritma genetika (Genetic Algorithm/GA untuk optimasi pemilihan portofolio saham dalam model markowitz dengan cara merepresentasikannya sebagai kumpulan portofolio yang efisien (the efficient set portofolio. GA merepresentasikan kumpulan yang effisien ini dengan menggunakan representasi tidak langsung untuk menghindari solusi yang tidak feasible dan fungsi penalti. Dari hasil yang telah diimplementasikan dapat disimpulkan bahwa GA dapat digunakan sebagai salah satu metode yang cukup berhasil dalam menemukan titik optimum dari sebuah portofolio. Kata kunci: markowitz, teori portofolio, algoritma genetika.
Testing APT Model upon a BVB Stocks’ Portfolio
Alexandra BONTAŞ
2011-01-01
Full Text Available Applying the Arbitrage Pricing Theory model (APT, there can be identified the major factors of influence for a BVB’ portfolio stocks' trend. There were taken into consideration two of the APT theory models, establishing influences upon portfolio's yield: given to macroeconomic environment and to some stochastic factors. The researchs results certify that, on the long term, what influences the stocks’ movement in the stock market is mostly the action of specific short-term factors, without general covering, like the ones that are classified in the research area of behavioral finance (investors’ preference towards risk and towards time.
Incorporating Contagion in Portfolio Credit Risk Models Using Network Theory
Anagnostou, I.; Sourabh, S.; Kandhai, D.
2018-01-01
Portfolio credit risk models estimate the range of potential losses due to defaults or deteriorations in credit quality. Most of these models perceive default correlation as fully captured by the dependence on a set of common underlying risk factors. In light of empirical evidence, the ability of
Continuous-Time Mean-Variance Portfolio Selection with Random Horizon
Yu, Zhiyong
2013-01-01
This paper examines the continuous-time mean-variance optimal portfolio selection problem with random market parameters and random time horizon. Treating this problem as a linearly constrained stochastic linear-quadratic optimal control problem, I explicitly derive the efficient portfolios and efficient frontier in closed forms based on the solutions of two backward stochastic differential equations. Some related issues such as a minimum variance portfolio and a mutual fund theorem are also addressed. All the results are markedly different from those in the problem with deterministic exit time. A key part of my analysis involves proving the global solvability of a stochastic Riccati equation, which is interesting in its own right
Continuous-Time Mean-Variance Portfolio Selection with Random Horizon
Yu, Zhiyong, E-mail: yuzhiyong@sdu.edu.cn [Shandong University, School of Mathematics (China)
2013-12-15
This paper examines the continuous-time mean-variance optimal portfolio selection problem with random market parameters and random time horizon. Treating this problem as a linearly constrained stochastic linear-quadratic optimal control problem, I explicitly derive the efficient portfolios and efficient frontier in closed forms based on the solutions of two backward stochastic differential equations. Some related issues such as a minimum variance portfolio and a mutual fund theorem are also addressed. All the results are markedly different from those in the problem with deterministic exit time. A key part of my analysis involves proving the global solvability of a stochastic Riccati equation, which is interesting in its own right.
The Effect of Exit Strategy on Optimal Portfolio Selection with Birandom Returns
Guohua Cao
2013-01-01
Full Text Available The aims of this paper are to use a birandom variable to denote the stock return selected by some recurring technical patterns and to study the effect of exit strategy on optimal portfolio selection with birandom returns. Firstly, we propose a new method to estimate the stock return and use birandom distribution to denote the final stock return which can reflect the features of technical patterns and investors' heterogeneity simultaneously; secondly, we build a birandom safety-first model and design a hybrid intelligent algorithm to help investors make decisions; finally, we innovatively study the effect of exit strategy on the given birandom safety-first model. The results indicate that (1 the exit strategy affects the proportion of portfolio, (2 the performance of taking the exit strategy is better than when the exit strategy is not taken, if the stop-loss point and the stop-profit point are appropriately set, and (3 the investor using the exit strategy become conservative.
A Polynomial Optimization Approach to Constant Rebalanced Portfolio Selection
Takano, Y.; Sotirov, R.
2010-01-01
We address the multi-period portfolio optimization problem with the constant rebalancing strategy. This problem is formulated as a polynomial optimization problem (POP) by using a mean-variance criterion. In order to solve the POPs of high degree, we develop a cutting-plane algorithm based on
Optimal portfolio selection for cashflows with bounded capital at risk
Vyncke, D.; Goovaerts, M.J.; Dhaene, J.L.M.; Vanduffel, S.
2005-01-01
We consider a continuous-time Markowitz type portfolio problem that consists of minimizing the discounted cost of a given cash-fl ow under the constraint of a restricted Capital at Risk. In a Black-Scholes setting, upper and lower bounds are obtained by means of simple analytical expressions that
A polynomial optimization approach to constant rebalanced portfolio selection
Takano, Y.; Sotirov, R.
2012-01-01
We address the multi-period portfolio optimization problem with the constant rebalancing strategy. This problem is formulated as a polynomial optimization problem (POP) by using a mean-variance criterion. In order to solve the POPs of high degree, we develop a cutting-plane algorithm based on
Quantifying credit portfolio losses under multi-factor models
G. Colldeforns-Papiol (Gemma); L. Ortiz Gracia (Luis); C.W. Oosterlee (Kees)
2018-01-01
textabstractIn this work, we investigate the challenging problem of estimating credit risk measures of portfolios with exposure concentration under the multi-factor Gaussian and multi-factor t-copula models. It is well-known that Monte Carlo (MC) methods are highly demanding from the computational
Introducing Model Predictive Control for Improving Power Plant Portfolio Performance
Edlund, Kristian Skjoldborg; Bendtsen, Jan Dimon; Børresen, Simon
2008-01-01
This paper introduces a model predictive control (MPC) approach for construction of a controller for balancing the power generation against consumption in a power system. The objective of the controller is to coordinate a portfolio consisting of multiple power plant units in the effort to perform...
Mean-variance portfolio selection for defined-contribution pension funds with stochastic salary.
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.
Mean-Variance Portfolio Selection for Defined-Contribution Pension Funds with Stochastic Salary
Chubing Zhang
2014-01-01
Full Text Available 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.
Mean-Variance Portfolio Selection for Defined-Contribution Pension Funds with Stochastic Salary
Chubing Zhang
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.
Mean-Variance Portfolio Selection for Defined-Contribution Pension Funds with Stochastic Salary
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
System Architecture Modeling for Technology Portfolio Management using ATLAS
Thompson, Robert W.; O'Neil, Daniel A.
2006-01-01
Strategic planners and technology portfolio managers have traditionally relied on consensus-based tools, such as Analytical Hierarchy Process (AHP) and Quality Function Deployment (QFD) in planning the funding of technology development. While useful to a certain extent, these tools are limited in the ability to fully quantify the impact of a technology choice on system mass, system reliability, project schedule, and lifecycle cost. The Advanced Technology Lifecycle Analysis System (ATLAS) aims to provide strategic planners a decision support tool for analyzing technology selections within a Space Exploration Architecture (SEA). Using ATLAS, strategic planners can select physics-based system models from a library, configure the systems with technologies and performance parameters, and plan the deployment of a SEA. Key parameters for current and future technologies have been collected from subject-matter experts and other documented sources in the Technology Tool Box (TTB). ATLAS can be used to compare the technical feasibility and economic viability of a set of technology choices for one SEA, and compare it against another set of technology choices or another SEA. System architecture modeling in ATLAS is a multi-step process. First, the modeler defines the system level requirements. Second, the modeler identifies technologies of interest whose impact on an SEA. Third, the system modeling team creates models of architecture elements (e.g. launch vehicles, in-space transfer vehicles, crew vehicles) if they are not already in the model library. Finally, the architecture modeler develops a script for the ATLAS tool to run, and the results for comparison are generated.
A Bayesian joint model for population and portfolio-specific mortality
van Berkum, F.; Antonio, K.; Vellekoop, M.
2015-01-01
Insurers and pension funds must value liabilities using mortality rates that are appropriate for their portfolio. Current practice is to multiply available projections of population mortality with portfolio-specific factors, which are often determined using Generalised Linear Models. Alternatively,
Multi-period project portfolio selection under risk considerations and stochastic income
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.
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.
Portfolio optimization by using linear programing models based on genetic algorithm
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.
Application of an integrated model for evaluation and optimization of business projects portfolios
Camila Costa Dutra
2016-12-01
Full Text Available This work presents an application of an integrated model for the evaluation and probabilistic optimization of projects portfolios, integrating economic, risk and social and environmental impacts analysis. The model uses the Monte Carlo simulation and linear programming techniques for treatment of uncertainties and optimization of projects portfolio. The integrated model was applied in a Brazilian company of electricity distributions. The portfolio of selected projects was related to the expansion of the supply of electricity in a town in the south of the country and the analysis horizon was set in ten years. The aim of the application was to maximize the return for the implementation of a substation and a transmission line in a set of projects, which are diverse in terms of costs, benefits and environmental and social impacts. As a result, the model generates: i an analysis of each individual projects, from budget information (costs and benefits involved and estimation of social and environmental impacts generated by the project and the risks (uncertainties involved and ii the optimum combination of projects that the company should prioritize to ensure the best financial return and lower social and environmental impacts, thus generating an optimal portfolio.
APPLICATION OF AN INTEGRATED MODEL FOR EVALUATION AND OPTIMIZATION OF BUSINESS PROJECTS PORTFOLIOS
Maria Auxiliadora Cannarozzo Tinoco
2016-12-01
Full Text Available This work presents an application of an integrated model for the evaluation and probabilistic optimization of projects portfolios, integrating economic, risk and social and environmental impacts analysis. The model uses the Monte Carlo simulation and linear programming techniques for treatment of uncertainties and optimization of projects portfolio. The integrated model was applied in a Brazilian company of electricity distributions. The portfolio of selected projects was related to the expansion of the supply of electricity in a town in the south of the country and the analysis horizon was set in ten years. The aim of the application was to maximize the return for the implementation of a substation and a transmission line in a set of projects, which are diverse in terms of costs, benefits and environmental and social impacts. As a result, the model generates: i an analysis of each individual projects, from budget information (costs and benefits involved and estimation of social and environmental impacts generated by the project and the risks (uncertainties involved and ii the optimum combination of projects that the company should prioritize to ensure the best financial return and lower social and environmental impacts, thus generating an optimal portfolio
Duncan, T.; Pasik Duncan, B.; Stettner, L.
2011-01-01
A continuous time long run growth optimal or optimal logarithmic utility portfolio with proportional transaction costs consisting of a fixed proportional cost and a cost proportional to the volume of transaction is considered. The asset prices are modeled as exponent of diffusion with jumps whose parameters depend on a finite state Markov process of economic factors. An obligatory portfolio diversification is introduced, accordingly to which it is required to invest at least a fixed small portion of our wealth in each asset.
Flightdeck Automation Problems (FLAP) Model for Safety Technology Portfolio Assessment
Ancel, Ersin; Shih, Ann T.
2014-01-01
NASA's Aviation Safety Program (AvSP) develops and advances methodologies and technologies to improve air transportation safety. The Safety Analysis and Integration Team (SAIT) conducts a safety technology portfolio assessment (PA) to analyze the program content, to examine the benefits and risks of products with respect to program goals, and to support programmatic decision making. The PA process includes systematic identification of current and future safety risks as well as tracking several quantitative and qualitative metrics to ensure the program goals are addressing prominent safety risks accurately and effectively. One of the metrics within the PA process involves using quantitative aviation safety models to gauge the impact of the safety products. This paper demonstrates the role of aviation safety modeling by providing model outputs and evaluating a sample of portfolio elements using the Flightdeck Automation Problems (FLAP) model. The model enables not only ranking of the quantitative relative risk reduction impact of all portfolio elements, but also highlighting the areas with high potential impact via sensitivity and gap analyses in support of the program office. Although the model outputs are preliminary and products are notional, the process shown in this paper is essential to a comprehensive PA of NASA's safety products in the current program and future programs/projects.
Supplier Portfolio Selection and Optimum Volume Allocation: A Knowledge Based Method
Aziz, Romana; Aziz, R.; van Hillegersberg, Jos; Kersten, W.; Blecker, T.; Luthje, C.
2010-01-01
Selection of suppliers and allocation of optimum volumes to suppliers is a strategic business decision. This paper presents a decision support method for supplier selection and the optimal allocation of volumes in a supplier portfolio. The requirements for the method were gathered during a case
Vast Volatility Matrix Estimation using High Frequency Data for Portfolio Selection*
Fan, Jianqing; Li, Yingying; Yu, Ke
2012-01-01
Portfolio allocation with gross-exposure constraint is an effective method to increase the efficiency and stability of portfolios selection among a vast pool of assets, as demonstrated in Fan et al. (2011). The required high-dimensional volatility matrix can be estimated by using high frequency financial data. This enables us to better adapt to the local volatilities and local correlations among vast number of assets and to increase significantly the sample size for estimating the volatility matrix. This paper studies the volatility matrix estimation using high-dimensional high-frequency data from the perspective of portfolio selection. Specifically, we propose the use of “pairwise-refresh time” and “all-refresh time” methods based on the concept of “refresh time” proposed by Barndorff-Nielsen et al. (2008) for estimation of vast covariance matrix and compare their merits in the portfolio selection. We establish the concentration inequalities of the estimates, which guarantee desirable properties of the estimated volatility matrix in vast asset allocation with gross exposure constraints. Extensive numerical studies are made via carefully designed simulations. Comparing with the methods based on low frequency daily data, our methods can capture the most recent trend of the time varying volatility and correlation, hence provide more accurate guidance for the portfolio allocation in the next time period. The advantage of using high-frequency data is significant in our simulation and empirical studies, which consist of 50 simulated assets and 30 constituent stocks of Dow Jones Industrial Average index. PMID:23264708
Vast Volatility Matrix Estimation using High Frequency Data for Portfolio Selection.
Fan, Jianqing; Li, Yingying; Yu, Ke
2012-01-01
Portfolio allocation with gross-exposure constraint is an effective method to increase the efficiency and stability of portfolios selection among a vast pool of assets, as demonstrated in Fan et al. (2011). The required high-dimensional volatility matrix can be estimated by using high frequency financial data. This enables us to better adapt to the local volatilities and local correlations among vast number of assets and to increase significantly the sample size for estimating the volatility matrix. This paper studies the volatility matrix estimation using high-dimensional high-frequency data from the perspective of portfolio selection. Specifically, we propose the use of "pairwise-refresh time" and "all-refresh time" methods based on the concept of "refresh time" proposed by Barndorff-Nielsen et al. (2008) for estimation of vast covariance matrix and compare their merits in the portfolio selection. We establish the concentration inequalities of the estimates, which guarantee desirable properties of the estimated volatility matrix in vast asset allocation with gross exposure constraints. Extensive numerical studies are made via carefully designed simulations. Comparing with the methods based on low frequency daily data, our methods can capture the most recent trend of the time varying volatility and correlation, hence provide more accurate guidance for the portfolio allocation in the next time period. The advantage of using high-frequency data is significant in our simulation and empirical studies, which consist of 50 simulated assets and 30 constituent stocks of Dow Jones Industrial Average index.
Application of Vine Copulas to Credit Portfolio Risk Modeling
Marco Geidosch
2016-06-01
Full Text Available In this paper, we demonstrate the superiority of vine copulas over conventional copulas when modeling the dependence structure of a credit portfolio. We show statistical and economic implications of replacing conventional copulas by vine copulas for a subportfolio of the Euro Stoxx 50 and the S&P 500 companies, respectively. Our study includes D-vines and R-vines where the bivariate building blocks are chosen from the Gaussian, the t and the Clayton family. Our findings are (i the conventional Gauss copula is deficient in modeling the dependence structure of a credit portfolio and economic capital is seriously underestimated; (ii D-vine structures offer a better statistical fit to the data than classical copulas, but underestimate economic capital compared to R-vines; (iii when mixing different copula families in an R-vine structure, the best statistical fit to the data can be achieved which corresponds to the most reliable estimate for economic capital.
Incorporating Contagion in Portfolio Credit Risk Models Using Network Theory
Ioannis Anagnostou
2018-01-01
Full Text Available Portfolio credit risk models estimate the range of potential losses due to defaults or deteriorations in credit quality. Most of these models perceive default correlation as fully captured by the dependence on a set of common underlying risk factors. In light of empirical evidence, the ability of such a conditional independence framework to accommodate for the occasional default clustering has been questioned repeatedly. Thus, financial institutions have relied on stressed correlations or alternative copulas with more extreme tail dependence. In this paper, we propose a different remedy—augmenting systematic risk factors with a contagious default mechanism which affects the entire universe of credits. We construct credit stress propagation networks and calibrate contagion parameters for infectious defaults. The resulting framework is implemented on synthetic test portfolios wherein the contagion effect is shown to have a significant impact on the tails of the loss distributions.
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.
Risk-aware multi-armed bandit problem with application to portfolio selection.
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.
Risk-Controlled Multiobjective Portfolio Selection Problem Using a Principle of Compromise
Takashi Hasuike
2014-01-01
Full Text Available This paper proposes a multiobjective portfolio selection problem with most probable random distribution derived from current market data and other random distributions of boom and recession under the risk-controlled parameters determined by an investor. The current market data and information include not only historical data but also interpretations of economists’ oral and linguistic information, and hence, the boom and recession are often caused by these nonnumeric data. Therefore, investors need to consider several situations from most probable condition to boom and recession and to avoid the risk less than the target return in each situation. Furthermore, it is generally difficult to set random distributions of these cases exactly. Therefore, a robust-based approach for portfolio selection problems using the only mean values and variances of securities is proposed as a multiobjective programming problem. In addition, an exact algorithm is developed to obtain an explicit optimal portfolio using a principle of compromise.
A Generalized Measure for the Optimal Portfolio Selection Problem and its Explicit Solution
Zinoviy Landsman
2018-03-01
Full Text Available In this paper, we offer a novel class of utility functions applied to optimal portfolio selection. This class incorporates as special cases important measures such as the mean-variance, Sharpe ratio, mean-standard deviation and others. We provide an explicit solution to the problem of optimal portfolio selection based on this class. Furthermore, we show that each measure in this class generally reduces to the efficient frontier that coincides or belongs to the classical mean-variance efficient frontier. In addition, a condition is provided for the existence of the a one-to-one correspondence between the parameter of this class of utility functions and the trade-off parameter λ in the mean-variance utility function. This correspondence essentially provides insight into the choice of this parameter. We illustrate our results by taking a portfolio of stocks from National Association of Securities Dealers Automated Quotation (NASDAQ.
Shih, Ann T.; Ancel, Ersin; Jones, Sharon M.
2012-01-01
The concern for reducing aviation safety risk is rising as the National Airspace System in the United States transforms to the Next Generation Air Transportation System (NextGen). The NASA Aviation Safety Program is committed to developing an effective aviation safety technology portfolio to meet the challenges of this transformation and to mitigate relevant safety risks. The paper focuses on the reasoning of selecting Object-Oriented Bayesian Networks (OOBN) as the technique and commercial software for the accident modeling and portfolio assessment. To illustrate the benefits of OOBN in a large and complex aviation accident model, the in-flight Loss-of-Control Accident Framework (LOCAF) constructed as an influence diagram is presented. An OOBN approach not only simplifies construction and maintenance of complex causal networks for the modelers, but also offers a well-organized hierarchical network that is easier for decision makers to exploit the model examining the effectiveness of risk mitigation strategies through technology insertions.
Modelling on optimal portfolio with exchange rate based on discontinuous stochastic process
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.
A Hybrid MCDM Approach for Strategic Project Portfolio Selection of Agro By-Products
Animesh Debnath
2017-07-01
Full Text Available Due to the increasing size of the population, society faces several challenges for sustainable and adequate agricultural production, quality, distribution, and food safety in the strategic project portfolio selection (SPPS. The initial adaptation of strategic portfolio management of genetically modified (GM Agro by-products (Ab-Ps is a huge challenge in terms of processing the agro food product supply-chain practices in an environmentally nonthreatening way. As a solution to the challenges, the socio-economic characteristics for SPPS of GM food purchasing scenarios are studied. Evaluation and selection of the GM agro portfolio management are the dynamic issues due to physical and immaterial criteria involving a hybrid multiple criteria decision making (MCDM approach, combining modified grey Decision-Making Trial and Evaluation Laboratory (DEMATEL, Multi-Attributive Border Approximation area Comparison (MABAC and sensitivity analysis. Evaluation criteria are grouped into social, differential and beneficial clusters, and the modified DEMATEL procedure is used to derive the criteria weights. The MABAC method is applied to rank the strategic project portfolios according to the aggregated preferences of decision makers (DMs. The usefulness of the proposed research framework is validated with a case study. The GM by-products are found to be the best portfolio. Moreover, this framework can unify the policies of agro technological improvement, corporate social responsibility (CSR and agro export promotion.
Portfolio selection problem: a comparison of fuzzy goal programming and linear physical programming
Fusun Kucukbay
2016-04-01
Full Text Available Investors have limited budget and they try to maximize their return with minimum risk. Therefore this study aims to deal with the portfolio selection problem. In the study two criteria are considered which are expected return, and risk. In this respect, linear physical programming (LPP technique is applied on Bist 100 stocks to be able to find out the optimum portfolio. The analysis covers the period April 2009- March 2015. This period is divided into two; April 2009-March 2014 and April 2014 – March 2015. April 2009-March 2014 period is used as data to find an optimal solution. April 2014-March 2015 period is used to test the real performance of portfolios. The performance of the obtained portfolio is compared with that obtained from fuzzy goal programming (FGP. Then the performances of both method, LPP and FGP are compared with BIST 100 in terms of their Sharpe Indexes. The findings reveal that LPP for portfolio selection problem is a good alternative to FGP.
Optimal portfolio selection between different kinds of Renewable energy sources
Zakerinia, MohammadSaleh; Piltan, Mehdi; Ghaderi, Farid
2010-09-15
In this paper, selection of the optimal energy supply system in an industrial unit is taken into consideration. This study takes environmental, economical and social parameters into consideration in modeling along with technical factors. Several alternatives which include renewable energy sources, micro-CHP systems and conventional system has been compared by means of an integrated model of linear programming and three multi-criteria approaches (AHP, TOPSIS and ELECTRE III). New parameters like availability of sources, fuels' price volatility, besides traditional factors are considered in different scenarios. Results show with environmental preferences, renewable sources and micro-CHP are good alternatives for conventional systems.
Ant Colony Optimization for Markowitz Mean-Variance Portfolio Model
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.
Pindoriya, N.M.; Singh, S.N. [Department of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur 208016 (India); Singh, S.K. [Indian Institute of Management Lucknow, Lucknow 226013 (India)
2010-10-15
This paper proposes an approach for generation portfolio allocation based on mean-variance-skewness (MVS) model which is an extension of the classical mean-variance (MV) portfolio theory, to deal with assets whose return distribution is non-normal. The MVS model allocates portfolios optimally by considering the maximization of both the expected return and skewness of portfolio return while simultaneously minimizing the risk. Since, it is competing and conflicting non-smooth multi-objective optimization problem, this paper employed a multi-objective particle swarm optimization (MOPSO) based meta-heuristic technique to provide Pareto-optimal solution in a single simulation run. Using a case study of the PJM electricity market, the performance of the MVS portfolio theory based method and the classical MV method is compared. It has been found that the MVS portfolio theory based method can provide significantly better portfolios in the situation where non-normally distributed assets exist for trading. (author)
Pindoriya, N.M.; Singh, S.N.; Singh, S.K.
2010-01-01
This paper proposes an approach for generation portfolio allocation based on mean-variance-skewness (MVS) model which is an extension of the classical mean-variance (MV) portfolio theory, to deal with assets whose return distribution is non-normal. The MVS model allocates portfolios optimally by considering the maximization of both the expected return and skewness of portfolio return while simultaneously minimizing the risk. Since, it is competing and conflicting non-smooth multi-objective optimization problem, this paper employed a multi-objective particle swarm optimization (MOPSO) based meta-heuristic technique to provide Pareto-optimal solution in a single simulation run. Using a case study of the PJM electricity market, the performance of the MVS portfolio theory based method and the classical MV method is compared. It has been found that the MVS portfolio theory based method can provide significantly better portfolios in the situation where non-normally distributed assets exist for trading. (author)
Product Portfolio Management Best Practices For New Product Development: A Review Of Models
Doorasamy Mishelle
2017-02-01
Full Text Available The survival of any industrial organization depends on whether producing goods or services hinge on how innovative they have become in managing their product portfolio to craft new products that changes with the ever-changing tastes and needs of their customers. This study delves in to the models and theories that drive product portfolio management practices in a way that they support the successes of new product development. Our review is based on selected studies at the frontier of product management, summarized, and compared based on authors experiences, subsisting models, and theories with the results purely based on qualitative rather than quantitative approaches. The essence is to explore possible new theory or model in this field of research.
Robust portfolio selection based on asymmetric measures of variability of stock returns
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.
Afrika Statistika ISSN 2316-090X The price of portfolio selection ...
The price of portfolio selection under tail conditional expectation with ... TCE provides a more conservative measure of risk than VaR for the same level ...... Substituting the new value function and its derivatives with respect to h into the .... the optimal condition is that the discount rate is proxy of the systematic volatility factor.
Mean-Variance Portfolio Selection with a Fixed Flow of Investment in ...
We consider a mean-variance portfolio selection problem for a fixed flow of investment in a continuous time framework. We consider a market structure that is characterized by a cash account, an indexed bond and a stock. We obtain the expected optimal terminal wealth for the investor. We also obtain a closed-form ...
Chen-Tung Chen
2009-01-01
Full Text Available The purpose of stock portfolio selection is how to allocate the capital to a large number of stocks in order to bring a most profitable return for investors. In most of past literatures, experts considered the portfolio of selection problem only based on past crisp or quantitative data. However, many qualitative and quantitative factors will influence the stock portfolio selection in real investment situation. It is very important for experts or decision-makers to use their experience or knowledge to predict the performance of each stock and make a stock portfolio. Because of the knowledge, experience, and background of each expert are different and vague, different types of 2-tuple linguistic variable are suitable used to express experts' opinions for the performance evaluation of each stock with respect to criteria. According to the linguistic evaluations of experts, the linguistic TOPSIS and linguistic ELECTRE methods are combined to present a new decision-making method for dealing with stock selection problems in this paper. Once the investment set has been determined, the risk preferences of investor are considered to calculate the investment ratio of each stock in the investment set. Finally, an example is implemented to demonstrate the practicability of the proposed method.
van Weert, K.; Dhaene, J.; Goovaerts, M.
2011-01-01
In this paper we discuss multiperiod portfolio selection problems related to a specific provisioning problem. Our results are an extension of Dhaene et al. (2005) [14], where optimal constant mix investment strategies are obtained in a provisioning and savings context, using an analytical approach
Differentiability properties of the efficient (u,q2)-set in the Markowitz portfolio selection method
Kriens, J.; Strijbosch, L.W.G.; Vörös, J.
1994-01-01
The set of efficient (Rho2)-combinations in the (Rho2)-plane of the Markowitz portfolio selection method consists of a series of strictly convex parabola. In the transition points from one parabola to the next one, the curve may be indifferentiable. The article gives necessary and sufficient
On the non-stationarity of financial time series: impact on optimal portfolio selection
Livan, Giacomo; Inoue, Jun-ichi; Scalas, Enrico
2012-01-01
We investigate the possible drawbacks of employing the standard Pearson estimator to measure correlation coefficients between financial stocks in the presence of non-stationary behavior, and we provide empirical evidence against the well-established common knowledge that using longer price time series provides better, more accurate, correlation estimates. Then, we investigate the possible consequences of instabilities in empirical correlation coefficient measurements on optimal portfolio selection. We rely on previously published works which provide a framework allowing us to take into account possible risk underestimations due to the non-optimality of the portfolio weights being used in order to distinguish such non-optimality effects from risk underestimations genuinely due to non-stationarities. We interpret such results in terms of instabilities in some spectral properties of portfolio correlation matrices. (paper)
A Closed-Form Solution for Robust Portfolio Selection with Worst-Case CVaR Risk Measure
Le Tang
2014-01-01
Full Text Available With the uncertainty probability distribution, we establish the worst-case CVaR (WCCVaR risk measure and discuss a robust portfolio selection problem with WCCVaR constraint. The explicit solution, instead of numerical solution, is found and two-fund separation is proved. The comparison of efficient frontier with mean-variance model is discussed and finally we give numerical comparison with VaR model and equally weighted strategy. The numerical findings indicate that the proposed WCCVaR model has relatively smaller risk and greater return and relatively higher accumulative wealth than VaR model and equally weighted strategy.
Cross sectional moments and portfolio returns: Evidence for select emerging markets
Sanjay Sehgal
2016-09-01
Full Text Available Research does not indicate a consensus on the relationship between idiosyncratic volatility and asset returns. Moreover, the role of cross sectional higher order moments in predicting market returns is relatively unexplored. We show that the cross sectional volatility measure suggested by Garcia et al. is highly correlated with alternative measures of idiosyncratic volatility constructed as variance of errors from the capital asset pricing model and the Fama French model. We find that cross sectional moments help in predicting aggregate market returns in some sample countries and also provide information for portfolio formation, which is more consistent for portfolios sorted on sensitivity to cross sectional skewness.
Introducing Model Predictive Control for Improving Power Plant Portfolio Performance
Edlund, Kristian Skjoldborg; Bendtsen, Jan Dimon; Børresen, Simon
2008-01-01
This paper introduces a model predictive control (MPC) approach for construction of a controller for balancing the power generation against consumption in a power system. The objective of the controller is to coordinate a portfolio consisting of multiple power plant units in the effort to perform...... reference tracking and disturbance rejection in an economically optimal way. The performance function is chosen as a mixture of the `1-norm and a linear weighting to model the economics of the system. Simulations show a significant improvement of the performance of the MPC compared to the current...
Analysis of the portfolio of sites to characterize for selecting a nuclear repository
Keeney, R.L.
1987-01-01
The US Department of Energy has selected three sites, from five nominated, to characterize for a nuclear repository to permanently dispose of nuclear waste. This decision was made without the benefit of an analysis of this portfolio problem. This paper analyzes different portfolios of three sites for simultaneous characterization and strategies for sequential characterization. Characterization of each site, which involves significant subsurface excavation, is now estimated to cost $1 billion. Mainly because of the high characterization costs, sequential characterization strategies are identified which are the equivalent of $1.7-2.0 billion less expensive than the selected DOE simultaneous characterization of the three sites. If three sites are simultaneously characterized, one portfolio is estimated to be the equivalent of $100-400 million better than the selected DOE portfolio. Because of these potential savings and several other complicating factors that may influence the relative desirability of characterization strategies, a thorough analysis of characterization strategies that addresses the likelihood of finding disqualifying conditions during site characterization, uncertainties, and dependencies in forecast site repository costs, preclosure and postclosure health and safety impacts, potential delays of both sequential and simultaneous characterization strategies, and the environmental, socioeconomic, and health and safety impacts of characterization activities is recommended
Project portfolio selection of banking services using COPRAS and Fuzzy-TOPSIS
C.O. Anyaeche
2017-04-01
Full Text Available Portfolio selection is a business process which has helped organisations identify an area of com-petitive advantage and it is a major concern to industrial players in the banking sectors. In order to enhance bank portfolio selection, cost, profitability, time and location are important parameters that decision-makers often consider. This study implements a fuzzy-TOPSIS (Technique for Or-der Preference by Similarity to Ideal Solution framework to evaluate three potential portfolios (automated teller machine gallery, quick service point and branch for a bank using the infor-mation from three decision-makers. An illustrative example of real bank information is used to demonstrate the proposed framework applicability. The complex proportional assessment of al-ternatives (COPRAS method is also used as an evaluation technique and the results are com-pared, which yields that the results from the ranking order of fuzzy-TOPSIS and COPRAS were different. However, there is a consistency between the aggregation of intuition-based, fuzzy-TOPSIS and COPRAS ranks and fuzzy-TOPSIS ranking results. The presented framework is an easy-to-apply tool that improves portfolio selection decision in the banking system.
The Critical Infrastructure Portfolio Selection Model
2008-06-13
metering/ billing 7 Rehabilitation of WTP 20 Maintain potable water production capacity and improve quality (esp. turbidity and color) 8 Construction of...junction/ segment of rail (rehab) 5 Shrine (rehab) 6 Rehabilitation of water distribution network 7 Rehabilitation of WTP 8 Construction of...
On Partial Defaults in Portfolio Credit Risk : A Poisson Mixture Model Approach
Weißbach, Rafael; von Lieres und Wilkau, Carsten
2005-01-01
Most credit portfolio models exclusively calculate the loss distribution for a portfolio of performing counterparts. Conservative default definitions cause considerable insecurity about the loss for a long time after the default. We present three approaches to account for defaulted counterparts in the calculation of the economic capital. Two of the approaches are based on the Poisson mixture model CreditRisk+ and derive a loss distribution for an integrated portfolio. The third method treats ...
Replica Analysis for Portfolio Optimization with Single-Factor Model
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.
The Dirichlet Portfolio Model: Uncovering the Hidden Composition of Hedge Fund Investments
Korsos, Laszlo F.
2013-01-01
Hedge funds have long been viewed as a veritable "black box" of investing since outsiders may never view the exact composition of portfolio holdings. Therefore, the ability to estimate an informative set of asset weights is highly desirable for analysis. We present a compositional state space model for estimation of an investment portfolio's unobserved asset allocation weightings on a set of candidate assets when the only observed information is the time series of portfolio returns and the ca...
On the Computation of the Efficient Frontier of the Portfolio Selection Problem
Clara Calvo
2012-01-01
Full Text Available An easy-to-use procedure is presented for improving the ε-constraint method for computing the efficient frontier of the portfolio selection problem endowed with additional cardinality and semicontinuous variable constraints. The proposed method provides not only a numerical plotting of the frontier but also an analytical description of it, including the explicit equations of the arcs of parabola it comprises and the change points between them. This information is useful for performing a sensitivity analysis as well as for providing additional criteria to the investor in order to select an efficient portfolio. Computational results are provided to test the efficiency of the algorithm and to illustrate its applications. The procedure has been implemented in Mathematica.
Representation Bias, Return Forecast, and Portfolio Selection in the Stock Market of China
Daping Zhao
2014-01-01
Full Text Available Representation bias means a kind of cognitive tendency, and, for investors, it can affect their behavior in the stock market. Whether the representation bias can help the return forecast and portfolio selection is an interesting problem that is less studied. In this paper, based on the representation bias theory and current markets situation in China, a new hierarchy of stock measurement system is constructed and a corresponding set of criteria is also proposed. On each criterion, we try to measure the influence among stocks with adapted fuzzy AHP. Then the Hausdorff distance is applied to weight and compute the horizontal representation returns. For the forecast returns, according to representation behaviors, there is also a new computation method. Empirical results show that the representation bias information is useful to the return forecast as well as the portfolio selection.
A new enhanced index tracking model in portfolio optimization with sum weighted approach
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.
Selecting the Best of Portfolio Using OWA Operator Weights in Cross Efficiency-Evaluation
Sanei, Masoud; Banihashemi, Shokoofeh
2014-01-01
The present study is an attempt toward evaluating the performance of portfolios and asset selection using cross-efficiency evaluation. Cross-efficiency evaluation is an effective way of ranking decision making units (DMUs) in data envelopment analysis (DEA). The most widely used approach is to evaluate the efficiencies in each row or column in the cross-efficiency matrix with equal weights into an average cross-efficiency score for each DMU and consider it as the overall performance measureme...
Multiperiod Telser’s Safety-First Portfolio Selection with Regime Switching
Chuangwei Lin
2018-01-01
Full Text Available This paper investigates a multiperiod Telser’s safety-first portfolio selection model with regime switching where the returns of the assets are assumed to depend on the market states modulated by a discrete-time Markov chain. The investor aims to maximize the expected terminal wealth and does not want the probability of the terminal wealth to fall short of a disaster level to exceed a predetermined number called the risk control level. Referring to Tchebycheff inequality, we modify Telser’s safety-first model to the case that aims to maximize the expected terminal wealth subject to a constraint where the upper bound of the disaster probability is less than the risk control level. By the Lagrange multiplier technique and the embedding method, we study in detail the existence of the optimal strategy and derive the closed-form optimal strategy. Finally, by mathematical and numerical analysis, we analyze the effects of the disaster level, the risk control level, the transition matrix of the Markov chain, the expected excess return, and the variance of the risky return.
Clarke, Ann Højbjerg; Freytag, Per Vagn; Zolkiewski, Judith
2017-01-01
gives managers a tool to help to cope with the dynamic aspects of the customer portfolio. Recognition of the importance of communication to the process, the development of trust and the role of legitimacy also provides areas that managers can focus upon in their relationship management processes......Purpose The purpose of this paper is to extend the discussion about customer portfolios beyond simple identification of models and how they can be used for balanced resource allocation to a discussion about how portfolios should take into account views from relationship partners and how they should...... that helps improve the understanding of how customer portfolio models can actually be applied from a relational perspective. Findings The key aspects of the conceptual framework relate to how alignment of the relationships in the portfolio is achieved. Critical to this are the interaction spaces...
Purpose and Pedagogy: A Conceptual Model for an ePortfolio
Buyarski, Catherine A.; Aaron, Robert W.; Hansen, Michele J.; Hollingsworth, Cynthia D.; Johnson, Charles A.; Kahn, Susan; Landis, Cynthia M.; Pedersen, Joan S.; Powell, Amy A.
2015-01-01
This conceptual model emerged from the need to balance multiple purposes and perspectives associated with developing an ePortfolio designed to promote student development and success. A comprehensive review of literature from various disciplines, theoretical frameworks, and scholarship, including self-authorship, reflection, ePortfolio pedagogy,…
The Effects of ePortfolio-Based Learning Model on Student Self-Regulated Learning
Nguyen, Lap Trung; Ikeda, Mitsuru
2015-01-01
Self-regulated learners are aware of their knowledge and skills and proactive in learning. They view learning as a controllable process and accept more responsibility for the results of this process. The research described in this article proposes, implements, and evaluates an ePortfolio-based self-regulated learning model. An ePortfolio system…
Time-Consistent Strategies for a Multiperiod Mean-Variance Portfolio Selection Problem
Huiling Wu
2013-01-01
Full Text Available It remained prevalent in the past years to obtain the precommitment strategies for Markowitz's mean-variance portfolio optimization problems, but not much is known about their time-consistent strategies. This paper takes a step to investigate the time-consistent Nash equilibrium strategies for a multiperiod mean-variance portfolio selection problem. Under the assumption that the risk aversion is, respectively, a constant and a function of current wealth level, we obtain the explicit expressions for the time-consistent Nash equilibrium strategy and the equilibrium value function. Many interesting properties of the time-consistent results are identified through numerical sensitivity analysis and by comparing them with the classical pre-commitment solutions.
A risk-return based model to measure the performance of portfolio management
Hamid Reza Vakili Fard
2014-10-01
Full Text Available The primary concern in all portfolio management systems is to find a good tradeoff between risk and expected return and a good balance between accepted risk and actual return indicates the performance of a particular portfolio. This paper develops “A-Y Model” to measure the performance of a portfolio and analyze it during the bull and the bear market. This paper considers the daily information of one year before and one year after Iran's 2013 precedential election. The proposed model of this paper provides lost profit and unrealized loss to measure the portfolio performance. The proposed study first ranks the resulted data and then uses some non-parametric methods to see whether there is any change because of the changes in markets on the performance of the portfolio. The results indicate that despite increasing profitable opportunities in bull market, the performance of the portfolio did not match the target risk. As a result, using A-Y Model as a risk and return base model to measure portfolio management's performance appears to reduce risks and increases return of portfolio.
Maier, Sebastian; Street, Alexandre; McKinnon, Ken
2016-01-01
Investment decisions in renewable energy sources such as small hydro, wind power, biomass and solar are frequently made in the context of enormous uncertainty surrounding both intermittent generation and the highly volatile electricity spot prices that are used for clearing of trades. This paper presents a new portfolio-based approach for selecting long-term investments in small-scale renewable energy projects and matching contracts for the sale of the resulting electricity. Using this approach, we have formulated a stochastic optimisation model that maximises a holding company's risk-averse measure of value. Using an illustrative example representative of investment decisions within the Brazilian electricity system, we investigate the sensitivity of the optimised portfolio composition and commercialisation strategy to contract prices in the free contracting environment and to the decision maker's attitude towards risk. The numerical results demonstrate it is possible to reduce significantly financial risks, such as the price-quantity risk, not only by exploiting the complementarity of the considered renewable sources generation profiles, but also by selecting the optimal mix of commercialisation contracts from different markets. We find that the multi-market strategy generally results in appreciably higher optimal value than single-market strategies and can be applied to a wide range of renewable generators and contracts. - Highlights: • Gives a portfolio-based multi-market, multi-asset approach to renewable investment. • Details how to model currently used contract types in each of the Brazilian markets. • Presents a test case using realistic contract and real renewable data from Brazil. • Shows that the approach controls financial risks and boosts optimal values. • Explains how relative contract prices and attitude to risk affect optimal decisions.
On Two Mixture-Based Clustering Approaches Used in Modeling an Insurance Portfolio
Tatjana Miljkovic
2018-05-01
Full Text Available We review two complementary mixture-based clustering approaches for modeling unobserved heterogeneity in an insurance portfolio: the generalized linear mixed cluster-weighted model (CWM and mixture-based clustering for an ordered stereotype model (OSM. The latter is for modeling of ordinal variables, and the former is for modeling losses as a function of mixed-type of covariates. The article extends the idea of mixture modeling to a multivariate classification for the purpose of testing unobserved heterogeneity in an insurance portfolio. The application of both methods is illustrated on a well-known French automobile portfolio, in which the model fitting is performed using the expectation-maximization (EM algorithm. Our findings show that these mixture-based clustering methods can be used to further test unobserved heterogeneity in an insurance portfolio and as such may be considered in insurance pricing, underwriting, and risk management.
Rethinking the Educator Portfolio: An Innovative Criteria-Based Model.
Shinkai, Kanade; Chen, Chen Amy; Schwartz, Brian S; Loeser, Helen; Ashe, Cynthia; Irby, David M
2017-11-07
Academic medical centers struggle to achieve parity in advancement and promotions between educators and discovery-oriented researchers in part because of narrow definitions of scholarship, lack of clear criteria for measuring excellence, and barriers to making educational contributions available for peer review. Despite recent progress in expanding scholarship definitions and identifying excellence criteria, these advances are not integrated into educator portfolio (EP) templates or curriculum vitae platforms. From 2013 to 2015, a working group from the Academy of Medical Educators (AME) at the University of California, San Francisco (UCSF) designed a streamlined, criteria-based EP (EP 2.0) template highlighting faculty members' recent activities in education and setting rigorous evaluation methods to enable educational scholarship to be objectively evaluated for academic advancement, AME membership, and professional development. The EP 2.0 template was integrated into the AME application, resulting in high overall satisfaction among candidates and the selection committee and positive feedback on the template's transparency, ease of use, and streamlined format. In 2016, the EP 2.0 template was integrated into the campus-wide curriculum vitae platform and academic advancement system. The authors plan to increase awareness of the EP 2.0 template by educating promotions committees and faculty at UCSF and partnering with other institutions to disseminate it for use. They also plan to study the impact of the template on supporting educators by making their important scholarly contributions available for peer review, providing guidance for professional development, and decreasing disparities in promotions.
Mean-variance portfolio selection and efficient frontier for defined contribution pension schemes
Hoejgaard, B.; Vigna, E.
2007-01-01
We solve a mean-variance portfolio selection problem in the accumulation phase of a defined contribution pension scheme. The efficient frontier, which is found for the 2 asset case as well as the n + 1 asset case, gives the member the possibility to decide his own risk/reward profile. The mean-variance approach is then compared to other investment strategies adopted in DC pension schemes, namely the target-based approach and the lifestyle strategy. The comparison is done both in a theoretical...
Mohammad Ali Barati
2016-04-01
Full Text Available Multi-period models of portfolio selection have been developed in the literature with respect to certain assumptions. In this study, for the first time, the portfolio selection problem has been modeled based on mean-semi variance with transaction cost and minimum transaction lots considering functional constraints and fuzzy parameters. Functional constraints such as transaction cost and minimum transaction lots were included. In addition, the returns on assets parameters were considered as trapezoidal fuzzy numbers. An efficient genetic algorithm (GA was designed, results were analyzed using numerical instances and sensitivity analysis were executed. In the numerical study, the problem was solved based on the presence or absence of each mode of constraints including transaction costs and minimum transaction lots. In addition, with the use of sensitivity analysis, the results of the model were presented with the variations of minimum expected rate of programming periods.
2015-05-01
Modern Portfolio Theory (MPT) • Joint EEA and MPT Method... Modern Portfolio Theory (MPT) for Engineering Portfolios Consistencies • Value elicitation from stakeholders • Modeling of asset value • Founded...correlation • Asset availability is dynamic • Costs may accompany diversification Select elements of Modern Portfolio Theory can improve the design
Pinon, Olivia J.
-step process developed in this research leverages the benefits yielded by impact assessment techniques, system dynamics modeling, and real options analysis to 1) provide the decision maker with a rigorous, structured, and traceable process for technology selection, 2) assess the combined impact of interrelated technologies, 3) support the translation of technology impact factors into airport performance indicators, and help identify the factors that drive the need for capacity expansion, and finally 4) enable the quantitative assessment of the strategic value of embedding flexibility in the formulation of technology portfolios and investment options. In particular, the development of this methodology highlights the successful implementation of relevance tree analysis, morphological analysis, filters and dependency tables to support the aforementioned process for technology selection. Further, it illustrates the limited capability of Cross Impact Analysis to identify technology relationships for the problem at hand. Finally, this methodology demonstrates, through a change in demand at the airport modeled, the importance of being able to weigh both the technological and strategic performance of the technology portfolios considered. In particular, it illustrates the impact that the level of traffic, the presence of congestion, the timing and sequence of investments, and the number of technologies included, have on the strategic value of a portfolio. Hence, by capturing the time dimension and technology causality impacts in technology portfolio selection, this work helps identify key technologies or technology groupings, and assess their performance on airport metrics. By embedding flexibility in the formulation of investment scenarios, it provides the decision maker with a more accurate picture of the options available to him, as well as the time and sequence under which these should be exercised.
Portfolio size as funktion of the premium: modeling and optimization
Asmussen, Søren; Christensen, Bent Jesper; Taksar, Michael I
An insurance company has a large number N of potential customers characterized by i.i.d. r.v.'s A1,…,AN giving the arrival rates of claims. Customers are risk averse, and a customer accepts an offered premium p according to his A-value. The modeling further involves a discount rate d>r of customers......, where r is the risk-free interest rate. Based on calculations of the customers' present values of the alternative strategies of insuring and not insuring, the portfolio size n(p) is derived, and also the rate of claims from the insured customers is given. Further, the value of p which is optimal...... for minimizing the ruin probability is derived in a diffusion approximation to the Cramér-Lundberg risk process with an added liability rate L of the company. The solution involves the Lambert W function. Similar discussion is given for extensions involving customers having only partial information...
Establishing psychiatric registrars' competence in psychotherapy: a portfolio based model.
Naidu, T; Ramlall, S
2008-11-01
During most of the latter part of the last century, South Africa has followed international trends in the training of psychiatrists. Training programmes have become increasingly focused on the neurobiological aspects of psychiatric disorders with less attention being paid to psychotherapy. This is consistent with developments in psychiatric research. In the clinical arena this manifests as a focus on pharmacological and medically based interventions and a resulting relative inattention to non-pharmacological interventions, most especially psychotherapy. In an effort to address this imbalance there has been an international initiative, over the past two decades, to establish an acceptable level of competence in psychotherapy in the training of psychiatrists. A South African programme is needed that can take account of international trends and adapt them for the local context. In order to produce a programme for establishing competence in psychotherapy for psychiatric registrars at the Nelson R. Mandela School of Medicine, the authors examine directives for the development of psychotherapy skills from international regulatory bodies for graduate medical training and their application. Defining and setting preliminary standards for competence is emphasized. A programme based on five core psychotherapy components using a portfolio based model to facilitate learning and assessment of competence in psychotherapy, is proposed.
Risk of portfolio with simulated returns based on copula model
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.
ECLIPPx: an innovative model for reflective portfolios in life-long learning.
Cheung, C Ronny
2011-03-01
For healthcare professionals, the educational portfolio is the most widely used component of lifelong learning - a vital aspect of modern medical practice. When used effectively, portfolios provide evidence of continuous learning and promote reflective practice. But traditional portfolio models are in danger of becoming outmoded, in the face of changing expectations of healthcare provider competences today. Portfolios in health care have generally focused on competencies in clinical skills. However, many other domains of professional development, such as professionalism and leadership skills, are increasingly important for doctors and health care professionals, and must be addressed in amassing evidence for training and revalidation. There is a need for modern health care learning portfolios to reflect this sea change. A new model for categorising the health care portfolios of professionals is proposed. The ECLIPPx model is based on personal practice, and divides the evidence of ongoing professional learning into four categories: educational development; clinical practice; leadership, innovation and professionalism; and personal experience. The ECLIPPx model offers a new approach for personal reflection and longitudinal learning, one that gives flexibility to the user whilst simultaneously encompassing the many relatively new areas of competence and expertise that are now required of a modern doctor. © Blackwell Publishing Ltd 2011.
Estimating Risk of Natural Gas Portfolios by Using GARCH-EVT-Copula Model.
Tang, Jiechen; Zhou, Chao; Yuan, Xinyu; Sriboonchitta, Songsak
2015-01-01
This paper concentrates on estimating the risk of Title Transfer Facility (TTF) Hub natural gas portfolios by using the GARCH-EVT-copula model. We first use the univariate ARMA-GARCH model to model each natural gas return series. Second, the extreme value distribution (EVT) is fitted to the tails of the residuals to model marginal residual distributions. Third, multivariate Gaussian copula and Student t-copula are employed to describe the natural gas portfolio risk dependence structure. Finally, we simulate N portfolios and estimate value at risk (VaR) and conditional value at risk (CVaR). Our empirical results show that, for an equally weighted portfolio of five natural gases, the VaR and CVaR values obtained from the Student t-copula are larger than those obtained from the Gaussian copula. Moreover, when minimizing the portfolio risk, the optimal natural gas portfolio weights are found to be similar across the multivariate Gaussian copula and Student t-copula and different confidence levels.
Estimating Risk of Natural Gas Portfolios by Using GARCH-EVT-Copula Model
Jiechen Tang
2015-01-01
Full Text Available 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.
Essays on Rational Portfolio Theory
Nielsen, Simon Ellersgaard
market prices, we findonly a very modest improvement in portfolio wealth over the corresponding strategy whichonly trades in bonds and stocks. Optimal Hedge Tracking Portfolios in a Limit Order Book. In this paper we developa control theoretic solution to the manner in which a portfolio manager optimally...... shouldtrack a targeted D, given that he wishes to hedge a short position in European call optionsthe underlying of which is traded in a limit order book. Specifically, we are interested in theinterplay between posting limit and market orders respectively: when should the portfoliomanager do what (and at what......’s theory of optimal portfolio selection for wealth maximisingagents. In this paper we present a systematic analysis of the optimal asset allocation in aderivative-free market for the Heston model, the 3/2 model, and a Fong Vasicek type model.Under the assumption that the market price of risk...
Model of formation of low-risk stock portfolio in modern financial markets
Дмитро Сергійович Богач
2016-03-01
Full Text Available The basic principles of formation of an investment portfolio in modern financial markets are determined. A method of forming stock portfolio due to the statistical properties of stationary process and relations between the behavior of stocks and economic sector, characterizing these actions, is proposed. Optimal points of recalculation of model depends on changes in current trends in the financial market is described
Portfolio Optimization: A Combined Regime-Switching and Black–Litterman Model
Edwin O. Fischer; Immanuel Seidl
2013-01-01
Traditionally portfolios are optimized with the single-regime Markowitz model using the volatility as the risk measure and the historical return as the expected return. This study shows the effects that a regime-switching framework and alternative risk measures (modified value at risk and conditional value at risk) and return measures (CAPM estimates and Black–Litterman estimates) have on the asset allocation and on the absolute and relative performance of portfolios. It demonstrates that the...
Foroogh Ghasemi
2018-05-01
Full Text Available An organization’s strategic objectives are accomplished through portfolios. However, the materialization of portfolio risks may affect a portfolio’s sustainable success and the achievement of those objectives. Moreover, project interdependencies and cause–effect relationships between risks create complexity for portfolio risk analysis. This paper presents a model using Bayesian network (BN methodology for modeling and analyzing portfolio risks. To develop this model, first, portfolio-level risks and risks caused by project interdependencies are identified. Then, based on their cause–effect relationships all portfolio risks are organized in a BN. Conditional probability distributions for this network are specified and the Bayesian networks method is used to estimate the probability of portfolio risk. This model was applied to a portfolio of a construction company located in Iran and proved effective in analyzing portfolio risk probability. Furthermore, the model provided valuable information for selecting a portfolio’s projects and making strategic decisions.
Shatilova Olena V.
2014-01-01
Full Text Available The article considers urgent problems of enterprise management under conditions of external environment instability, studies problems of the enterprise strategic flexibility management. It shows that one of the efficient mechanisms of ensuring strategic flexibility is restructuring of the enterprise business portfolio in accordance with the change of the situation in the target market of enterprise functioning. The goal of the article is development of a model of formation of enterprise business portfolio in the context of ensuring strategic flexibility. The main method of optimisation of the enterprise business portfolio in the context of ensuring strategic flexibility is the use of modification of the Markowitz model of investment portfolio formation. The offered model of the enterprise business portfolio formation allows taking into account changes of external and internal environments and conducting portfolio restructuring in the event of the change of the enterprise target market situation. Prospects of further studies in this direction are detailed elaboration and formalisation of the organisational and economic mechanism of realisation of strategic flexibility at an enterprise.
Mean-variance portfolio selection and efficient frontier for defined contribution pension schemes
Højgaard, Bjarne; Vigna, Elena
We solve a mean-variance portfolio selection problem in the accumulation phase of a defined contribution pension scheme. The efficient frontier, which is found for the 2 asset case as well as the n + 1 asset case, gives the member the possibility to decide his own risk/reward profile. The mean...... as a mean-variance optimization problem. It is shown that the corresponding mean and variance of the final fund belong to the efficient frontier and also the opposite, that each point on the efficient frontier corresponds to a target-based optimization problem. Furthermore, numerical results indicate...... that the largely adopted lifestyle strategy seems to be very far from being efficient in the mean-variance setting....
Analysis of the rebalancing frequency in log-optimal portfolio selection
Kuhn, Daniel; Luenberger, David G.
2010-01-01
In a dynamic investment situation, the right timing of portfolio revisions and adjustments is essential to sustain long-term growth. A high rebalancing frequency reduces the portfolio performance in the presence of transaction costs, whereas a low rebalancing frequency entails a static investment strategy that hardly reacts to changing market conditions. This article studies a family of portfolio problems in a Black-Scholes type economy which depend parametrically on the rebalancing frequency...
Allan, Grant; Eromenko, Igor; McGregor, Peter [Fraser of Allander Institute, Department of Economics, University of Strathclyde, Sir William Duncan Building, 130 Rottenrow, Glasgow G4 0GE (United Kingdom); Swales, Kim [Department of Economics, University of Strathclyde, Sir William Duncan Building, 130 Rottenrow, Glasgow G4 0GE (United Kingdom)
2011-01-15
Standalone levelised cost assessments of electricity supply options miss an important contribution that renewable and non-fossil fuel technologies can make to the electricity portfolio: that of reducing the variability of electricity costs, and their potentially damaging impact upon economic activity. Portfolio theory applications to the electricity generation mix have shown that renewable technologies, their costs being largely uncorrelated with non-renewable technologies, can offer such benefits. We look at the existing Scottish generation mix and examine drivers of changes out to 2020. We assess recent scenarios for the Scottish generation mix in 2020 against mean-variance efficient portfolios of electricity-generating technologies. Each of the scenarios studied implies a portfolio cost of electricity that is between 22% and 38% higher than the portfolio cost of electricity in 2007. These scenarios prove to be mean-variance 'inefficient' in the sense that, for example, lower variance portfolios can be obtained without increasing portfolio costs, typically by expanding the share of renewables. As part of extensive sensitivity analysis, we find that Wave and Tidal technologies can contribute to lower risk electricity portfolios, while not increasing portfolio cost. (author)
Pimentel, Livia F.; Santiago, Leonardo
2015-01-01
We introduce a dynamic formulation for the problem of portfolio selection of pension funds in the absence of a risk-free asset. In emerging markets, a risk-free asset might be unavailable, and the approaches commonly used may no longer be suitable. We use a parametric approach to combine dynamic...
Bozhalkina, Yana; Timofeeva, Galina
2016-12-01
Mathematical model of loan portfolio in the form of a controlled Markov chain with discrete time is considered. It is assumed that coefficients of migration matrix depend on corrective actions and external factors. Corrective actions include process of receiving applications, interaction with existing solvent and insolvent clients. External factors are macroeconomic indicators, such as inflation and unemployment rates, exchange rates, consumer price indices, etc. Changes in corrective actions adjust the intensity of transitions in the migration matrix. The mathematical model for forecasting the credit portfolio structure taking into account a cumulative impact of internal and external changes is obtained.
Smooth Solutions to Optimal Investment Models with Stochastic Volatilities and Portfolio Constraints
Pham, H.
2002-01-01
This paper deals with an extension of Merton's optimal investment problem to a multidimensional model with stochastic volatility and portfolio constraints. The classical dynamic programming approach leads to a characterization of the value function as a viscosity solution of the highly nonlinear associated Bellman equation. A logarithmic transformation expresses the value function in terms of the solution to a semilinear parabolic equation with quadratic growth on the derivative term. Using a stochastic control representation and some approximations, we prove the existence of a smooth solution to this semilinear equation. An optimal portfolio is shown to exist, and is expressed in terms of the classical solution to this semilinear equation. This reduction is useful for studying numerical schemes for both the value function and the optimal portfolio. We illustrate our results with several examples of stochastic volatility models popular in the financial literature
Different Variants of Fundamental Portfolio
Tarczyński Waldemar
2014-06-01
Full Text Available The paper proposes the fundamental portfolio of securities. This portfolio is an alternative for the classic Markowitz model, which combines fundamental analysis with portfolio analysis. The method’s main idea is based on the use of the TMAI1 synthetic measure and, in limiting conditions, the use of risk and the portfolio’s rate of return in the objective function. Different variants of fundamental portfolio have been considered under an empirical study. The effectiveness of the proposed solutions has been related to the classic portfolio constructed with the help of the Markowitz model and the WIG20 market index’s rate of return. All portfolios were constructed with data on rates of return for 2005. Their effectiveness in 2006- 2013 was then evaluated. The studied period comprises the end of the bull market, the 2007-2009 crisis, the 2010 bull market and the 2011 crisis. This allows for the evaluation of the solutions’ flexibility in various extreme situations. For the construction of the fundamental portfolio’s objective function and the TMAI, the study made use of financial and economic data on selected indicators retrieved from Notoria Serwis for 2005.
Local Politics and Portfolio Management Models: National Reform Ideas and Local Control
Bulkley, Katrina E.; Henig, Jeffrey R.
2015-01-01
Amid the growth of charter schools, autonomous schools, and private management organizations, an increasing number of urban districts are moving toward a portfolio management model (PMM). In a PMM, the district central office oversees schools that operate under a variety of governance models. The expansion of PMMs raises questions about local…
Evaluating Portfolio Value-At-Risk Using Semi-Parametric GARCH Models
J.V.K. Rombouts; M.J.C.M. Verbeek (Marno)
2009-01-01
textabstractIn this paper we examine the usefulness of multivariate semi-parametric GARCH models for evaluating the Value-at-Risk (VaR) of a portfolio with arbitrary weights. We specify and estimate several alternative multivariate GARCH models for daily returns on the S&P 500 and Nasdaq indexes.
Renaldas Vilkancas
2016-05-01
Full Text Available Purpose of the article: While using asymmetric risk-return measures an important role is played by selection of the investor‘s required or threshold rate of return. The scientific literature usually states that every investor should define this rate according to their degree of risk aversion. In this paper, it is attempted to look at the problem from a different perspective – empirical research is aimed at determining the influence of the threshold rate of return on the portfolio characteristics. Methodology/methods: In order to determine the threshold rate of return a stochastic dominance criterion was used. The results are verified using the commonly applied method of backtesting. Scientific aim: The aim of this paper is to propose a method allowing selecting the threshold rate of return reliably and objectively. Findings: Empirical research confirms that stochastic dominance criteria can be successfully applied to determine the rate of return preferred by the investor. Conclusions: A risk-free investment rate or simply a zero rate of return commonly used in practice is often justified neither by theoretical nor empirical studies. This work suggests determining the threshold rate of return by applying the stochastic dominance criterion
A Balanced Portfolio Model For Improving Health: Concept And Vermont's Experience.
Hester, James
2018-04-01
A successful strategy for improving population health requires acting in several sectors by implementing a portfolio of interventions. The mix of interventions should be both tailored to meet the community's needs and balanced in several dimensions-for example, time frame, level of risk, and target population. One obstacle is finding sustainable financing for both the interventions and the community infrastructure needed. This article first summarizes Vermont's experience as a laboratory for health reform. It then presents a conceptual model for a community-based population health strategy, using a balanced portfolio and diversified funding approaches. The article then reviews Vermont's population health initiative, including an example of a balanced portfolio and lessons learned from the state's experience.
The difference between LSMC and replicating portfolio in insurance liability modeling.
Pelsser, Antoon; Schweizer, Janina
2016-01-01
Solvency II requires insurers to calculate the 1-year value at risk of their balance sheet. This involves the valuation of the balance sheet in 1 year's time. As for insurance liabilities, closed-form solutions to their value are generally not available, insurers turn to estimation procedures. While pure Monte Carlo simulation set-ups are theoretically sound, they are often infeasible in practice. Therefore, approximation methods are exploited. Among these, least squares Monte Carlo (LSMC) and portfolio replication are prominent and widely applied in practice. In this paper, we show that, while both are variants of regression-based Monte Carlo methods, they differ in one significant aspect. While the replicating portfolio approach only contains an approximation error, which converges to zero in the limit, in LSMC a projection error is additionally present, which cannot be eliminated. It is revealed that the replicating portfolio technique enjoys numerous advantages and is therefore an attractive model choice.
Higher order saddlepoint approximations in the Vasicek portfolio credit loss model
Huang, X.; Oosterlee, C.W.; van der Weide, J.A.M.
2006-01-01
This paper utilizes the saddlepoint approximation as an efficient tool to estimate the portfolio credit loss distribution in the Vasicek model. Value at Risk (VaR), the risk measure chosen in the Basel II Accord for the evaluation of capital requirement, can then be found by inverting the loss
2013-06-11
... Balanced Fund, Compass EMP Multi-Asset Growth Fund, Compass EMP Alternative Strategies Fund, Compass EMP Balanced Volatility Weighted Fund, Compass EMP Growth Volatility Weighted Fund, and Compass EMP... Efficient Model Portfolios, LLC and Compass EMP Funds Trust; Notice of Application June 4, 2013. AGENCY...
Developing evaluation instrument based on CIPP models on the implementation of portfolio assessment
Kurnia, Feni; Rosana, Dadan; Supahar
2017-08-01
This study aimed to develop an evaluation instrument constructed by CIPP model on the implementation of portfolio assessment in science learning. This study used research and development (R & D) method; adapting 4-D by the development of non-test instrument, and the evaluation instrument constructed by CIPP model. CIPP is the abbreviation of Context, Input, Process, and Product. The techniques of data collection were interviews, questionnaires, and observations. Data collection instruments were: 1) the interview guidelines for the analysis of the problems and the needs, 2) questionnaire to see level of accomplishment of portfolio assessment instrument, and 3) observation sheets for teacher and student to dig up responses to the portfolio assessment instrument. The data obtained was quantitative data obtained from several validators. The validators consist of two lecturers as the evaluation experts, two practitioners (science teachers), and three colleagues. This paper shows the results of content validity obtained from the validators and the analysis result of the data obtained by using Aikens' V formula. The results of this study shows that the evaluation instrument based on CIPP models is proper to evaluate the implementation of portfolio assessment instruments. Based on the experts' judgments, practitioners, and colleagues, the Aikens' V coefficient was between 0.86-1,00 which means that it is valid and can be used in the limited trial and operational field trial.
Issagali, Aizhan; Alshimbayeva, Damira; Zhalgas, Aidana
2015-01-01
In this paper Portfolio Optimization techniques were used to determine the most favorable investment portfolio. In particular, stock indices of three companies, namely Microsoft Corporation, Christian Dior Fashion House and Shevron Corporation were evaluated. Using this data the amounts invested in each asset when a portfolio is chosen on the efficient frontier were calculated. In addition, the Portfolio with minimum variance, tangency portfolio and optimal Markowitz portfolio are presented.
A General Framework for Portfolio Theory—Part I: Theory and Various Models
Stanislaus Maier-Paape
2018-05-01
Full Text Available Utility and risk are two often competing measurements on the investment success. We show that efficient trade-off between these two measurements for investment portfolios happens, in general, on a convex curve in the two-dimensional space of utility and risk. This is a rather general pattern. The modern portfolio theory of Markowitz (1959 and the capital market pricing model Sharpe (1964, are special cases of our general framework when the risk measure is taken to be the standard deviation and the utility function is the identity mapping. Using our general framework, we also recover and extend the results in Rockafellar et al. (2006, which were already an extension of the capital market pricing model to allow for the use of more general deviation measures. This generalized capital asset pricing model also applies to e.g., when an approximation of the maximum drawdown is considered as a risk measure. Furthermore, the consideration of a general utility function allows for going beyond the “additive” performance measure to a “multiplicative” one of cumulative returns by using the log utility. As a result, the growth optimal portfolio theory Lintner (1965 and the leverage space portfolio theory Vince (2009 can also be understood and enhanced under our general framework. Thus, this general framework allows a unification of several important existing portfolio theories and goes far beyond. For simplicity of presentation, we phrase all for a finite underlying probability space and a one period market model, but generalizations to more complex structures are straightforward.
Business Model Innovation Portfolio Strategy for Growth Under Product-Market Configurations
Bert Verhoeven; Lester W. Johnson
2017-01-01
Purpose: The research links three concepts: product market growth strategy, the magnitude of innovation and Business Model Innovation, merging them together into a dynamic Business Model Innovation strategy framework. Design/Methodology/Approach: The paper is conceptual and exploratory in nature and builds on existing literature and the author’s experience with developing business models. Findings: The BMI strategy framework can help managers establish a BMI portfolio strategy followi...
Digital portfolio for learning: A new communication channel for education
Judit Coromina
2011-04-01
Full Text Available Purpose: The Catalonian Government has the intention of introducing the digital portfolio before 2017, an initiative related to new approaches for learning. Taking in consideration the increasing interest for digital portfolio as a new communication channel for education, the article aims are: on the one hand to describe how the digital portfolio works and on the other hand, to identify a list of criteria that should be useful for educative centers to select the best application to create the digital portfolio according to their needs.Design/methodology/approach: Firstly, a theoretical framework for portfolio functioning is described. After, applications to support the digital portfolio are classified. Next, a requirement analysis on an ideal application to support the portfolio is made, according to those phases for the portfolio creation identified in the theoretical framework. Lastly, a list of criteria is established to select the application for creating the digital portfolio.Findings and Originality/value: The article contributes to structure the portfolio creation process in some stages and phases in a wider way that it is described in the literature. In addition, a list of criteria is defined to help educative centers to select the application for managing the portfolio that fits better with their objectives. These criteria have been obtained with an exhaustive methodology.Research limitations/implications: In order to put in practice the identified criteria it is proposed to complete the multi-criteria decision model in a new study. It should include processes to weigh criteria and define normalizations. Afterwards it would be able to analyze the value of the model studying the satisfaction for using it by a sample of educative centers.Practical implications: The list of criteria identified should facilitate the selection of the more adequate application to create the learning portfolio to the educative centers, according to their
Anita V. Sotnikova
2015-01-01
Full Text Available Article is devoted to a problem of effective distribution of the general budget of a portfolio between the IT projects which are its part taking into ac-count their priority. The designated problem is actual in view of low results of activity of the consulting companies in the sphere of information technologies.For determination of priority of IT projects the method of analytical networks developed by T. Saati is used. For the purpose of application of this method the system of criteria (indicators reflecting influence of IT projects of a portfolio on the most significant purposes of implementation of IT projects of a portfolio is developed. As system of criteria the key indicators of efficiency defined when developing the Balanced system of indicators which meet above-mentioned requirements are used. The essence of a method of analytical net-works consists in paired comparison of key indicators of efficiency concerning the purpose of realization of a portfolio and IT projects which are a part of a portfolio. Result of use of a method of analytical networks are coefficients of priority of each IT project of a portfolio. The received coefficients of priority of IT projects are used in the offered model of distribution of the budget of a portfolio between IT projects. Thus, the budget of a portfolio of IT projects is distributed between them taking into account not only the income from implementation of each IT project, but also other criteria, important for the IT company, for example: the degree of compliance of the IT project to strategic objectives of the IT company defining expediency of implementation of the IT project; the term of implementation of the IT project determined by the customer. The developed model of distribution of the budget of a portfolio between IT projects is approved on the example of distribution of the budget between IT projects of the portfolio consisting of three IT projects. Taking into account the received
Power Grid Construction Project Portfolio Optimization Based on Bi-level programming model
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.
Methods and Models of Market Risk Stress-Testing of the Portfolio of Financial Instruments
Alexander M. Karminsky
2015-01-01
Full Text Available Amid instability of financial markets and macroeconomic situation the necessity of improving bank risk-management instrument arises. New economic reality defines the need for searching for more advanced approaches of estimating banks vulnerability to exceptional, but plausible events. Stress-testing belongs to such instruments. The paper reviews and compares the models of market risk stress-testing of the portfolio of different financial instruments. These days the topic of the paper is highly acute due to the fact that now stress-testing is becoming an integral part of anticrisis risk-management amid macroeconomic instability and appearance of new risks together with close interest to the problem of risk-aggregation. The paper outlines the notion of stress-testing and gives coverage of goals, functions of stress-tests and main criteria for market risk stress-testing classification. The paper also stresses special aspects of scenario analysis. Novelty of the research is explained by elaborating the programme of aggregated complex multifactor stress-testing of the portfolio risk based on scenario analysis. The paper highlights modern Russian and foreign models of stress-testing both on solo-basis and complex. The paper lays emphasis on the results of stress-testing and revaluations of positions for all three complex models: methodology of the Central Bank of stress-testing portfolio risk, model relying on correlations analysis and copula model. The models of stress-testing on solo-basis are different for each financial instrument. Parametric StressVaR model is applicable to shares and options stress-testing;model based on "Grek" indicators is used for options; for euroobligation regional factor model is used. Finally some theoretical recommendations about managing market risk of the portfolio are given.
Aldrin Herwany
2008-09-01
This study assesses the cointegration and causal relations among seven developed Asian markets, i.e., Tokyo, Hong Kong, Korea, Taiwan, Shanghai, Singapore, and Kuala Lumpur stock exchanges, using more frequent time series data. It employs the recently developed techniques for investigating unit roots, cointegration, time-varying volatility, and causality in variance. For estimating portfolio market risk, this study employs Value-at-Risk with delta normal approach. The results would recommend whether fund managers are able to diversify their portfolio in these developed stock markets either in long run or in short run.
Modeling of Mean-VaR portfolio optimization by risk tolerance when the utility function is quadratic
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.
Application of the Beck model to stock markets: Value-at-Risk and portfolio risk assessment
Kozaki, M.; Sato, A.-H.
2008-02-01
We apply the Beck model, developed for turbulent systems that exhibit scaling properties, to stock markets. Our study reveals that the Beck model elucidates the properties of stock market returns and is applicable to practical use such as the Value-at-Risk estimation and the portfolio analysis. We perform empirical analysis with daily/intraday data of the S&P500 index return and find that the volatility fluctuation of real markets is well-consistent with the assumptions of the Beck model: The volatility fluctuates at a much larger time scale than the return itself and the inverse of variance, or “inverse temperature”, β obeys Γ-distribution. As predicted by the Beck model, the distribution of returns is well-fitted by q-Gaussian distribution of Tsallis statistics. The evaluation method of Value-at-Risk (VaR), one of the most significant indicators in risk management, is studied for q-Gaussian distribution. Our proposed method enables the VaR evaluation in consideration of tail risk, which is underestimated by the variance-covariance method. A framework of portfolio risk assessment under the existence of tail risk is considered. We propose a multi-asset model with a single volatility fluctuation shared by all assets, named the single β model, and empirically examine the agreement between the model and an imaginary portfolio with Dow Jones indices. It turns out that the single β model gives good approximation to portfolios composed of the assets with non-Gaussian and correlated returns.
Decentralized portfolio management
Coutinho, Paulo; Tabak, Benjamin Miranda
2003-01-01
We use a mean-variance model to analyze the problem of decentralized portfolio management. We find the solution for the optimal portfolio allocation for a head trader operating in n different markets, which is called the optimal centralized portfolio. However, as there are many traders specialized in different markets, the solution to the problem of optimal decentralized allocation should be different from the centralized case. In this paper we derive conditions for the solutions to be equiva...
Multi-Period Structural Model of a Mortgage Portfolio with Cointegrated Factors
Gapko, Petr; Šmíd, Martin
2016-01-01
Roč. 66, č. 6 (2016), s. 565-574 ISSN 0015-1920 R&D Projects: GA ČR GA15-10331S Institutional support: RVO:67985556 Keywords : credit risk * mortgage * loan portfolio * dynamic model * estimation Subject RIV: AH - Economics Impact factor: 0.604, year: 2016 http://library.utia.cas.cz/separaty/2016/E/smid-0467176.pdf
A linear allocation of spending-power system : consumer demand and portfolio model
Clements, Ken
2017-01-01
In the applied literature the household's consumption and portfolio decisions have tended to be viewed separately. This thesis is an initial attempt to remedy this. The household's demand for both commodities and assets, at a reasonably low level of aggregation, is integrated by using a tightly specified utility maximizing model. Utility is a function of both the flow of commodities consumed and the stock of assets held. The consumer demand literature is used as a starting point. The solutio...
Fakhri Husein
2017-03-01
Full Text Available Shariah Compliant Asset Pricing Model (SCAPM is a modification of the model Capital Asset Pricing Model (CAPM. This research is quantitative descriptive study of theories of optimal portfolio analysis applied to trading stocks, especially in stocks Jakarta Islamic Index. Sampling technique used was purposive sampling and obtained 26 shares. The analysis tool used is MatLab R2010a. The results of this study are not prove theMarkowitz portfolio theory. This is explained by the amount of Beta market (β_m a value beta below 1 indicates that the fluctuation of stocks returns do not follow the movement of market fluctuations. Investors are likely to want a high profit, the investors are advised to choose a second portfolio groups, with rate of 0.176722% and investors are likely to enjoy a substantial risk in the investment portfolio are advised to choose the first group with a great risk of 0.8501%.
A class of multi-period semi-variance portfolio for petroleum exploration and development
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.
Xinfeng Ruan
2013-01-01
Full Text Available We study option pricing with risk-minimization criterion in an incomplete market where the dynamics of the risky underlying asset are governed by a jump diffusion equation. We obtain the Radon-Nikodym derivative in the minimal martingale measure and a partial integrodifferential equation (PIDE of European call option. In a special case, we get the exact solution for European call option by Fourier transformation methods. Finally, we employ the pricing kernel to calculate the optimal portfolio selection by martingale methods.
DIFFERENCES BETWEEN MEAN-VARIANCE AND MEAN-CVAR PORTFOLIO OPTIMIZATION MODELS
Panna Miskolczi
2016-07-01
Full Text Available Everybody heard already that one should not expect high returns without high risk, or one should not expect safety without low returns. The goal of portfolio theory is to find the balance between maximizing the return and minimizing the risk. To do so we have to first understand and measure the risk. Naturally a good risk measure has to satisfy several properties - in theory and in practise. Markowitz suggested to use the variance as a risk measure in portfolio theory. This led to the so called mean-variance model - for which Markowitz received the Nobel Prize in 1990. The model has been criticized because it is well suited for elliptical distributions but it may lead to incorrect conclusions in the case of non-elliptical distributions. Since then many risk measures have been introduced, of which the Value at Risk (VaR is the most widely used in the recent years. Despite of the widespread use of the Value at Risk there are some fundamental problems with it. It does not satisfy the subadditivity property and it ignores the severity of losses in the far tail of the profit-and-loss (P&L distribution. Moreover, its non-convexity makes VaR impossible to use in optimization problems. To come over these issues the Expected Shortfall (ES as a coherent risk measure was developed. Expected Shortfall is also called Conditional Value at Risk (CVaR. Compared to Value at Risk, ES is more sensitive to the tail behaviour of the P&L distribution function. In the first part of the paper I state the definition of these three risk measures. In the second part I deal with my main question: What is happening if we replace the variance with the Expected Shortfall in the portfolio optimization process. Do we have different optimal portfolios as a solution? And thus, does the solution suggests to decide differently in the two cases? To answer to these questions I analyse seven Hungarian stock exchange companies. First I use the mean-variance portfolio optimization model
Backtesting Portfolio Value-at-Risk with Estimated Portfolio Weights
Pei Pei
2010-01-01
This paper theoretically and empirically analyzes backtesting portfolio VaR with estimation risk in an intrinsically multivariate framework. For the first time in the literature, it takes into account the estimation of portfolio weights in forecasting portfolio VaR and its impact on backtesting. It shows that the estimation risk from estimating the portfolio weights as well as that from estimating the multivariate dynamic model of asset returns make the existing methods in a univariate framew...
Land-use planning for nearshore ecosystem services—the Puget Sound Ecosystem Portfolio Model
Byrd, Kristin
2011-01-01
The 2,500 miles of shoreline and nearshore areas of Puget Sound, Washington, provide multiple benefits to people—"ecosystem services"—including important fishing, shellfishing, and recreation industries. To help resource managers plan for expected growth in coming decades, the U.S. Geological Survey Western Geographic Science Center has developed the Puget Sound Ecosystem Portfolio Model (PSEPM). Scenarios of urban growth and shoreline modifications serve as model inputs to develop alternative futures of important nearshore features such as water quality and beach habitats. Model results will support regional long-term planning decisions for the Puget Sound region.
Modeling and Forecasting Large Realized Covariance Matrices and Portfolio Choice
Callot, Laurent A.F.; Kock, Anders B.; Medeiros, Marcelo C.
2017-01-01
We consider modeling and forecasting large realized covariance matrices by penalized vector autoregressive models. We consider Lasso-type estimators to reduce the dimensionality and provide strong theoretical guarantees on the forecast capability of our procedure. We show that we can forecast
Application of Markowitz Portfolio Theory by Building Optimal Portfolio on the US Stock Market
Širůček, Martin; Křen, Lukáš
2015-01-01
ŠIRŮČEK MARTIN, KŘEN LUKÁŠ. 2015. Application of Markowitz Portfolio Theory by Building Optimal Portfolio on the US Stock Market. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 63(4): 1375–1386. This paper is focused on building investment portfolios by using the Markowitz Portfolio Theory (MPT). Derivation based on the Capital Asset Pricing Model (CAPM) is used to calculate the weights of individual securities in portfolios. The calculated portfolios include a po...
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.
Sparse and stable Markowitz portfolios.
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.
A Dynamic Spreadsheet Model for Determining the Portfolio Frontier for BSE30 Stocks
Dr. Anupam Mitra
2014-01-01
Full Text Available Introductory investments courses revolve around Harry Markowitz’s modern portfolio theory and William Sharpe’s Index for the performance measurement of those portfolios. This paper presents a simplified perspective of Markowitz’s contributions to Modern Portfolio Theory. It is to see the effect of duration of historical data on the risk and return of the portfolio and to see the applicability of risk-reward logic. The empirical results also show that short selling may increase the risk of the portfolio when the investor is instability preferred.
Ling Zhang
2012-01-01
Full Text Available We study a multi-period mean-variance portfolio selection problem with an uncertain time horizon and serial correlations. Firstly, we embed the nonseparable multi-period optimization problem into a separable quadratic optimization problem with uncertain exit time by employing the embedding technique of Li and Ng (2000. Then we convert the later into an optimization problem with deterministic exit time. Finally, using the dynamic programming approach, we explicitly derive the optimal strategy and the efficient frontier for the dynamic mean-variance optimization problem. A numerical example with AR(1 return process is also presented, which shows that both the uncertainty of exit time and the serial correlations of returns have significant impacts on the optimal strategy and the efficient frontier.
Optimal portfolio selection in a Lévy market with uncontrolled cash flow and only risky assets
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.
Jalimar Guimarães Simplício
2012-01-01
Full Text Available The objective of this article is to compare investment project selection using the efficient frontier in the mean-variance space based on optimization models introduced by Markowitz (1952 with the project ranking method according to the profitability index (PI. The selection of real assets by companies did not incorporate the mean-variance optimization procedure in the same way the selection of financial assets in investment portfolios did. The process of selection and formation of portfolios of investment projects for the oil area of a company in the energy industry was analyzed. Project portfolios formed according to the usual company practice of ranking by their PI were compared with those that result from applying mean-variance optimization through Monte Carlo simulation, which allows the computation of mean returns, variances, and covariances for the set of projects considered. The inefficiency of project portfolios obtained by ranking according to the PI compared to those obtained by the method of Markowitz suggests that there are opportunities to improve the process of selecting the set of projects to be implemented by companies.O objetivo deste artigo é comparar a seleção de projetos de investimento segundo a fronteira eficiente no espaço média-variância com base em modelos de otimização introduzidos por Markowitz (1952 com o método do ordenamento de projetos segundo o índice de lucratividade (IL. A seleção de ativos reais pelas empresas não incorporou o procedimento de otimização de média-variância da mesma forma que na seleção de ativos financeiros para carteiras de investimento. O processo de seleção e formação de carteiras de projetos de investimento pela área de petróleo de uma empresa do setor de energia foi analisado. Carteiras de projetos constituídas de acordo com a prática usual da empresa de ordenamento pelo IL foram comparadas com as que resultariam da aplicação da otimização de m
Portfolio Diversification in the South-East European Equity Markets
Zaimovic Azra
2017-04-01
Full Text Available Diversification potential enables investors to manage their risk and decrease risk exposure. Good diversification policy is a safety net that prevents a portfolio from losing its value. A well-diversified portfolio consists of different categories of property with low correlations, while highly correlated markets have the feature of low possibilities for diversification. The biggest riddle in the world of investments is to find the optimal portfolio within a set of available assets with limited capital. There are numerous studies and mathematical models that deal with portfolio investment strategies. These strategies take advantage of diversification by spreading risk over several financial assets. Modern portfolio theory seeks to find the optimal model with the best results. This paper tries to identify relationships between returns of companies traded in South-East European equity markets. A Markowitz mean-variance (MV portfolio optimization method is used to identify possibilities for diversification among these markets and world leading capital markets. This research also offers insight into to the level of integration of South-East European equity markets. Principal component analysis (PCA is used to determine components that describe the strong patterns and co-movements of the dataset. Finally, we combined MV efficient frontier and equity, which represent PCA components, to draw conclusions. Our findings show that PC analysis substantially simplifies asset selection process in portfolio management. The results of the paper have practical applications for portfolio investors.
Probabilistic disaggregation model with application to natural hazard risk assessment of portfolios
Custer, Rocco; Nishijima, Kazuyoshi
In natural hazard risk assessment, a resolution mismatch between hazard data and aggregated exposure data is often observed. A possible solution to this issue is the disaggregation of exposure data to match the spatial resolution of hazard data. Disaggregation models available in literature...... disaggregation model that considers the uncertainty in the disaggregation, taking basis in the scaled Dirichlet distribution. The proposed probabilistic disaggregation model is applied to a portfolio of residential buildings in the Canton Bern, Switzerland, subject to flood risk. Thereby, the model is verified...... are usually deterministic and make use of auxiliary indicator, such as land cover, to spatially distribute exposures. As the dependence between auxiliary indicator and disaggregated number of exposures is generally imperfect, uncertainty arises in disaggregation. This paper therefore proposes a probabilistic...
Hong-Ghi Min
2011-01-01
Using Monte Carlo simulation of the Portfolio-balance model of the exchange rates, we report finite sample properties of the GMM estimator for testing over-identifying restrictions in the simultaneous equations model. F-form of Sargans statistic performs better than its chi-squared form while Hansens GMM statistic has the smallest bias.
A MODEL OF HETEROGENEOUS DISTRIBUTED SYSTEM FOR FOREIGN EXCHANGE PORTFOLIO ANALYSIS
Dragutin Kermek
2006-06-01
Full Text Available The paper investigates the design of heterogeneous distributed system for foreign exchange portfolio analysis. The proposed model includes few separated and dislocated but connected parts through distributed mechanisms. Making system distributed brings new perspectives to performance busting where software based load balancer gets very important role. Desired system should spread over multiple, heterogeneous platforms in order to fulfil open platform goal. Building such a model incorporates different patterns from GOF design patterns, business patterns, J2EE patterns, integration patterns, enterprise patterns, distributed design patterns to Web services patterns. The authors try to find as much as possible appropriate patterns for planned tasks in order to capture best modelling and programming practices.
Wolfe-Quintero, Kate; Brown, James Dean
1998-01-01
A portfolio of achievements, experiences, and reflections can help English-as-a-Second-Language teachers attain professional development goals and offer administrators greater insight for making informed hiring and job-performance decisions. This paper focuses on what teacher portfolios are, what their contents should be, and what their uses are…
Pedersen, Christian Fischer
The present teaching portfolio has been submitted for evaluation in partial fulfillment of the requirements of the teacher training programme for Assistant Professors at Department of Engineering, Aarhus University, Denmark.......The present teaching portfolio has been submitted for evaluation in partial fulfillment of the requirements of the teacher training programme for Assistant Professors at Department of Engineering, Aarhus University, Denmark....
Teresia Diana Lewe van Aduard de Macedo-Soares
2016-10-01
Full Text Available The objective of this article is to present a model for analysing the role of absorptive capacity in the relationship between strategic alliance portfolios and innovation performance based on the results of bibliographic research on the subject published between 2000 and 2015. The research was carried out in three stages, involving both quantitative - bibliometric and bibliographic coupling - and qualitative content analyses. AP management capabilities were found to have a fundamental moderating role in the AP–IP relationship, and amongst these capabilities AC was highlighted by several authors. However, its role was found to vary according to AP characteristics, notably AP diversity – functional, geographic and institutional, but also centrality, size, stability and volume of resources, alliance and partner types as well as country type: emerging versus developed economies. This research formed the basis for the development of the model and the formulation of some propositions that focused on emerging countries.
Hidden Markov Model for Stock Selection
Nguyet Nguyen
2015-10-01
Full Text Available The hidden Markov model (HMM is typically used to predict the hidden regimes of observation data. Therefore, this model finds applications in many different areas, such as speech recognition systems, computational molecular biology and financial market predictions. In this paper, we use HMM for stock selection. We first use HMM to make monthly regime predictions for the four macroeconomic variables: inflation (consumer price index (CPI, industrial production index (INDPRO, stock market index (S&P 500 and market volatility (VIX. At the end of each month, we calibrate HMM’s parameters for each of these economic variables and predict its regimes for the next month. We then look back into historical data to find the time periods for which the four variables had similar regimes with the forecasted regimes. Within those similar periods, we analyze all of the S&P 500 stocks to identify which stock characteristics have been well rewarded during the time periods and assign scores and corresponding weights for each of the stock characteristics. A composite score of each stock is calculated based on the scores and weights of its features. Based on this algorithm, we choose the 50 top ranking stocks to buy. We compare the performances of the portfolio with the benchmark index, S&P 500. With an initial investment of $100 in December 1999, over 15 years, in December 2014, our portfolio had an average gain per annum of 14.9% versus 2.3% for the S&P 500.
Svend Reuse
2010-09-01
Full Text Available Portfolio theory and the basic ideas of Markowitz have been extended in the recent past by alternative risk models as historical simulation or even copula functions. The central question of this paper is if these approaches lead to different results compared to the classical variance/covariance approach. Therefore, empirical data of the last 10 years is analysed. Both approaches are compared in the special context of the financial crisis. The worst case optimization and the Value at Risk (VaR are defined in order to define the minimum risk portfolio before and after the financial crisis. The result is that the financial crisis has nearly no impact onto the portfolio, but the two approaches lead to different results.
Specific patterns in portfolio analysis
Gabriela Victoria ANGHELACHE
2013-11-01
Full Text Available In the mid-twentieth century, under an unprecedented growth of the business of trading in securities, the need to provide a modern framework for assessing the performance of portfolios of financial instruments was felt. To that effect, it is noted that over this period, more and more economists have attempted to develop statistical mathematical models that ensure the evaluation of profitability and portfolio risk securities. These models are considered to be part of "the modern portfolio theory".
Universal portfolios generated by the Bregman divergence
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.
Alimbaev Farkhad
2009-11-01
Full Text Available The financial crisis gave an impetus to finding “weaknesses” in financial institutions. One such tool is the stress-testing. This method is intended to identify through modeling “hypothetical” or “historical” scenarios, the most losses, in the execution of a script. In the simulation of hypothetical scenarios to find the impact factor, as shock events on the trade portfolio. When using historical scenarios, as the shocks applied developments in the past that have caused catastrophic losses, both in quantitative and qualitative size. For example, such scenarios can be: financial crises of the 90-ies and the current decline in international stock markets, a drop or increase in foreign exchange rates, etc.
Applying the Land Use Portfolio Model with Hazus to analyse risk from natural hazard events
Dinitz, Laura B.; Taketa, Richard A.
2013-01-01
This paper describes and demonstrates the integration of two geospatial decision-support systems for natural-hazard risk assessment and management. Hazus is a risk-assessment tool developed by the Federal Emergency Management Agency to identify risks and estimate the severity of risk from natural hazards. The Land Use Portfolio Model (LUPM) is a risk-management tool developed by the U.S. Geological Survey to evaluate plans or actions intended to reduce risk from natural hazards. We analysed three mitigation policies for one earthquake scenario in the San Francisco Bay area to demonstrate the added value of using Hazus and the LUPM together. The demonstration showed that Hazus loss estimates can be input to the LUPM to obtain estimates of losses avoided through mitigation, rates of return on mitigation investment, and measures of uncertainty. Together, they offer a more comprehensive approach to help with decisions for reducing risk from natural hazards.
Bakker, Diederich; Raabe, Thorsten; Haas, Sandra
2014-01-01
Brand portfolio strategies are an essential prerequisite for securing long-term success for multi-brand companies. Only by focusing on the entire portfolio can it be ensured that all brands “act in concert” to achieve superordinate objectives. Thereby, an increasing vertical competition caused by
Dynamic Portfolio Strategy Using Clustering Approach.
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.
Dynamic Portfolio Strategy Using Clustering Approach.
Fei Ren
Full Text Available 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.
Equity portfolio optimization: A DEA based methodology applied to the Zagreb Stock Exchange
Margareta Gardijan
2015-10-01
Full Text Available Most strategies for selection portfolios focus on utilizing solely market data and implicitly assume that stock markets communicate all relevant information to all market stakeholders, and that these markets cannot be influenced by investor activities. However convenient, this is a limited approach, especially when applied to small and illiquid markets such as the Croatian market, where such assumptions are hardly realistic. Thus, there is a demand for including other sources of data, such as financial reports. Research poses the question of whether financial ratios as criteria for stock selection are of any use to Croatian investors. Financial and market data from selected publicly companies listed on the Croatian capital market are used. A two-stage portfolio selection strategy is applied, where the first stage involves selecting stocks based on the respective Data Envelopment Analysis (DEA efficiency scores. DEA models are becoming popular in stock portfolio selection given that the methodology includes numerous models that provide a great flexibility in selecting inputs and outputs, which in turn are considered as criteria for portfolio selection. Accordingly, there is much room for improvement of the current proposed strategies for selecting portfolios. In the second stage, two portfolio-weighting strategies are applied using equal proportions and score-weighting. To show whether these strategies create outstanding out–of–sample portfolios in time, time-dependent DEA Window Analysis is applied using a reference time of one year, and portfolio returns are compared with the market portfolio for each period. It is found that the financial data are a significant indicator of the future performance of a stock and a DEA-based portfolio strategy outperforms market return.
N.J. Timofeeva
2011-05-01
Full Text Available This article examines the financial planning of working capital organizations, in particular presented a software implementation of the algorithm analyzes the budget forecast working capital, identify and take advantage of temporarily free money using a model of a decision on the choice of the optimal bond portfolio, consistent with the free flow of liquidity of the enterprise.
Empirical test of Capital Asset Pricing Model on Selected Banking Shares from Borsa Istanbul
Fuzuli Aliyev
2018-03-01
Full Text Available In this paper we tested Capital Asset Pricing Model (shortly CAPM hereafter on the selected banking stocks of Borsa Istanbul. Here we tried to explain how to price financial assets based on their risks in the case of BIST-100 index. CAPM is an important model in the portfolio management theory used by economic agents for the selection of financial assets. We used 12 random banking stocks’ monthly return data for 2001–2010 periods. To test the validity of the CAPM, we first derived the regression equation for the risk-free interest rate and risk premium relationship using January 2001–December 2009 data. Then, estimated January–December 2010 returns with the equation. Comparing forecasted return with the actual return, we concluded that the CAPM is valid for the portfolio consisting of the 12 banks traded in the ISE, i.e. The model could predict the overall outcome of portfolio of selected banking shares
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.
Purchasing portfolio usage and purchasing sophistication
Gelderman, C.J.; Weele, van A.J.
2005-01-01
Purchasing portfolio models have caused considerable controversy in literature. Many advantages and disadvantages have been put forward, revealing a strong disagreement on the merits of portfolio models. This study addresses the question whether or not the use of purchasing portfolio models should
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
Portfolio optimization with structured products under return constraint
Baweja Meena
2015-01-01
Full Text Available A new approach for optimizing risk in a portfolio of financial instruments involving structured products is presented. This paper deals with a portfolio selection model which uses optimization methodology to minimize conditional Value-at-Risk (CVaR under return constraint. It focuses on minimizing CVaR rather than on minimizing value-at-Risk VaR, as portfolios with low CVaR necessarily have low VaR as well. We consider a simple investment problem where besides stocks and bonds, the investor can also include structured products into the investment portfolio. Due to possible intermediate payments from structured product, we have to deal with a re-investment problem modeled as a linear optimization problem.
Developing R&D Portfolio Business Validity Simulation Model and System
Hyun Jin Yeo
2015-01-01
Full Text Available The R&D has been recognized as critical method to take competitiveness by not only companies but also nations with its value creation such as patent value and new product. Therefore, R&D has been a decision maker’s burden in that it is hard to decide how much money to invest, how long time one should spend, and what technology to develop which means it accompanies resources such as budget, time, and manpower. Although there are diverse researches about R&D evaluation, business factors are not concerned enough because almost all previous studies are technology oriented evaluation with one R&D technology based. In that, we early proposed R&D business aspect evaluation model which consists of nine business model components. In this research, we develop a simulation model and system evaluating a company or industry’s R&D portfolio with business model point of view and clarify default and control parameters to facilitate evaluator’s business validity work in each evaluation module by integrate to one screen.
Developing R&D portfolio business validity simulation model and system.
Yeo, Hyun Jin; Im, Kwang Hyuk
2015-01-01
The R&D has been recognized as critical method to take competitiveness by not only companies but also nations with its value creation such as patent value and new product. Therefore, R&D has been a decision maker's burden in that it is hard to decide how much money to invest, how long time one should spend, and what technology to develop which means it accompanies resources such as budget, time, and manpower. Although there are diverse researches about R&D evaluation, business factors are not concerned enough because almost all previous studies are technology oriented evaluation with one R&D technology based. In that, we early proposed R&D business aspect evaluation model which consists of nine business model components. In this research, we develop a simulation model and system evaluating a company or industry's R&D portfolio with business model point of view and clarify default and control parameters to facilitate evaluator's business validity work in each evaluation module by integrate to one screen.
Developing R&D Portfolio Business Validity Simulation Model and System
2015-01-01
The R&D has been recognized as critical method to take competitiveness by not only companies but also nations with its value creation such as patent value and new product. Therefore, R&D has been a decision maker's burden in that it is hard to decide how much money to invest, how long time one should spend, and what technology to develop which means it accompanies resources such as budget, time, and manpower. Although there are diverse researches about R&D evaluation, business factors are not concerned enough because almost all previous studies are technology oriented evaluation with one R&D technology based. In that, we early proposed R&D business aspect evaluation model which consists of nine business model components. In this research, we develop a simulation model and system evaluating a company or industry's R&D portfolio with business model point of view and clarify default and control parameters to facilitate evaluator's business validity work in each evaluation module by integrate to one screen. PMID:25893209
Smith-Perera, Aida [Universidad Metropolitana de Caracas, Departamento de Gestion Tecnologica, Caracas 1071, Edo Miranda (Venezuela); Garcia-Melon, Monica; Poveda-Bautista, Rocio; Pastor-Ferrando, Juan-Pascual [Universidad Politecnica de Valencia, Departamento de Proyectos de Ingenieria, Camino de vera s/n 46022 Valencia (Spain)
2010-08-15
In this paper a new approach to prioritize project portfolio in an efficient and reliable way is presented. It is based on strategic objectives of the company and multicriteria decision methods. The paper introduces a rigorous method with acceptable complexity which seeks to assist managers of a big Electrical Company of Venezuela to distribute the annual budget among the possible improvement actions to be conducted on the electrical network of Caracas. A total of 15 network improvement actions grouped into three clusters according to the strategic objectives of the company have been analyzed using the Project Strategic Index (PSI) proposed. The approach combines the use of the Analytic Network Process (ANP) method with the information obtained from the experts during the decision-making process. The ANP method allows the aggregation of the experts' judgments on each of the indicators used into one Project Strategic Index. In addition, ANP is based on utility ratio functions which are the most appropriate for the analysis of uncertain data, like experts' estimations. Finally, unlike the other multicriteria techniques, ANP allows the decision problem to be modelled using the relationships among dependent criteria. The participating experts coincided in the appreciation that the method proposed in this paper is useful and an improvement from traditional budget distribution techniques. They find the results obtained coherent, the process seems sufficiently rigorous and precise, and the use of resources is significantly less than in other methods. (author)
Smith-Perera, Aida; Garcia-Melon, Monica; Poveda-Bautista, Rocio; Pastor-Ferrando, Juan-Pascual
2010-01-01
In this paper a new approach to prioritize project portfolio in an efficient and reliable way is presented. It is based on strategic objectives of the company and multicriteria decision methods. The paper introduces a rigorous method with acceptable complexity which seeks to assist managers of a big Electrical Company of Venezuela to distribute the annual budget among the possible improvement actions to be conducted on the electrical network of Caracas. A total of 15 network improvement actions grouped into three clusters according to the strategic objectives of the company have been analyzed using the Project Strategic Index (PSI) proposed. The approach combines the use of the Analytic Network Process (ANP) method with the information obtained from the experts during the decision-making process. The ANP method allows the aggregation of the experts' judgments on each of the indicators used into one Project Strategic Index. In addition, ANP is based on utility ratio functions which are the most appropriate for the analysis of uncertain data, like experts' estimations. Finally, unlike the other multicriteria techniques, ANP allows the decision problem to be modelled using the relationships among dependent criteria. The participating experts coincided in the appreciation that the method proposed in this paper is useful and an improvement from traditional budget distribution techniques. They find the results obtained coherent, the process seems sufficiently rigorous and precise, and the use of resources is significantly less than in other methods. (author)
The Finite and Moving Order Multinomial Universal Portfolio
Tan, Choon Peng; Pang, Sook Theng
2013-01-01
An upper bound for the ratio of wealths of the best constant -rebalanced portfolio to that of the multinomial universal portfolio is derived. The finite- order multinomial universal portfolios can reduce the implementation time and computer-memory requirements for computation. The improved performance of the finite-order portfolios on some selected local stock-price data sets is observed.
Management of Portfolio Investment Held by Pension Funds
Dan Armeanu
2008-09-01
Full Text Available As a result of the fact that pension funds are financial intermediaries, the value of their assets and liabilities is influenced by changing conditions in financial markets. The market image of a pension fund (and hence its perceived value are closely tied to the “financial health” of the fund. Setting up and managing complex investment portfolios requires that pension administrators use scientific models of portfolio selection and optimization based on the risk-expected return relationship. Most investment portfolios are modified in time as result of changing stock prices and investment policy objectives. Having established investment policy guidelines, the administrators of pension funds have to determine the structure of their portfolios so that the latter meet legal requirements.
An, Da; Yang, Yu; Chai, Xilong
2015-01-01
In order to solve the environmental contaminations and human health problems caused by the inappropriate treatment of waste electrical and electronic equipment (WEEE) in China, sustainable e-waste treatment has emerged in China's WEEE recycling industry. This study aims to develop a multi......-criteria decision making method by integrating interval Analytic Hierarchy Process and interval VIKOR method for China's stakeholders to select the most efficacious portfolio for solving the severe problems caused by the informal e-waste recycling and promote the development of China's WEEE recycling industry...... in a sustainable approach. An illustrative case in Guiyu has been studied by the developed method, and the results show that the portfolio of supporting the informal peddlers for legal transition, investing on infrastructure for WEEE recycling, training and education on China's residents, and restricting...
Yuhong Zhou
2013-03-01
Full Text Available For the presence of non-normal distribution characteristics in the financial assets returns, the model of AR(1-GJR(1,1 is used to characterize the marginal distribution of the style assets in China stock market. The Copula function is introduced to analyze the dependency structure between the six style assets, combined with the marginal distributed residual sequences. And the joint return distribution of the style portfolios is simulated, combined with extreme value theory and Monte Carlo simulation method. Then the market risks (VaR and CVaR of the style portfolios in China stock markets are obtained. The results of the study show that the generalized Pareto distribution Model can well fit the non-normal distribution characteristics such as peak and fat tail in the style assets returns.
Nomeda Dobrovolskienė
2016-05-01
Full Text Available Modern portfolio theory attempts to maximize the expected return of a portfolio for a given level of portfolio risk, or equivalently minimize risk for a given level of expected return. The reality, however, shows that, when selecting projects to a portfolio and allocating resources in the portfolio, an increasing number of organizations take into account other aspects as well. As a result of the sole purpose (risk-return, it offers only a partial solution for a sustainable organization. Existing project portfolio selection and resource allocation methods and models do not consider sustainability. Therefore, the aim of this article is to develop a sustainability-oriented model of financial resource allocation in a project portfolio by integrating a composite sustainability index of a project into Markowitz’s classical risk-return scheme (mean-variance model. The model was developed by applying multi-criteria decision-making methods. The practicability of the model was tested by an empirical study in a selected construction company. The proposed sustainability-oriented financial resource allocation model could be used in allocating financial resources in any type of business. The use of the model would not only help organisations to manage risk and achieve higher return but would also allow carrying out sustainable projects, thereby promoting greater environmental responsibility and giving more consideration to the wellbeing of future generations. Moreover, the model allows quantifying the impact of the integration of sustainability into financial resource allocation on the return of a portfolio.
Modeling the resilience of urban water supply using the capital portfolio approach
Krueger, E. H.; Klammler, H.; Borchardt, D.; Frank, K.; Jawitz, J. W.; Rao, P. S.
2017-12-01
The dynamics of global change challenge the resilience of cities in a multitude of ways, including pressures resulting from population and consumption changes, production patterns, climate and landuse change, as well as environmental hazards. Responses to these challenges aim to improve urban resilience, but lack an adequate understanding of 1) the elements and processes that lead to the resilience of coupled natural-human-engineered systems, 2) the complex dynamics emerging from the interaction of these elements, including the availability of natural resources, infrastructure, and social capital, which may lead to 3) unintended consequences resulting from management responses. We propose a new model that simulates the coupled dynamics of five types of capitals (water resources, infrastructure, finances, political capital /management, and social adaptive capacity) that are necessary for the provision of water supply to urban residents. We parameterize the model based on data for a case study city, which is limited by constraints in water availability, financial resources, and faced with degrading infrastructure, as well as population increase, which challenge the urban management institutions. Our model analyzes the stability of the coupled system, and produces time series of the capital dynamics to quantify its resilience as a result of the portfolio of capitals available to usher adaptive capacity and to secure water supply subjected to multiple recurring shocks. We apply our model to one real urban water supply system located in an arid environment, as well as a wide range of hypothetical case studies, which demonstrates its applicability to various types of cities, and its ability to quantify and compare water supply resilience. The analysis of a range of urban water systems provides valuable insights into guiding more sustainable responses for maintaining the resilience of urban water supply around the globe, by showing how unsustainable responses risk the
Modern Portfolio Theory: Some Main Results
Müller, Heinz H.
2017-01-01
This article summarizes some main results in modern portfolio theory. First, the Markowitz approach is presented. Then the capital asset pricing model is derived and its empirical testability is discussed. Afterwards Neumann-Morgenstern utility theory is applied to the portfolio problem. Finally, it is shown how optimal risk allocation in an economy may lead to portfolio insurance
Nonzero-Sum Stochastic Differential Portfolio Games under a Markovian Regime Switching Model
Chaoqun Ma
2015-01-01
Full Text Available We consider a nonzero-sum stochastic differential portfolio game problem in a continuous-time Markov regime switching environment when the price dynamics of the risky assets are governed by a Markov-modulated geometric Brownian motion (GBM. The market parameters, including the bank interest rate and the appreciation and volatility rates of the risky assets, switch over time according to a continuous-time Markov chain. We formulate the nonzero-sum stochastic differential portfolio game problem as two utility maximization problems of the sum process between two investors’ terminal wealth. We derive a pair of regime switching Hamilton-Jacobi-Bellman (HJB equations and two systems of coupled HJB equations at different regimes. We obtain explicit optimal portfolio strategies and Feynman-Kac representations of the two value functions. Furthermore, we solve the system of coupled HJB equations explicitly in a special case where there are only two states in the Markov chain. Finally we provide comparative statics and numerical simulation analysis of optimal portfolio strategies and investigate the impact of regime switching on optimal portfolio strategies.
A Relationship Strategy Perspective on Relationship Portfolios
Ritter, Thomas; Andersen, Henrik
2014-01-01
The paper develops a three-dimensional portfolio model for business relationships which distinguishes among six different categories. Based on assessments of customer profitability, customer commitment, and growth potential, the positioning of a given customer relationship in the portfolio allows...... managers to determine appropriate customer relationship strategies and appropriate performance indicators. Results from applying the portfolio model are reported and managerial implications and future research are discussed.......The paper develops a three-dimensional portfolio model for business relationships which distinguishes among six different categories. Based on assessments of customer profitability, customer commitment, and growth potential, the positioning of a given customer relationship in the portfolio allows...
A Numerical Study for Robust Active Portfolio Management with Worst-Case Downside Risk Measure
Aifan Ling
2014-01-01
Full Text Available Recently, active portfolio management problems are paid close attention by many researchers due to the explosion of fund industries. We consider a numerical study of a robust active portfolio selection model with downside risk and multiple weights constraints in this paper. We compare the numerical performance of solutions with the classical mean-variance tracking error model and the naive 1/N portfolio strategy by real market data from China market and other markets. We find from the numerical results that the tested active models are more attractive and robust than the compared models.
Portfolio optimization using median-variance approach
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.
Manuel Sousa Gabrie
2014-09-01
Full Text Available This study analyzed market risk of an international investment portfolio by means of a new methodological proposal based on Value-at- Risk, using the covariance matrix of multivariate GARCH-type models and the extreme value theory to realize if an international diversification strategy minimizes market risk, and to determine if the VaR methodology adequately captures market risk, by applying Backtesting tests. To this end, we considered twelve international stock indexes, accounting for about 62% of the world stock market capitalization, and chose the period from the Dot-Com crisis to the current global financial crisis. Results show that the proposed methodology is a good alternative to accommodate the high market turbulence and can be considered as an adequate portfolio risk management instrument.
Decentralized Portfolio Management
Benjamin Miranda Tabak
2003-12-01
Full Text Available We use a mean-variance model to analyze the problem of decentralized portfolio management. We find the solution for the optimal portfolio allocation for a head trader operating in n different markets, which is called the optimal centralized portfolio. However, as there are many traders specialized in different markets, the solution to the problem of optimal decentralized allocation should be different from the centralized case. In this paper we derive conditions for the solutions to be equivalent. We use multivariate normal returns and a negative exponential function to solve the problem analytically. We generate the equivalence of solutions by assuming that different traders face different interest rates for borrowing and lending. This interest rate is dependent on the ratio of the degrees of risk aversion of the trader and the head trader, on the excess return, and on the correlation between asset returns.
Hierarchical model-based predictive control of a power plant portfolio
Edlund, Kristian; Bendtsen, Jan Dimon; Jørgensen, John Bagterp
2011-01-01
One of the main difficulties in large-scale implementation of renewable energy in existing power systems is that the production from renewable sources is difficult to predict and control. For this reason, fast and efficient control of controllable power producing units – so-called “portfolio...... design for power system portfolio control, which aims specifically at meeting these demands.The design involves a two-layer hierarchical structure with clearly defined interfaces that facilitate an object-oriented implementation approach. The same hierarchical structure is reflected in the underlying...... optimisation problem, which is solved using Dantzig–Wolfe decomposition. This decomposition yields improved computational efficiency and better scalability compared to centralised methods.The proposed control scheme is compared to an existing, state-of-the-art portfolio control system (operated by DONG Energy...
Linearly Adjustable International Portfolios
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.
Linearly Adjustable International Portfolios
Fonseca, R. J.; Kuhn, D.; Rustem, B.
2010-01-01
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.
Søberg, Peder Veng
2009-01-01
As a result of an inquiry concerning how to evaluate IP (intellectual property) portfolios in order to enable the best possible use of IP resources within organizations, an IP evaluation approach primarily applicable for patents and utility models is developed. The developed approach is useful...... of the organization owning the IP....
Efficient Cardinality/Mean-Variance Portfolios
Brito, R. Pedro; Vicente, Luís Nunes
2014-01-01
International audience; We propose a novel approach to handle cardinality in portfolio selection, by means of a biobjective cardinality/mean-variance problem, allowing the investor to analyze the efficient tradeoff between return-risk and number of active positions. Recent progress in multiobjective optimization without derivatives allow us to robustly compute (in-sample) the whole cardinality/mean-variance efficient frontier, for a variety of data sets and mean-variance models. Our results s...
McGilliard, Carey R; Punt, André E; Hilborn, Ray; Essington, Tim
2017-10-01
Many rockfish species are long-lived and thought to be susceptible to being overfished. Hypotheses about the importance of older female rockfish to population persistence have led to arguments that marine reserves are needed to ensure the sustainability of rockfish populations. However, the implications of these hypotheses for rockfish population dynamics are still unclear. We modeled two mechanisms by which reducing the proportion of older fish in a population has been hypothesized to influence sustainability, and explored whether these mechanisms influenced mean population dynamics and recruitment variability. We explored whether populations with these mechanisms could be managed more sustainably with a marine reserve in addition to a constant fishing mortality rate (F) than with a constant F alone. Both hypotheses can be seen as portfolio effects whereby risk of recruitment failure is spread over a "portfolio" of maternal ages. First, we modeled a spawning window effect whereby mothers of different ages spawned in different times or locations (windows) with local environmental conditions. Second, we modeled an offspring size effect whereby older mothers produced larger offspring than younger mothers, where length of a starvation period over which offspring could survive increased with maternal age. Recruitment variability resulting from both models was 55-65% lower than for models without maternal age-related portfolio effects in the absence of fishing and increased with increases in Fs for both models. An offspring size effect caused lower output reproductive rates such that the specified reproductive rate input as a model parameter was no longer the realized rate measured as the reproductive rate observed in model results; this quirk is not addressed in previous analyses of offspring size effects. We conducted a standardization such that offspring size effect and control models had the same observed reproductive rates. A comparison of long-term catch, the
Modelling of and empirical studies on portfolio choice, option pricing, and credit risk
Polbennikov, S.Y.
2005-01-01
This thesis develops and applies a statistical spanning test for mean-coherent regular risk portfolios. Similarly in spirt to Huberman and Kandel (1987), this test can be implemented by means of a simple semi-parametric instrumental variable regression, where instruments have a direct link with a
A Maximum Entropy Method for a Robust Portfolio Problem
Yingying Xu
2014-06-01
Full Text Available We propose a continuous maximum entropy method to investigate the robustoptimal portfolio selection problem for the market with transaction costs and dividends.This robust model aims to maximize the worst-case portfolio return in the case that allof asset returns lie within some prescribed intervals. A numerical optimal solution tothe problem is obtained by using a continuous maximum entropy method. Furthermore,some numerical experiments indicate that the robust model in this paper can result in betterportfolio performance than a classical mean-variance model.
Performance of the reverse Helmbold universal portfolio
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.
USEFULNESS OF BOOTSTRAPPING IN PORTFOLIO MANAGEMENT
Boris Radovanov
2012-12-01
Full Text Available This paper contains a comparison of in-sample and out-of-sample performances between the resampled efficiency technique, patented by Richard Michaud and Robert Michaud (1999, and traditional Mean-Variance portfolio selection, presented by Harry Markowitz (1952. Based on the Monte Carlo simulation, data (samples generation process determines the algorithms by using both, parametric and nonparametric bootstrap techniques. Resampled efficiency provides the solution to use uncertain information without the need for constrains in portfolio optimization. Parametric bootstrap process starts with a parametric model specification, where we apply Capital Asset Pricing Model. After the estimation of specified model, the series of residuals are used for resampling process. On the other hand, nonparametric bootstrap divides series of price returns into the new series of blocks containing previous determined number of consecutive price returns. This procedure enables smooth resampling process and preserves the original structure of data series.
Frey, Thorsten
2014-01-01
Due to the growing importance of IT-based innovations, contemporary firms face an excessive number of proposals for IT projects. As typically only a fraction of these projects can be implemented with the given capacity, IT project portfolio management as a relatively new discipline has received growing attention in research and practice in recent years.?Thorsten Frey demonstrates how companies are struggling to find the right balance between local autonomy and central overview about all projects in the organization. In this context, impacts of different contextual factors on the design of governance arrangements for IT project portfolio management are demonstrated. Moreover, consequences of the use of different organizational designs are analyzed. The author presents insights from a qualitative empirical study as well as a simulative approach.
Numerical approach to optimal portfolio in a power utility regime-switching model
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.
Giulio PALOMBA
2006-01-01
In a typical tactical asset allocation set up managers generally make their investment decisions by inserting private information in an optimisation mechanism used to beat a benchmark portfolio; in this context the sole approach a' la Markowitz (1959) does not use all the available information about expected excess return and especially it does not take two main factors into account: first, asset returns often show changes in volatility, and second, the manager's private information plays no ...
Mahmood Hashemian
2013-07-01
Full Text Available The purpose of this study was to investigate the impact of portfolio assessment as a process-oriented mechanism on the autonomy of Iranian advanced EFL learners. A particular concern was to examine the potential effect of gender on portfolio assessment by taking the learners’ writing ability into account. The participants were 80 male and female advanced EFL learners to whom the Learner Autonomy Questionnaire (Kashefian, 2002 was administered to check their homogeneity prior to the study in terms of autonomy; a truncated form of a TOEFL test was also given to the participants to assess their language proficiency. The participants were then randomly divided into 4 groups: 2 experimental groups (20 females in class A and 20 males in class B and 2 control groups (20 females in class C and 20 males in class D. The portfolio assessment was integrated into the experimental groups to explore whether and to what extent their autonomy might enhance and also to investigate the possible effect of gender on portfolio assessment in writing ability. The portfolio assessment was based on the classroom portfolio model adopted from Hamp-Lyons and Condon (2000, consisting of 3 procedures: collection, selection, and reflection. In contrast, the control groups received the traditional assessment of writing. The data were analyzed using 2 independent samples t tests, mean, and the effect size. The results showed that the portfolio procedures considerably improved the autonomy of the participants. Also, gender had no impact on portfolio assessment.
Portfolio optimization retail investor
I. А. Kiseleva
2016-01-01
Full Text Available The article notes that the task of the investor's risk management is to, on the one hand, as much as possible to strive to achieve the criterion of risk level, and on the other hand, in any case not exceed it. Since the domestic theory of risk management is under development, the problem of the optimal ratio of "risk-income" becomes now of particular relevance. This article discusses the different distribution areas of the private investor in order to obtain the maximum profit. The analysis showed us the overall economic and political system of the country, as well as the legislative provision of guarantees to the investor. To obtain sufficient income and reduce losses it is important to maintain the optimum value found between the amount of the investor's risk and capital transactions. Model of optimal placement of funds led to the conclusion about inexpediency strong increase in the diversification of the investment portfolio (more than 10 different types of assets in the portfolio, since it increases the complexity of its practical form, while the portfolio characteristics are improved significantly. It is concluded that it is impossible to increase revenue without increasing the risk or reduce risk without reducing income. The analysis shows that there is no single best asset portfolio. It is impossible to increase revenue without increasing the risk or reduce risk without reducing income. Possible combination of the "riskincome" will depend on the objective function. Most diversified and bringing the best return per unit of risk, is a portfolio that contains the most risky assets.
Halstead, John B
2006-01-01
.... The research uses a combination of statistical learning, feature selection methods, and multivariate statistics to determine the better prediction function approximation with features obtained...
Asset Allocation and Optimal Contract for Delegated Portfolio Management
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.
Robust Portfolio Optimization Using Pseudodistances.
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.
Optimal Investment Under Transaction Costs: A Threshold Rebalanced Portfolio Approach
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.
Information Acquisition and Portfolio Performance
Guiso, Luigi; Jappelli, Tullio
2006-01-01
Rational investors perceive correctly the value of financial information. Investment in information is therefore rewarded with a higher Sharpe ratio. Overconfident investors overstate the quality of their own information, and thus attain a lower Sharpe ratio. We contrast the implications of the two models using a unique survey of customers of an Italian leading bank with portfolio data and measures of financial information. We find that the portfolio Sharpe ratio is negatively associated with...
Parametric Portfolio Policies with Common Volatility Dynamics
Ergemen, Yunus Emre; Taamouti, Abderrahim
A parametric portfolio policy function is considered that incorporates common stock volatility dynamics to optimally determine portfolio weights. Reducing dimension of the traditional portfolio selection problem significantly, only a number of policy parameters corresponding to first- and second......-order characteristics are estimated based on a standard method-of-moments technique. The method, allowing for the calculation of portfolio weight and return statistics, is illustrated with an empirical application to 30 U.S. industries to study the economic activity before and after the recent financial crisis....
Universal portfolios in stochastic portfolio theory
Wong, Ting-Kam Leonard
2015-01-01
Consider a family of portfolio strategies with the aim of achieving the asymptotic growth rate of the best one. The idea behind Cover's universal portfolio is to build a wealth-weighted average which can be viewed as a buy-and-hold portfolio of portfolios. When an optimal portfolio exists, the wealth-weighted average converges to it by concentration of wealth. Working under a discrete time and pathwise setup, we show under suitable conditions that the distribution of wealth in the family sati...
An Empirical Exploration of the Antecedents and Outcomes of NPD Portfolio Success
Kester, L.; Hultink, H.J.; Griffin, A.
2013-01-01
The manuscript first combines theory and previous empirical findings to build a model of new product development portfolio success. Because relationships between product development portfolio decision-making effectiveness, portfolio success and firm-level success have not previously been
Welsh, Richard; Hall, Michelle
2018-01-01
Context: Given the growing popularity of the portfolio management model (PMM) as a method of improving education, it is important to examine how these market-based reforms are sustained over time and how the politics of sustaining this model have substantial policy implications. Purpose of Study: The purpose of this article is to examine important…
Model selection in periodic autoregressions
Ph.H.B.F. Franses (Philip Hans); R. Paap (Richard)
1994-01-01
textabstractThis paper focuses on the issue of period autoagressive time series models (PAR) selection in practice. One aspect of model selection is the choice for the appropriate PAR order. This can be of interest for the valuation of economic models. Further, the appropriate PAR order is important
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.
Esquível, Manuel L.; Fernandes, José Moniz; Guerreiro, Gracinda R.
2016-06-01
We introduce a schematic formalism for the time evolution of a random population entering some set of classes and such that each member of the population evolves among these classes according to a scheme based on a Markov chain model. We consider that the flow of incoming members is modeled by a time series and we detail the time series structure of the elements in each of the classes. We present a practical application to data from a credit portfolio of a Cape Verdian bank; after modeling the entering population in two different ways - namely as an ARIMA process and as a deterministic sigmoid type trend plus a SARMA process for the residues - we simulate the behavior of the population and compare the results. We get that the second method is more accurate in describing the behavior of the populations when compared to the observed values in a direct simulation of the Markov chain.
Simple Models for Model-based Portfolio Load Balancing Controller Synthesis
Edlund, Kristian Skjoldborg; Mølbak, Tommy; Bendtsen, Jan Dimon
2010-01-01
of generation units existing in an electrical power supply network, for instance in model-based predictive control or declarative control schemes. We focus on the effectuators found in the Danish power system. In particular, the paper presents models for boiler load, district heating, condensate throttling...
Energy technology R&D portfolio management: Modeling uncertain returns and market diffusion
Bistline, John E.
2016-01-01
Highlights: • Analyzes energy R&D decisions with uncertainty in research outcomes and markets. • R&D is shown to be more valuable in second-best planning and policy environments. • Deterministic R&D approaches likely undervalue the optionality of technologies. - Abstract: The allocation of research and development (R&D) funds across a portfolio of programs must simultaneously consider uncertainty from research outcomes and from market acceptance of the resulting technologies. We introduce a stochastic R&D portfolio management framework for addressing both sources of uncertainty and present numerical results for energy technology R&D strategy under uncertainties in climate policy and natural gas prices. Numerical experiments indicate that R&D may be more valuable in second-best planning environments where decision-makers use expected-value approaches, and recourse investments occur after R&D has reduced costs. We also find that deterministic R&D valuation approaches likely overestimate the expected value of R&D success but undervalue the optionality and hedging potential of technologies relative to sequential decision-making approaches under uncertainty. The results also highlight the role of R&D in second-best policy environments.
Reflection during Portfolio-Based Conversations
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…
Bogiages, Christopher A.; Lotter, Christine
2011-01-01
In their research, scientists generate, test, and modify scientific models. These models can be shared with others and demonstrate a scientist's understanding of how the natural world works. Similarly, students can generate and modify models to gain a better understanding of the content, process, and nature of science (Kenyon, Schwarz, and Hug…
Martin Llorente, F.
1990-01-01
The models of atmospheric pollutants dispersion are based in mathematic algorithms that describe the transport, diffusion, elimination and chemical reactions of atmospheric contaminants. These models operate with data of contaminants emission and make an estimation of quality air in the area. This model can be applied to several aspects of atmospheric contamination
A CONCEPTUAL MODEL FOR IMPROVED PROJECT SELECTION AND PRIORITISATION
P. J. Viljoen
2012-01-01
Full Text Available
ENGLISH ABSTRACT: Project portfolio management processes are often designed and operated as a series of stages (or project phases and gates. However, the flow of such a process is often slow, characterised by queues waiting for a gate decision and by repeated work from previous stages waiting for additional information or for re-processing. In this paper the authors propose a conceptual model that applies supply chain and constraint management principles to the project portfolio management process. An advantage of the proposed model is that it provides the ability to select and prioritise projects without undue changes to project schedules. This should result in faster flow through the system.
AFRIKAANSE OPSOMMING: Prosesse om portefeuljes van projekte te bestuur word normaalweg ontwerp en bedryf as ’n reeks fases en hekke. Die vloei deur so ’n proses is dikwels stadig en word gekenmerk deur toue wat wag vir besluite by die hekke en ook deur herwerk van vorige fases wat wag vir verdere inligting of vir herprosessering. In hierdie artikel word ‘n konseptuele model voorgestel. Die model berus op die beginsels van voorsieningskettings sowel as van beperkingsbestuur, en bied die voordeel dat projekte geselekteer en geprioritiseer kan word sonder onnodige veranderinge aan projekskedules. Dit behoort te lei tot versnelde vloei deur die stelsel.
Estimating risk of foreign exchange portfolio: Using VaR and CVaR based on GARCH-EVT-Copula model
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.
Correlation risk and optimal portfolio choice
Buraschi, Andrea; Porchia, Paolo; Trojani, Fabio
2010-01-01
We develop a new framework for multivariate intertemporal portfolio choice that allows us to derive optimal portfolio implications for economies in which the degree of correlation across industries, countries, or asset classes is stochastic. Optimal portfolios include distinct hedging components against both stochastic volatility and correlation risk. We find that the hedging demand is typically larger than in univariate models, and it includes an economically significant covariance hedging...
Asset Attribution Stability and Portfolio Construction: An Educational Example
Chong, James T.; Jennings, William P.; Phillips, G. Michael
2014-01-01
This paper illustrates how a third statistic from asset pricing models, the R-squared statistic, may have information that can help in portfolio construction. Using a traditional CAPM model in comparison to an 18-factor Arbitrage Pricing Style Model, a portfolio separation test is conducted. Portfolio returns and risk metrics are compared using…
Schmidt-Eisenlohr, F.; Puñal, O.; Klagges, K.; Kirsche, M.
Apart from the general issue of modeling the channel, the PHY and the MAC of wireless networks, there are specific modeling assumptions that are considered for different systems. In this chapter we consider three specific wireless standards and highlight modeling options for them. These are IEEE 802.11 (as example for wireless local area networks), IEEE 802.16 (as example for wireless metropolitan networks) and IEEE 802.15 (as example for body area networks). Each section on these three systems discusses also at the end a set of model implementations that are available today.
Memmel, Christoph; Wehn, Carsten
2005-01-01
The Value at Risk of a portfolio differs from the sum of the Values at Risk of the portfolio's components. In this paper, we analyze the problem of how a single economic risk figure for the Value at Risk of a hypothetical portfolio composed of different commercial banks might be obtained for a supervisor. Using the daily profits and losses and the daily Value at Risk figures of twelve German banks for the period from 2001 to 2003, we estimate the Value at Risk of the entire portfolio. We assu...
Charles Nkeki
2013-11-01
Full Text Available This paper examines a mean-variance portfolio selection problem with stochastic salary and inflation protection strategy in the accumulation phase of a defined contribution (DC pension plan. The utility function is assumed to be quadratic. It was assumed that the flow of contributions made by the PPM are invested into a market that is characterized by a cash account, an inflation-linked bond and a stock. In this paper, inflationlinked bond is traded and used to hedge inflation risks associated with the investment. The aim of this paper is to maximize the expected final wealth and minimize its variance. Efficient frontier for the three classes of assets (under quadratic utility function that will enable pension plan members (PPMs to decide their own wealth and risk in their investment profile at retirement was obtained.
Launch vehicle selection model
Montoya, Alex J.
1990-01-01
Over the next 50 years, humans will be heading for the Moon and Mars to build scientific bases to gain further knowledge about the universe and to develop rewarding space activities. These large scale projects will last many years and will require large amounts of mass to be delivered to Low Earth Orbit (LEO). It will take a great deal of planning to complete these missions in an efficient manner. The planning of a future Heavy Lift Launch Vehicle (HLLV) will significantly impact the overall multi-year launching cost for the vehicle fleet depending upon when the HLLV will be ready for use. It is desirable to develop a model in which many trade studies can be performed. In one sample multi-year space program analysis, the total launch vehicle cost of implementing the program reduced from 50 percent to 25 percent. This indicates how critical it is to reduce space logistics costs. A linear programming model has been developed to answer such questions. The model is now in its second phase of development, and this paper will address the capabilities of the model and its intended uses. The main emphasis over the past year was to make the model user friendly and to incorporate additional realistic constraints that are difficult to represent mathematically. We have developed a methodology in which the user has to be knowledgeable about the mission model and the requirements of the payloads. We have found a representation that will cut down the solution space of the problem by inserting some preliminary tests to eliminate some infeasible vehicle solutions. The paper will address the handling of these additional constraints and the methodology for incorporating new costing information utilizing learning curve theory. The paper will review several test cases that will explore the preferred vehicle characteristics and the preferred period of construction, i.e., within the next decade, or in the first decade of the next century. Finally, the paper will explore the interaction
Optimisation of the securities portfolio as a part of the risk management process
Srečko Devjak
2004-01-01
Full Text Available Securities of Slovene companies are listed at the Ljubljana Stock Exchange. Market capitalisation at the Ljubljana Stock Exchange has been growing since 1996 due to new listings of equities. On the basis of financial data time series for listed equities, the financial investor can calculate a risk for each individual security with a selected risk measure and can determine an optimal portfolio, subject to selected constraints. In this paper, we shall consequently determine an optimal portfolio of equities for the financial investor, investing his assets only in selected equities listed at the Ljubljana Stock Exchange. Selecting an appropriate risk measure is especially important for a commercial bank in a risk management process. Commercial banks can use internal models in the risk management process and for the purpose of capital charges as well. An optimal portfolio will be calculated, using a non-linear mathematical model.
Marchenko, Yulia V.
2012-03-01
Sample selection arises often in practice as a result of the partial observability of the outcome of interest in a study. In the presence of sample selection, the observed data do not represent a random sample from the population, even after controlling for explanatory variables. That is, data are missing not at random. Thus, standard analysis using only complete cases will lead to biased results. Heckman introduced a sample selection model to analyze such data and proposed a full maximum likelihood estimation method under the assumption of normality. The method was criticized in the literature because of its sensitivity to the normality assumption. In practice, data, such as income or expenditure data, often violate the normality assumption because of heavier tails. We first establish a new link between sample selection models and recently studied families of extended skew-elliptical distributions. Then, this allows us to introduce a selection-t (SLt) model, which models the error distribution using a Student\\'s t distribution. We study its properties and investigate the finite-sample performance of the maximum likelihood estimators for this model. We compare the performance of the SLt model to the conventional Heckman selection-normal (SLN) model and apply it to analyze ambulatory expenditures. Unlike the SLNmodel, our analysis using the SLt model provides statistical evidence for the existence of sample selection bias in these data. We also investigate the performance of the test for sample selection bias based on the SLt model and compare it with the performances of several tests used with the SLN model. Our findings indicate that the latter tests can be misleading in the presence of heavy-tailed data. © 2012 American Statistical Association.
HEURISTIC APPROACHES FOR PORTFOLIO OPTIMIZATION
Manfred Gilli, Evis Kellezi
2000-01-01
The paper first compares the use of optimization heuristics to the classical optimization techniques for the selection of optimal portfolios. Second, the heuristic approach is applied to problems other than those in the standard mean-variance framework where the classical optimization fails.
Lafontaine, J.; Hay, L.; Markstrom, S. L.
2016-12-01
The United States Geological Survey (USGS) has developed a National Hydrologic Model (NHM) to support coordinated, comprehensive and consistent hydrologic model development, and facilitate the application of hydrologic simulations within the conterminous United States (CONUS). As many stream reaches in the CONUS are either not gaged, or are substantially impacted by water use or flow regulation, ancillary information must be used to determine reasonable parameter estimations for streamflow simulations. Hydrologic models for 1,576 gaged watersheds across the CONUS were developed to test the feasibility of improving streamflow simulations linking physically-based hydrologic models with remotely-sensed data products (i.e. snow water equivalent). Initially, the physically-based models were calibrated to measured streamflow data to provide a baseline for comparison across multiple calibration strategy tests. In addition, not all ancillary datasets are appropriate for application to all parts of the CONUS (e.g. snow water equivalent in the southeastern U.S., where snow is a rarity). As it is not expected that any one data product or model simulation will be sufficient for representing hydrologic behavior across the entire CONUS, a systematic evaluation of which data products improve hydrologic simulations for various regions across the CONUS was performed. The resulting portfolio of calibration strategies can be used to guide selection of an appropriate combination of modeled and measured information for hydrologic model development and calibration. In addition, these calibration strategies have been developed to be flexible so that new data products can be assimilated. This analysis provides a foundation to understand how well models work when sufficient streamflow data are not available and could be used to further inform hydrologic model parameter development for ungaged areas.
Ng, Curtise K C; White, Peter; McKay, Janice C
2009-04-01
Increasingly, the use of web database portfolio systems is noted in medical and health education, and for continuing professional development (CPD). However, the functions of existing systems are not always aligned with the corresponding pedagogy and hence reflection is often lost. This paper presents the development of a tailored web database portfolio system with Picture Archiving and Communication System (PACS) connectivity, which is based on the portfolio pedagogy. Following a pre-determined portfolio framework, a system model with the components of web, database and mail servers, server side scripts, and a Query/Retrieve (Q/R) broker for conversion between Hypertext Transfer Protocol (HTTP) requests and Q/R service class of Digital Imaging and Communication in Medicine (DICOM) standard, is proposed. The system was piloted with seventy-seven volunteers. A tailored web database portfolio system (http://radep.hti.polyu.edu.hk) was developed. Technological arrangements for reinforcing portfolio pedagogy include popup windows (reminders) with guidelines and probing questions of 'collect', 'select' and 'reflect' on evidence of development/experience, limitation in the number of files (evidence) to be uploaded, the 'Evidence Insertion' functionality to link the individual uploaded artifacts with reflective writing, capability to accommodate diversity of contents and convenient interfaces for reviewing portfolios and communication. Evidence to date suggests the system supports users to build their portfolios with sound hypertext reflection under a facilitator's guidance, and with reviewers to monitor students' progress providing feedback and comments online in a programme-wide situation.
Portfolio Optimization of Nanomaterial Use in Clean Energy Technologies.
Moore, Elizabeth A; Babbitt, Callie W; Gaustad, Gabrielle; Moore, Sean T
2018-04-03
While engineered nanomaterials (ENMs) are increasingly incorporated in diverse applications, risks of ENM adoption remain difficult to predict and mitigate proactively. Current decision-making tools do not adequately account for ENM uncertainties including varying functional forms, unique environmental behavior, economic costs, unknown supply and demand, and upstream emissions. The complexity of the ENM system necessitates a novel approach: in this study, the adaptation of an investment portfolio optimization model is demonstrated for optimization of ENM use in renewable energy technologies. Where a traditional investment portfolio optimization model maximizes return on investment through optimal selection of stock, ENM portfolio optimization maximizes the performance of energy technology systems by optimizing selective use of ENMs. Cumulative impacts of multiple ENM material portfolios are evaluated in two case studies: organic photovoltaic cells (OPVs) for renewable energy and lithium-ion batteries (LIBs) for electric vehicles. Results indicate ENM adoption is dependent on overall performance and variance of the material, resource use, environmental impact, and economic trade-offs. From a sustainability perspective, improved clean energy applications can help extend product lifespans, reduce fossil energy consumption, and substitute ENMs for scarce incumbent materials.
Robust Active Portfolio Management
Erdogan, E; Goldfarb, D; Iyengar, G
2006-01-01
... on the portfolio beta, and limits on cash and industry exposure. We show that the optimal portfolios can be computed by solving second-order cone programs -- a class of optimization problems with a worst case complexity (i.e...
Minimum Variance Portfolios in the Brazilian Equity Market
Alexandre Rubesam
2013-03-01
Full Text Available We investigate minimum variance portfolios in the Brazilian equity market using different methods to estimate the covariance matrix, from the simple model of using the sample covariance to multivariate GARCH models. We compare the performance of the minimum variance portfolios to those of the following benchmarks: (i the IBOVESPA equity index, (ii an equally-weighted portfolio, (iii the maximum Sharpe ratio portfolio and (iv the maximum growth portfolio. Our results show that the minimum variance portfolio has higher returns with lower risk compared to the benchmarks. We also consider long-short 130/30 minimum variance portfolios and obtain similar results. The minimum variance portfolio invests in relatively few stocks with low βs measured with respect to the IBOVESPA index, being easily replicable by individual and institutional investors alike.
Managing R&D Alliance Portfolios
Engel Nielsen, Lars; Mahnke, Volker
2003-01-01
be observed in several companies engaged in the cross section of telecommunication and mobile technology where increased complexity magnifies managerial challenges. Drawing on modern portfolio theory, this paper offers a model for managing portfolios of R&D alliances. In particular, an analysis...
Essays on intertemporal consumption and portfolio choice
van Bilsen, Servaas
2015-01-01
This dissertation consists of two parts, preceded by an introductory chapter. Part I (Chapters 2, 3 and 4) considers optimal consumption and portfolio choice using preference models. Chapter 2 analyzes optimal consumption and portfolio choice under loss aversion and endogenous updating of the
Predictors and Portfolios Over the Life Cycle
Kraft, Holger; Munk, Claus; Weiss, Farina
In a calibrated consumption-portfolio model with stock, housing, and labor income predictability, we evaluate the welfare effects of predictability on life-cycle consumption-portfolio choice. We compare skilled investors who are able to take advantage of all sources of predictability with unskilled...
Optimal Portfolio Choice with Wash Sale Constraints
Astrup Jensen, Bjarne; Marekwica, Marcel
2011-01-01
We analytically solve the portfolio choice problem in the presence of wash sale constraints in a two-period model with one risky asset. Our results show that wash sale constraints can heavily affect portfolio choice of investors with unrealized losses. The trading behavior of such investors...
Optimization of the bank's operating portfolio
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.
ALPHA-BETA SEPARATION PORTFOLIO STRATEGIES FOR ISLAMIC FINANCE
Valentyn Khokhlov
2016-01-01
The purpose of this paper is to develop a mathematical alpha-beta separation model that can be used to create a core-satellite portfolio management strategy that complies with the principles of Islamic finance. Methodology. Core-satellite portfolio construction methodology is used to implement the alpha-beta separation approach, where the core part of the portfolio is managed using the tracking error minimization strategy, and the satellite part of the portfolio is managed using the mean-vari...
Dynamic Portfolio Choice with Frictions
Garleanu, Nicolae; Heje Pedersen, Lasse
2016-01-01
We show how portfolio choice can be modeled in continuous time with transitory and persistent transaction costs, multiple assets, multiple signals predicting returns, and general signal dynamics. The objective function is derived from the limit of discrete-time models with endogenous transaction...
Online Learning of Commission Avoidant Portfolio Ensembles
Uziel, Guy; El-Yaniv, Ran
2016-01-01
We present a novel online ensemble learning strategy for portfolio selection. The new strategy controls and exploits any set of commission-oblivious portfolio selection algorithms. The strategy handles transaction costs using a novel commission avoidance mechanism. We prove a logarithmic regret bound for our strategy with respect to optimal mixtures of the base algorithms. Numerical examples validate the viability of our method and show significant improvement over the state-of-the-art.
A Risk-Sensitive Portfolio Optimization Problem with Fixed Incomes Securities
Goel, Mayank; Kumar, K. Suresh
2007-01-01
We discuss a class of risk-sensitive portfolio optimization problems. We consider the portfolio optimization model investigated by Nagai in 2003. The model by its nature can include fixed income securities as well in the portfolio. Under fairly general conditions, we prove the existence of optimal portfolio in both finite and infinite horizon problems.
Kai Wu; Nagurney, A.; University of Massachusetts, Amherst, MA; Zugang Liu; Stranlund, J.K.
2006-01-01
Global climate change and fuel security risks have encouraged international and regional adoption of pollution/carbon taxes. A major portion of such policy interventions is directed at the electric power industry with taxes applied according to the type of fuel used by the power generators in their power plants. This paper proposes an electric power supply chain network model that captures the behavior of power generators faced with a portfolio of power plant options and subject to pollution taxes. We demonstrate that this general model can be reformulated as a transportation network equilibrium model with elastic demands and qualitatively analyzed and solved as such. The connections between these two different modeling schemas is done through finite-dimensional variational inequality theory. The numerical examples illustrate how changes in the pollution/carbon taxes affect the equilibrium electric power supply chain network production outputs, the transactions between the various decision-makers the demand market prices, as well as the total amount of carbon emissions generated. (author)
Characklis, G. W.; Ramsey, J.
2004-12-01
Water scarcity has become a reality in many areas as a result of population growth, fewer available sources, and reduced tolerance for the environmental impacts of developing the new supplies that do exist. As a result, successfully managing future water supply risk will become more dependent on coordinating the use of existing resources. Toward that end, flexible supply strategies that can rapidly respond to hydrologic variability will provide communities with increasing economic advantages, particularly if the frequency of more extreme events (e.g., drought) increases due to global climate change. Markets for established commodities (e.g., oil, gas) often provide a framework for efficiently responding to changes in supply and demand. Water markets, however, have remained relatively crude, with most transactions involving permanent transfers and long regulatory processes. Recently, interest in the use of flexible short-term transfers (e.g., leases, options) has begun to motivate consideration of more sophisticated strategies for managing supply risk, strategies similar to those used in more mature markets. In this case, communities can benefit from some of the advantages that water enjoys over other commodities, in particular, the ability to accurately characterize the stochastic nature of supply and demand through hydrologic modeling. Hydrologic-economic models are developed for two different water scarce regions supporting active water markets: Edward Aquifer and Lower Rio Grande Valley. These models are used to construct portfolios of water supply transfers (e.g., permanent transfers, options, and spot leases) that minimize the cost of meeting a probabilistic reliability constraint. Real and simulated spot price distributions allow each type of transfer to be priced in a manner consistent with financial theory (e.g., Black-Scholes). Market simulations are integrated with hydrologic models such that variability in supply and demand are linked with price behavior
Marchenko, Yulia V.; Genton, Marc G.
2012-01-01
for sample selection bias based on the SLt model and compare it with the performances of several tests used with the SLN model. Our findings indicate that the latter tests can be misleading in the presence of heavy-tailed data. © 2012 American Statistical
Performance of finite order distribution-generated universal portfolios
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.
Marisa Padovani
2010-01-01
Full Text Available Escolher dentre dezenas ou centenas de alternativas, aquelas que deverão compor o portfólio de projetos de uma organização e com qual prioridade, é um problema de decisão multicritério complexo. Este trabalho teve como foco duas etapas críticas da gestão de portfólio: a seleção de projetos e a alocação de recursos. A abordagem metodológica utilizada foi a pesquisa-ação, partindo-se de uma estrutura teórico-conceitual que integra os métodos AHP (Analytic Hierarchy Process e programação inteira em um modelo híbrido. A pesquisa de campo foi desenvolvida em uma empresa do setor químico, escolhida como unidade de análise, na qual foi implementado o modelo híbrido, de tal forma que os diferentes cenários propostos fossem comparados com o cenário real da organização estudada. Pretendeu-se avaliar a importância e utilidade desse modelo no auxílio à tomada de decisões relacionadas à seleção, priorização e alocação de recursos em projetos. Como principal resultado obtido, verificou-se que o uso do modelo contribui para o alinhamento estratégico, melhora a troca de informações entre os tomadores de decisão da empresa; possibilita a simulação de cenários estratégicos em tempo real e a verificação do impacto na carteira de projetos em execução; prioriza os projetos de forma justificável e estruturada; e permite a alocação de recursos baseada em prioridades.Among dozens or hundreds of alternatives, choosing those which should make up the projects portfolio of an organization and which priority level is a complex multi-criteria decision matter. This work aims to apply a management model of projects portfolio, using the AHP (Analytic Hierarchy Process method and an integrated integer program. Another purpose is to validate and evaluate the importance and use of the model to help the decision-making related to the selection, prioritization and balance of projects. Thus, such a model was applied to select and
Ivan Ricardo Gartner
2012-08-01
Full Text Available Faced with so many risk modeling alternatives in portfolio optimization, several questions arise regarding their legitimacy, utility and applicability. In particular, a question arises involving the adherence of the alternative models with regard to the basic presupposition of Markowitz's classical model, with regard to the concept of diversification as a means of controlling the relationship between risk and return within a process of optimization. In this context, the aim of this article is to explore the risk-differentiated configurations that entropy can provide, from the point of view of the repercussions that these have on the degree of diversification and on portfolios performance. The reach of this objective requires that a comparative analysis is made between models that include entropy in their formulation and the classic Markowitz model. In order to contribute to this debate, this article proposes that adaptations are made to the models of relative minimum entropy and of maximum entropy, so that these can be applied to investment portfolio optimizations. The comparative analysis was based on performance indicators and on a ratio of the degree of portfolio diversification. The portfolios were formed by considering a sample of fourteen assets that compose the IBOVESPA, which were projected during the period from January 2007 to December 2009, and took into account the matrices of covariance that were formed as from January 1999. When comparing the Markowitz model with two models that were constructed to represent new risk configurations based on entropy optimization, the present study concluded that the first model was far superior to the others. Not only did the Markowitz model present better accumulated nominal yields, it also presented a far greater predictive efficiency and better effective performance, when considering the trade-off between risk and return. However, with regards to diversification, the Markowitz model concentrated
Application of Project Portfolio Management
Pankowska, Malgorzata
The main goal of the chapter is the presentation of the application project portfolio management approach to support development of e-Municipality and public administration information systems. The models of how people publish and utilize information on the web have been transformed continually. Instead of simply viewing on static web pages, users publish their own content through blogs and photo- and video-sharing slides. Analysed in this chapter, ICT (Information Communication Technology) projects for municipalities cover the mixture of the static web pages, e-Government information systems, and Wikis. So, for the management of the ICT projects' mixtures the portfolio project management approach is proposed.
Comprehensive Education Portfolio with a Career Focus
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…
Concurrent credit portfolio losses.
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.
Mean-Variance portfolio optimization when each asset has individual uncertain exit-time
Reza Keykhaei
2016-12-01
Full Text Available The standard Markowitz Mean-Variance optimization model is a single-period portfolio selection approach where the exit-time (or the time-horizon is deterministic. In this paper we study the Mean-Variance portfolio selection problem with uncertain exit-time when each has individual uncertain xit-time, which generalizes the Markowitz's model. We provide some conditions under which the optimal portfolio of the generalized problem is independent of the exit-times distributions. Also, it is shown that under some general circumstances, the sets of optimal portfolios in the generalized model and the standard model are the same.
Reinforcement Learning in Repeated Portfolio Decisions
Diao, Linan; Rieskamp, Jörg
2011-01-01
How do people make investment decisions when they receive outcome feedback? We examined how well the standard mean-variance model and two reinforcement models predict people's portfolio decisions. The basic reinforcement model predicts a learning process that relies solely on the portfolio's overall return, whereas the proposed extended reinforcement model also takes the risk and covariance of the investments into account. The experimental results illustrate that people reacted sensitively to...
R functions development for stockPortfolio package
Luo, Rui
2013-01-01
Modern portfolio theory is a statistical framework to allocate investment assets properly, with the aim of reducing risk by diversification. In the past decades, a variety of index and group models (with different covariance assumption) have been proposed to optimize the portfolio, including Single Index Model, Constant Correlation Model, Multi-Group Model, and Multi-Index Model. An R package "stockPortfolio" is developed by Drs. Christou and Diez, and fully implemented Single Index Model, Co...
Turnover activity in wealth portfolios
Castaldi, C.; Milakovic, M.
2007-01-01
We examine several subsets of the wealthiest individuals in the US and the UK that are compiled by Forbes Magazine and the Sunday Times. Since these are named subsets, we can calculate the returns to wealth portfolios, and calibrate a statistical equilibrium model of wealth distribution that
Turnover activity in wealth portfolios
Castaldi, Carolina; Milakovic, Mishael
We examine several subsets of the wealthiest individuals in the US and the UK that are compiled by Forbes Magazine and the Sunday Times. Since these are named subsets, we can calculate the returns to wealth portfolios, and calibrate a statistical equilibrium model of wealth distribution that
Quantifying the role of personal management style in the success of investment portfolios
E.A. Wagenaar
2014-01-01
Full Text Available It is extremely difficult to quantify the effect of different management styles of portfolio managers upon the success of their portfolios. Various mathematical models in the literature attempt to predict the risk and returns of portfolios according to changes in the economic arena, but these models usually do not take into account the personal styles of portfolio managers. The aim of this paper is a modest attempt at quantifying the effect of different managerial styles upon decisions regarding portfolios. This is accomplished by the formulation of a mathematical performance index that portrays the influence of a portfolio manager's personal and managerial characteristics on the success of his portfolio.
Byrd, Kristin B.; Kreitler, Jason R.; Labiosa, William B.
2011-01-01
The U.S. Geological Survey Puget Sound Ecosystem Portfolio Model (PSEPM) is a decision-support tool that uses scenarios to evaluate where, when, and to what extent future population growth, urban growth, and shoreline development may threaten the Puget Sound nearshore environment. This tool was designed to be used iteratively in a workshop setting in which experts, stakeholders, and decisionmakers discuss consequences to the Puget Sound nearshore within an alternative-futures framework. The PSEPM presents three possible futures of the nearshore by analyzing three growth scenarios developed out to 2060: Status Quo—continuation of current trends; Managed Growth—adoption of an aggressive set of land-use management policies; and Unconstrained Growth—relaxation of land-use restrictions. The PSEPM focuses on nearshore environments associated with barrier and bluff-backed beaches—the most dominant shoreforms in Puget Sound—which represent 50 percent of Puget Sound shorelines by length. This report provides detailed methodologies for development of three submodels within the PSEPM—the Shellfish Pollution Model, the Beach Armoring Index, and the Recreation Visits Model. Results from the PSEPM identify where and when future changes to nearshore ecosystems and ecosystem services will likely occur within the three growth scenarios. Model outputs include maps that highlight shoreline sections where nearshore resources may be at greater risk from upland land-use changes. The background discussed in this report serves to document and supplement model results displayed on the PSEPM Web site located at http://geography.wr.usgs.gov/pugetSound/.
Antonio Almuedo-Paz
2014-07-01
Full Text Available This study aims to determine the reliability of assessment criteria used for a portfolio at the Andalusian Agency for Healthcare Quality (ACSA. Data: all competences certification processes, regardless of their discipline. Period: 2010-2011. Three types of tests are used: 368 certificates, 17,895 reports and 22,642 clinical practice reports (N = 3,010 candidates. The tests were evaluated in pairs by the ACSA team of raters using two categories: valid and invalid. Results: The percentage agreement in assessments of certificates was 89,9%, while for the reports of clinical practice was 85,1 % and for clinical practice reports was 81,7%. The inter-rater agreement coefficients (kappa ranged from 0,468 to 0,711. Discussion: The results of this study show that the inter-rater reliability of assessments varies from fair to good. Compared with other similar studies, the results put the reliability of the model in a comfortable position. Among the improvements incorporated, progressive automation of evaluations must be highlighted.
A portfolio risk analysis on electricity supply planning
Huang, Y.-H.; Wu, J.-H.
2008-01-01
Conventional electricity planning selects from a range of alternative technologies based on the least-cost method without assessing cost-related risks. The current approach to determining energy generation portfolios creates a preference for fossil fuel. Consequently, this preference results in increased exposure to recent fluctuations in fossil fuel prices, particularly for countries heavily depend on imported energy. This paper applies portfolio theory in conventional electricity planning with Taiwan as a case study. The model objective is to minimize the 'risk-weighted present value of total generation cost'. Both the present value of generating cost and risk (variance of the generating cost) are considered. Risk of generating cost is introduced for volatile fuel prices and uncertainty of technological change and capital cost reduction. The impact of risk levels on the portfolio of power generation technologies is also examined to provide some valuable policy suggestions. Study results indicate that replacing fossil fuel with renewable energy helps reduce generating cost risk. However, due to limited renewable development potential in Taiwan, there is an upper bound of 15% on the maximum share of renewable energy in the generating portfolio. In the meantime, reevaluating the current nuclear energy policy for reduced exposure to fossil fuel price fluctuations is worthwhile
Does asymmetric correlation affect portfolio optimization?
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.
Robust Portfolio Optimization Using Pseudodistances
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
Oudkerk Pool, Andrea; Govaerts, Marjan J B; Jaarsma, Debbie A D C; Driessen, Erik W
2018-05-01
While portfolios are increasingly used to assess competence, the validity of such portfolio-based assessments has hitherto remained unconfirmed. The purpose of the present research is therefore to further our understanding of how assessors form judgments when interpreting the complex data included in a competency-based portfolio. Eighteen assessors appraised one of three competency-based mock portfolios while thinking aloud, before taking part in semi-structured interviews. A thematic analysis of the think-aloud protocols and interviews revealed that assessors reached judgments through a 3-phase cyclical cognitive process of acquiring, organizing, and integrating evidence. Upon conclusion of the first cycle, assessors reviewed the remaining portfolio evidence to look for confirming or disconfirming evidence. Assessors were inclined to stick to their initial judgments even when confronted with seemingly disconfirming evidence. Although assessors reached similar final (pass-fail) judgments of students' professional competence, they differed in their information-processing approaches and the reasoning behind their judgments. Differences sprung from assessors' divergent assessment beliefs, performance theories, and inferences about the student. Assessment beliefs refer to assessors' opinions about what kind of evidence gives the most valuable and trustworthy information about the student's competence, whereas assessors' performance theories concern their conceptualizations of what constitutes professional competence and competent performance. Even when using the same pieces of information, assessors furthermore differed with respect to inferences about the student as a person as well as a (future) professional. Our findings support the notion that assessors' reasoning in judgment and decision-making varies and is guided by their mental models of performance assessment, potentially impacting feedback and the credibility of decisions. Our findings also lend further
Selected Tether Applications Cost Model
Keeley, Michael G.
1988-01-01
Diverse cost-estimating techniques and data combined into single program. Selected Tether Applications Cost Model (STACOM 1.0) is interactive accounting software tool providing means for combining several independent cost-estimating programs into fully-integrated mathematical model capable of assessing costs, analyzing benefits, providing file-handling utilities, and putting out information in text and graphical forms to screen, printer, or plotter. Program based on Lotus 1-2-3, version 2.0. Developed to provide clear, concise traceability and visibility into methodology and rationale for estimating costs and benefits of operations of Space Station tether deployer system.
Systemic risk contributions: a credit portfolio approach
Düllmann, Klaus; Puzanova, Natalia
2011-01-01
We put forward a Merton-type multi-factor portfolio model for assessing banks' contributions to systemic risk. This model accounts for the major drivers of banks' systemic relevance: size, default risk and correlation of banks' assets as a proxy for interconnectedness. We measure systemic risk in terms of the portfolio expected shortfall (ES). Banks' (marginal) risk contributions are calculated based on partial derivatives of the ES in order to ensure a full risk allocation among institutions...
Essays on portfolio choice with Bayesian methods
Kebabci, Deniz
2007-01-01
How investors should allocate assets to their portfolios in the presence of predictable components in asset returns is a question of great importance in finance. While early studies took the return generating process as given, recent studies have addressed issues such as parameter estimation and model uncertainty. My dissertation develops Bayesian methods for portfolio choice - and industry allocation in particular - under parameter and model uncertainty. The first chapter of my dissertation,...
A Comparative Analysis of Ability of Mimicking Portfolios in Representing the Background Factors
Asgharian, Hossein
2004-01-01
Our aim is to give a comparative analysis of ability of different factor mimicking portfolios in representing the background factors. Our analysis contains a cross-sectional regression approach, a time-series regression approach and a portfolio approach for constructing factor mimicking portfolios. The focus of the analysis is the power of mimicking portfolios in the asset pricing models. We conclude that the time series regression approach, with the book-to-market sorted portfolios as the ba...
Does health affect portfolio choice?
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.
Real Time Investments with Adequate Portfolio Theory
Alina Kvietkauskienė
2015-02-01
Full Text Available The objective of this paper is to identify investment decision makingschemes using the adequate portfolio model. This approach can be employed to project investment in stocks, using the opportunities offered by the markets and investor intelligence. It was decided to use adequate portfolio theory for investment decision making, simulation of financial markets, and optimisation of utility function. The main conclusion of article suggests investigating return on individual portfolio level. Real investment is a way to make sure of the soundness of applicable strategies.
Financial Modelling: Where to go? with an illustration for portfolio management
W.G.P.M. Hallerbach (Winfried); J. Spronk (Jaap)
1997-01-01
textabstractThe definition of Financial Modelling chosen by the EURO working group on financial modelling is ‘the development and implementation of tools supporting firms, investors, intermediaries, governments and others in their financial-economic decision making, including the validation of the
Credibilistic multi-period portfolio optimization based on scenario tree
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.
AREVA's nuclear reactors portfolio
Marincic, A.
2009-01-01
A reasonable assumption for the estimated new build market for the next 25 years is over 340 GWe net. The number of prospect countries is growing almost each day. To address this new build market, AREVA is developing a comprehensive portfolio of reactors intended to meet a wide range of power requirements and of technology choices. The EPR reactor is the flagship of the fleet. Intended for large power requirements, the four first EPRs are being built in Finland, France and China. Other countries and customers are in view, citing just two examples: the Usa where the U.S. EPR has been selected as the technology of choice by several U.S utilities; and the United Kingdom where the Generic Design Acceptance process of the EPR design submitted by AREVA and EDF is well under way, and where there is a strong will to have a plant on line in 2017. For medium power ranges, the AREVA portfolio includes a boiling water reactor and a pressurized water reactor which both offer all of the advantages of an advanced plant design, with excellent safety performance and competitive power generation cost: -) KERENA (1250+ MWe), developed in collaboration with several European utilities, and in particular with Eon; -) ATMEA 1 (1100+ MWe), a 3-loop evolutionary PWR which is being developed by AREVA and Mitsubishi. AREVA is also preparing the future and is deeply involved into Gen IV concepts. It has developed the ANTARES modular HTR reactor (pre-conceptual design completed) and is building upon its vast Sodium Fast Reactor experience to take part into the development of the next prototype. (author)
Project Portfolio Management: An Investigation of One Air Force Product Center
Edmunds, Bryan D
2005-01-01
.... This research focuses on the portfolio management (project selection and resource allocation) part of the CTRRP. The purpose of this research effort was to investigate the use of portfolio management within the Air Force...
METHODICAL BASES OF MANAGEMENT OF INSURANCE PORTFOLIO
Serdechna Yulia
2018-01-01
Full Text Available Introduction. Despite the considerable arsenal of developments in the issues of assessing the management of the insurance portfolio remains unresolved. In order to detail, specify and further systematize the indicators for the indicated evaluation, the publications of scientists are analyzed. The purpose of the study is to analyze existing methods by which it is possible to formulate and manage the insurance portfolio in order to achieve its balance, which will contribute to ensuring the financial reliability of the insurance company. Results. The description of the essence of the concept of “management of insurance portfolio”, as the application of actuarial methods and techniques to the combination of various insurance risks offered for insurance or are already part of the insurance portfolio, allowing to adjust the size and structure of the portfolio in order to ensure its financial stability, achievement the maximum level of income of an insurance organization, preservation of the value of its equity and financial security of insurance liabilities. It is determined that the main methods by which the insurer’s insurance portfolio can be formed and managed is the selection of risks; reinsurance operations that ensure diversification of risks; formation and placement of insurance reserves, which form the financial basis of insurance activities. The method of managing an insurance portfolio, which can be both active and passive, is considered. Conclusions. It is determined that the insurance portfolio is the basis on which all the activities of the insurer are based and which determines its financial stability. The combination of methods and technologies applied to the insurance portfolio is a management method that can be both active and passive and has a number of specific methods through which the insurer’s insurance portfolio can be formed and managed. It is substantiated that each insurance company aims to form an efficient and
Portfolio analysis based on the example of Zagreb Stock Exchange
Bogdan, Sinisa; Baresa, Suzana; Ivanovic, Sasa
2010-01-01
In this paper we analyze the portfolio that was selected from the Zagreb Stock Exchange and also try to assess its risks and its future offerings that are relevant in making the decisions about investments. Through the work we will explain the importance of diversification and how the very diversification reduces risk. We will also analyze the systemic risk of individual stocks within the portfolio and the systemic risk of the given portfolio and explain its importance. Through regression ana...
Methods of Choosing an Optimal Portfolio of Projects
Yakovlev, A.; Chernenko, M.
2016-01-01
This paper presents an analysis of existing methods for a portfolio of project optimization. The necessity for their improvement is shown. It is suggested to assess the portfolio of projects on the basis of the amount in the difference between the results and costs during development and implementation of selected projects and the losses caused by non-implementation or delayed implementation of projects that were not included in the portfolio. Consideration of capital and current costs compon...
Woldeyesus, Tibebe Argaw
Water supply constraints can significantly restrict electric power generation, and such constraints are expected to worsen with future climate change. The overarching goal of this thesis is to incorporate stochastic water-climate interactions into electricity portfolio models and evaluate various pathways for water savings in co-managed water-electric utilities. Colorado Springs Utilities (CSU) is used as a case study to explore the above issues. The thesis consists of three objectives: Characterize seasonality of water withdrawal intensity factors (WWIF) for electric power generation and develop a risk assessment framework due to water shortages; Incorporate water constraints into electricity portfolio models and evaluate the impact of varying capital investments (both power generation and cooling technologies) on water use and greenhouse gas emissions; Compare the unit cost and overall water savings from both water and electric sectors in co-managed utilities to facilitate overall water management. This thesis provided the first discovery and characterization of seasonality of WWIF with distinct summertime and wintertime variations of +/-17% compared to the power plant average (0.64gal/kwh) which itself is found to be significantly higher than the literature average (0.53gal/kwh). Both the streamflow and WWIF are found to be highly correlated with monthly average temperature (r-sq = 89%) and monthly precipitation (r-sq of 38%) enabling stochastic simulation of future WWIF under moderate climate change scenario. Future risk to electric power generation also showed the risk to be underestimated significantly when using either the literature average or the power plant average WWIF. Seasonal variation in WWIF along with seasonality in streamflow, electricity demand and other municipal water demands along with storage are shown to be important factors for more realistic risk estimation. The unlimited investment in power generation and/or cooling technologies is also
Cortes, Jordi Magrina; Nizamani, Sarwat; Memon, Nasrullah
2014-01-01
In this paper we present a web-based information system which is a portfolio social network (PSN) that provides solutions to the recruiters and job seekers. The proposed system enables users to create portfolio so that he/she can add his specializations with piece of code if any specifically...
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,…
Hochgürtel, S.
1998-01-01
This thesis presents four topics on households' portfolio choices. Empirically, households do not hold well-diversified wealth portfolios. In particular, they refrain from putting their savings into risky assets. We explore several ways that might help explaining this observation. Using Dutch
Portfolio i erhvervsuddannelserne
2008-01-01
Materialet kombinerer korte film med introducerende tekster og belyser fra forskellige vinkler, hvordan portfolio kan bruges som evalueringsmetode i erhvervsuddannelserne. Udgiver: Undervisningsministeriet Udgivelsessted: Pub.uvm.dk......Materialet kombinerer korte film med introducerende tekster og belyser fra forskellige vinkler, hvordan portfolio kan bruges som evalueringsmetode i erhvervsuddannelserne. Udgiver: Undervisningsministeriet Udgivelsessted: Pub.uvm.dk...
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.
Optimal diversification of the securities portfolio
Валентина Михайловна Андриенко
2016-09-01
Full Text Available The article deals with problems of the theory and methods of forming the optimal portfolio of financial markets. The analytical review of methods in their historical development is given. Recommendations on the use of a particular method depends on the specific conditions are formulated. The classical and alternative methods are considered. The main attention is paid to the analysis of the investment portfolio of derivative securities in B/S-market modelThe article deals with problems of the theory and methods of forming the optimal portfolio of financial markets. The analytical review of methods in their historical development is given. Recommendations on the use of a particular method depends on the specific conditions are formulated. The classical and alternative methods are considered. The main attention is paid to the analysis of the investment portfolio of derivative securities in -market model
Time-varying coefficient estimation in SURE models. Application to portfolio management
Casas, Isabel; Ferreira, Eva; Orbe, Susan
This paper provides a detailed analysis of the asymptotic properties of a kernel estimator for a Seemingly Unrelated Regression Equations model with time-varying coefficients (tv-SURE) under very general conditions. Theoretical results together with a simulation study differentiates the cases...
Bao, T.; Diks, C.; Li, H.
We estimate the CAPM model on European stock market data, allowing for asymmetric and fat-tailed return distributions using independent and identically asymmetric power distributed (IIAPD) innovations. The results indicate that the generalized CAPM with IIAPD errors has desirable properties. It is
An optimization model for natural gas supply portfolios of a power generation company
Jirutitijaroen, Panida; Kim, Sujin; Kittithreerapronchai, Oran; Prina, José
2013-01-01
Highlights: ► An optimization model for daily operation of a natural gas-fired generation company is proposed. ► The model considers uncertainties in electricity price and natural gas price. ► The model is formulated to capture the hedging decisions by the company. ► The solution yields quantities of natural gas, generating schedule and purchasing quantities of electricity. ► Higher profit can be achieved by adapting inventory and production to the actual spot prices of natural gas and electricity. - Abstract: This paper considers a deregulated electricity market environment where a natural gas-fired generation company can engage in different types of contracts to manage its natural gas supply as well as trade on the electricity market. If the contracts are properly designed, they can protect the company from fluctuations in electricity price and demand, at some cost to the company’s expected profit. This reduction in profit can be mitigated by trading on the natural gas and electricity spot markets, but this trading activity may also sometimes result in losses. A stochastic programming model is formulated to capture the hedging decisions made by the company, as well as the interactions between the natural gas and electricity markets. The benefits offered by this approach for profit maximization in a variety of business scenarios, such as the case where the company can hold some amount of gas in storage are studied and presented. It is found that the stochastic model enables the company to optimize the electricity generation schedule and the natural gas consumption, including spot price transactions and gas storage management. Several managerial insights into the natural gas market, natural gas storage, and distribution profit are given
Probabilistic disaggregation model with application to natural hazard risk assessment of portfolios
Custer, Rocco; Nishijima, Kazuyoshi
2012-01-01
In natural hazard risk assessment, a resolution mismatch between hazard data and aggregated exposure data is often observed. A possible solution to this issue is the disaggregation of exposure data to match the spatial resolution of hazard data. Disaggregation models available in literature are usually deterministic and make use of auxiliary indicator, such as land cover, to spatially distribute exposures. As the dependence between auxiliary indicator and disaggregated number of exposures is ...
Testing for structural changes in large portfolios
Posch, Peter N.; Ullmann, Daniel; Wied, Dominik
2015-01-01
Model free tests for constant parameters often fail to detect structural changes in high dimensions. In practice, this corresponds to a portfolio with many assets and a reasonable long time series. We reduce the dimensionality of the problem by looking a compressed panel of time series obtained by cluster analysis and the principal components of the data. Using our methodology we are able to extend a test for a constant correlation matrix from a sub portfolio to whole indices a...
A method for minimum risk portfolio optimization under hybrid uncertainty
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.
Analysis and modeling of a hail event consequences on a building portfolio
Nicolet, Pierrick; Voumard, Jérémie; Choffet, Marc; Demierre, Jonathan; Imhof, Markus; Jaboyedoff, Michel
2014-05-01
North-West Switzerland has been affected by a severe Hail Storm in July 2011, which was especially intense in the Canton of Aargau. The damage cost of this event is around EUR 105 Million only for the Canton of Aargau, which corresponds to half of the mean annual consolidated damage cost of the last 20 years for the 19 Cantons (over 26) with a public insurance. The aim of this project is to benefit from the collected insurance data to better understand and estimate the risk of such event. In a first step, a simple hail event simulator, which has been developed for a previous hail episode, is modified. The geometric properties of the storm is derived from the maximum intensity radar image by means of a set of 2D Gaussians instead of using 1D Gaussians on profiles, as it was the case in the previous version. The tool is then tested on this new event in order to establish its ability to give a fast damage estimation based on the radar image and buildings value and location. The geometrical properties are used in a further step to generate random outcomes with similar characteristics, which are combined with a vulnerability curve and an event frequency to estimate the risk. The vulnerability curve comes from a 2009 event and is improved with data from this event, whereas the frequency for the Canton is estimated from insurance records. In addition to this regional risk analysis, this contribution aims at studying the relation of the buildings orientation with the damage rate. Indeed, it is expected that the orientation of the roof influences the aging of the material by controlling the frequency and amplitude of thaw-freeze cycles, changing then the vulnerability over time. This part is established by calculating the hours of sunshine, which are used to derive the material temperatures. This information is then compared with insurance claims. A last part proposes a model to study the hail impact on a building, by modeling the different equipment on each facade of the
The standard for portfolio management
2017-01-01
The Standard for Portfolio Management – Fourth Edition has been updated to best reflect the current state of portfolio management. It describe the principles that drive accepted good portfolio management practices in today’s organizations. It also expands the description of portfolio management to reflect its relation to organizational project management and the organization.
Multi-Period Portfolio Optimization of Power Generation Assets
Barbara Glensk
2013-01-01
Full Text Available The liberalization and deregulation of the energy industry in the past decades have been significantly affected by changes in the strategies of energy firms. The traditionally used approach of cost minimization was no longer sufficient, risk and market behavior could no longer be ignored and the need for more appropriate optimization methods for uncertain environments was increased. Meanvariance portfolio (MVP theory is one of the more advanced financial methods that has been successfully applied to the energy sector. Unfortunately, this static approach is inadequate for studying multi-stage investment decision problems. The methodology proposed in this paper considering power generation assets is based on the model introduced by Mulvey, who suggests a reallocation approach using the analysis of various scenarios. The adoption of this methodology to power generation assets allows us to capture the impact of variations in the economic and technical parameters considered. The results of our study show that the application of a model for selection of multi-period portfolio can indeed improve the decision making process. Especially for the case of adding new investments to the portfolio mix, this rebalancing model captures new entries very well. (original abstract
Utility portfolio diversification
Griffes, P.H.
1990-01-01
This paper discusses portfolio analysis as a method to evaluate utility supply decisions. Specifically a utility is assumed to increase the value of its portfolio of assets whenever it invests in a new supply technology. This increase in value occurs because the new asset either enhances the return or diversifies the risks of the firm's portfolio of assets. This evaluation method is applied to two supply innovations in the electric utility industry: jointly-owned generating plants and supply contracts with independent power producers (IPPs)
Constant Proportion Portfolio Insurance
Jessen, Cathrine
2014-01-01
on the theme, originally proposed by Fischer Black. In CPPI, a financial institution guarantees a floor value for the “insured” portfolio and adjusts the stock/bond mix to produce a leveraged exposure to the risky assets, which depends on how far the portfolio value is above the floor. Plain-vanilla portfolio...... insurance largely died with the crash of 1987, but CPPI is still going strong. In the frictionless markets of finance theory, the issuer’s strategy to hedge its liability under the contract is clear, but in the real world with transactions costs and stochastic jump risk, the optimal strategy is less obvious...
The Effects of Portfolio Assessment on Writing of EFL Students
Nezakatgoo, Behzad
2011-01-01
The primary focus of this study was to determine the effect of portfolio assessment on final examination scores of EFL students' writing skill. To determine the impact of portfolio-based writing assessment 40 university students who enrolled in composition course were initially selected and divided randomly into two experimental and control…
Can One Portfolio Measure the Six ACGME General Competencies?
Jarvis, Robert M.; O'Sullivan, Patricia S.; McClain, Tina; Clardy, James A.
2004-01-01
Objective: To determine that portfolios, useable by any program, can provide needed evidence of resident performance within the ACGME general competencies. Methods: Eighteen residents constructed portfolios with selected entries from thirteen psychiatric skills. Two raters assessed whether entries reflected resident performance within the general…
Portfolio optimization with skewness and kurtosis
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.
Mario Linares Vásquez
2008-01-01
Full Text Available Selecting an investment portfolio has inspired several models aimed at optimising the set of securities which an in-vesttor may select according to a number of specific decision criteria such as risk, expected return and planning hori-zon. The classical approach has been developed for supporting the two stages of portfolio selection and is supported by disciplines such as econometrics, technical analysis and corporative finance. However, with the emerging field of computational finance, new and interesting techniques have arisen in line with the need for the automatic processing of vast volumes of information. This paper surveys such new techniques which belong to the body of knowledge con-cerning computing and systems engineering, focusing on techniques particularly aimed at producing beliefs regar-ding investment portfolios.
Large deviations and portfolio optimization
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.
US Agency for International Development — PfMS is an implementation of WorkLenz. WorkLenz is USAID's portfolio management system tool. It is a commercially available, off-the-shelf (COTS) package that...
Rodrigo Alves Silva
2017-09-01
Full Text Available This paper aims to show the importance of the use of financial metrics in decision-making of credit scoring models selection. In order to achieve such, we considered an automatic approval system approach and we carried out a performance analysis of the financial metrics on the theoretical portfolios generated by seven credit scoring models based on main statistical learning techniques. The models were estimated on German Credit dataset and the results were analyzed based on four metrics: total accuracy, error cost, risk adjusted return on capital and Sharpe index. The results show that total accuracy, widely used as a criterion for selecting credit scoring models, is unable to select the most profitable model for the company, indicating the need to incorporate financial metrics into the credit scoring model selection process. Keywords Credit risk; Model’s selection; Statistical learning.
Designing Modern Equity Portfolios
Ronald Jean Degen
2011-01-01
This aim of this paper is to describe possible ways of investing in equity; choosing the right stocks(among small-cap, large-cap, value, growth, and foreign) using fundamental analysis, defining their appropriate mix in the portfolios according to the desired return-risk profiles based on Markowitz?s modern portfolio theory, and using technical analysis to buy and sell them.
IT APPLICATIONS PORTFOLIO MANAGEMENT UNDER BUSINESS AND IMPLEMENTATION UNCERTAINTY
Masafumi KOTANI; Junichi IIJIMA
2008-01-01
Corporations need to improve business processes in order to enhance velocity and service levels while reducing their processing costs and differentiating themselves in the face of competition.The levitation of importance beyond support roles has raised IT investment decisions to high priority in chief executive officers'agendas.Corporate planning groups as well as lines of business are increasingly applying techniques of IT applications portfolio management in a more systematic fashion to improve decision-making and resource-allocation processes. Recent advances in software engineering and IT service delivery methodologies have achieved the logical separation of business functions from implementation.This separation has made a new breed of innovative IT project possible with a new project risk structure;the adjustment of portfolio management techniques is appropriate.We present an integrated portfolio management model so that the corporation can focus on organic growth through sources at both the department and top management levels.The research gives clear advice as to how top management can seek economic growth by selecting an entrepreneurial strategic posture,implying a strong risk-taking propensity.By integrating a risk-return model and risk-tolerance paradigm to cope with today's risk structure,overall capabilities can improve the decision process and the corporation's performance as well.The application of the integrated technique to a Japanese manufacturing firm is described.
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
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.
Labiosa, William B.; Bernknopf, Richard; Hearn, Paul; Hogan, Dianna; Strong, David; Pearlstine, Leonard; Mathie, Amy M.; Wein, Anne M.; Gillen, Kevin; Wachter, Susan
2009-01-01
The South Florida Ecosystem Portfolio Model (EPM) prototype is a regional land-use planning Web tool that integrates ecological, economic, and social information and values of relevance to decision-makers and stakeholders. The EPM uses a multicriteria evaluation framework that builds on geographic information system-based (GIS) analysis and spatially-explicit models that characterize important ecological, economic, and societal endpoints and consequences that are sensitive to regional land-use/land-cover (LULC) change. The EPM uses both economics (monetized) and multiattribute utility (nonmonetized) approaches to valuing these endpoints and consequences. This hybrid approach represents a methodological middle ground between rigorous economic and ecological/ environmental scientific approaches. The EPM sacrifices some degree of economic- and ecological-forecasting precision to gain methodological transparency, spatial explicitness, and transferability, while maintaining credibility. After all, even small steps in the direction of including ecosystem services evaluation are an improvement over current land-use planning practice (Boyd and Wainger, 2003). There are many participants involved in land-use decision-making in South Florida, including local, regional, State, and Federal agencies, developers, environmental groups, agricultural groups, and other stakeholders (South Florida Regional Planning Council, 2003, 2004). The EPM's multicriteria evaluation framework is designed to cut across the objectives and knowledge bases of all of these participants. This approach places fundamental importance on social equity and stakeholder participation in land-use decision-making, but makes no attempt to determine normative socially 'optimal' land-use plans. The EPM is thus a map-based set of evaluation tools for planners and stakeholders to use in their deliberations of what is 'best', considering a balancing of disparate interests within a regional perspective. Although
Portfolio Management with Stochastic Interest Rates and Inflation Ambiguity
Munk, Claus; Rubtsov, Alexey Vladimirovich
2014-01-01
prices. The investor is ambiguous about the inflation model and prefers a portfolio strategy which is robust to model misspecification. Ambiguity about the inflation dynamics is shown to affect the optimal portfolio fundamentally different than ambiguity about the price dynamics of traded assets...
Testing the Market Model – A Case Study of Fondul Proprietatea (FP)
Sorin Claudiu Radu
2014-01-01
The financial theory related to the bond portfolio analysis was coined by Harry Markowitz, an authentic’ pioneer of the modern bond theory’, and his well-thought interpretation of the bond selection model may be found in his research papers “Portfolio Selection” (Markowitz M. Harry, 1952) and “Portfolio Selection: Efficient Diversification of Investments” (Markowitz M. Harry 1960). This paper is proposed to test the market model in the Romanian stock market, case of Property Fund.
Optimization of investment portfolio weight of stocks affected by market index
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.
PORTFOLIO OPTIMIZATION ON CROATIAN CAPITAL MARKET
Sinisa Bogdan
2013-12-01
Full Text Available Purpose of this paper was to research portfolio optimization problem on Croatian capital market using Markowitz theory. Research systematically investigated the selection of securities, and defined the importance of using fundamental analysis when selecting the best combination of securities. Since fundamental analysis involves a large number of indicators, this paper selected key indicators that enable a complete and quick securities review on the market. This paper clarifies diversification effect and influence of the correlation coefficient on diversification. Two basic types of assets (stocks and cash funds have been chosen to build the optimal portfolio. Cash funds were selected because they represent a form of risk-free investment, while stocks were chosen because of the high level of return which they achieve. At the end of paper, optimal portfolio was calculated with an excellent yield of 1.82% and deviation of 5.77% on a monthly basis which corresponds to the minimum deviation of the selected stocks. Calculated optimal portfolio achieves better expected value than investing in stock index CROBEX, which for the same period achieves the expected result of -0.02%.
A semiparametric graphical modelling approach for large-scale equity selection.
Liu, Han; Mulvey, John; Zhao, Tianqi
2016-01-01
We propose a new stock selection strategy that exploits rebalancing returns and improves portfolio performance. To effectively harvest rebalancing gains, we apply ideas from elliptical-copula graphical modelling and stability inference to select stocks that are as independent as possible. The proposed elliptical-copula graphical model has a latent Gaussian representation; its structure can be effectively inferred using the regularized rank-based estimators. The resulting algorithm is computationally efficient and scales to large data-sets. To show the efficacy of the proposed method, we apply it to conduct equity selection based on a 16-year health care stock data-set and a large 34-year stock data-set. Empirical tests show that the proposed method is superior to alternative strategies including a principal component analysis-based approach and the classical Markowitz strategy based on the traditional buy-and-hold assumption.
Making practice transparent through e-portfolio.
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.
Robust Portfolio Optimization using CAPM Approach
mohsen gharakhani
2013-08-01
Full Text Available In this paper, a new robust model of multi-period portfolio problem has been developed. One of the key concerns in any asset allocation problem is how to cope with uncertainty about future returns. There are some approaches in the literature for this purpose including stochastic programming and robust optimization. Applying these techniques to multi-period portfolio problem may increase the problem size in a way that the resulting model is intractable. In this paper, a novel approach has been proposed to formulate multi-period portfolio problem as an uncertain linear program assuming that asset return follows the single-index factor model. Robust optimization technique has been also used to solve the problem. In order to evaluate the performance of the proposed model, a numerical example has been applied using simulated data.
Quantifying the role of personal management style in the success of investment portfolios
E.A. Wagenaar; J.H. Van Vuuren
2014-01-01
It is extremely difficult to quantify the effect of different management styles of portfolio managers upon the success of their portfolios. Various mathematical models in the literature attempt to predict the risk and returns of portfolios according to changes in the economic arena, but these models usually do not take into account the personal styles of portfolio managers. The aim of this paper is a modest attempt at quantifying the effect of different managerial styles upon decisions regard...
Akyer, Hasan; Kalaycı, Can Berk; Aygören, Hakan
2018-01-01
Whileinvestors used to create their portfolios according to traditional portfoliotheory in the past, today modern portfolio approach is widely preferred. Thebasis of the modern portfolio theory was suggested by Harry Markowitz with themean variance model. A greater number of securities in a portfolio is difficultto manage and has an increased transaction cost. Therefore, the number ofsecurities in the portfolio should be restricted. The problem of portfoliooptimization with cardinality constr...
ALPHA-BETA SEPARATION PORTFOLIO STRATEGIES FOR ISLAMIC FINANCE
Valentyn Khokhlov
2016-11-01
Full Text Available The purpose of this paper is to develop a mathematical alpha-beta separation model that can be used to create a core-satellite portfolio management strategy that complies with the principles of Islamic finance. Methodology. Core-satellite portfolio construction methodology is used to implement the alpha-beta separation approach, where the core part of the portfolio is managed using the tracking error minimization strategy, and the satellite part of the portfolio is managed using the mean-variance optimization strategy. Results of the portfolio dynamics clearly show that a significant amount of value was created by alpha-beta separation. The typical alpha ranges from 4% to 5.7%. The most aggressive portfolio strategies that allow short positions in the satellite portfolio work best with frequent rebalancing and benefit from the active bets. Smoothing technique that was introduced to decrease the portfolio turnover and stabilize its composition works better when active bets are less efficient, particularly with less frequent rebalancing. The best risk-return combinations are achieved with modest (3% to 10% allocation of the total portfolio to the satellite, and the remaining part (90% to 97% being managed in order to minimize the tracking error. Practical implications. The alpha-beta separation framework suggested in this paper can be used to enhance the portfolio management techniques for the hedge funds that operate under tight restrictions, particularly under the Islamic finance principles. The mathematical models developed in this paper allow practical implementation of the alphabeta separation concept. Originality/value. While the idea of alpha-beta separation existed in hedge fund management before, there was no comprehensive mathematical model under it, so its implementation was based on the ad hoc approach. This paper introduces such a mathematical model and demonstrates how portfolio managers can create value for their clients using it.
Optimization of a dynamic supply portfolio considering risks and discount’s constraints
Masoud Rabbani
2014-01-01
Full Text Available Purpose: Nowadays finding reliable suppliers in the global supply chains has become so important for success, because reliable suppliers would lead to a reliable supply and besides that orders of customer are met effectively . Yet, there is little empirical evidence to support this view, hence the purpose of this paper is to fill this need by considering risk in order to find the optimum supply portfolio. Design/methodology/approach: This paper proposes a multi objective model for the supplier selection portfolio problem that uses conditional value at risk (CVaR criteria to control the risks of delayed, disrupted and defected supplies via scenario analysis. Also we consider discount’s constraints which are common assumptions in supplier selection problems. The proposed approach is capable of determining the optimal supply portfolio by calculating value-at-risk and minimizing conditional value-at-risk. In this study the Reservation Level driven Tchebycheff Procedure (RLTP which is one of the reference point methods, is used to solve small size of our model through coding in GAMS. As our model is NP-hard; a meta-heuristic approach, Non-dominated Sorting Genetic Algorithm (NSGA which is one of the most efficient methods for optimizing multi objective models, is applied to solve large scales of our model. Findings and Originality/value: In order to find a dynamic supply portfolio, we developed a Mixed Integer Linear Programming (MILP model which contains two objectives. One objective minimizes the cost and the other minimizes the risks of delayed, disrupted and defected supplies. CVaR is used as the risk controlling method which emphases on low-probability, high-consequence events. Discount option as a common offer from suppliers is also implanted in the proposed model. Our findings show that the proposed model can help in optimization of a dynamic supplier selection portfolio with controlling the corresponding risks for large scales of real word
Belief Propagation Algorithm for Portfolio Optimization Problems.
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.
A Bicriteria Approach Identifying Nondominated Portfolios
Javier Pereira
2014-01-01
Full Text Available We explore a portfolio constructive model, formulated in terms of satisfaction of a given set of technical requirements, with the minimum number of projects and minimum redundancy. An algorithm issued from robust portfolio modeling is adapted to a vector model, modifying the dominance condition as convenient, in order to find the set of nondominated portfolios, as solutions of a bicriteria integer linear programming problem. In order to improve the former algorithm, a process finding an optimal solution of a monocriteria version of this problem is proposed, which is further used as a first feasible solution aiding to find nondominated solutions more rapidly. Next, a sorting process is applied on the input data or information matrix, which is intended to prune nonfeasible solutions early in the constructive algorithm. Numerical examples show that the optimization and sorting processes both improve computational efficiency of the original algorithm. Their limits are also shown on certain complex instances.
Belief Propagation Algorithm for Portfolio Optimization Problems.
Takashi Shinzato
Full Text Available 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.
Selected sports talent development models
Michal Vičar
2017-06-01
Full Text Available Background: Sports talent in the Czech Republic is generally viewed as a static, stable phenomena. It stands in contrast with widespread praxis carried out in Anglo-Saxon countries that emphasise its fluctuant nature. This is reflected in the current models describing its development. Objectives: The aim is to introduce current models of talent development in sport. Methods: Comparison and analysing of the following models: Balyi - Long term athlete development model, Côté - Developmental model of sport participation, Csikszentmihalyi - The flow model of optimal expertise, Bailey and Morley - Model of talent development. Conclusion: Current models of sport talent development approach talent as dynamic phenomenon, varying in time. They are based in particular on the work of Simonton and his Emergenic and epigenic model and of Gagné and his Differentiated model of giftedness and talent. Balyi's model is characterised by its applicability and impications for practice. Côté's model highlights the role of family and deliberate play. Both models describe periodization of talent development. Csikszentmihalyi's flow model explains how the athlete acquires experience and develops during puberty based on the structure of attention and flow experience. Bailey and Morley's model accents the situational approach to talent and development of skills facilitating its growth.
Portfolio optimization of the construction sector companies in ...
The objective of this paper is to construct the optimal portfolio that will minimize the portfolio risk and can achieve the investors target rate of return by using the mean-semi absolute deviation model. The data of this study comprises 20 construction sector companies that listed in Malaysia stock market from July 2011 until ...
Selected sports talent development models
Michal Vičar
2017-01-01
Background: Sports talent in the Czech Republic is generally viewed as a static, stable phenomena. It stands in contrast with widespread praxis carried out in Anglo-Saxon countries that emphasise its fluctuant nature. This is reflected in the current models describing its development. Objectives: The aim is to introduce current models of talent development in sport. Methods: Comparison and analysing of the following models: Balyi - Long term athlete development model, Côté - Developmen...
Product Portfolio Management: An Important Business Strategy
Doorasamy Mishelle
2015-06-01
Full Text Available The aim of this article is to provide reader with a comprehensive insight on the theories, empirical findings and models of Product Portfolio Management (PPM during new product development. This article will allow for an in-depth theoretical approach on PPM and demonstrate to managers the importance of adopting PPM as business strategy during decision making. The objective of this paper is to present a literature review of models, theories, approaches and findings on the relationship between Product Portfolio Management and new product development. Relevant statistical trends, historical developments, published opinion of major writers in this field will be presented to provide concrete evidence of the problem being discussed.
Agile Project Portfolio Management
Andersen, Jesper Rank; Riis, Jens Ove; Mikkelsen, Hans
2005-01-01
This paper will provide a preliminary introduction to the application of Agile Thinking in management of project portfolio and company development. At any point in time, companies have a crowd of development initiatives spread around the organisation and managed at different levels...... in the managerial hierarchy. They compete for resources and managerial attention, and they often take too long time - and some do not survive in the rapid changing context. Top man¬agers ask for speed, flexibility and effectiveness in the portfolio of development activities (projects). But which competencies...
Portfolio Analysis for Vector Calculus
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…
Two Portfolio Systems: EFL Students' Perceptions of Writing Ability, Text Improvement, and Feedback
Lam, Ricky
2013-01-01
Research into portfolio assessment ("PA") typically describes teachers' development and implementation of different portfolio models in their respective teaching contexts, however, not much attention is paid to student perceptions of the portfolio approach or its impact on the learning of writing. To this end, this study aims to…
MODEL SELECTION FOR SPECTROPOLARIMETRIC INVERSIONS
Asensio Ramos, A.; Manso Sainz, R.; Martínez González, M. J.; Socas-Navarro, H.; Viticchié, B.; Orozco Suárez, D.
2012-01-01
Inferring magnetic and thermodynamic information from spectropolarimetric observations relies on the assumption of a parameterized model atmosphere whose parameters are tuned by comparison with observations. Often, the choice of the underlying atmospheric model is based on subjective reasons. In other cases, complex models are chosen based on objective reasons (for instance, the necessity to explain asymmetries in the Stokes profiles) but it is not clear what degree of complexity is needed. The lack of an objective way of comparing models has, sometimes, led to opposing views of the solar magnetism because the inferred physical scenarios are essentially different. We present the first quantitative model comparison based on the computation of the Bayesian evidence ratios for spectropolarimetric observations. Our results show that there is not a single model appropriate for all profiles simultaneously. Data with moderate signal-to-noise ratios (S/Ns) favor models without gradients along the line of sight. If the observations show clear circular and linear polarization signals above the noise level, models with gradients along the line are preferred. As a general rule, observations with large S/Ns favor more complex models. We demonstrate that the evidence ratios correlate well with simple proxies. Therefore, we propose to calculate these proxies when carrying out standard least-squares inversions to allow for model comparison in the future.
Environment and economic risk: An analysis of carbon emission market and portfolio management.
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.
Spin glasses and nonlinear constraints in portfolio optimization
Andrecut, M., E-mail: mircea.andrecut@gmail.com
2014-01-17
We discuss the portfolio optimization problem with the obligatory deposits constraint. Recently it has been shown that as a consequence of this nonlinear constraint, the solution consists of an exponentially large number of optimal portfolios, completely different from each other, and extremely sensitive to any changes in the input parameters of the problem, making the concept of rational decision making questionable. Here we reformulate the problem using a quadratic obligatory deposits constraint, and we show that from the physics point of view, finding an optimal portfolio amounts to calculating the mean-field magnetizations of a random Ising model with the constraint of a constant magnetization norm. We show that the model reduces to an eigenproblem, with 2N solutions, where N is the number of assets defining the portfolio. Also, in order to illustrate our results, we present a detailed numerical example of a portfolio of several risky common stocks traded on the Nasdaq Market.
Spin glasses and nonlinear constraints in portfolio optimization
Andrecut, M.
2014-01-01
We discuss the portfolio optimization problem with the obligatory deposits constraint. Recently it has been shown that as a consequence of this nonlinear constraint, the solution consists of an exponentially large number of optimal portfolios, completely different from each other, and extremely sensitive to any changes in the input parameters of the problem, making the concept of rational decision making questionable. Here we reformulate the problem using a quadratic obligatory deposits constraint, and we show that from the physics point of view, finding an optimal portfolio amounts to calculating the mean-field magnetizations of a random Ising model with the constraint of a constant magnetization norm. We show that the model reduces to an eigenproblem, with 2N solutions, where N is the number of assets defining the portfolio. Also, in order to illustrate our results, we present a detailed numerical example of a portfolio of several risky common stocks traded on the Nasdaq Market.
A Computational Model of Selection by Consequences
McDowell, J. J.
2004-01-01
Darwinian selection by consequences was instantiated in a computational model that consisted of a repertoire of behaviors undergoing selection, reproduction, and mutation over many generations. The model in effect created a digital organism that emitted behavior continuously. The behavior of this digital organism was studied in three series of…
Students' reflections in a portfolio pilot: highlighting professional issues.
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
Large portfolio risk management and optimal portfolio allocation with dynamic elliptical copulas
Jin Xisong
2018-02-01
Full Text Available Previous research has focused on the importance of modeling the multivariate distribution for optimal portfolio allocation and active risk management. However, existing dynamic models are not easily applied to high-dimensional problems due to the curse of dimensionality. In this paper, we extend the framework of the Dynamic Conditional Correlation/Equicorrelation and an extreme value approach into a series of Dynamic Conditional Elliptical Copulas. We investigate risk measures such as Value at Risk (VaR and Expected Shortfall (ES for passive portfolios and dynamic optimal portfolios using Mean-Variance and ES criteria for a sample of US stocks over a period of 10 years. Our results suggest that (1 Modeling the marginal distribution is important for dynamic high-dimensional multivariate models. (2 Neglecting the dynamic dependence in the copula causes over-aggressive risk management. (3 The DCC/DECO Gaussian copula and t-copula work very well for both VaR and ES. (4 Grouped t-copulas and t-copulas with dynamic degrees of freedom further match the fat tail. (5 Correctly modeling the dependence structure makes an improvement in portfolio optimization with respect to tail risk. (6 Models driven by multivariate t innovations with exogenously given degrees of freedom provide a flexible and applicable alternative for optimal portfolio risk management.
Schneider, Georges
1994-01-01
This chapter demonstrates the need for acreage portfolio management at the stage of maturity which has been reached in the UK sector of the North Sea petroleum industry. It outlines the goals, the main features of the deals and the business process. (UK)
Portfolio, refleksion og feedback
Hansen, Jens Jørgen; Qvortrup, Ane; Christensen, Inger-Marie F.
2017-01-01
Denne leder definerer indledningsvist begrebet portfolio og gør rede for anvendelsesmuligheder i en uddannelseskontekst. Dernæst behandles portfoliometodens kvalitet og effekt for læring og undervisning og de centrale begreber refleksion, progression og feedback præsenteres og diskuteres. Herefter...
Portfolio optimization using fuzzy linear programming
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.
A computational model of selection by consequences.
McDowell, J J
2004-01-01
Darwinian selection by consequences was instantiated in a computational model that consisted of a repertoire of behaviors undergoing selection, reproduction, and mutation over many generations. The model in effect created a digital organism that emitted behavior continuously. The behavior of this digital organism was studied in three series of computational experiments that arranged reinforcement according to random-interval (RI) schedules. The quantitative features of the model were varied o...
Investment risk management by applying contemporary modern portfolio theory
Jakšić Milena
2015-01-01
Full Text Available Investment risk is the principal threat to the assets side of the balance sheets of financial institutions. It is evident that investors who concentrate their wealth on one type of securities can rarely be found. Instead, they tend to invest diversified portfolio of securities. This reduces the degree of risk of the expected return, which depends both on the absolute risk of each investment in the portfolio, and the relationship that exists between individual investments within the portfolio. The paper analyzes the investment risk management by using modern portfolio theory in both national and global financial f lows. At the same time, the paper considers the risk management models that ensures efficient portfolio diversification, aiming at investment risk reduction. It is pointed out that the investment risk management in modern financial f lows is a complex process, and that the development of financial theory goes towards improving, soft risk management method.
METHODS OF PORTFOLIO MANAGEMENT - A REVIEW OF LITERATURE -
CRISTINA CURUTIU
2008-01-01
In recent years, a growing body of literature in portfolio management has devoted a great deal of attention for this subject. The theoretical foundation to portfolio management was offered by Harry Markowitz at the beginning of the 1950s. The limitations of the original Markowitz model have stimulated the occurrence of extended or modified models – two of the best known (and criticized) being the equilibrium models: CAPM (capital asset pricing model) and APT (arbitrage pricing theory). Altern...
Dinitz, Laura B.
2008-01-01
With costs of natural disasters skyrocketing and populations increasingly settling in areas vulnerable to natural hazards, society is challenged to better allocate its limited risk-reduction resources. In 2000, Congress passed the Disaster Mitigation Act, amending the Robert T. Stafford Disaster Relief and Emergency Assistance Act (Robert T. Stafford Disaster Relief and Emergency Assistance Act, Pub. L. 93-288, 1988; Federal Emergency Management Agency, 2002, 2008b; Disaster Mitigation Act, 2000), mandating that State, local, and tribal communities prepare natural-hazard mitigation plans to qualify for pre-disaster mitigation grants and post-disaster aid. The Federal Emergency Management Agency (FEMA) was assigned to coordinate and implement hazard-mitigation programs, and it published information about specific mitigation-plan requirements and the mechanisms (through the Hazard Mitigation Grant Program-HMGP) for distributing funds (Federal Emergency Management Agency, 2002). FEMA requires that each community develop a mitigation strategy outlining long-term goals to reduce natural-hazard vulnerability, mitigation objectives and specific actions to reduce the impacts of natural hazards, and an implementation plan for those actions. The implementation plan should explain methods for prioritizing, implementing, and administering the actions, along with a 'cost-benefit review' justifying the prioritization. FEMA, along with the National Institute of Building Sciences (NIBS), supported the development of HAZUS ('Hazards U.S.'), a geospatial natural-hazards loss-estimation tool, to help communities quantify potential losses and to aid in the selection and prioritization of mitigation actions. HAZUS was expanded to a multiple-hazard version, HAZUS-MH, that combines population, building, and natural-hazard science and economic data and models to estimate physical damages, replacement costs, and business interruption for specific natural-hazard scenarios. HAZUS
Bayesian Model Selection under Time Constraints
Hoege, M.; Nowak, W.; Illman, W. A.
2017-12-01
Bayesian model selection (BMS) provides a consistent framework for rating and comparing models in multi-model inference. In cases where models of vastly different complexity compete with each other, we also face vastly different computational runtimes of such models. For instance, time series of a quantity of interest can be simulated by an autoregressive process model that takes even less than a second for one run, or by a partial differential equations-based model with runtimes up to several hours or even days. The classical BMS is based on a quantity called Bayesian model evidence (BME). It determines the model weights in the selection process and resembles a trade-off between bias of a model and its complexity. However, in practice, the runtime of models is another weight relevant factor for model selection. Hence, we believe that it should be included, leading to an overall trade-off problem between bias, variance and computing effort. We approach this triple trade-off from the viewpoint of our ability to generate realizations of the models under a given computational budget. One way to obtain BME values is through sampling-based integration techniques. We argue with the fact that more expensive models can be sampled much less under time constraints than faster models (in straight proportion to their runtime). The computed evidence in favor of a more expensive model is statistically less significant than the evidence computed in favor of a faster model, since sampling-based strategies are always subject to statistical sampling error. We present a straightforward way to include this misbalance into the model weights that are the basis for model selection. Our approach follows directly from the idea of insufficient significance. It is based on a computationally cheap bootstrapping error estimate of model evidence and is easy to implement. The approach is illustrated in a small synthetic modeling study.
PORTFOLIO ANALYSIS BASED ON THE EXAMPLE OF ZAGREB STOCK EXCHANGE
Sinisa Bogdan
2010-06-01
Full Text Available In this paper we analyze the portfolio that was selected from the Zagreb Stock Exchange and also try to assess its risks and its future offerings that are relevant in making the decisions about investments. Through the work we will explain the importance of diversification and how the very diversification reduces risk. We will also analyze the systemic risk of individual stocks within the portfolio and the systemic risk of the given portfolio and explain its importance. Through regression analysis we will analyze the securities with the highest and lowest systemic risk and will clarify the results. At the end we will explain the correlation in the selected portfolio and point out the importance of the correlation and diversification itself.
Aircraft technology portfolio optimization using ant colony optimization
Villeneuve, Frederic J.; Mavris, Dimitri N.
2012-11-01
Technology portfolio selection is a combinatorial optimization problem often faced with a large number of combinations and technology incompatibilities. The main research question addressed in this article is to determine if Ant Colony Optimization (ACO) is better suited than Genetic Algorithms (GAs) and Simulated Annealing (SA) for technology portfolio optimization when incompatibility constraints between technologies are present. Convergence rate, capability to find optima, and efficiency in handling of incompatibilities are the three criteria of comparison. The application problem consists of finding the best technology portfolio from 29 aircraft technologies. The results show that ACO and GAs converge faster and find optima more easily than SA, and that ACO can optimize portfolios with technology incompatibilities without using penalty functions. This latter finding paves the way for more use of ACO when the number of constraints increases, such as in the technology and concept selection for complex engineering systems.
A Dynamic Model for Limb Selection
Cox, R.F.A; Smitsman, A.W.
2008-01-01
Two experiments and a model on limb selection are reported. In Experiment 1 left-handed and right-handed participants (N = 36) repeatedly used one hand for grasping a small cube. After a clear switch in the cube’s location, perseverative limb selection was revealed in both handedness groups. In
A Gambler's Model of Natural Selection.
Nolan, Michael J.; Ostrovsky, David S.
1996-01-01
Presents an activity that highlights the mechanism and power of natural selection. Allows students to think in terms of modeling a biological process and instills an appreciation for a mathematical approach to biological problems. (JRH)
Portfolio Decision Analysis Framework for Value-Focused Ecosystem Management.
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
Portfolio Decision Analysis Framework for Value-Focused Ecosystem Management.
Matteo Convertino
Full Text Available 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
Portfolio Decision Analysis Framework for Value-Focused Ecosystem Management
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
Strategic innovation portfolio management
Stanković Ljiljana
2015-01-01
Full Text Available In knowledge-based economy, strategic innovation portfolio management becomes more and more important and critical factor of enterprise's success. Value creation for all the participants in value chain is more successful if it is based on efficient resource allocation and improvement of innovation performances. Numerous researches have shown that companies with best position on the market found their competitiveness on efficient development and exploitation of innovations. In decision making process, enterprise's management is constantly faced with challenge to allocate resources and capabilities as efficiently as possible, in both short and long term. In this paper authors present preliminary results of realized empirical research related to strategic innovation portfolio management in ten chosen enterprises in Serbia. The structure of the paper includes the following parts: theoretical background, explanation of research purpose and methodology, discussion of the results and concluding remarks, including limitations and directions for further research.
Schneider, G.M.
1992-01-01
This paper reports that the need for managing the acreage portfolio in the UK North Sea arises from fragmentation of holdings and complex field partnerships. The main concepts are building up the heartlands and balancing cashflow forecasts. This has generated a number of friendly win-win deals, motivated by differences in perception of values. The business process includes identifying, evaluating and negotiating deals. The Petroleum Economist plays a central role throughout this process, seeking value gaps and supporting negotiations. Variations in reserves estimates present a major source of value gaps between buyer and seller. Economists need to work closely with engineers and geologists. Portfolio management is an exciting and challenging task which broadens the traditional role of the Petroleum Economist
On portfolio risk diversification
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.
Hvorfor anvende portfolio eksamen?
Elley, Tina Ninka
2015-01-01
from the clinical part. The two topics are weighted according to the distribution of ECTS points between theory and clinic. We implemented the portfolio format in November 2012, and the evaluations from the students have shown that the format is good; the students get less stressed at the exam......In Denmark the Biomedical Laboratory Scientist programme lasts for 3½ years, divided into 14 modules of 10 weeks. Every module concludes with an exam, which can be very stressful for the students. A survey was made among the students, confirming this. How can we change some of the exams in order...... to minimize the students' stress level? Then the pedagogical considerations started – where and how to do this? The conclusion was to work with the portfolio format at module 6 and module 7 and make it the exam form, as it was possible to divide the expected learning outcome for the two modules into topics...
Review and selection of unsaturated flow models
Reeves, M.; Baker, N.A.; Duguid, J.O. [INTERA, Inc., Las Vegas, NV (United States)
1994-04-04
Since the 1960`s, ground-water flow models have been used for analysis of water resources problems. In the 1970`s, emphasis began to shift to analysis of waste management problems. This shift in emphasis was largely brought about by site selection activities for geologic repositories for disposal of high-level radioactive wastes. Model development during the 1970`s and well into the 1980`s focused primarily on saturated ground-water flow because geologic repositories in salt, basalt, granite, shale, and tuff were envisioned to be below the water table. Selection of the unsaturated zone at Yucca Mountain, Nevada, for potential disposal of waste began to shift model development toward unsaturated flow models. Under the US Department of Energy (DOE), the Civilian Radioactive Waste Management System Management and Operating Contractor (CRWMS M&O) has the responsibility to review, evaluate, and document existing computer models; to conduct performance assessments; and to develop performance assessment models, where necessary. This document describes the CRWMS M&O approach to model review and evaluation (Chapter 2), and the requirements for unsaturated flow models which are the bases for selection from among the current models (Chapter 3). Chapter 4 identifies existing models, and their characteristics. Through a detailed examination of characteristics, Chapter 5 presents the selection of models for testing. Chapter 6 discusses the testing and verification of selected models. Chapters 7 and 8 give conclusions and make recommendations, respectively. Chapter 9 records the major references for each of the models reviewed. Appendix A, a collection of technical reviews for each model, contains a more complete list of references. Finally, Appendix B characterizes the problems used for model testing.
Review and selection of unsaturated flow models
Reeves, M.; Baker, N.A.; Duguid, J.O.
1994-01-01
Since the 1960's, ground-water flow models have been used for analysis of water resources problems. In the 1970's, emphasis began to shift to analysis of waste management problems. This shift in emphasis was largely brought about by site selection activities for geologic repositories for disposal of high-level radioactive wastes. Model development during the 1970's and well into the 1980's focused primarily on saturated ground-water flow because geologic repositories in salt, basalt, granite, shale, and tuff were envisioned to be below the water table. Selection of the unsaturated zone at Yucca Mountain, Nevada, for potential disposal of waste began to shift model development toward unsaturated flow models. Under the US Department of Energy (DOE), the Civilian Radioactive Waste Management System Management and Operating Contractor (CRWMS M ampersand O) has the responsibility to review, evaluate, and document existing computer models; to conduct performance assessments; and to develop performance assessment models, where necessary. This document describes the CRWMS M ampersand O approach to model review and evaluation (Chapter 2), and the requirements for unsaturated flow models which are the bases for selection from among the current models (Chapter 3). Chapter 4 identifies existing models, and their characteristics. Through a detailed examination of characteristics, Chapter 5 presents the selection of models for testing. Chapter 6 discusses the testing and verification of selected models. Chapters 7 and 8 give conclusions and make recommendations, respectively. Chapter 9 records the major references for each of the models reviewed. Appendix A, a collection of technical reviews for each model, contains a more complete list of references. Finally, Appendix B characterizes the problems used for model testing
Portfolio management of hydropower producer via stochastic programming
Liu, Hongling; Jiang, Chuanwen; Zhang, Yan
2009-01-01
This paper presents a stochastic linear programming framework for the hydropower portfolio management problem with uncertainty in market prices and inflows on medium term. The uncertainty is modeled as a scenario tree using the Monte Carlo simulation method, and the objective is to maximize the expected revenue over the entire scenario tree. The portfolio decisions of the stochastic model are formulated as a tradeoff involving different scenarios. Numerical results illustrate the impact of uncertainty on the portfolio management decisions, and indicate the significant value of stochastic solution. (author)
ANALYSIS OF PROJECT PORTFOLIO MANAGEMENT MATURITY: THE CASE OF A SMALL FINANCIAL INSTITUTION
Karoline Doro Alves Carneiro
2012-04-01
Full Text Available This study explores the implementation of project portfolio management in the organizational context. The objective is to analyze the methodology of project portfolio management adopted by an organization based in the project portfolio management maturity model proposed by Rad and Levin (2006. We developed an exploratory case study in a small financial institution that experienced problems with the implementation of its methodology in project portfolio management. As a result of study, we found that the organization has maturity level 2 in portfolio project management, and that some methodology aspects are not appropriate at this level.
Dilip Kumar
2014-03-01
Full Text Available The paper investigates the first and second orders moment transmission between gold and Indian industrial sectors with an application of portfolio design and hedging effectiveness using generalised VAR-ADCC-BVGARCH model. Our findings indicate unidirectional significant return spillover from gold to stock sectors. The negative values of estimated time varying conditional correlations are mainly observed during periods of market turbulence and crisis indicating the scope of portfolio diversification and hedging during these periods. We also estimate optimal weights, hedge ratios, and hedging effectiveness for the stock-gold portfolios. Our findings suggest that stock-gold portfolio provides better diversification benefits than stock portfolios.
Schneider
1992-01-01
This paper reports that the need to manage U.K. North Sea acreage portfolios arises from fragmentation of holdings and complex partnerships. This management has generated friendly rationalization deals motivated by differences in perception of values and aimed at building up heartlands and balancing cash-flow forecasts. The business process includes identifying, evaluating, and negotiating deals. The economist plays a central role within the evaluation team and supports the negotiators
Labiosa, Bill; Forney, William M.; Hearn,, Paul P.; Hogan, Dianna M.; Strong, David R.; Swain, Eric D.; Esnard, Ann-Margaret; Mitsova-Boneva, D.; Bernknopf, R.; Pearlstine, Leonard; Gladwin, Hugh
2013-01-01
Land-use land-cover change is one of the most important and direct drivers of changes in ecosystem functions and services. Given the complexity of the decision-making, there is a need for Internet-based decision support systems with scenario evaluation capabilities to help planners, resource managers and communities visualize, compare and consider trade-offs among the many values at stake in land use planning. This article presents details on an Ecosystem Portfolio Model (EPM) prototype that integrates ecological, socio-economic information and associated values of relevance to decision-makers and stakeholders. The EPM uses a multi-criteria scenario evaluation framework, Geographic Information Systems (GIS) analysis and spatially-explicit land-use/land-cover change-sensitive models to characterize changes in important land-cover related ecosystem values related to ecosystem services and functions, land parcel prices, and community quality-of-life (QoL) metrics. Parameters in the underlying models can be modified through the interface, allowing users in a facilitated group setting to explore simultaneously issues of scientific uncertainty and divergence in the preferences of stakeholders. One application of the South Florida EPM prototype reported in this article shows the modeled changes (which are significant) in aggregate ecological value, landscape patterns and fragmentation, biodiversity potential and ecological restoration potential for current land uses compared to the 2050 land-use scenario. Ongoing refinements to EPM, and future work especially in regard to modifiable sea level rise scenarios are also discussed.
portfolio optimization based on nonparametric estimation methods
mahsa ghandehari
2017-03-01
Full Text Available One of the major issues investors are facing with in capital markets is decision making about select an appropriate stock exchange for investing and selecting an optimal portfolio. This process is done through the risk and expected return assessment. On the other hand in portfolio selection problem if the assets expected returns are normally distributed, variance and standard deviation are used as a risk measure. But, the expected returns on assets are not necessarily normal and sometimes have dramatic differences from normal distribution. This paper with the introduction of conditional value at risk ( CVaR, as a measure of risk in a nonparametric framework, for a given expected return, offers the optimal portfolio and this method is compared with the linear programming method. The data used in this study consists of monthly returns of 15 companies selected from the top 50 companies in Tehran Stock Exchange during the winter of 1392 which is considered from April of 1388 to June of 1393. The results of this study show the superiority of nonparametric method over the linear programming method and the nonparametric method is much faster than the linear programming method.
Model Selection with the Linear Mixed Model for Longitudinal Data
Ryoo, Ji Hoon
2011-01-01
Model building or model selection with linear mixed models (LMMs) is complicated by the presence of both fixed effects and random effects. The fixed effects structure and random effects structure are codependent, so selection of one influences the other. Most presentations of LMM in psychology and education are based on a multilevel or…
An evolutionary algorithm for model selection
Bicker, Karl [CERN, Geneva (Switzerland); Chung, Suh-Urk; Friedrich, Jan; Grube, Boris; Haas, Florian; Ketzer, Bernhard; Neubert, Sebastian; Paul, Stephan; Ryabchikov, Dimitry [Technische Univ. Muenchen (Germany)
2013-07-01
When performing partial-wave analyses of multi-body final states, the choice of the fit model, i.e. the set of waves to be used in the fit, can significantly alter the results of the partial wave fit. Traditionally, the models were chosen based on physical arguments and by observing the changes in log-likelihood of the fits. To reduce possible bias in the model selection process, an evolutionary algorithm was developed based on a Bayesian goodness-of-fit criterion which takes into account the model complexity. Starting from systematically constructed pools of waves which contain significantly more waves than the typical fit model, the algorithm yields a model with an optimal log-likelihood and with a number of partial waves which is appropriate for the number of events in the data. Partial waves with small contributions to the total intensity are penalized and likely to be dropped during the selection process, as are models were excessive correlations between single waves occur. Due to the automated nature of the model selection, a much larger part of the model space can be explored than would be possible in a manual selection. In addition the method allows to assess the dependence of the fit result on the fit model which is an important contribution to the systematic uncertainty.
Portfolios in Saudi medical colleges
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
Genetic search feature selection for affective modeling
Martínez, Héctor P.; Yannakakis, Georgios N.
2010-01-01
Automatic feature selection is a critical step towards the generation of successful computational models of affect. This paper presents a genetic search-based feature selection method which is developed as a global-search algorithm for improving the accuracy of the affective models built....... The method is tested and compared against sequential forward feature selection and random search in a dataset derived from a game survey experiment which contains bimodal input features (physiological and gameplay) and expressed pairwise preferences of affect. Results suggest that the proposed method...
Cluster analysis for portfolio optimization
Vincenzo Tola; Fabrizio Lillo; Mauro Gallegati; Rosario N. Mantegna
2005-01-01
We consider the problem of the statistical uncertainty of the correlation matrix in the optimization of a financial portfolio. We show that the use of clustering algorithms can improve the reliability of the portfolio in terms of the ratio between predicted and realized risk. Bootstrap analysis indicates that this improvement is obtained in a wide range of the parameters N (number of assets) and T (investment horizon). The predicted and realized risk level and the relative portfolio compositi...
Driessen, Erik
2017-03-01
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 surrounding portfolio implementation in competency-based education. It could be argued that mass adoption without careful attention to purpose and format may well jeopardize portfolios' viability in health sciences education. This paper explores this proposition by addressing the following three main questions: (1) Why do portfolios meet with such resistance from students and teachers, while educators love them?; (2) Is it ethical to require students to reflect and then grade their reflections?; (3) Does competency-based education empower or hamper the learner during workplace-based learning? Twenty-five years of portfolio reveal a clear story: without mentoring, portfolios have no future and are nothing short of bureaucratic hurdles in our competency-based education programs. Moreover, comprehensive portfolios, which are integrated into the curriculum and much more diverse in content than reflective portfolios, can serve as meaningful patient charts, providing doctor and patient with useful information to discuss well-being and treatment. In this sense, portfolios are also learner charts that comprehensively document progress in a learning trajectory which is lubricated by meaningful dialogue between learner and mentor in a trusting relationship to foster learning. If we are able to make such comprehensive and meaningful use of portfolios, then, yes, portfolios do have a bright future in medical education.
Project Portfolio Management Applications Testing
Paul POCATILU
2006-01-01
Many IT companies are running project simultaneously. In order to achieve the best results, they have to group to the project in portfolios, and to use specific software that helps to manage them. Project portfolio management applications have a high degree of complexity and they are very important for the companies that are using it. This paper focuses on some characteristics of the testing process for project portfolio management applications
Project Portfolio Management Applications Testing
Paul POCATILU
2006-01-01
Full Text Available Many IT companies are running project simultaneously. In order to achieve the best results, they have to group to the project in portfolios, and to use specific software that helps to manage them. Project portfolio management applications have a high degree of complexity and they are very important for the companies that are using it. This paper focuses on some characteristics of the testing process for project portfolio management applications
Portfolio insurance using traded options
Machado-Santos, Carlos
2001-01-01
Literature concerning the institutional use of options indicates that the main purpose of option trading is to provide investors with the opportunity to create return distributions previously unavailable, considering that options provide the means to manipulate portfolio returns. In such a context, this study intends to analyse the returns of insured portfolios generated by hedging strategies on underlying stock portfolios. Because dynamic hedging is too expensive, we have hedged the stock po...
Building a Smart E-Portfolio Platform for Optimal E-Learning Objects Acquisition
Chih-Kun Ke
2013-01-01
Full Text Available In modern education, an e-portfolio platform helps students in acquiring e-learning objects in a learning activity. Quality is an important consideration in evaluating the desirable e-learning object. Finding a means of determining a high quality e-learning object from a large number of candidate e-learning objects is an important requirement. To assist student learning in a modern e-portfolio platform, this work proposed an optimal selection approach determining a reasonable e-learning object from various candidate e-learning objects. An optimal selection approach which uses advanced information techniques is proposed. Each e-learning object undergoes a formalization process. An Information Retrieval (IR technique extracts and analyses key concepts from the student’s previous learning contexts. A context-based utility model computes the expected utility values of various e-learning objects based on the extracted key concepts. The expected utility values of e-learning objects are used in a multicriteria decision analysis to determine the optimal selection order of the candidate e-learning objects. The main contribution of this work is the demonstration of an effective e-learning object selection method which is easy to implement within an e-portfolio platform and which makes it smarter.
Fuzzy portfolio optimization advances in hybrid multi-criteria methodologies
Gupta, Pankaj; Inuiguchi, Masahiro; Chandra, Suresh
2014-01-01
This monograph presents a comprehensive study of portfolio optimization, an important area of quantitative finance. Considering that the information available in financial markets is incomplete and that the markets are affected by vagueness and ambiguity, the monograph deals with fuzzy portfolio optimization models. At first, the book makes the reader familiar with basic concepts, including the classical mean–variance portfolio analysis. Then, it introduces advanced optimization techniques and applies them for the development of various multi-criteria portfolio optimization models in an uncertain environment. The models are developed considering both the financial and non-financial criteria of investment decision making, and the inputs from the investment experts. The utility of these models in practice is then demonstrated using numerical illustrations based on real-world data, which were collected from one of the premier stock exchanges in India. The book addresses both academics and professionals pursuin...
STRATEGY FOR BUSINESS PORTFOLIO DEVELOPMENT OF PT SEKAR LAUT, TBK.
Homisah Homisah
2016-01-01
Full Text Available PT Sekar Laut, Tbk. (PTSL, as a local company, has three main business units including snack crackers, cooking spices and private label. Due to the potentials of Indonesia, it is expected that PTSL can upscale its competitive advantage and has an ability to compete with global companies as well. The objectives of this research were 1 analyzing relative positioning of PTSL compared with market leaders in snack and cooking spices industries, 2 analyzing Life Cycle phase per business unit, 3 analyzing positioning of each product category in portfolio matrix, 4 formulating strategic recommendations to the management for each product category of PTSL. The method used in this study was descriptive analysis. The analysis tools used in this study were BCG matrix, Life Cycle model, IFE, IFI and GE matrix. The results showed that relative positioning of crackers and cooking spices business units in BCG matrix is in Question Marks quadrant. The results of Life Cycle model for snack crackers, cooking spices, and private label showed that they are in Growth phase. The result of portfolio analysis by GE matrix showed that shrimp cracker and fish cracker product categories are in Selective Growth quadrant. Vegetables cracker, cooking spices, uleg chili sauce, burger buns are in Investment and Growth quadrant. The strategic recommendation for shrimp and fish crackers is to identify the growth segment, aggressive investment and uphold position. The strategic recommendations for vegetable cracker, cooking spices, uleg chili sauce, and burger buns are growth, seeking for dominance and maximum investment.Keywords: portfolio analyzing, crackers, cooking spices, uleg chili sauce, burger buns
Labor Supply Flexibility and Portfolio Choice
Zvi Bodie; William Samuelson
1989-01-01
This paper develops a model showing that people who have flexibility in choosing how much to work will prefer to invest substantially more of their money in risky assets than if they had no such flexibility. Viewed in this way, labor supply flexibility offers insurance against adverse investment outcomes. The model provides support for the conventional wisdom that the young can tolerate more risk in their investment portfolios than the old. The model has other implications for the study of ho...
Geometrical framework for robust portfolio optimization
Bazovkin, Pavel
2014-01-01
We consider a vector-valued multivariate risk measure that depends on the user's profile given by the user's utility. It is constructed on the basis of weighted-mean trimmed regions and represents the solution of an optimization problem. The key feature of this measure is convexity. We apply the measure to the portfolio selection problem, employing different measures of performance as objective functions in a common geometrical framework.
Financial Advice and Individual Investor Portfolio Performance
Kramer, M.M.
2012-01-01
This paper investigates whether financial advisers add value to individual investors portfolio decisions by comparing portfolios of advised and self-directed (execution-only) Dutch individual investors. The results indicate significant differences in characteristics and portfolios between these
Melody Track Selection Using Discriminative Language Model
Wu, Xiao; Li, Ming; Suo, Hongbin; Yan, Yonghong
In this letter we focus on the task of selecting the melody track from a polyphonic MIDI file. Based on the intuition that music and language are similar in many aspects, we solve the selection problem by introducing an n-gram language model to learn the melody co-occurrence patterns in a statistical manner and determine the melodic degree of a given MIDI track. Furthermore, we propose the idea of using background model and posterior probability criteria to make modeling more discriminative. In the evaluation, the achieved 81.6% correct rate indicates the feasibility of our approach.
Model selection for Gaussian kernel PCA denoising
Jørgensen, Kasper Winther; Hansen, Lars Kai
2012-01-01
We propose kernel Parallel Analysis (kPA) for automatic kernel scale and model order selection in Gaussian kernel PCA. Parallel Analysis [1] is based on a permutation test for covariance and has previously been applied for model order selection in linear PCA, we here augment the procedure to also...... tune the Gaussian kernel scale of radial basis function based kernel PCA.We evaluate kPA for denoising of simulated data and the US Postal data set of handwritten digits. We find that kPA outperforms other heuristics to choose the model order and kernel scale in terms of signal-to-noise ratio (SNR...
On the Benefits of Equicorrelation for Portfolio Allocation
Adam Clements; Ayesha Scott; Annastiina Silvennoinen
2013-01-01
The importance of modelling correlation has long been recognised in the field of portfolio management with large dimensional multivariate problems are increasingly becoming the focus of research. This paper provides a straightforward and commonsense approach toward investigating a number of models used to generate forecasts of the correlation matrix for large dimensional problems. We find evidence in favour of assuming equicorrelation across various portfolio sizes, particularly during times ...
Eyre, Harris A; Mitchell, Rob D; Milford, Will; Vaswani, Nitin; Moylan, Steven
2014-06-01
Portfolio careers in medicine can be defined as significant involvement in one or more portfolios of activity beyond a practitioner's primary clinical role, either concurrently or in sequence. Portfolio occupations may include medical education, research, administration, legal medicine, the arts, engineering, business and consulting, leadership, politics and entrepreneurship. Despite significant interest among junior doctors, portfolios are poorly integrated with prevocational and speciality training programs in Australia. The present paper seeks to explore this issue. More formal systems for portfolio careers in Australia have the potential to increase job satisfaction, flexibility and retention, as well as diversify trainee skill sets. Although there are numerous benefits from involvement in portfolio careers, there are also risks to the trainee, employing health service and workforce modelling. Formalising pathways to portfolio careers relies on assessing stakeholder interest, enhancing flexibility in training programs, developing support programs, mentorship and coaching schemes and improving support structures in health services.
Multiperiod Mean-Variance Portfolio Optimization via Market Cloning
Ankirchner, Stefan, E-mail: ankirchner@hcm.uni-bonn.de [Rheinische Friedrich-Wilhelms-Universitaet Bonn, Institut fuer Angewandte Mathematik, Hausdorff Center for Mathematics (Germany); Dermoune, Azzouz, E-mail: Azzouz.Dermoune@math.univ-lille1.fr [Universite des Sciences et Technologies de Lille, Laboratoire Paul Painleve UMR CNRS 8524 (France)
2011-08-15
The problem of finding the mean variance optimal portfolio in a multiperiod model can not be solved directly by means of dynamic programming. In order to find a solution we therefore first introduce independent market clones having the same distributional properties as the original market, and we replace the portfolio mean and variance by their empirical counterparts. We then use dynamic programming to derive portfolios maximizing a weighted sum of the empirical mean and variance. By letting the number of market clones converge to infinity we are able to solve the original mean variance problem.