Transaction fees and optimal rebalancing in the growth-optimal portfolio

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

2011-05-01

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

Post-modern portfolio theory supports diversification in an investment portfolio to measure investment's performance

OpenAIRE

Rasiah, Devinaga

2012-01-01

This study looks at the Post-Modern Portfolio Theory that maintains greater diversification in an investment portfolio by using the alpha and the beta coefficient to measure investment performance. Post-Modern Portfolio Theory appreciates that investment risk should be tied to each investor's goals and the outcome of this goal did not symbolize economic of the financial risk. Post-Modern Portfolio Theory's downside measure generated a noticeable distinction between downside and upside volatil...

12 CFR 347.108 - Portfolio investments.

Science.gov (United States)

2010-01-01

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

Fuzzy Investment Portfolio Selection Models Based on Interval Analysis Approach

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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.

Portfolio optimization in the cryptocurrency market : an evaluation of the performance of momentum strategies in the cryptocurrency market and cryptocurrency’s place in an optimized investment portfolio

OpenAIRE

Bjordal, Andreas; Opdahl, Espen

2017-01-01

In this paper, we rigorously investigate the benefit of utilizing an active investment strategy based on momentum when investing in cryptocurrencies. We also examine how including cryptocurrencies in a more traditional asset allocation can optimize an investment portfolio. First, we create strategies with the use of exponential moving averages and simple average filters to generate a trading signal. Second, we provide evidence that the active strategies receive positive return,...

CHARACTERISTICS OF INVESTMENT PORTFOLIOS PASSIVE MANAGEMENT STRATEGY ON THE CAPITAL MARKET

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MIHAELA SUDACEVSCHI

2013-05-01

Full Text Available The strategies of investment portfolios management on the capital market involves a range of transactions with different financial securities, aimed at optimizing the results. On a developed and efficient capital market, with a high liquidity level, portfolio management primarly depends on investor’s targeted level of return and the risk profile of the investor. Passive strategy of investment portfolios management is applied especially by risk aversion investors, who are taking into account all existing risks in the capital market and seeking to preserve the value of investments, rather than increasing its value. This strategy presume that the investor has no information about the prices and the return of securities that would make him to give to his investment portfolio a different structure from the structure of capital market portfolio. Therefore, he will seek a return level equal to the return on the market portfolio, minimizing the portfolio risk up to eliminating the specific risk.

Quantitative investment strategies and portfolio management

NARCIS (Netherlands)

Guo, J.

2012-01-01

This book contains three essays on alternative investments and portfolio management. Taking from a portfolio investor’s perspective, the first essay analyzes the portfolio implication of investing in hedge funds when there is a hedge fund lockup period. The second essay studies the investment

Optimal diversification of the securities portfolio

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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

Formation of the Optimal Investment Portfolio as a Precondition for the Bank’s Financial Security

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Anna Shapovalova

2015-01-01

Full Text Available This article analyses the definition of the bank’s financial security and investment activities. It describes a few types of models of bank’s risks management and the method CAPM, which is chosen for use. In support for the chosen CAPM method, we included the mathematical model that allows elaborating an optimal investment portfolio. The model stands at the basis of this method and a case study of one of Ukrainian banks.

Formation of the Optimal Investment Portfolio as a Precondition for the Bank’s Financial Security

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Anna Shapovalova

2016-01-01

Full Text Available This article analyses the definition of the bank’s financial security and investment activities. It describes a few types of models of bank’s risks management and the method CAPM, which is chosen for use. In support for the chosen CAPM method, we included the mathematical model that allows elaborating an optimal investment portfolio. The model stands at the basis of this method and a case study of one of Ukrainian banks.

The returns and risks of investment portfolio in stock market crashes

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

2015-06-01

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

PORTFOLIO OPTIMIZATION ON CROATIAN CAPITAL MARKET

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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%.

Power sector investment risk and renewable energy: A Japanese case study using portfolio risk optimization method

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Bhattacharya, Anindya; Kojima, Satoshi

2012-01-01

The conventional pricing mechanism used for electricity systematically hides huge investment risks which are embedded in the overall cost of production. Although consumers are often unaware of these risks, they present a large financial burden on the economy. This study applies the portfolio optimization concepts from the field of finance to demonstrate the scope of greater utilization of renewable energies (RE) while reducing the embedded investment risk in the conventional electricity sector and its related financial burden. This study demonstrates that RE investment can compensate for the risks associated with the total input costs; such costs being external volatilities of fossil fuel prices, capital costs, operating and maintenance costs and the carbon costs. By means of example, this case study shows that Japan could in theory obtain up to 9% of its electricity supply from green sources, as compared to the present 1.37%, based on the utilization of a portfolio risk-analysis evaluation. Explicit comparison of the monetary values of the investment risks of conventional and renewable energy sources shows that renewable energies have high market competitiveness. The study concludes with a recommendation that, as a business objective, investors would benefit by focusing on electricity supply portfolio risk minimization instead of cost. This could also inherently increase the supply of renewable energy in the market. - Research highlights: ►Energy sector investors should not be bothered only about the absolute cost figures of the input factors like fossil fuels but should also be careful about the fluctuation of their costs while making the investment decisions. ►Inclusion of renewable energy in the investment portfolio can increase the cost apparently but can reduce the risk hedging costs, too. ►International carbon price may not be a good factor to encourage renewable energy investment in the market.

Cluster analysis for portfolio optimization

OpenAIRE

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...

Portfolio Optimization of Nanomaterial Use in Clean Energy Technologies.

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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.

Random Matrix Approach for Primal-Dual Portfolio Optimization Problems

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Tada, Daichi; Yamamoto, Hisashi; Shinzato, Takashi

2017-12-01

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

Application of Markowitz Portfolio Theory by Building Optimal Portfolio on the US Stock Market

OpenAIRE

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...

Comparison of Portfolio Selection and Performance: Shari’ah-Compliant and Socially Responsible Investment Portfolios

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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. 

Fuzzy portfolio optimization advances in hybrid multi-criteria methodologies

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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...

Foreign Direct Investment versus Portfolio Investment : A Global Games Approach

OpenAIRE

Yamin Ahmad; Pietro Cova; Rodrigo Harrison

2004-01-01

We present a model of investment under uncertainty about fundamentals, using a global games approach. Goldstein & Razin (2003) show that there is an information based trade-off between foreign direct investment (FDI) and portfolio investment (PI) which rationalizes some well known stylised facts in the literature - the relative volatility and reversibility of foreign direct investment versus portfolio investment. We extend their result and show that uncertainty about fundamentals does not imp...

Linear versus quadratic portfolio optimization model with transaction cost

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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.

Real Time Investments with Adequate Portfolio Theory

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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.

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

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

2017-01-01

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

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

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Shinzato, Takashi

2016-12-01

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

Optimal consumption—portfolio problem with CVaR constraints

International Nuclear Information System (INIS)

Zhang, Qingye; Gao, Yan

2016-01-01

The optimal portfolio selection is a fundamental issue in finance, and its two most important ingredients are risk and return. Merton's pioneering work in dynamic portfolio selection emphasized only the expected utility of the consumption and the terminal wealth. To make the optimal portfolio strategy be achievable, risk control over bankruptcy during the investment horizon is an indispensable ingredient. So, in this paper, we consider the consumption-portfolio problem coupled with a dynamic risk control. More specifically, different from the existing literature, we impose a dynamic relative CVaR constraint on it. By the stochastic dynamic programming techniques, we derive the corresponding Hamilton–Jacobi–Bellman (HJB) equation. Moreover, by the Lagrange multiplier method, the closed form solution is provided when the utility function is a logarithmic one. At last, an illustrative empirical study is given. The results show the distinct difference of the portfolio strategies with and without the CVaR constraints: the proportion invested in the risky assets is reduced over time with CVaR constraint instead of being constant without CVaR constraints. This can provide a good decision-making reference for the investors.

A Simulation Approach to Statistical Estimation of Multiperiod Optimal Portfolios

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Hiroshi Shiraishi

2012-01-01

Full Text Available This paper discusses a simulation-based method for solving discrete-time multiperiod portfolio choice problems under AR(1 process. The method is applicable even if the distributions of return processes are unknown. We first generate simulation sample paths of the random returns by using AR bootstrap. Then, for each sample path and each investment time, we obtain an optimal portfolio estimator, which optimizes a constant relative risk aversion (CRRA utility function. When an investor considers an optimal investment strategy with portfolio rebalancing, it is convenient to introduce a value function. The most important difference between single-period portfolio choice problems and multiperiod ones is that the value function is time dependent. Our method takes care of the time dependency by using bootstrapped sample paths. Numerical studies are provided to examine the validity of our method. The result shows the necessity to take care of the time dependency of the value function.

Application of Markowitz Portfolio Theory by Building Optimal Portfolio on the US Stock Market

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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.

Log-Optimal Portfolio Selection Using the Blackwell Approachability Theorem

OpenAIRE

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...

Investment risk management by applying contemporary modern portfolio theory

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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.

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

Science.gov (United States)

Qaradaghi, Mohammed

Complexity of the capital intensive oil and gas portfolio investments is continuously growing. It is manifested in the constant increase in the type, number and degree of risks and uncertainties, which consequently lead to more challenging decision making problems. A typical complex decision making problem in petroleum exploration and production (E&P) is the selection and prioritization of oilfields/projects in a portfolio investment. Prioritizing oilfields maybe required for different purposes, including the achievement of a targeted production and allocation of limited available development resources. These resources cannot be distributed evenly nor can they be allocated based on the oilfield size or production capacity alone since various other factors need to be considered simultaneously. These factors may include subsurface complexity, size of reservoir, plateau production and needed infrastructure in addition to other issues of strategic concern, such as socio-economic, environmental and fiscal policies, particularly when the decision making involves governments or national oil companies. Therefore, it would be imperative to employ decision aiding tools that not only address these factors, but also incorporate the decision makers' preferences clearly and accurately. However, the tools commonly used in project portfolio selection and optimization, including intuitive approaches, vary in their focus and strength in addressing the different criteria involved in such decision problems. They are also disadvantaged by a number of drawbacks, which may include lacking the capacity to address multiple and interrelated criteria, uncertainty and risk, project relationship with regard to value contribution and optimum resource utilization, non-monetary attributes, decision maker's knowledge and expertise, in addition to varying levels of ease of use and other practical and theoretical drawbacks. These drawbacks have motivated researchers to investigate other tools and

Alternative Investments: Valuation of Wine as a Means for Portfolio Diversification

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Daiva Jurevičienė

2015-03-01

Full Text Available This article analyses wine as an alternative investment tool and its relevance for investment portfolio diversification. Advantages and disadvantages of alternatives, benefits and weakness and peculiarities of investing in wine are systemised. In addition, the article looks at statistical data analysis of fine wine market and compares wine with other investment tools. The examination is based on three investment instruments: US equities (using S&P 500 index, bonds (using US 20-Year treasury constant maturity rate/DGS20 and wine (based on Fine Wine Investable index using 1993–2012 (end of year data. The investment portfolios made with two and three above-mentioned investment tools basing on H. Markowitz’s investment portfolio theory and effective curves are presented. It was found that return on investments only from equities and bonds or wine and one of these traditional instruments are signally less than from the investment mix of all three tools. Furthermore, portfolios made only from equities and bonds provide the lowest return compared to others. Choosing from two investments portfolios, results of bond/wine portfolios propose higher return with the same risk level compared to equities/wine portfolio. Consequently, despite some slowdown of wine index during financial crises, wine relevance for portfolio diversification in post crises period was proved.

An Optimal Portfolio and Capital Management Strategy for Basel III Compliant Commercial Banks

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Grant E. Muller

2014-01-01

Full Text Available We model a Basel III compliant commercial bank that operates in a financial market consisting of a treasury security, a marketable security, and a loan and we regard the interest rate in the market as being stochastic. We find the investment strategy that maximizes an expected utility of the bank’s asset portfolio at a future date. This entails obtaining formulas for the optimal amounts of bank capital invested in different assets. Based on the optimal investment strategy, we derive a model for the Capital Adequacy Ratio (CAR, which the Basel Committee on Banking Supervision (BCBS introduced as a measure against banks’ susceptibility to failure. Furthermore, we consider the optimal investment strategy subject to a constant CAR at the minimum prescribed level. We derive a formula for the bank’s asset portfolio at constant (minimum CAR value and present numerical simulations on different scenarios. Under the optimal investment strategy, the CAR is above the minimum prescribed level. The value of the asset portfolio is improved if the CAR is at its (constant minimum value.

On the optimization of a CAPM portfolio using lower partial moments as measure of risk and using the possibility of safeguarding its loss

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Spreitzer, U. W.; Reznik, V.

2007-05-01

Using a portfolio built from bonds (investment without volatility) and shares (investment with volatility) corresponding to the CAPM we calculate the possible loss of this portfolio. The loss is measured by a so-called lower partial moment of the rate of return of the portfolio. Using this loss, we optimize the composition of the portfolio with respect to this loss. Also we investigate the optimization of the portfolio when the loss can be underwritten by an insurance. Concerning the premium of this insurance contract, we show that when the premium is defined inadequate, e.g. proportional to the investment or proportional to the amount of investment in shares, the optimal portfolio consists only of investment in shares. When the premium is defined more suitable, e.g. proportional to the loss, the optimal portfolio is built by an investment in bonds and shares.

Portfolio optimization for index tracking modelling in Malaysia stock market

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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.

Investment portfolio management from cybernetic point of view

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Marchev, Angel, Jr.; Marchev, Angel

2013-12-01

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

Assessing the economic value of co-optimized grid-scale energy storage investments in supporting high renewable portfolio standards

International Nuclear Information System (INIS)

Go, Roderick S.; Munoz, Francisco D.; Watson, Jean-Paul

2016-01-01

Highlights: • We present a MILP to co-optimize generation, transmission, and storage investments. • We find significant value in co-optimized storage via investment deferrals. • Operational savings from bulk services are small relative to investment deferrals. • Co-optimized energy storage significantly reduces prices associated with RPS. - Abstract: Worldwide, environmental regulations such as Renewable Portfolio Standards (RPSs) are being broadly adopted to promote renewable energy investments. With corresponding increases in renewable energy deployments, there is growing interest in grid-scale energy storage systems (ESS) to provide the flexibility needed to efficiently deliver renewable power to consumers. Our contribution in this paper is to introduce a unified generation, transmission, and bulk ESS expansion planning model subject to an RPS constraint, formulated as a two-stage stochastic mixed-integer linear program (MILP) optimization model, which we then use to study the impact of co-optimization and evaluate the economic interaction between investments in these three asset classes in achieving high renewable penetrations. We present numerical case studies using the 24-bus IEEE RTS-96 test system considering wind and solar as available renewable energy resources, and demonstrate that up to $180 million/yr in total cost savings can result from the co-optimization of all three assets, relative to a situation in which no ESS investment options are available. Surprisingly, we find that co-optimized bulk ESS investments provide significant economic value through investment deferrals in transmission and generation capacity, but very little savings in operational cost. Finally, we observe that planning transmission and generation infrastructure first and later optimizing ESS investments—as is common in industry—captures at most 1.7% ($3 million/yr) of the savings that result from co-optimizing all assets simultaneously.

The returns and risks of investment portfolio in a financial market

Science.gov (United States)

Li, Jiang-Cheng; Mei, Dong-Cheng

2014-07-01

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

Portfolio Optimization and Mortgage Choice

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Maj-Britt Nordfang

2017-01-01

Full Text Available This paper studies the optimal mortgage choice of an investor in a simple bond market with a stochastic interest rate and access to term life insurance. The study is based on advances in stochastic control theory, which provides analytical solutions to portfolio problems with a stochastic interest rate. We derive the optimal portfolio of a mortgagor in a simple framework and formulate stylized versions of mortgage products offered in the market today. This allows us to analyze the optimal investment strategy in terms of optimal mortgage choice. We conclude that certain extreme investors optimally choose either a traditional fixed rate mortgage or an adjustable rate mortgage, while investors with moderate risk aversion and income prefer a mix of the two. By matching specific investor characteristics to existing mortgage products, our study provides a better understanding of the complex and yet restricted mortgage choice faced by many household investors. In addition, the simple analytical framework enables a detailed analysis of how changes to market, income and preference parameters affect the optimal mortgage choice.

Risk and utility in portfolio optimization

Science.gov (United States)

Cohen, Morrel H.; Natoli, Vincent D.

2003-06-01

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

An Information-Based Trade Off between Foreign Direct Investment and Foreign Portfolio Investment

OpenAIRE

Itay Goldstein; Assaf Razin

2005-01-01

The paper develops a model of foreign direct investments (FDI) and foreign portfolio investments (FPI).The model describes an information-based trade off between direct investments and portfolio investments. Direct investors are more informed about the fundamentals of their projects. This information enables them to manage their projects more efficiently. However, it also creates an asymmetric-information problem in case they need to sell their projects prematurely, and reduces the price they...

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

Science.gov (United States)

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

2017-03-01

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

Portfolio optimization retail investor

Directory of Open Access Journals (Sweden)

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.

Optimal investment portfolio in renewable energy. The Spanish case

International Nuclear Information System (INIS)

Munoz, Jose Ignacio; Sanchez de la Nieta, Agustin A.; Contreras, Javier; Bernal-Agustin, Jose L.

2009-01-01

This article presents a model for investing in renewable energies in the framework of the Spanish electricity market in a way that risk is minimised for the investor while returns are maximised. The model outlined here is based on an economic model for calculating cash flows intended to obtain the internal rate of return (IRR) of the different energies being studied: wind, photovoltaic, mini hydro and thermo electrical. The IRRs obtained are considered the returns on investments, while their standard deviations are considered associated risks. In order to minimise risk, a comprehensive portfolio of investments is created that includes all of the available energies by means of a system of linear equations. The solution of the linear system is graphically checked using the efficient frontier method for the different financing options. Several case studies within the Renewable Energies Plan (PER is its Spanish abbreviation) that is in force in Spain in the period 2005-2010 are analysed in order to illustrate the method, as are other case studies using different types of financing, helping us to reach the pertinent conclusions. (author)

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

Science.gov (United States)

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

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

Optimization of revenues from a distributed generation portfolio: a case study

NARCIS (Netherlands)

Geysen, D.; Kessels, K.; Hommelberg, M.; Ghijsen, M.; Tielemans, Y.; Vinck, K.

2011-01-01

Many companies are investing in energy production from renewable energy sources and are looking at ways to optimize their portfolio performance. The case study under consideration aims at maximizing the revenues from such a distributed energy generation portfolio, consisting of gas engines and a PV

Dynamic Portfolio Strategy Using Clustering Approach.

Science.gov (United States)

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.

Directory of Open Access Journals (Sweden)

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.

Portfolio Optimization with Stochastic Dividends and Stochastic Volatility

Science.gov (United States)

Varga, Katherine Yvonne

2015-01-01

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

Portfolio Implementation Risk Management Using Evolutionary Multiobjective Optimization

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David Quintana

2017-10-01

Full Text Available Portfolio management based on mean-variance portfolio optimization is subject to different sources of uncertainty. In addition to those related to the quality of parameter estimates used in the optimization process, investors face a portfolio implementation risk. The potential temporary discrepancy between target and present portfolios, caused by trading strategies, may expose investors to undesired risks. This study proposes an evolutionary multiobjective optimization algorithm aiming at regions with solutions more tolerant to these deviations and, therefore, more reliable. The proposed approach incorporates a user’s preference and seeks a fine-grained approximation of the most relevant efficient region. The computational experiments performed in this study are based on a cardinality-constrained problem with investment limits for eight broad-category indexes and 15 years of data. The obtained results show the ability of the proposed approach to address the robustness issue and to support decision making by providing a preferred part of the efficient set. The results reveal that the obtained solutions also exhibit a higher tolerance to prediction errors in asset returns and variance–covariance matrix.

Large-Scale Portfolio Optimization Using Multiobjective Evolutionary Algorithms and Preselection Methods

Directory of Open Access Journals (Sweden)

B. Y. Qu

2017-01-01

Full Text Available Portfolio optimization problems involve selection of different assets to invest in order to maximize the overall return and minimize the overall risk simultaneously. The complexity of the optimal asset allocation problem increases with an increase in the number of assets available to select from for investing. The optimization problem becomes computationally challenging when there are more than a few hundreds of assets to select from. To reduce the complexity of large-scale portfolio optimization, two asset preselection procedures that consider return and risk of individual asset and pairwise correlation to remove assets that may not potentially be selected into any portfolio are proposed in this paper. With these asset preselection methods, the number of assets considered to be included in a portfolio can be increased to thousands. To test the effectiveness of the proposed methods, a Normalized Multiobjective Evolutionary Algorithm based on Decomposition (NMOEA/D algorithm and several other commonly used multiobjective evolutionary algorithms are applied and compared. Six experiments with different settings are carried out. The experimental results show that with the proposed methods the simulation time is reduced while return-risk trade-off performances are significantly improved. Meanwhile, the NMOEA/D is able to outperform other compared algorithms on all experiments according to the comparative analysis.

Bond portfolio's duration and investment term-structure management problem

OpenAIRE

Liu, Daobai

2006-01-01

In the considered bond market, there are N zero-coupon bonds transacted continuously, which will mature at equally spaced dates. A duration of bond portfolios under stochastic interest rate model is introduced, which provides a measurement for the interest rate risk. Then we consider an optimal bond investment term-structure management problem using this duration as a performance index, and with the short-term interest rate process satisfying some stochastic differential ...

Large deviations and portfolio optimization

Science.gov (United States)

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.

Comparative Analysis of Investment Funds Stocks-based Portfolios and BET Stocks-based Portfolios

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Ion STANCU

2010-04-01

Full Text Available In this paper we intend to find out what is the best choice of stocks-based portfolio. The major goal is to find whether is more efficient to invest the whole capital in a single sector, like financial investments, or to create a diversified portfolio, taking into account assets from various economic sectors. Capital allocation will be based on the concept of cointegration. We have chosen this method because it can be applied on non-stationary data series, and, besides, it has the advantage of using the whole set of information provided by the financial assets. Another goal is to study how the portfolio structure adjusts if a shock occurs during the period under analysis so that to preserve a certain return or minimize a potential loss. The study will result in an investment solution in the Romanian capital market, even in the context of financial crisis.

Mean-Variance Portfolio Selection with a Fixed Flow of Investment in ...

African Journals Online (AJOL)

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 ...

Optimal lag in dynamical investments

OpenAIRE

Serva, M.

1998-01-01

A portfolio of different stocks and a risk-less security whose composition is dynamically maintained stable by trading shares at any time step leads to a growth of the capital with a nonrandom rate. This is the key for the theory of optimal-growth investment formulated by Kelly. In presence of transaction costs, the optimal composition changes and, more important, it turns out that the frequency of transactions must be reduced. This simple observation leads to the definition of an optimal lag...

Macroeconomic factors and foreign portfolio investment volatility: A case of South Asian countries

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Yahya Waqas

2015-12-01

Full Text Available Macroeconomic factors play a pivotal role in attracting foreign investment in the country. This study investigates the relationship between macroeconomic factors and foreign portfolio investment volatility in South Asian countries. The monthly data is collected for the period ranging from 2000 to 2012 for four Asian countries i.e. China, India, Pakistan and Sri Lanka because monthly data is ideal for measuring portfolio investment volatility. For measuring volatility in foreign portfolio investment, GARCH (1,1 is used because shocks are responded quickly by this model. The results reveal that there exists significant relationship between macroeconomic factors and foreign portfolio investment volatility. Thus, less volatility in international portfolio flows is associated with high interest rate, currency depreciation, foreign direct investment, lower inflation, and higher GDP growth rate of the host country. Thus findings of this study suggest that foreign portfolio investors focus on stable macroeconomic environment of country.

Growth Optimal Portfolio Selection Under Proportional Transaction Costs with Obligatory Diversification

International Nuclear Information System (INIS)

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.

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

Science.gov (United States)

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.

Optimal static allocation decisions in the presence of portfolio insurance

OpenAIRE

Goltz, Felix; Martellini, Lionel; Şimşek, Koray Deniz; Simsek, Koray Deniz

2008-01-01

The focus of this paper is to determine what fraction a myopic risk-averse investor should allocate to investment strategies with convex exposure to stock market returns in a general economy with stochastically time-varying interest rates and equity risk premium. Our conclusion is that typical investors should optimally allocate a sizable fraction of their portfolio to such portfolio insurance strategies, and the associated utility gains are significant. While the fact that static investors w...

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

Science.gov (United States)

Liu, Qingshan; Dang, Chuangyin; Huang, Tingwen

2013-02-01

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

Optimal annuity portfolio under inflation risk

DEFF Research Database (Denmark)

Konicz, Agnieszka Karolina; Pisinger, David; Weissensteiner, Alex

2015-01-01

The paper investigates the importance of in ation-linked annuities to individuals facing in ation risk. Given the investment opportunities in nominal, real, and variable annuities, as well as cash and stocks, we investigate the consumption and investment decisions under two different objective fu...... and risk aversion, real annuities are a crucial asset in every portfolio. In addition, without investing in real annuities, the retiree has to rebalance the portfolio more frequently, and still obtains the lower and more volatile real consumption....

An Analysis of a Free Cashflow Portfolio Investment Strategy ...

African Journals Online (AJOL)

An Analysis of a Free Cashflow Portfolio Investment Strategy. ... African Journal of Finance and Management ... risks that are less than one, so without additional risk, the investment strategy yields higher returns than an international investment ...

Replica Analysis for Portfolio Optimization with Single-Factor Model

Science.gov (United States)

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.

Ant Colony Optimization for Markowitz Mean-Variance Portfolio Model

Science.gov (United States)

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.

Portfolio Optimization under Local-Stochastic Volatility: Coefficient Taylor Series Approximations & Implied Sharpe Ratio

OpenAIRE

Lorig, Matthew; Sircar, Ronnie

2015-01-01

We study the finite horizon Merton portfolio optimization problem in a general local-stochastic volatility setting. Using model coefficient expansion techniques, we derive approximations for the both the value function and the optimal investment strategy. We also analyze the `implied Sharpe ratio' and derive a series approximation for this quantity. The zeroth-order approximation of the value function and optimal investment strategy correspond to those obtained by Merton (1969) when the risky...

Optimal portfolio selection for general provisioning and terminal wealth problems

NARCIS (Netherlands)

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

NARCIS (Netherlands)

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

The rule of nuclear power in the base-load portfolio optimization process

International Nuclear Information System (INIS)

Desiata, L.; D'Alberti, F.

2007-01-01

The pursuit of optimal portfolios, maximizing long-term profitability, is the main strategic challenge faced by electricity producers nowadays. Investment decisions, worth billions of euros, are affected by spot factors (such as current fuel prices volatility) that often lead to unbalanced generation mixes. Our analysis presents a statistical-financial approach that highlights the role of nuclear within the base-load portfolio optimisation process [it

Enhanced index tracking modeling in portfolio optimization with mixed-integer programming z approach

Science.gov (United States)

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 optimization based on nonparametric estimation methods

Directory of Open Access Journals (Sweden)

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.

Multi-Period Portfolio Optimization of Power Generation Assets

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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

Portfolio management for investment projects in the construction industry

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Kozlov Alexander

2017-01-01

Full Text Available The Russian business community has realized the need for project/targeted programme management procedures; therefore, the demand for customized project-oriented management methods goes up. In the meantime, this demand is not supplied in full, and the supply is far from being efficient. Project management methodologies need further improvement, including development of portfolio management processes applicable to investment projects developed and implemented in the construction industry. The article considers General approaches to the formalization of the management of portfolios of investment–construction projects. For the main groups of processes portfolio management (“Formation and alignment”, “Monitoring and control” and “Support and development” deals with their constituent sub-processes. The proposed decomposition can be used for both portfolio construction and investment projects and also has an invariant character, which allows extending the proposed approaches to other system target–oriented and project–oriented management.

Replica analysis for the duality of the portfolio optimization problem.

Science.gov (United States)

Shinzato, Takashi

2016-11-01

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

Replica analysis for the duality of the portfolio optimization problem

Science.gov (United States)

Shinzato, Takashi

2016-11-01

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

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

Science.gov (United States)

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

2015-11-15

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

Risk-averse portfolio selection of renewable electricity generator investments in Brazil: An optimised multi-market commercialisation strategy

International Nuclear Information System (INIS)

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.

Portfolio assessments for future generation investment in newly industrializing countries – A case study of Thailand

International Nuclear Information System (INIS)

Vithayasrichareon, Peerapat; MacGill, Iain F.

2012-01-01

This paper assesses future electricity generation portfolios in Thailand in 2030 given uncertain future fossil-fuel prices, carbon pricing policies, electricity demand, and capital costs. Thailand faces challenges for generation investment given its rapid socio-economic progress and fast growing demand. A novel generation investment and planning decision-support tool which incorporates a Monte Carlo extension to conventional optimal generation mix methods combined with portfolio-based analysis techniques, is used. The tool can formally assess tradeoffs between expected future generation costs, cost uncertainties, and CO 2 emissions for the range of different generation portfolios. Results highlight that different levels of future carbon pricing will have significant impacts on the most appropriate generation portfolios. The impact of carbon pricing, however, is not on the appropriate proportion of combined cycle gas turbines (CCGT) in the mix but, instead, on the future role of coal versus nuclear in Thailand. Compared with the current proposed 2030 generation mix, it is possible that there are other generation portfolios that offer lower expected costs, cost uncertainty, and CO 2 emissions depending on future carbon pricing. Results suggest that this investment decision-support approach may have value for electric utilities and policy-makers contemplating significant generation investments under high future uncertainty and conflicting policy objectives. -- Highlights: ► Assess Thailand's future generation portfolios in 2030 under uncertainties. ► Future carbon prices have significant impacts on the appropriate generation mixes. ► Carbon pricing affects the future role of coal versus nuclear in Thailand. ► There may be more appropriate alternatives than the proposed 2030 generation mix. ► This decision-support approach has value for utility and policy decision-making.

Comparative evaluation of fuzzy logic and genetic algorithms models for portfolio optimization

Directory of Open Access Journals (Sweden)

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.

Robust and Reliable Portfolio Optimization Formulation of a Chance Constrained Problem

Directory of Open Access Journals (Sweden)

Sengupta Raghu Nandan

2017-02-01

Full Text Available We solve a linear chance constrained portfolio optimization problem using Robust Optimization (RO method wherein financial script/asset loss return distributions are considered as extreme valued. The objective function is a convex combination of portfolio’s CVaR and expected value of loss return, subject to a set of randomly perturbed chance constraints with specified probability values. The robust deterministic counterpart of the model takes the form of Second Order Cone Programming (SOCP problem. Results from extensive simulation runs show the efficacy of our proposed models, as it helps the investor to (i utilize extensive simulation studies to draw insights into the effect of randomness in portfolio decision making process, (ii incorporate different risk appetite scenarios to find the optimal solutions for the financial portfolio allocation problem and (iii compare the risk and return profiles of the investments made in both deterministic as well as in uncertain and highly volatile financial markets.

The Dirichlet Portfolio Model: Uncovering the Hidden Composition of Hedge Fund Investments

OpenAIRE

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...

Portfolio optimization and performance evaluation

DEFF Research Database (Denmark)

Juhl, Hans Jørn; Christensen, Michael

2013-01-01

Based on an exclusive business-to-business database comprising nearly 1,000 customers, the applicability of portfolio analysis is documented, and it is examined how such an optimization analysis can be used to explore the growth potential of a company. As opposed to any previous analyses, optimal...... customer portfolios are determined, and it is shown how marketing decision-makers can use this information in their marketing strategies to optimize the revenue growth of the company. Finally, our analysis is the first analysis which applies portfolio based methods to measure customer performance......, and it is shown how these performance measures complement the optimization analysis....

Comparison of Optimal Portfolios Selected by Multicriterial Model Using Absolute and Relative Criteria Values

Directory of Open Access Journals (Sweden)

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.

Research on the robust optimization of the enterprise's decision on the investment to the collaborative innovation: Under the risk constraints

International Nuclear Information System (INIS)

Zhou, Qing; Fang, Gang; Wang, Dong-peng; Yang, Wei

2016-01-01

Abstracts: The robust optimization model is applied to analyze the enterprise's decision of the investment portfolio for the collaborative innovation under the risk constraints. Through the mathematical model deduction and the simulation analysis, the research result shows that the enterprise's investment to the collaborative innovation has relatively obvious robust effect. As for the collaborative innovation, the return from the investment coexists with the risk of it. Under the risk constraints, the robust optimization method could solve the minimum risk as well as the proportion of each investment scheme in the portfolio on the condition of different target returns from the investment. On the basis of the result, the enterprise could balance between the investment return and risk and make optimal decision on the investment scheme.

More efficient optimization of long-term water supply portfolios

Science.gov (United States)

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

2009-03-01

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

Portfolios of adaptation investments in water management

NARCIS (Netherlands)

Aerts, Jeroen C.J.H.; Botzen, Wouter; Werners, Saskia E.

2015-01-01

This study explores how Modern Portfolio Theory (MPT) can guide investment decisions in integrated water resources management (IWRM) and climate change adaptation under uncertainty. The objectives of the paper are to: (i) explain the concept of diversification to reduce risk, as formulated in

Exploring International Investment through a Classroom Portfolio Simulation Project

Science.gov (United States)

Chen, Xiaoying; Yur-Austin, Jasmine

2013-01-01

A rapid integration of financial markets has prevailed during the last three decades. Investors are able to diversify investment beyond national markets to mitigate return volatility of a "pure domestic portfolio." This article discusses a simulation project through which students learn the role of international investment by managing…

Optimal Portfolio Rebalancing Strategy : Evidence from Finnish Stocks

OpenAIRE

Savage, Akinwunmi

2010-01-01

Portfolio rebalancing is an established concept in portfolio management and investing generally. Assets within a portfolio have different return and risk prospects, and this inevitably leads them to drift away from their initial allocation weights overtime. Portfolio rebalancing is arguably the only method by which such assets can be reset to their initial weights, thus ensuring the portfolio reflects the risk appetite of the investor. Like many other concepts and practices in finance, portfo...

Analysis of Scientific and Methodical Approaches to Portfolio Investment as a Tool of Financial Provision of Sustainable Economic Development

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Leus Daryna V.

2013-12-01

Full Text Available The article analyses scientific and methodical approaches to portfolio investment. It develops recommendations on specification of the categorical apparatus of portfolio investment in the context of differentiation of strategic (direct and portfolio investments as alternative approaches to the conduct of investment activity. It identifies the composition and functions of objects and subjects of portfolio investment under conditions of globalisation of the world financial markets. It studies main postulates of the portfolio theory and justifies a necessity of identification of the place, role and functions of subjects of portfolio investment in them for ensuring sustainable development of the economy. It offers to specify, as one of the ways of further development of portfolio theories, a separate direction in the financial provision of economy with consideration of ecologic and social components – socio responsible investment.

Aircraft technology portfolio optimization using ant colony optimization

Science.gov (United States)

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.

Alternatives in international diversification for investment portfolios focused in stocks of Lima Stock Exchange

OpenAIRE

Juan Carlos Ames Santillán

2012-01-01

This paper gives an estimation of efficient frontiers for investment portfolios, they include stocks from Lima Stock Exchange General Index, Dow Jones Industrial Average, Gold, Cooper, Fixed Income Instruments of Peruvian government and savings in Peruvian financial institutions. The paper concludes that risk of investment in local portfolio reduces as a consequence of diversification, gold is an important asset and contributes to reduce portfolio risk.

Investment Portfolios in an Emerging Economy: What Drives Portfolio’s Diversification?

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Pedro Luiz Albertin Bono Milan

2017-09-01

Full Text Available This study sheds light on the investment portfolio’s decisions through behavioral insights. The study intends to identify personal characteristics that drive the level of diversification and lead investors to allocate resources in risky assets in an emergent economy, deepening the discussion about investment decisions and bringing some behavioral insights to the debate. The study has a unique and heterogeneous database of individual financial allocations from Brazil, one of the largest emergent economies. The characteristics of Brazilian investors play an important role in investment decisions, high educated and married investors tend to display diversified portfolios. To invest in risky assets, male investors have a 43% greater likelihood of investing in risky assets than females, highlighting the discussion on gender and investment decisions. Moreover, married investors tend to exhibit conservative portfolios. We observed that traditional investors are under-diversified, allocating primarily in traditional and safety assets. The results suggest that the investment decisions can be subject to psychological biases defined in behavioral finance theory.

Alternatives in international diversification for investment portfolios focused in stocks of Lima Stock Exchange

Directory of Open Access Journals (Sweden)

Juan Carlos Ames Santillán

2012-06-01

Full Text Available This paper gives an estimation of efficient frontiers for investment portfolios, they include stocks from Lima Stock Exchange General Index, Dow Jones Industrial Average, Gold, Cooper, Fixed Income Instruments of Peruvian government and savings in Peruvian financial institutions. The paper concludes that risk of investment in local portfolio reduces as a consequence of diversification, gold is an important asset and contributes to reduce portfolio risk.

Alternatives in international diversification for investment portfolios focused in stocks of Lima Stock Exchange

OpenAIRE

Ames Santillán, Juan Carlos

2012-01-01

This paper gives an estimation of efficient frontiers for investment portfolios, they include stocks from Lima Stock Exchange General Index, Dow Jones Industrial Average, Gold, Cooper, Fixed Income Instruments of Peruvian government and savings in Peruvian financial institutions. The paper concludes that risk of investment in local portfolio reduces as a consequence of diversification, gold is an important asset and contributes to reduce portfolio risk. El presente trabajo estima la fronte...

Comonotonic approximations for a generalized provisioning problem with application to optimal portfolio selection

NARCIS (Netherlands)

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

Transaction fees and optimal rebalancing in the growth-optimal portfolio

OpenAIRE

Yu Feng; Matus Medo; Liang Zhang; Yi-Cheng Zhang

2010-01-01

The growth-optimal portfolio optimization strategy pioneered by Kelly is based on constant portfolio rebalancing which makes it sensitive to transaction fees. We examine the effect of fees on an example of a risky asset with a binary return distribution and show that the fees may give rise to an optimal period of portfolio rebalancing. The optimal period is found analytically in the case of lognormal returns. This result is consequently generalized and numerically verified for broad return di...

Portfolio optimization using fundamental indicators based on multi-objective EA

CERN Document Server

Silva, Antonio Daniel; Horta, Nuno

2016-01-01

This work presents a new approach to portfolio composition in the stock market. It incorporates a fundamental approach using financial ratios and technical indicators with a Multi-Objective Evolutionary Algorithms to choose the portfolio composition with two objectives the return and the risk. Two different chromosomes are used for representing different investment models with real constraints equivalents to the ones faced by managers of mutual funds, hedge funds, and pension funds. To validate the present solution two case studies are presented for the SP&500 for the period June 2010 until end of 2012. The simulations demonstrates that stock selection based on financial ratios is a combination that can be used to choose the best companies in operational terms, obtaining returns above the market average with low variances in their returns. In this case the optimizer found stocks with high return on investment in a conjunction with high rate of growth of the net income and a high profit margin. To obtain s...

Optimal Portfolio Strategy under Rolling Economic Maximum Drawdown Constraints

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Xiaojian Yu

2014-01-01

Full Text Available This paper deals with the problem of optimal portfolio strategy under the constraints of rolling economic maximum drawdown. A more practical strategy is developed by using rolling Sharpe ratio in computing the allocation proportion in contrast to existing models. Besides, another novel strategy named “REDP strategy” is further proposed, which replaces the rolling economic drawdown of the portfolio with the rolling economic drawdown of the risky asset. The simulation tests prove that REDP strategy can ensure the portfolio to satisfy the drawdown constraint and outperforms other strategies significantly. An empirical comparison research on the performances of different strategies is carried out by using the 23-year monthly data of SPTR, DJUBS, and 3-month T-bill. The investment cases of single risky asset and two risky assets are both studied in this paper. Empirical results indicate that the REDP strategy successfully controls the maximum drawdown within the given limit and performs best in both return and risk.

Credibilistic multi-period portfolio optimization based on scenario tree

Science.gov (United States)

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.

Analysis of the rebalancing frequency in log-optimal portfolio selection

OpenAIRE

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...

RISK MANAGEMENT OF INVESTMENT PORTFOLIO BY FUTURE

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K. Kerimov Alexandr

2017-01-01

Full Text Available The article considers the problem of the dynamic risk management of the investment portfolio using future con- tracts. The management starts with the concept of effective inhomogeneous portfolios, which contain futures together with underlying asserts. The effective portfolios are defined as the ones of the minimal dispersion with the expected return greater or equal to the specified value. Risk is measured by the probability of losing of a certain part of the portfolio value. The control parameters are the number of futures for each asset of portfolio, which is defined from the condition of effec- tiveness of portfolio and risk acceptability on each step.The effective adaptive strategies of portfolio risk management together with comparative analysis on a concrete example are presented. The proposed approach provides the forecast correction of the expected income and its variance for the assets with the emergence of new data. The financial time series are determined by volatility clustering, i.e. relative or absolute price changes tend to keep high or low magnitude for some time, with the result that clusters are created - periods of high or low volatility. Then adaptive estimate of correlational relationships between asset prices are essential because the degree of correlational relationship also changes in time. So the correlation of future and spot price changes considerably increases while approaching to performance of contracts. For taking into account of data instability of dispersion and correlation simple methods of volatility forecasting and correlation of relative changes of price data based on exponential smoothing are implemented.

Investment Portfolio Formation Using Multi-criteria evaluation Method MULTIMOORA

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Vilius Vaišvilas

2017-06-01

Full Text Available Information that has to be analyzed by investors is complicated and can be interpreted differently by different people, which is why choosing what should be added to the investment portfolio is complicated task. Complexity grows substantially when there are more alternatives to choose from. Multi – criteria evaluation method can be used to choose the best alternatives. Multi–criteria evaluation method MULTIMOORA is not subjective because there is no need to decide ratio of any given variable that is evaluated. MULTIMOORA consists of: formation of ratio system, application of multi – criteria evaluation method as well as investment evaluation and ranking. Purpose of this article is to apply multi – criteria evaluation method MULTIMOORA for the formation and management of investment portfolio from stocks of the Baltic stock market companies. Methods used in the analysis for the article: analysis of scientific literature, statistical analysis, organization and comparison of data, idealization, calculations of MULTIMOORA.

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

Science.gov (United States)

Bard, Gregory V.

2016-12-01

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

The development of the portfolio management for the unit investment funds

OpenAIRE

Sergeeva, Irina; Nikiforova, Vera

2012-01-01

The paper analyses common Russian practice of assessment of the effectiveness of the unit investment fund portfolio management based on the risk/return tradeoff. The paper identifies characteristics, advantages and disadvantages of various portfolio risk measures, and introduces the approach to risk assessment based on the analytical coefficient calculations.

Robust Portfolio Optimization Using Pseudodistances

Science.gov (United States)

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

Robust Portfolio Optimization Using Pseudodistances.

Science.gov (United States)

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.

Correlation risk and optimal portfolio choice

OpenAIRE

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...

Replica Approach for Minimal Investment Risk with Cost

Science.gov (United States)

Shinzato, Takashi

2018-06-01

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

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

Science.gov (United States)

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.

Optimization Stock Portfolio With Mean-Variance and Linear Programming: Case In Indonesia Stock Market

Directory of Open Access Journals (Sweden)

Yen Sun

2010-05-01

Full Text Available It is observed that the number of Indonesia’s domestic investor who involved in the stock exchange is very less compare to its total number of population (only about 0.1%. As a result, Indonesia Stock Exchange (IDX is highly affected by foreign investor that can threat the economy. Domestic investor tends to invest in risk-free asset such as deposit in the bank since they are not familiar yet with the stock market and anxious about the risk (risk-averse type of investor. Therefore, it is important to educate domestic investor to involve in the stock exchange. Investing in portfolio of stock is one of the best choices for risk-averse investor (such as Indonesia domestic investor since it offers lower risk for a given level of return. This paper studies the optimization of Indonesian stock portfolio. The data is the historical return of 10 stocks of LQ 45 for 5 time series (January 2004 – December 2008. It will be focus on selecting stocks into a portfolio, setting 10 of stock portfolios using mean variance method combining with the linear programming (solver. Furthermore, based on Efficient Frontier concept and Sharpe measurement, there will be one stock portfolio picked as an optimum Portfolio (Namely Portfolio G. Then, Performance of portfolio G will be evaluated by using Sharpe, Treynor and Jensen Measurement to show whether the return of Portfolio G exceeds the market return. This paper also illustrates how the stock composition of the Optimum Portfolio (G succeeds to predict the portfolio return in the future (5th January – 3rd April 2009. The result of the study observed that optimization portfolio using Mean-Variance (consistent with Markowitz theory combine with linear programming can be applied into Indonesia stock’s portfolio. All the measurements (Sharpe, Jensen, and Treynor show that the portfolio G is a superior portfolio. It is also been found that the composition (weights stocks of optimum portfolio (G can be used to

Portfolio Optimization in a Semi-Markov Modulated Market

International Nuclear Information System (INIS)

Ghosh, Mrinal K.; Goswami, Anindya; Kumar, Suresh K.

2009-01-01

We address a portfolio optimization problem in a semi-Markov modulated market. We study both the terminal expected utility optimization on finite time horizon and the risk-sensitive portfolio optimization on finite and infinite time horizon. We obtain optimal portfolios in relevant cases. A numerical procedure is also developed to compute the optimal expected terminal utility for finite horizon problem

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

Science.gov (United States)

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.

Optimal investment horizons

Science.gov (United States)

Simonsen, I.; Jensen, M. H.; Johansen, A.

2002-06-01

In stochastic finance, one traditionally considers the return as a competitive measure of an asset, i.e., the profit generated by that asset after some fixed time span Δt, say one week or one year. This measures how well (or how bad) the asset performs over that given period of time. It has been established that the distribution of returns exhibits ``fat tails'' indicating that large returns occur more frequently than what is expected from standard Gaussian stochastic processes [1-3]. Instead of estimating this ``fat tail'' distribution of returns, we propose here an alternative approach, which is outlined by addressing the following question: What is the smallest time interval needed for an asset to cross a fixed return level of say 10%? For a particular asset, we refer to this time as the investment horizon and the corresponding distribution as the investment horizon distribution. This latter distribution complements that of returns and provides new and possibly crucial information for portfolio design and risk-management, as well as for pricing of more exotic options. By considering historical financial data, exemplified by the Dow Jones Industrial Average, we obtain a novel set of probability distributions for the investment horizons which can be used to estimate the optimal investment horizon for a stock or a future contract.

Divesting Fossil Fuels : The Implications for Investment Portfolios

NARCIS (Netherlands)

Trinks, Arjan; Scholtens, Bert; Mulder, Machiel; Dam, Lammertjan

2017-01-01

Fossil fuel divestment campaigns urge investors to sell their stakes in companies that supply coal, oil, and gas. However, avoiding investments in such companies can be expected to impose a financial cost on the investor because of reduced opportunities for portfolio diversification. We compare the

A Framework for Managing a Portfolio of Socially Responsible Investments

NARCIS (Netherlands)

W.G.P.M. Hallerbach (Winfried); H. Ning (Haikun); A.B.M. Soppe (Aloy); J. Spronk (Jaap)

2002-01-01

textabstractIn this paper we present and illustrate using real-life data a framework for managing an investment portfolio in which the investment opportunities are described in terms of a set of attributes and part of this set is intended to capture the effects on society. Here we link with the

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

Science.gov (United States)

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.

Portfolios Dominating Indices: Optimization with Second-Order Stochastic Dominance Constraints vs. Minimum and Mean Variance Portfolios

Directory of Open Access Journals (Sweden)

Neslihan Fidan Keçeci

2016-10-01

Full Text Available The paper compares portfolio optimization with the Second-Order Stochastic Dominance (SSD constraints with mean-variance and minimum variance portfolio optimization. As a distribution-free decision rule, stochastic dominance takes into account the entire distribution of return rather than some specific characteristic, such as variance. The paper is focused on practical applications of the portfolio optimization and uses the Portfolio Safeguard (PSG package, which has precoded modules for optimization with SSD constraints, mean-variance and minimum variance portfolio optimization. We have done in-sample and out-of-sample simulations for portfolios of stocks from the Dow Jones, S&P 100 and DAX indices. The considered portfolios’ SSD dominate the Dow Jones, S&P 100 and DAX indices. Simulation demonstrated a superior performance of portfolios with SD constraints, versus mean-variance and minimum variance portfolios.

Portfolio optimization with skewness and kurtosis

Science.gov (United States)

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.

Optimal Portfolio of Corporate Investment and Consumption Problem under Market Closure: Inflation Case

Directory of Open Access Journals (Sweden)

Zongyuan Huang

2013-01-01

Full Text Available We present the model of corporate optimal investment with consideration of the influence of inflation and the difference between the market opening and market closure. In our model, the investor has three market activities of his or her choice: investment in project A, investment in project B, and consumption. The optimal strategy for the investor is obtained using the Hamilton-Jacobi-Bellman equation which is derived using the dynamic programming principle. Further along, a specific case, the Hyperbolic Absolute Risk Aversion case, is discussed in detail, where the explicit optimal strategy can be obtained using a very simple and direct method. At the very end, we present some simulation results along with a brief analysis of the relationship between the optimal strategy and other factors.

Alternative Investments: Valuation of Wine as a Means for Portfolio Diversification

OpenAIRE

Jurevičienė, Daiva; Jakavonytė, Agnė

2015-01-01

This article analyses wine as an alternative investment tool and its relevance for investment portfolio diversification. Advantages and disadvantages of alternatives, benefits and weakness and peculiarities of investing in wine are systemised. In addition, the article looks at statistical data analysis of fine wine market and compares wine with other investment tools. The examination is based on three investment instruments: US equities (using S&P 500 index), bonds (using US 20-Year treasury ...

Windfall profit in portfolio diversification? An empirical analysis of the potential benefits of renewable energy investments

Energy Technology Data Exchange (ETDEWEB)

Bruns, Frederik

2013-05-01

Modern Portfolio Theory is a theory which was introduced by Markowitz, and which suggests the building of a portfolio with assets that have low or, in the best case, negative correlation. In times of financial crises, however, the positive diversification effect of a portfolio can fail when Traditional Assets are highly correlated. Therefore, many investors search for Alternative Asset classes, such as Renewable Energies, that tend to perform independently from capital market performance. 'Windfall Profit in Portfolio Diversification?' discusses the potential role of Renewable Energy investments in an institutional investor's portfolio by applying the main concepts from Modern Portfolio Theory. Thereby, the empirical analysis uses a unique data set from one of the largest institutional investors in the field of Renewable Energies, including several wind and solar parks. The study received the Science Award 2012 of the German Alternative Investments Association ('Bundesverband Alternative Investments e.V.').

Estimation of influence of banks' recourse potential upon their credit and investment portfolio

OpenAIRE

Petro Karas'; Nataliya Prykhod'ko

2015-01-01

In the article the negative trends of the Ukrainian banking system functioning caused by the crisis phenomena are considered. The analysis of credit and investment portfolio and resource potential of Ukrainian banks is carried out. Main problems of this process are identified. Influence of the banks' resource potential upon credit and investment portfolio is estimated by constructing multivariate correlation-regression models. The proposals for the government regulation of the bank's credit a...

Multi-objective portfolio optimization of mutual funds under downside risk measure using fuzzy theory

OpenAIRE

M. Amiri; M. Zandieh; A. Alimi

2012-01-01

Mutual fund is one of the most popular techniques for many people to invest their funds where a professional fund manager invests people's funds based on some special predefined objectives; therefore, performance evaluation of mutual funds is an important problem. This paper proposes a multi-objective portfolio optimization to offer asset allocation. The proposed model clusters mutual funds with two methods based on six characteristics including rate of return, variance, semivariance, turnove...

17 CFR 274.130 - Form N-Q, quarterly schedule of portfolio holdings of registered management investment company.

Science.gov (United States)

2010-04-01

... of portfolio holdings of registered management investment company. 274.130 Section 274.130 Commodity... INVESTMENT COMPANY ACT OF 1940 Forms for Reports § 274.130 Form N-Q, quarterly schedule of portfolio holdings of registered management investment company. This form shall be used by registered management...

Investment Portfolio Simulation: An Assessment Task in Finance

Science.gov (United States)

Parle, Gabrielle; Laing, Gregory K.

2017-01-01

The use of an investment portfolio simulation as an assessment task is intended to reinforce learning by involving students in practical application of theoretical principles in a real-time actual financial market. Simulation as a teaching pedagogy promotes individual involvement and provides students with a deeper understanding of the issues, and…

Particle Swarm Optimization of Electricity Market Negotiating Players Portfolio

DEFF Research Database (Denmark)

Pinto, Tiago; Vale, Zita; Sousa, Tiago

2014-01-01

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors......, the type of day (business day, weekend, holiday, etc.) and most important, the renewable based distributed generation forecast. The proposed approach is tested and validated using real electricity markets data from the Iberian operator – MIBEL.......’ research group has developed a multi-agent system: MASCEM (Multi- Agent System for Competitive Electricity Markets), which performs realistic simulations of the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system...... for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from each market context. However, it is still necessary to adequately optimize the players’ portfolio investment. For this purpose, this paper proposes a market portfolio optimization method...

Investment characteristics, stock characteristics and portfolio diversification of finance professionals

OpenAIRE

Mohammad Tariqul Islam Khan; Siow-Hooi Tan; Lee-Lee Chong; Hway-Boon Ong

2017-01-01

This study estimates if Malaysian finance professionals' investment characteristics and stock characteristics' preferences affect their portfolio diversification, and whether the effects of these predictors vary across professionals' gender, income and experience. Employing a survey and ordinal regression models, the findings demonstrate that investment characteristics such as active trading, usage of internet and telephone, and saving for retirement objective are likely to improve diversific...

Ant colony algorithm for clustering in portfolio optimization

Science.gov (United States)

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

2018-03-01

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

Asset Allocation and Optimal Contract for Delegated Portfolio Management

Science.gov (United States)

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.

Regularizing portfolio optimization

International Nuclear Information System (INIS)

Still, Susanne; Kondor, Imre

2010-01-01

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

Regularizing portfolio optimization

Science.gov (United States)

Still, Susanne; Kondor, Imre

2010-07-01

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

Portfolios dominating indices: Optimization with second-order stochastic dominance constraints vs. minimum and mean variance portfolios

OpenAIRE

Keçeci, Neslihan Fidan; Kuzmenko, Viktor; Uryasev, Stan

2016-01-01

The paper compares portfolio optimization with the Second-Order Stochastic Dominance (SSD) constraints with mean-variance and minimum variance portfolio optimization. As a distribution-free decision rule, stochastic dominance takes into account the entire distribution of return rather than some specific characteristic, such as variance. The paper is focused on practical applications of the portfolio optimization and uses the Portfolio Safeguard (PSG) package, which has precoded modules for op...

Portfolios Dominating Indices: Optimization with Second-Order Stochastic Dominance Constraints vs. Minimum and Mean Variance Portfolios

OpenAIRE

Neslihan Fidan Keçeci; Viktor Kuzmenko; Stan Uryasev

2016-01-01

The paper compares portfolio optimization with the Second-Order Stochastic Dominance (SSD) constraints with mean-variance and minimum variance portfolio optimization. As a distribution-free decision rule, stochastic dominance takes into account the entire distribution of return rather than some specific characteristic, such as variance. The paper is focused on practical applications of the portfolio optimization and uses the Portfolio Safeguard (PSG) package, which has precoded modules for op...

PORTFOLIO INSURANCE INVESTMENT STRATEGIES: A RISK-MANAGEMENT TOOL

Directory of Open Access Journals (Sweden)

Elma Agic-Sabeta

2017-06-01

Full Text Available Unsystemic risks in financial markets may be reduced through diversification. Systemic risks relate to the overall economy, cannot be influenced by a single company, and require special attention. Empirical research on return distributions in the long-term shows that investing under the assumption of normal distribution of returns may be dangerous. The main objectives of this article are to describe portfolio insurance strategies and investigate their advantages and disadvantages. Furthermore, their use in financial markets in both developed and emerging markets is explored, with special consideration placed on southeast European markets. Theoretical models are reviewed, including recent research articles in the field. The results are analyzed, summarized, and presented in the form of tables and graphs. The main finding of the article is identification of strategies that could be used in southeast Europe. It concludes that implementation of portfolio insurance strategies by asset managers may reduce financial risks in southeast European markets if implementation is done professionally and, simultaneously, it is monitored during the entire investment horizon.

Renewable portfolio standards and cost-effective energy-efficiency investment

International Nuclear Information System (INIS)

Mahone, A.; Woo, C.K.; Williams, J.; Horowitz, I.

2009-01-01

Renewable portfolio standards (RPSs) and mandates to invest in cost-effective energy efficiency (EE) are increasingly popular policy tools to combat climate change and dependence on fossil fuels. These supply-side and demand-side policies, however, are often uncoordinated. Using California as a case in point, this paper demonstrates that states could improve resource allocation if these two policies were coordinated by incorporating renewable-energy procurement cost into the cost-effectiveness determination for EE investment. In particular, if renewable energy is relatively expensive when compared to conventional energy, increasing the RPS target raises the cost-effective level of EE investment

Optimal Portfolios in Wishart Models and Effects of Discrete Rebalancing on Portfolio Distribution and Strategy Selection

OpenAIRE

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.

Large portfolio risk management and optimal portfolio allocation with dynamic elliptical copulas

Directory of Open Access Journals (Sweden)

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.

Noisy covariance matrices and portfolio optimization II

Science.gov (United States)

Pafka, Szilárd; Kondor, Imre

2003-03-01

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

Multi-objective portfolio optimization of mutual funds under downside risk measure using fuzzy theory

Directory of Open Access Journals (Sweden)

M. Amiri

2012-10-01

Full Text Available Mutual fund is one of the most popular techniques for many people to invest their funds where a professional fund manager invests people's funds based on some special predefined objectives; therefore, performance evaluation of mutual funds is an important problem. This paper proposes a multi-objective portfolio optimization to offer asset allocation. The proposed model clusters mutual funds with two methods based on six characteristics including rate of return, variance, semivariance, turnover rate, Treynor index and Sharpe index. Semivariance is used as a downside risk measure. The proposed model of this paper uses fuzzy variables for return rate and semivariance. A multi-objective fuzzy mean-semivariance portfolio optimization model is implemented and fuzzy programming technique is adopted to solve the resulted problem. The proposed model of this paper has gathered the information of mutual fund traded on Nasdaq from 2007 to 2009 and Pareto optimal solutions are obtained considering different weights for objective functions. The results of asset allocation, rate of return and risk of each cluster are also determined and they are compared with the results of two clustering methods.

Does asymmetric correlation affect portfolio optimization?

Science.gov (United States)

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.

Formation and bases of the analysis of the investment portfolio of the enterprise

Directory of Open Access Journals (Sweden)

I. I. Hasanshin

2018-01-01

Full Text Available This article discusses several methods for project design and analysis. After all, they are the key ones in creating a new IT portfolio of the enterprise, according to the standards for the formation and management of projects, which is especially important in investment analysis. Considering these stages, we touch topics from the beginning of an enterprise to its formation, as a working business. After all, every enterprise begins its life with a choice of methods, stopping at one, it chooses a plan and sets tasks. Attraction of investments will be one of the main points in this task. For today, investments are the cause for the consequences of economic processes and various phenomena in the economy. This view will be of interest to specialists in the field of information technology and economic sciences. The idea is substantiated that the analysis of such results gives a good assessment in order to further identify weaknesses, build business processes and solutions from the point of view of forming a new portfolio of the enterprise and tools that allow determining the profitability of the module or the project as a whole in terms of money and technical equivalents. The article helps to reveal the topic and the main problem that is interesting and relevant for today, what method of attracting investors and implementing / shaping the IT portfolio of the project, choose which innovative portfolio management systems should be used and how they differ from traditional ones and how to properly link them with architecture of the enterprise. The key stages of investment analysis will be: increase in profits, accumulation of resources, proper portfolio formation and diversification.

Optimal bank portfolio choice under fixed-rate deposit insurance

OpenAIRE

Anlong Li

1991-01-01

An analysis of the investment decisions of a bank whose deposits are fully insured under fixed-rate insurance, showing how banks dynamically adjust their investment portfolios in response to market information and how this flexibility affects both investment decisions and the fair cost of deposit insurance.

HEURISTIC APPROACHES FOR PORTFOLIO OPTIMIZATION

OpenAIRE

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.

A Risk-Sensitive Portfolio Optimization Problem with Fixed Incomes Securities

OpenAIRE

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.

Contract portfolio optimization for a gasoline supply chain

Science.gov (United States)

Wang, Shanshan

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

Belief Propagation Algorithm for Portfolio Optimization Problems.

Science.gov (United States)

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.

Belief Propagation Algorithm for Portfolio Optimization Problems.

Directory of Open Access Journals (Sweden)

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.

Optimal portfolio choice under loss aversion

NARCIS (Netherlands)

A.B. Berkelaar (Arjan); R.R.P. Kouwenberg (Roy)

2000-01-01

textabstractProspect theory and loss aversion play a dominant role in behavioral finance. In this paper we derive closed-form solutions for optimal portfolio choice under loss aversion. When confronted with gains a loss averse investor behaves similar to a portfolio insurer. When confronted with

Perhitungan Value at Risk Pada Portfolio Optimal: Studi Perbandingan Saham Syariah dan Saham Konvensional

Directory of Open Access Journals (Sweden)

Sri Astuti Heryanti

2017-05-01

Full Text Available The aim of this study was to obtain empirical evidence about the difference between the level of risk when investing stocks in the Islamic and conventional by using Value at Risk (VaR. The object of research including consistent stock in the Jakarta Islamic Index and LQ45. The analytical method used in this research is quantitative analysis consisting of the establishment of the optimal portfolio by Markowitz method, calculation of VaR and testing the differences with Independent sample t-test. This study indicated that the value every stock can be reduced by diversifying through the establishment of an optimal portfolio. Based on the calculation Independent sample t-test, it is known that there is no difference between VaR of Islamic stocks and conventional stocks.

Evaluating dynamic covariance matrix forecasting and portfolio optimization

OpenAIRE

Sendstad, Lars Hegnes; Holten, Dag Martin

2012-01-01

In this thesis we have evaluated the covariance forecasting ability of the simple moving average, the exponential moving average and the dynamic conditional correlation models. Overall we found that a dynamic portfolio can gain significant improvements by implementing a multivariate GARCH forecast. We further divided the global investment universe into sectors and regions in order to investigate the relative portfolio performance of several asset allocation strategies with both variance and c...

Three Essays on Robust Optimization of Efficient Portfolios

OpenAIRE

Liu, Hao

2013-01-01

The mean-variance approach was first proposed by Markowitz (1952), and laid the foundation of the modern portfolio theory. Despite its theoretical appeal, the practical implementation of optimized portfolios is strongly restricted by the fact that the two inputs, the means and the covariance matrix of asset returns, are unknown and have to be estimated by available historical information. Due to the estimation risk inherited from inputs, desired properties of estimated optimal portfolios are ...

Spin glasses and nonlinear constraints in portfolio optimization

International Nuclear Information System (INIS)

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.

Spin glasses and nonlinear constraints in portfolio optimization

Energy Technology Data Exchange (ETDEWEB)

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.

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

Science.gov (United States)

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.

Optimization of China's generating portfolio and policy implications based on portfolio theory

International Nuclear Information System (INIS)

Zhu, Lei; Fan, Ying

2010-01-01

This paper applies portfolio theory to evaluate China's 2020-medium-term plans for generating technologies and its generating portfolio. With reference to the risk of relevant generating-cost streams, the paper discusses China's future development of efficient (Pareto optimal) generating portfolios that enhance energy security in different scenarios, including CO 2 -emission-constrained scenarios. This research has found that the future adjustment of China's planned 2020 generating portfolio can reduce the portfolio's cost risk through appropriate diversification of generating technologies, but a price will be paid in the form of increased generating cost. In the CO 2 -emission-constrained scenarios, the generating-cost risk of China's planned 2020 portfolio is even greater than that of the 2005 portfolio, but increasing the proportion of nuclear power in the generating portfolio can reduce the cost risk effectively. For renewable-power generation, because of relatively high generating costs, it will be necessary to obtain stronger policy support to promote renewable-power development.

Macroscopic relationship in primal-dual portfolio optimization problem

Science.gov (United States)

Shinzato, Takashi

2018-02-01

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

An Optimal Investment Strategy and Multiperiod Deposit Insurance Pricing Model for Commercial Banks

Directory of Open Access Journals (Sweden)

Grant E. Muller

2018-01-01

Full Text Available We employ the method of stochastic optimal control to derive the optimal investment strategy for maximizing an expected exponential utility of a commercial bank’s capital at some future date T>0. In addition, we derive a multiperiod deposit insurance (DI pricing model that incorporates the explicit solution of the optimal control problem and an asset value reset rule comparable to the typical practice of insolvency resolution by insuring agencies. By way of numerical simulations, we study the effects of changes in the DI coverage horizon, the risk associated with the asset portfolio of the bank, and the bank’s initial leverage level (deposit-to-asset ratio on the DI premium while the optimal investment strategy is followed.

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

Science.gov (United States)

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

2017-12-01

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

Construction of uncertainty sets for portfolio selection problems

OpenAIRE

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 ...

The Formation of Optimal Portfolio of Mutual Shares Funds using Multi-Objective Genetic Algorithm

Directory of Open Access Journals (Sweden)

Yandra Arkeman

2013-09-01

Full Text Available Investments in financial assets have become a trend in the globalization era, especially the investment in mutual fund shares. Investors who want to invest in stock mutual funds can set up an investment portfolio in order to generate a minimal risk and maximum return. In this study the authors used the Multi-Objective Genetic Algorithm Non-dominated Sorting II (MOGA NSGA-II technique with the Markowitz portfolio principle to find the best portfolio from several mutual funds. The data used are 10 company stock mutual funds with a period of 12 months, 24 months and 36 months. The genetic algorithm parameters used are crossover probability of 0.65, mutation probability of 0.05, Generation 400 and a population numbering 20 individuals. The study produced a combination of the best portfolios for the period of 24 months with a computing time of 63,289 seconds.

Portfolio optimization using fuzzy linear programming

Science.gov (United States)

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.

Enhanced index tracking modelling in portfolio optimization

Science.gov (United States)

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 Robust Statistics Approach to Minimum Variance Portfolio Optimization

Science.gov (United States)

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

2015-12-01

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

Robust Portfolio Optimization using CAPM Approach

Directory of Open Access Journals (Sweden)

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.

Optimal Portfolio Choice with Annuitization

NARCIS (Netherlands)

Koijen, R.S.J.; Nijman, T.E.; Werker, B.J.M.

2006-01-01

We study the optimal consumption and portfolio choice problem over an individual's life-cycle taking into account annuity risk at retirement. Optimally, the investor allocates wealth at retirement to nominal, inflation-linked, and variable annuities and conditions this choice on the state of the

Optimization of the bank's operating portfolio

Science.gov (United States)

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.

Portfolio optimization using median-variance approach

Science.gov (United States)

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.

Quantitative Portfolio Optimization Techniques Applied to the Brazilian Stock Market

Directory of Open Access Journals (Sweden)

André Alves Portela Santos

2012-09-01

Full Text Available In this paper we assess the out-of-sample performance of two alternative quantitative portfolio optimization techniques - mean-variance and minimum variance optimization – and compare their performance with respect to a naive 1/N (or equally-weighted portfolio and also to the market portfolio given by the Ibovespa. We focus on short selling-constrained portfolios and consider alternative estimators for the covariance matrices: sample covariance matrix, RiskMetrics, and three covariance estimators proposed by Ledoit and Wolf (2003, Ledoit and Wolf (2004a and Ledoit and Wolf (2004b. Taking into account alternative portfolio re-balancing frequencies, we compute out-of-sample performance statistics which indicate that the quantitative approaches delivered improved results in terms of lower portfolio volatility and better risk-adjusted returns. Moreover, the use of more sophisticated estimators for the covariance matrix generated optimal portfolios with lower turnover over time.

Penentuan Portofolio Investasi Optimal Dengan Menggunakan Persamaan Diferensial Stokastik

OpenAIRE

Saragi, Desi Natalia

2016-01-01

In investing, the investors choose to invest their wealth in various financial assets both on the risky assets either on the risk-free assets. Generally, those financial assets are formed into a portfolio. Portfolio theory discuss how to establish an optimal portfolio. In determining the optimal investment, at first the investation which had Stochastic Differential Equations (SDE) will be modeled. The model is solved by Ito‟s lemma then by using optimal control theory with utility function ap...

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

OpenAIRE

Krzysztof Urbanowicz; Janusz A. Holyst

2004-01-01

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

Fault Tolerant Distributed Portfolio Optimization in Smart Grids

DEFF Research Database (Denmark)

Juelsgaard, Morten; Wisniewski, Rafal; Bendtsen, Jan Dimon

2014-01-01

optimization scheme for power balancing, where communication is allowed only between units that are linked in the graph. We include consumers with controllable consumption as an active part of the portfolio. We show that a suboptimal, but arbitrarily good power balancing can be obtained in an uncoordinated......, distributed optimization framework, and argue that the scheme will work even if the computation time is limited. We further show that our approach can tolerate changes in the portfolio, in the sense that increasing or reducing the number of units in the portfolio requires only local updates. This ensures......This work considers a portfolio of units for electrical power production and the problem of utilizing it to maintain power balance in the electrical grid. We treat the portfolio as a graph in which the nodes are distributed generators and the links are communication paths. We present a distributed...

R functions development for stockPortfolio package

OpenAIRE

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...

On portfolio risk diversification

Science.gov (United States)

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.

Portfolio Diversification in the South-East European Equity Markets

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

Urbanowicz, Krzysztof; Hołyst, Janusz A.

2004-12-01

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

H–J–B Equations of Optimal Consumption-Investment and Verification Theorems

Energy Technology Data Exchange (ETDEWEB)

Nagai, Hideo, E-mail: nagaih@kansai-u.ac.jp [Kansai University, Department of Mathematics, Faculty of Engineering Science (Japan)

2015-04-15

We consider a consumption-investment problem on infinite time horizon maximizing discounted expected HARA utility for a general incomplete market model. Based on dynamic programming approach we derive the relevant H–J–B equation and study the existence and uniqueness of the solution to the nonlinear partial differential equation. By using the smooth solution we construct the optimal consumption rate and portfolio strategy and then prove the verification theorems under certain general settings.

H–J–B Equations of Optimal Consumption-Investment and Verification Theorems

International Nuclear Information System (INIS)

Nagai, Hideo

2015-01-01

We consider a consumption-investment problem on infinite time horizon maximizing discounted expected HARA utility for a general incomplete market model. Based on dynamic programming approach we derive the relevant H–J–B equation and study the existence and uniqueness of the solution to the nonlinear partial differential equation. By using the smooth solution we construct the optimal consumption rate and portfolio strategy and then prove the verification theorems under certain general settings

Feature selection for portfolio optimization

DEFF Research Database (Denmark)

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...

Continuous Time Portfolio Selection under Conditional Capital at Risk

Directory of Open Access Journals (Sweden)

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.

Adaptive Portfolio Optimization for Multiple Electricity Markets Participation

DEFF Research Database (Denmark)

Pinto, Tiago; Morais, Hugo; Sousa, Tiago M.

2016-01-01

as the most suitable solution to facilitate the small players' participation in electric power negotiations while improving energy efficiency. The opportunity for players' participation in multiple energy negotiation environments (smart grid negotiation in addition to the already implemented market types......, such as day-ahead spot markets, balancing markets, intraday negotiations, bilateral contracts, forward and futures negotiations, and among other) requires players to take suitable decisions on whether to, and how to participate in each market type. This paper proposes a portfolio optimization methodology......, which provides the best investment profile for a market player, considering different market opportunities. The amount of power that each supported player should negotiate in each available market type in order to maximize its profits, considers the prices that are expected to be achieved in each market...

Fuel mix diversification incentives in liberalized electricity markets: A Mean-Variance Portfolio theory approach

International Nuclear Information System (INIS)

Roques, Fabien A.; Newbery, David M.; Nuttall, William J.

2008-01-01

Monte Carlo simulations of gas, coal and nuclear plant investment returns are used as inputs of a Mean-Variance Portfolio optimization to identify optimal base load generation portfolios for large electricity generators in liberalized electricity markets. We study the impact of fuel, electricity, and CO 2 price risks and their degree of correlation on optimal plant portfolios. High degrees of correlation between gas and electricity prices - as observed in most European markets - reduce gas plant risks and make portfolios dominated by gas plant more attractive. Long-term power purchase contracts and/or a lower cost of capital can rebalance optimal portfolios towards more diversified portfolios with larger shares of nuclear and coal plants

Fuel mix diversification incentives in liberalized electricity markets: A Mean-Variance Portfolio theory approach

Energy Technology Data Exchange (ETDEWEB)

Roques, F.A.; Newbery, D.M.; Nuffall, W.J. [University of Cambridge, Cambridge (United Kingdom). Faculty of Economics

2008-07-15

Monte Carlo simulations of gas, coal and nuclear plant investment returns are used as inputs of a Mean-Variance Portfolio optimization to identify optimal base load generation portfolios for large electricity generators in liberalized electricity markets. We study the impact of fuel, electricity, and CO{sub 2} price risks and their degree of correlation on optimal plant portfolios. High degrees of correlation between gas and electricity prices - as observed in most European markets - reduce gas plant risks and make portfolios dominated by gas plant more attractive. Long-term power purchase contracts and/or a lower cost of capital can rebalance optimal portfolios towards more diversified portfolios with larger shares of nuclear and coal plants.

17 CFR 249.332 - Form N-Q, quarterly schedule of portfolio holdings of registered management investment company.

Science.gov (United States)

2010-04-01

... of portfolio holdings of registered management investment company. 249.332 Section 249.332 Commodity... management investment company. This form shall be used by registered management investment companies, other than small business investment companies registered on Form N-5 (§§ 239.24 and 274.5 of this chapter...

USAGE OF THE MAIN COMPONENTS ANALYSIS IN THE MANAGEMENT OF THE INVESTMENT PORTFOLIO

OpenAIRE

Dan ARMEANU; Andreea NEGRU

2011-01-01

When managing investment portfolios on integrated capital markets, beyond the models put forth by the modern portfolio theory, (the Markowitz model, the CML model, the CAPM model, the Treynor-Black model and more), one can successfully resort to the statistical and mathematical tools made available by the multidimensional data analysis. The reason why we shall use those tools in our analysis is simple: they make it possible to reduce the number of variables in the analysis while preserving mu...

Dynamic portfolio optimization across hidden market regimes

DEFF Research Database (Denmark)

Nystrup, Peter; Madsen, Henrik; Lindström, Erik

2017-01-01

Regime-based asset allocation has been shown to add value over rebalancing to static weights and, in particular, reduce potential drawdowns by reacting to changes in market conditions. The predominant approach in previous studies has been to specify in advance a static decision rule for changing...... the allocation based on the state of financial markets or the economy. In this article, model predictive control (MPC) is used to dynamically optimize a portfolio based on forecasts of the mean and variance of financial returns from a hidden Markov model with time-varying parameters. There are computational...... than a buy-and-hold investment in various major stock market indices. This is after accounting for transaction costs, with a one-day delay in the implementation of allocation changes, and with zero-interest cash as the only alternative to the stock indices. Imposing a trading penalty that reduces...

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

Science.gov (United States)

Ando, Amy W; Mallory, Mindy L

2012-04-24

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

Mean-Reverting Portfolio With Budget Constraint

Science.gov (United States)

Zhao, Ziping; Palomar, Daniel P.

2018-05-01

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

PORTFOLIO COMPOSITION WITH MINIMUM VARIANCE: COMPARISON WITH MARKET BENCHMARKS

Directory of Open Access Journals (Sweden)

Daniel Menezes Cavalcante

2016-07-01

Full Text Available Portfolio optimization strategies are advocated as being able to allow the composition of stocks portfolios that provide returns above market benchmarks. This study aims to determine whether, in fact, portfolios based on the minimum variance strategy, optimized by the Modern Portfolio Theory, are able to achieve earnings above market benchmarks in Brazil. Time series of 36 securities traded on the BM&FBOVESPA have been analyzed in a long period of time (1999-2012, with sample windows of 12, 36, 60 and 120 monthly observations. The results indicated that the minimum variance portfolio performance is superior to market benchmarks (CDI and IBOVESPA in terms of return and risk-adjusted return, especially in medium and long-term investment horizons.

A mixed integer linear programming approach for optimal DER portfolio, sizing, and placement in multi-energy microgrids

International Nuclear Information System (INIS)

Mashayekh, Salman; Stadler, Michael; Cardoso, Gonçalo; Heleno, Miguel

2017-01-01

Highlights: • This paper presents a MILP model for optimal design of multi-energy microgrids. • Our microgrid design includes optimal technology portfolio, placement, and operation. • Our model includes microgrid electrical power flow and heat transfer equations. • The case study shows advantages of our model over aggregate single-node approaches. • The case study shows the accuracy of the integrated linearized power flow model. - Abstract: Optimal microgrid design is a challenging problem, especially for multi-energy microgrids with electricity, heating, and cooling loads as well as sources, and multiple energy carriers. To address this problem, this paper presents an optimization model formulated as a mixed-integer linear program, which determines the optimal technology portfolio, the optimal technology placement, and the associated optimal dispatch, in a microgrid with multiple energy types. The developed model uses a multi-node modeling approach (as opposed to an aggregate single-node approach) that includes electrical power flow and heat flow equations, and hence, offers the ability to perform optimal siting considering physical and operational constraints of electrical and heating/cooling networks. The new model is founded on the existing optimization model DER-CAM, a state-of-the-art decision support tool for microgrid planning and design. The results of a case study that compares single-node vs. multi-node optimal design for an example microgrid show the importance of multi-node modeling. It has been shown that single-node approaches are not only incapable of optimal DER placement, but may also result in sub-optimal DER portfolio, as well as underestimation of investment costs.

Adaptive Portfolio Optimization for Multiple Electricity Markets Participation.

Science.gov (United States)

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

2016-08-01

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

Optimal wind power deployment in Europe. A portfolio approach

International Nuclear Information System (INIS)

Roques, Fabien; Hiroux, Celine; Saguan, Marcelo

2010-01-01

Geographic diversification of wind farms can smooth out the fluctuations in wind power generation and reduce the associated system balancing and reliability costs. The paper uses historical wind production data from five European countries (Austria, Denmark, France, Germany, and Spain) and applies the Mean-Variance Portfolio theory to identify cross-country portfolios that minimise the total variance of wind production for a given level of production. Theoretical unconstrained portfolios show that countries (Spain and Denmark) with the best wind resource or whose size contributes to smoothing out the country output variability dominate optimal portfolios. The methodology is then elaborated to derive optimal constrained portfolios taking into account national wind resource potential and transmission constraints and compare them with the projected portfolios for 2020. Such constraints limit the theoretical potential efficiency gains from geographical diversification, but there is still considerable room to improve performance from actual or projected portfolios. These results highlight the need for more cross-border interconnection capacity, for greater coordination of European renewable support policies, and for renewable support mechanisms and electricity market designs providing locational incentives. Under these conditions, a mechanism for renewables credits trading could help aligning wind power portfolios with the theoretically efficient geographic dispersion. (author)

The benefit of regional diversification of cogeneration investments in Europe: A mean-variance portfolio analysis

Energy Technology Data Exchange (ETDEWEB)

Westner, Guenther, E-mail: guenther.westner@eon-energie.co [E.ON Energy Projects GmbH, Arnulfstrasse 56, 80335 Munich (Germany); Madlener, Reinhard, E-mail: rmadlener@eonerc.rwth-aachen.d [Institute for Future Energy Consumer Needs and Behavior (FCN), Faculty of Business and Economics/E.ON Energy Research Center, RWTH Aachen University, Mathieustrasse 6, 52074 Aachen (Germany)

2010-12-15

The EU Directive 2004/8/EC, concerning the promotion of cogeneration, established principles on how EU member states can support combined heat and power generation (CHP). Up to now, the implementation of these principles into national law has not been uniform, and has led to the adoption of different promotion schemes for CHP across the EU member states. In this paper, we first give an overview of the promotion schemes for CHP in various European countries. In a next step, we take two standard CHP technologies, combined-cycle gas turbines (CCGT-CHP) and engine-CHP, and apply exemplarily four selected support mechanisms used in the four largest European energy markets: feed-in tariffs in Germany; energy efficiency certificates in Italy; benefits through tax reduction in the UK; and purchase obligations for power from CHP generation in France. For contracting companies, it could be of interest to diversify their investment in new CHP facilities regionally over several countries in order to reduce country and regulatory risk. By applying the Mean-Variance Portfolio (MVP) theory, we derive characteristic return-risk profiles of the selected CHP technologies in different countries. The results show that the returns on CHP investments differ significantly depending on the country, the support scheme, and the selected technology studied. While a regional diversification of investments in CCGT-CHP does not contribute to reducing portfolio risks, a diversification of investments in engine-CHP can decrease the risk exposure. - Research highlights: {yields}Preconditions for CHP investments differ significantly between the EU member states. {yields}Regional diversification of CHP investments can reduce the total portfolio risk. {yields}Risk reduction depends on the chosen CHP technology.

Co-movement of Foreign Direct and Portfolio Investments in Central and Eastern Europe

OpenAIRE

Yaman O. Erzurumlu; Giray Gozgor

2014-01-01

This paper empirically examines short- and long-run relationships between foreign direct investments (FDI) and volatility of foreign portfolio investments (FPI) in 12 Central and Eastern European (CEE) countries. We use the Generalized Autoregressive Conditional Heteroskedasticity models to calculate volatility of the FPIs. We utilize the second generation panel unit root test, panel-Wald causality test procedure and panel cointegration analysis allowing for structural breaks, and cross-secti...

Electricity portfolio management : optimal peak/off-peak allocations

NARCIS (Netherlands)

Huisman, R.; Mahieu, R.J.; Schlichter, F.

2009-01-01

Electricity purchasers manage a portfolio of contracts in order to purchase the expected future electricity consumption profile of a company or a pool of clients. This paper proposes a mean-variance framework to address the concept of structuring the portfolio and focuses on how to optimally

Land-Use Portfolio Modeler, Version 1.0

Science.gov (United States)

Taketa, Richard; Hong, Makiko

2010-01-01

Natural hazards pose significant threats to the public safety and economic health of many communities throughout the world. Community leaders and decision-makers continually face the challenges of planning and allocating limited resources to invest in protecting their communities against catastrophic losses from natural-hazard events. Public efforts to assess community vulnerability and encourage loss-reduction measures through mitigation often focused on either aggregating site-specific estimates or adopting standards based upon broad assumptions about regional risks. The site-specific method usually provided the most accurate estimates, but was prohibitively expensive, whereas regional risk assessments were often too general to be of practical use. Policy makers lacked a systematic and quantitative method for conducting a regional-scale risk assessment of natural hazards. In response, Bernknopf and others developed the portfolio model, an intermediate-scale approach to assessing natural-hazard risks and mitigation policy alternatives. The basis for the portfolio-model approach was inspired by financial portfolio theory, which prescribes a method of optimizing return on investment while reducing risk by diversifying investments in different security types. In this context, a security type represents a unique combination of features and hazard-risk level, while financial return is defined as the reduction in losses resulting from an investment in mitigation of chosen securities. Features are selected for mitigation and are modeled like investment portfolios. Earth-science and economic data for the features are combined and processed in order to analyze each of the portfolios, which are then used to evaluate the benefits of mitigating the risk in selected locations. Ultimately, the decision maker seeks to choose a portfolio representing a mitigation policy that maximizes the expected return-on-investment, while minimizing the uncertainty associated with that return-on-investment

On the Computation of Optimal Monotone Mean-Variance Portfolios via Truncated Quadratic Utility

OpenAIRE

Ales Cerný; Fabio Maccheroni; Massimo Marinacci; Aldo Rustichini

2008-01-01

We report a surprising link between optimal portfolios generated by a special type of variational preferences called divergence preferences (cf. [8]) and optimal portfolios generated by classical expected utility. As a special case we connect optimization of truncated quadratic utility (cf. [2]) to the optimal monotone mean-variance portfolios (cf. [9]), thus simplifying the computation of the latter.

Portfolio Diversification in the South-East European Equity Markets

OpenAIRE

Zaimovic Azra; Arnaut-Berilo Almira; Mustafic Arnela

2017-01-01

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 limit...

The cost of geothermal energy in the western US region:a portfolio-based approach a mean-variance portfolio optimization of the regions' generating mix to 2013.

Energy Technology Data Exchange (ETDEWEB)

Beurskens, Luuk (ECN-Energy Research Centre of the Netherland); Jansen, Jaap C. (ECN-Energy Research Centre of the Netherlands); Awerbuch, Shimon Ph.D. (.University of Sussex, Brighton, UK); Drennen, Thomas E.

2005-09-01

Energy planning represents an investment-decision problem. Investors commonly evaluate such problems using portfolio theory to manage risk and maximize portfolio performance under a variety of unpredictable economic outcomes. Energy planners need to similarly abandon their reliance on traditional, ''least-cost'' stand-alone technology cost estimates and instead evaluate conventional and renewable energy sources on the basis of their portfolio cost--their cost contribution relative to their risk contribution to a mix of generating assets. This report describes essential portfolio-theory ideas and discusses their application in the Western US region. The memo illustrates how electricity-generating mixes can benefit from additional shares of geothermal and other renewables. Compared to fossil-dominated mixes, efficient portfolios reduce generating cost while including greater renewables shares in the mix. This enhances energy security. Though counter-intuitive, the idea that adding more costly geothermal can actually reduce portfolio-generating cost is consistent with basic finance theory. An important implication is that in dynamic and uncertain environments, the relative value of generating technologies must be determined not by evaluating alternative resources, but by evaluating alternative resource portfolios. The optimal results for the Western US Region indicate that compared to the EIA target mixes, there exist generating mixes with larger geothermal shares at equal-or-lower expected cost and risk.

MARKOV CHAIN PORTFOLIO LIQUIDITY OPTIMIZATION MODEL

Directory of Open Access Journals (Sweden)

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.

Art investment in South Africa: Portfolio diversification and art market efficiency

Directory of Open Access Journals (Sweden)

Ferdi Botha

2016-09-01

Full Text Available Art has been suggested as a good way to diversify investment portfolios during times of financial uncertainty. The argument is that art exhibits different risk and return characteristics to conventional investments in other asset classes. The new Citadel art price index offered the opportunity to test this theory in the South African context. Moreover, this paper tests whether art prices are efficient. The Citadel index uses the hedonic regression method with observations drawn from the top 100, 50 and 20 artists by sales volume, giving approximately 29 503 total auction observations. The Index consists of quarterly data from the period 2000Q1 to 2013Q3. A vector autoregression of the art price index, Johannesburg stock exchange all-share index, house price index, and South African government bond index were used. Results show that, when there are increased returns on the stock market in a preceding period and wealth increases, there is a change in the Citadel art price index in the same direction. No significant difference was found between the house price index and the art price index, or between the art and government bond price indices. The art market is also found to be inefficient, thereby exacerbating the risk of investing in art. Overall, the South African art market does not offer the opportunity to diversify portfolios dominated by either property, bonds, or shares.

Integrated Portfolio Analysis: Return on Investment and Real Options Analysis of Intelligence Information Systems (Cryptologic Carry On Program)

National Research Council Canada - National Science Library

Rios, Jr., Cesar G; Housel, Thomas; Mun, Johnathan

2006-01-01

...) on individual projects, programs, and processes within a portfolio of IT investments. Using KVA historical data as a platform, the authors evaluate potential strategic investments with real options analysis...

Methods of Choosing an Optimal Portfolio of Projects

OpenAIRE

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...

Characteristics of Omega-Optimized Portfolios at Different Levels of Threshold Returns

Directory of Open Access Journals (Sweden)

Renaldas Vilkancas

2014-12-01

Full Text Available There is little literature considering effects that the loss-gain threshold used for dividing good and bad outcomes by all downside (upside risk measures has on portfolio optimization and performance. The purpose of this study is to assess the performance of portfolios optimized with respect to the Omega function developed by Keating and Shadwick at different levels of the threshold returns. The most common choices of the threshold values used in various Omega studies cover the risk-free rate and the average market return or simply a zero return, even though the inventors of this measure for risk warn that “using the values of the Omega function at particular points can be critically misleading” and that “only the entire Omega function contains information on distribution”. The obtained results demonstrate the importance of the selected values of the threshold return on portfolio performance – higher levels of the threshold lead to an increase in portfolio returns, albeit at the expense of a higher risk. In fact, within a certain threshold interval, Omega-optimized portfolios achieved the highest net return, compared with all other strategies for portfolio optimization using three different test datasets. However, beyond a certain limit, high threshold values will actually start hurting portfolio performance while meta-heuristic optimizers typically are able to produce a solution at any level of the threshold, and the obtained results would most likely be financially meaningless.

Portfolio selection theory and wildlife management

Directory of Open Access Journals (Sweden)

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.

Electricity Portfolio Management: Optimal Peak / Off-Peak Allocations

OpenAIRE

Huisman, Ronald; Mahieu, Ronald; Schlichter, Felix

2007-01-01

textabstractElectricity purchasers manage a portfolio of contracts in order to purchase the expected future electricity consumption profile of a company or a pool of clients. This paper proposes a mean-variance framework to address the concept of structuring the portfolio and focuses on how to allocate optimal positions in peak and off-peak forward contracts. It is shown that the optimal allocations are based on the difference in risk premiums per unit of day-ahead risk as a measure of relati...

Dutch direct real estate investments in private portfolios

NARCIS (Netherlands)

Berkhout, T.M.; Geer, van der G.

2005-01-01

Direct real estate plays an important role in our daily lives. The place of direct real estate in the portfolio of a private investor is often limited however. The paper attempts to answer the question of how large the allocation to direct real estate should be to attain an optimal risk/return

Optimal investment in a portfolio of HIV prevention programs.

Science.gov (United States)

Zaric, G S; Brandeau, M L

2001-01-01

In this article, the authors determine the optimal allocation of HIV prevention funds and investigate the impact of different allocation methods on health outcomes. The authors present a resource allocation model that can be used to determine the allocation of HIV prevention funds that maximizes quality-adjusted life years (or life years) gained or HIV infections averted in a population over a specified time horizon. They apply the model to determine the allocation of a limited budget among 3 types of HIV prevention programs in a population of injection drug users and nonusers: needle exchange programs, methadone maintenance treatment, and condom availability programs. For each prevention program, the authors estimate a production function that relates the amount invested to the associated change in risky behavior. The authors determine the optimal allocation of funds for both objective functions for a high-prevalence population and a low-prevalence population. They also consider the allocation of funds under several common rules of thumb that are used to allocate HIV prevention resources. It is shown that simpler allocation methods (e.g., allocation based on HIV incidence or notions of equity among population groups) may lead to alloctions that do not yield the maximum health benefit. The optimal allocation of HIV prevention funds in a population depends on HIV prevalence and incidence, the objective function, the production functions for the prevention programs, and other factors. Consideration of cost, equity, and social and political norms may be important when allocating HIV prevention funds. The model presented in this article can help decision makers determine the health consequences of different allocations of funds.

RISK LOAN PORTFOLIO OPTIMIZATION MODEL BASED ON CVAR RISK MEASURE

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

Ando, Amy W.; Mallory, Mindy L.

2012-01-01

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

Optimization of portfolio of contracts for companies of electric power generation

International Nuclear Information System (INIS)

Gunn, Laura Keiko; Silva, Elisa Bastos; Correia, Paulo de Barros

2010-01-01

Portfolio optimization is a technique widely used to select investments in economic and financial zones. In the Brazilian Electric Market the portfolio models must consider not only different types of contracts used in the free market, but also different types of markets: the free market, the captive market and the spot market. Normally, the question is knowing which proportion of energy should be sold in each market, in order to maximize the return and minimize the risk. This article deals with a problem from the point of view of a power generator, where their objective is to maximize its profit, to serve their obligations regarding the delivery of energy and minimizing the risk associated with the occurrence of Spot Price - minimum (Spot Price). It is considered that the generator has flexible contracts and inflexible contracts to sell the energy. Inflexible contracts have delivery obligations of fixed energy and flexible contracts allow, the holder of the flexibility, to deliver or to receive an amount of variable energy. In this case, the holder of flexibility may be the purchaser or the generator. (author)

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

Science.gov (United States)

Morton de Lachapelle, David; Challet, Damien

2010-07-01

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

Influence Manager's Investment Attitude on Organization Environment and Portfolio Performance Reksadana Shares (Study on Mutual Fund Management Company Reksadana Shares in Indonesia)

OpenAIRE

Oswari, Teddy; Kowanda, Dionysia

2007-01-01

The purpose of this research is to measures the effect of investment manager attitude through operational employees to mutual funds work attitude portfolio, to analyse how big the organizational environment effect together with investment manager attitude, through operational employees to mutual funds work attitude portfolio and analyse the effect of organizational envirobment to investment manage attitude in mutual funds company. The observation conducted in 72 mutual funds company, the data...

Portfolio optimization of the construction sector companies in ...

African Journals Online (AJOL)

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 ...

Discrete Analysis of Portfolio Selection with Optimal Stopping Time

Directory of Open Access Journals (Sweden)

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.

On-Line Investment Analysis and Portfolio Management: Using Learning Outcome Statements To Design Projects.

Science.gov (United States)

Pettijohn, James B.; Ragan, Gay A.; Ragan, Kent P.

2003-01-01

Describes an Internet-based project to familiarize students with online investment analysis and stock portfolio management. Outlines a process for writing learning outcomes that address three levels of cognition: knowledge/comprehension, application/analysis, and synthesis/evaluation. (SK)

Multiperiod Mean-Variance Portfolio Optimization via Market Cloning

International Nuclear Information System (INIS)

Ankirchner, Stefan; Dermoune, Azzouz

2011-01-01

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.

Multiperiod Mean-Variance Portfolio Optimization via Market Cloning

Energy Technology Data Exchange (ETDEWEB)

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.

) Application of Value Management and Portfolio Optimization to the Nigerian Market

International Nuclear Information System (INIS)

Agbonyeme, C.

2003-01-01

The desire to thoroughly analyze the economic value of oil, gas and non-oil properties in Nigeria is increasing fast.This analysis is especially important for marginal fields where the borderline between technical success and financial disaster is small. Also, with the objective to increase daily output of oil to 4 million bbl/day by the year 2005 many dormant fields are re-appraised. This has to be done technically and financially. Oil and gas companies that optimize their portfolio through acquisition and divestiture face a lot of challenges. These challenges include decisions of whether to invest or divest, preparation of a divestiture package for analysis, and also the definition of a company's own most suitable economic performance indicators. In this evaluation process, the understanding and proper modelling of the local fiscal regime is of paramount importance. A quick and efficient method is presented which accounts for the complexity of the Nigerian fiscal regime-for computing the value of fields, analyzing the risks associated with a project and selecting the most profitable project from a range of available projects or portfolios. Tools for facilitating this multifaceted decision making process will be discussed as well as latest probabilistic techniques discussed as well as latest probabilistic techniques and optimization strategies. Example cases showing the successful application of these techniques in Nigeria will round off this paper

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

Science.gov (United States)

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

2010-11-01

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

Mean-Gini Portfolio Analysis: A Pedagogic Illustration

Directory of Open Access Journals (Sweden)

C. Sherman Cheung

2007-05-01

Full Text Available It is well known in the finance literature that mean-variance analysis is inappropriate when asset returns are not normally distributed or investors’ preferences of returns are not characterized by quadratic functions. The normality assumption has been widely rejected in cases of emerging market equities and hedge funds. The mean-Gini framework is an attractive alternative as it is consistent with stochastic dominance rules regardless of the probability distributions of asset returns. Applying mean-Gini to a portfolio setting involving multiple assets, however, has always been challenging to business students whose training in optimization is limited. This paper introduces a simple spreadsheet-based approach to mean-Gini portfolio optimization, thus allowing the mean-Gini concepts to be covered more effectively in finance courses such as portfolio theory and investment analysis.

THE EXTREME WEIGHTS IN THE INDEX PORTFOLIO OF CONSTANT-PROPORTION STRATEGIES

Directory of Open Access Journals (Sweden)

Yury F. Kasimov

2018-01-01

Full Text Available This paper analyzes the optimal of constant proportion index portfolio strategies. They are also called passive strategies which are becoming more common in Russia and abroad. They are significantly cheaper to implement than active strategies. In addition, as practice shows, in the long term they are more profitable and less risky. The main problem in these strategies is the choice of the proportions in which the investor allocates his capital between risky and risk-free assets. In constant proportion index portfolio the weight of risk asset remains constant throughout investment period. For this purpose, the investor with a certain frequency restores the desired balance between risky and risk-free assets. Each period at the beginning of which such recovery occurs is called the re-balancing period. In the case of strategies with index portfolios, risky assets are the shares of the index fund, and risk-free assets are the deposits in reliable bank or government bonds. According on the daily value of units of these funds and the annual interest rate for the 11-year period, using a specially developed program optimal weight index funds in the portfolios has been found. Parameters of the analyzed portfolios are: length of the investment period (from one year to 10 years and the frequency of weight rebalancing (month, quarter, year. The sequence of optimal weights and the corresponding optimum yield for consecutive investment periods with a specified frequency of re-balancing were determined for each fund. It was found that in almost all cases, the optimal weights of fund equals the extreme values 0 or 1. Also, the frequencies of these values in the selected sequence is about the same for all funds. This empiric fact can be conventionally called the principle of extremeness or “all or nothing” principle. 

Exploiting stock data: a survey of state of the art computational techniques aimed at producing beliefs regarding investment portfolios

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

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.

Robust portfolio choice with ambiguity and learning about return predictability

DEFF Research Database (Denmark)

Larsen, Linda Sandris; Branger, Nicole; Munk, Claus

2013-01-01

We analyze the optimal stock-bond portfolio under both learning and ambiguity aversion. Stock returns are predictable by an observable and an unobservable predictor, and the investor has to learn about the latter. Furthermore, the investor is ambiguity-averse and has a preference for investment...... strategies that are robust to model misspecifications. We derive a closed-form solution for the optimal robust investment strategy. We find that both learning and ambiguity aversion impact the level and structure of the optimal stock investment. Suboptimal strategies resulting either from not learning...... or from not considering ambiguity can lead to economically significant losses....

Dynamic Portfolio Optimization with Transaction Costs and State-Dependent Drift

DEFF Research Database (Denmark)

Palczewski, Jan; Poulsen, Rolf; Schenk-Hoppe, Klaus Reiner

2015-01-01

The problem of dynamic portfolio choice with transaction costs is often addressed by constructing a Markov Chain approximation of the continuous time price processes. Using this approximation, we present an efficient numerical method to determine optimal portfolio strategies under time- and state......-dependent drift and proportional transaction costs. This scenario arises when investors have behavioral biases or the actual drift is unknown and needs to be estimated. Our numerical method solves dynamic optimal portfolio problems with an exponential utility function for time-horizons of up to 40 years....... It is applied to measure the value of information and the loss from transaction costs using the indifference principle....

IMPROVING DEPOSIT POLICY BANK ON THE BASIS OF ANALYSIS OF THE INFLUENCE OF DEPOSIT PORTFOLIO STRUCTURE ON FORMATION OF INVESTMENT RESOURCE

Directory of Open Access Journals (Sweden)

Viadrova I.

2018-01-01

Full Text Available Introduction. The banking system as a part of the national economy contributes to the development of various branches of economy and trade, enabling the realization of economic interests of economic entities. One of the important tasks of the monetary system is the accumulation of financial resources necessary for the implementation of credit and investment projects and their further distribution. This task is performed by banking institutions by attracting funds from individuals and legal entities. The size of the bank’s resource base and the scale of its operations depend on the operations of attraction of funds. The priority task of the banking institution is the predominance of attracting long-term investments over short-term ones. That is why the problem that exists in the disproportion of the maturity of borrowed funds, the prevalence of short-term deposits over long-term and the minimum amount of long-term resources in the bank’s deposit portfolio is particularly relevant. Purpose. The purpose of the work is to generalize the theoretical aspects of bank deposit activity and to determine the optimal structure of the deposit portfolio for carrying out of credit and investment activity. Results. The article summarizes the essence of the concept of “deposit policy”, identifies the peculiarities of its formation and analyzes the main external and internal factors that have an impact on the deposit policy of domestic banks. The analysis of the dynamics and structure of deposit operations of banks at the state level was carried out and the analysis of deposit policy of a bank of foreign bank groups – PJSC “Ukrsotsbank” for 2010-2017 was provided. In this work, the factors of influence are investigated: external and internal, which determine the ways of formation of deposit policy by banks of Ukraine. The influence of the structure of the deposit portfolio of Ukrainian banks on the formation of the investment resource is analyzed

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

Science.gov (United States)

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.

Mean--variance portfolio optimization when means and covariances are unknown

OpenAIRE

Tze Leung Lai; Haipeng Xing; Zehao Chen

2011-01-01

Markowitz's celebrated mean--variance portfolio optimization theory assumes that the means and covariances of the underlying asset returns are known. In practice, they are unknown and have to be estimated from historical data. Plugging the estimates into the efficient frontier that assumes known parameters has led to portfolios that may perform poorly and have counter-intuitive asset allocation weights; this has been referred to as the "Markowitz optimization enigma." After reviewing differen...

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

Science.gov (United States)

2014-04-30

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

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

Science.gov (United States)

Shinzato, Takashi

2018-01-01

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

Worst-Case Portfolio Optimization under Stochastic Interest Rate Risk

Directory of Open Access Journals (Sweden)

Tina Engler

2014-12-01

Full Text Available We investigate a portfolio optimization problem under the threat of a market crash, where the interest rate of the bond is modeled as a Vasicek process, which is correlated with the stock price process. We adopt a non-probabilistic worst-case approach for the height and time of the market crash. On a given time horizon [0; T], we then maximize the investor’s expected utility of terminal wealth in the worst-case crash scenario. Our main result is an explicit characterization of the worst-case optimal portfolio strategy for the class of HARA (hyperbolic absolute risk aversion utility functions.

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

Science.gov (United States)

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.

On the Equivalence of Quadratic Optimization Problems Commonly Used in Portfolio Theory

OpenAIRE

Taras Bodnar; Nestor Parolya; Wolfgang Schmid

2012-01-01

In the paper, we consider three quadratic optimization problems which are frequently applied in portfolio theory, i.e, the Markowitz mean-variance problem as well as the problems based on the mean-variance utility function and the quadratic utility.Conditions are derived under which the solutions of these three optimization procedures coincide and are lying on the efficient frontier, the set of mean-variance optimal portfolios. It is shown that the solutions of the Markowitz optimization prob...

Product portfolio optimization based on substitution

DEFF Research Database (Denmark)

Myrodia, Anna; Moseley, A.; Hvam, Lars

2017-01-01

The development of production capabilities has led to proliferation of the product variety offered to the customer. Yet this fact does not directly imply increase of manufacturers' profitability, nor customers' satisfaction. Consequently, recent research focuses on portfolio optimization through...... substitution and standardization techniques. However when re-defining the strategic market decisions are characterized by uncertainty due to several parameters. In this study, by using a GAMS optimization model we present a method for supporting strategic decisions on substitution, by quantifying the impact...

The Optimal Allocation for Capital Preservation: an Evidence Australian Portfolio

Directory of Open Access Journals (Sweden)

Riznaldi Akbar

2018-05-01

Full Text Available This study analyzes optimal asset mix for Australian portfolios with the main investment objective for capital preservation. An alternative measure of risk of annual maximum drawdown has been used to reflect investor preference for capital preservation as opposed to conventional risk measure of standard deviation and variance. The contribution of the study is two folds. First, this study has put different perspective to look at portfolio risk in the view of capital preservation. Second, the optimal weight for asset class mix that minimizes annual maximum drawdown has been analyzed for the case of Australian market. The results suggest that for capital preservation, investors should expect lower returns and need to put a greater allocation on less risky assets such as cash or bond. To this end, cash and bond have provided stable long term annual returns along with contained level of annual maximum drawdowns. In contrast, when investors demand higher expected return, they should increase asset allocation into stocks (equities market at the expense of higher maximum drawdowns. Bahasa Indonesia Abstrak: Studi ini menganalisis bauran aset optimal untuk portofolio Australia dengan tujuan investasi utama untuk pelestarian modal. Ukuran alternatif risiko penarikan maksimum tahunan telah digunakan untuk mencerminkan preferensi investor untuk pelestarian modal dibandingkan dengan ukuran risiko konvensional standar deviasi dan varians. Kontribusi dari penelitian ini adalah dua lipatan. Pertama, penelitian ini telah menempatkan perspektif yang berbeda untuk melihat risiko portofolio dalam pandangan pelestarian modal. Kedua, bobot optimal untuk campuran kelas aset yang meminimalkan penarikan maksimum tahunan telah dianalisis untuk kasus pasar Australia. Hasilnya menunjukkan bahwa untuk pelestarian modal, investor harus mengharapkan pengembalian yang lebih rendah dan perlu menempatkan alokasi yang lebih besar pada aset yang kurang berisiko seperti uang tunai

Mean-Variance portfolio optimization when each asset has individual uncertain exit-time

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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.

Model Risk in Portfolio Optimization

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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.

Recent evolution of italian households’ equity portfolio choices: an empirical investigation

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Attilio Gardini

2013-05-01

Full Text Available We study Italian households’ portfolio choices, with a special focus on equity investments, by analysing jointly time series and cross-sectional portfolio data. We investigate the temporal evolution of the actual composition of Italian households’ investments in order to explain their portfolio choices and to detect possible determinants of the observed disequilibria phenomena. Moreover, we model the stock market participation choice by using probit regression techniques and we test for parameter stability over time. Instability of participation parameters and a peculiar evolution of Italian households’ portfolios pointed out by our concurrent analysis of cross-sectional and time series data seem to confirm the distance of Italian households’ financial decisions from the rational choice predicted by the Markowitz model. In particular, we find that the housing market bubbles interact strongly with the stock market and financial institutions seem to be unable to advise investors suggesting optimal portfolio choices. The deep reason behind these facts may be the bounded education of investors, in particular the low financial literacy of Italian households.

Automated Portfolio Optimization Based on a New Test for Structural Breaks

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Tobias Berens

2014-04-01

Full Text Available We present a completely automated optimization strategy which combines the classical Markowitz mean-variance portfolio theory with a recently proposed test for structural breaks in covariance matrices. With respect to equity portfolios, global minimum-variance optimizations, which base solely on the covariance matrix, yield considerable results in previous studies. However, financial assets cannot be assumed to have a constant covariance matrix over longer periods of time. Hence, we estimate the covariance matrix of the assets by respecting potential change points. The resulting approach resolves the issue of determining a sample for parameter estimation. Moreover, we investigate if this approach is also appropriate for timing the reoptimizations. Finally, we apply the approach to two datasets and compare the results to relevant benchmark techniques by means of an out-of-sample study. It is shown that the new approach outperforms equally weighted portfolios and plain minimum-variance portfolios on average.

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

Science.gov (United States)

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.

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

Science.gov (United States)

Shinzato, Takashi

2015-01-01

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

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

Directory of Open Access Journals (Sweden)

Takashi Shinzato

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

Strategic Technology Investment Analysis: An Integrated System Approach

Science.gov (United States)

Adumitroaie, V.; Weisbin, C. R.

2010-01-01

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

Robust Utility Maximization Under Convex Portfolio Constraints

International Nuclear Information System (INIS)

Matoussi, Anis; Mezghani, Hanen; Mnif, Mohamed

2015-01-01

We study a robust maximization problem from terminal wealth and consumption under a convex constraints on the portfolio. We state the existence and the uniqueness of the consumption–investment strategy by studying the associated quadratic backward stochastic differential equation. We characterize the optimal control by using the duality method and deriving a dynamic maximum principle

Considering barriers to investment in South Africa

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KB Afful

2014-10-01

Full Text Available This paper examines the effect of South Africa’s economic fundamentals on net direct investment and net portfolio investment. The results suggest that the main determinants of investment in South Africa are resource prices, input productivity and the economic performance of the domestic economy. The results illustrate that net direct investment and net portfolio investment are close but not perfect substitutes. In addition, we find that an increase in labour input costs reduces both net direct investment and net portfolio investment. Further, an increase in fixed capital productivity increases net direct investment. Further, also the results illustrate that subsidies increase both net direct investment and net portfolio investment. Moreover, an increase in exports increases both net direct investment and net portfolio investment. Policy recommendations are thus proposed that may increase foreign direct investment in South Africa.

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

Science.gov (United States)

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.

Model of formation of low-risk stock portfolio in modern financial markets

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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

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

OpenAIRE

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.

Portfolio selection problem with liquidity constraints under non-extensive statistical mechanics

International Nuclear Information System (INIS)

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.

Portfolio optimization using Mixture Design of Experiments. Scheduling trades within electricity markets

International Nuclear Information System (INIS)

Oliveira, Francisco Alexandre de; Paiva, Anderson Paulo de; Lima, Jose Wanderley Marangon; Balestrassi, Pedro Paulo; Mendes, Rona Rinston Amaury

2011-01-01

Deregulation of the electricity sector has given rise to several approaches to defining optimal portfolios of energy contracts. Financial tools - requiring substantial adjustments - are usually used to determine risk and return. This article presents a novel approach to adjusting the conditional value at risk (CVaR) metric to the mix of contracts on the energy markets; the approach uses Mixture Design of Experiments (MDE). In this kind of experimental strategy, the design factors are treated as proportions in a mixture system considered quite adequate for treating portfolios in general. Instead of using traditional linear programming, the concept of desirability function is here used to combine the multi-response, nonlinear objective functions for mean with the variance of a specific portfolio obtained through MDE. The maximization of the desirability function is implied in the portfolio optimization, generating an efficient recruitment frontier. This approach offers three main contributions: it includes risk aversion in the optimization routine, it assesses interaction between contracts, and it lessens the computational effort required to solve the constrained nonlinear optimization problem. A case study based on the Brazilian energy market is used to illustrate the proposal. The numerical results verify the proposal's adequacy. (author)

Portfolio optimization using Mixture Design of Experiments. Scheduling trades within electricity markets

Energy Technology Data Exchange (ETDEWEB)

Oliveira, Francisco Alexandre de; Paiva, Anderson Paulo de; Lima, Jose Wanderley Marangon; Balestrassi, Pedro Paulo; Mendes, Rona Rinston Amaury [Federal Univ. of Itajuba, Minas Gerais (Brazil)

2011-01-15

Deregulation of the electricity sector has given rise to several approaches to defining optimal portfolios of energy contracts. Financial tools - requiring substantial adjustments - are usually used to determine risk and return. This article presents a novel approach to adjusting the conditional value at risk (CVaR) metric to the mix of contracts on the energy markets; the approach uses Mixture Design of Experiments (MDE). In this kind of experimental strategy, the design factors are treated as proportions in a mixture system considered quite adequate for treating portfolios in general. Instead of using traditional linear programming, the concept of desirability function is here used to combine the multi-response, nonlinear objective functions for mean with the variance of a specific portfolio obtained through MDE. The maximization of the desirability function is implied in the portfolio optimization, generating an efficient recruitment frontier. This approach offers three main contributions: it includes risk aversion in the optimization routine, it assesses interaction between contracts, and it lessens the computational effort required to solve the constrained nonlinear optimization problem. A case study based on the Brazilian energy market is used to illustrate the proposal. The numerical results verify the proposal's adequacy. (author)

Portfolio optimization in enhanced index tracking with goal programming approach

Science.gov (United States)

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

2014-09-01

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

Desain Portofolio Optimal untuk Keputusan Investasi pada Fase Krisis Keuangan

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Deddy Saptomo

2017-05-01

Full Text Available This research aims to design optimal portfolio with a case study of stocks listed on the Indonesia Stock Exchange (IDX that conduct transactions in the period 2011-2015. The sample used were 396 companies listed on nine sectors in BEI. Arbitrage Pricing Theory (APT method is used to determine the realized return, expected return, and efficient portfolio involving four macroeconomic factors (Stock Price Index (IHSG, interest rate of Indonesian Bank Certificates (SBI, Inflation and Exchange Rate of Rupiah against the US Dollar. Efficient portfolio is formed by 231 undervalued companies. While the optimal portfolio with the Excess Return to Beta (ERB approach was formed by 42 companies with a ERB value greater than (or equal to cut-off point (0,1912. Under the uncertainty of the investment climate due to the global financial crisis, the decision to make investments needs to be done carefully and consider various factors, including macroeconomic factors. This research has succeeded in designing an optimal portfolio that can be a guide for investors to determine investment decisions.

Portfolio Optimization Using Particle Swarms with Stripes

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Mario Villalobos Arias

2011-04-01

Full Text Available In this paper it is consider the Portfolio Optimization Problem developed by Markowitz [11]. The basic assumption is that the investor tries to maximize his/her profit and at the same time, wants to minimize the risk. This problem is usually solved using a scalarization approach (with one objective. Here it is solved it as a bi-objective  optimization problem. It uses a new version of the algorithm of Particle Swarm Optimization for Multi-Objective Problems to which it implemented a method of the stripes to improve dispersion.

An Empirical Study on Hedge Fund Portfolio Optimization, Mean-Risk Based Approaches

OpenAIRE

Li, Yang

2011-01-01

Abstract This research attempts to investigate the divergences between the Mean-Variance and the Mean-CVaR portfolio optimization methods in examining various assets classes, such as equities, bonds, and especially hedge funds. In order to get a thorough understanding of hedge funds facts and available optimization techniques, relevant literatures are carefully reviewed and incorporated into later stage computer modelling. By constructing three hypothetical portfolios, including traditiona...

A Polynomial Optimization Approach to Constant Rebalanced Portfolio Selection

NARCIS (Netherlands)

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

A polynomial optimization approach to constant rebalanced portfolio selection

NARCIS (Netherlands)

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

Portfolio Diversification with Commodities in Times of Financialization

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Adam Zaremba

2015-03-01

Full Text Available The study concentrates on the benefits of passive commodity investments in the context of the phenomenon of financialization. The research investigates the implications of increase in the correlation coefficients between equity and commodity investments for investors in financial markets. The paper is composed of several parts. First, the attributes of commodity investments and their benefits in the portfolio optimization are explored. Second, the phenomenon of the financialization is described and the research hypothesis is developed. Next, an empirical analysis is performed. I simulate the mean-variance spanning tests to examine the benefits of commodity investments before and after accounting for the impact of financialization. I proceed separate analysis for pre- and post-financialization period. The empirical research is based on asset classes’ returns and other related variables from years 1991-2012. The performed investigations indicate that the market financialization may have significant implications for commodity investors. Due to increase in correlation coefficients, the inclusion of the commodity futures in the traditional stock-bond portfolio appears to be no longer reasonable.

The benefit of regional diversification of cogeneration investments in Europe. A mean-variance portfolio analysis

International Nuclear Information System (INIS)

Westner, Guenther; Madlener, Reinhard

2010-01-01

The EU Directive 2004/8/EC, concerning the promotion of cogeneration, established principles on how EU member states can support combined heat and power generation (CHP). Up to now, the implementation of these principles into national law has not been uniform, and has led to the adoption of different promotion schemes for CHP across the EU member states. In this paper, we first give an overview of the promotion schemes for CHP in various European countries. In a next step, we take two standard CHP technologies, combined-cycle gas turbines (CCGT-CHP) and engine-CHP, and apply exemplarily four selected support mechanisms used in the four largest European energy markets: feed-in tariffs in Germany; energy efficiency certificates in Italy; benefits through tax reduction in the UK; and purchase obligations for power from CHP generation in France. For contracting companies, it could be of interest to diversify their investment in new CHP facilities regionally over several countries in order to reduce country and regulatory risk. By applying the Mean-Variance Portfolio (MVP) theory, we derive characteristic return-risk profiles of the selected CHP technologies in different countries. The results show that the returns on CHP investments differ significantly depending on the country, the support scheme, and the selected technology studied. While a regional diversification of investments in CCGT-CHP does not contribute to reducing portfolio risks, a diversification of investments in engine-CHP can decrease the risk exposure. (author)

The benefit of regional diversification of cogeneration investments in Europe. A mean-variance portfolio analysis

Energy Technology Data Exchange (ETDEWEB)

Westner, Guenther; Madlener, Reinhard [E.ON Energy Projects GmbH, Arnulfstrasse 56, 80335 Munich (Germany)

2010-12-15

The EU Directive 2004/8/EC, concerning the promotion of cogeneration, established principles on how EU member states can support combined heat and power generation (CHP). Up to now, the implementation of these principles into national law has not been uniform, and has led to the adoption of different promotion schemes for CHP across the EU member states. In this paper, we first give an overview of the promotion schemes for CHP in various European countries. In a next step, we take two standard CHP technologies, combined-cycle gas turbines (CCGT-CHP) and engine-CHP, and apply exemplarily four selected support mechanisms used in the four largest European energy markets: feed-in tariffs in Germany; energy efficiency certificates in Italy; benefits through tax reduction in the UK; and purchase obligations for power from CHP generation in France. For contracting companies, it could be of interest to diversify their investment in new CHP facilities regionally over several countries in order to reduce country and regulatory risk. By applying the Mean-Variance Portfolio (MVP) theory, we derive characteristic return-risk profiles of the selected CHP technologies in different countries. The results show that the returns on CHP investments differ significantly depending on the country, the support scheme, and the selected technology studied. While a regional diversification of investments in CCGT-CHP does not contribute to reducing portfolio risks, a diversification of investments in engine-CHP can decrease the risk exposure. (author)

Large Portfolio Risk Management and Optimal Portfolio Allocation with Dynamic Copulas

OpenAIRE

Thorsten Lehnert; Xisong Jin

2011-01-01

Previous research focuses on the importance of modeling the multivariate distribution for optimal portfolio allocation and active risk management. However, available dynamic models are not easily applied for 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 like Value at Ris...

Portfolio optimization in electricity markets

International Nuclear Information System (INIS)

Liu, Min; Wu, Felix F.

2007-01-01

In a competitive electricity market, Generation companies (Gencos) face price risk and delivery risk that affect their profitability. Risk management is an important and essential part in the Genco's decision making. In this paper, risk management through diversification is considered. The problem of energy allocation between spot markets and bilateral contracts is formulated as a general portfolio optimization problem with a risk-free asset and n risky assets. Historical data of the PJM electricity market are used to demonstrate the approach. (author)

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

Directory of Open Access Journals (Sweden)

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

Science.gov (United States)

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

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

Science.gov (United States)

Hsu, Chih-Ming

2014-12-01

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

Optimal Regulation of Lumpy Investments

NARCIS (Netherlands)

Zwart, G.; Broer, D.P.

2012-01-01

When a monopolist has discretion over the timing of infrastructure investments, regulation of post-investment prices interferes with incentivizing socially optimal investment timing. In a model of regulated lumpy investment under uncertainty, we study regulation when the regulator can condition

Energy R and D portfolio analysis based on climate change mitigation

International Nuclear Information System (INIS)

Pugh, Graham; Clarke, Leon; Marlay, Robert; Kyle, Page; Wise, Marshall; McJeon, Haewon; Chan, Gabriel

2011-01-01

The diverse nature and uncertain potential of the energy technologies that are or may be available to mitigate greenhouse gas emissions pose a challenge to policymakers trying to invest public funds in an optimal R and D portfolio. This paper discusses two analytical approaches to this challenge used to inform funding decisions related to the U.S. Department of Energy (DOE) applied energy R and D portfolio. The two approaches are distinguished by the constraints under which they were conducted: the need to provide an end-to-end portfolio analysis as input to internal DOE budgeting processes, but with limited time and subject to institutional constraints regarding important issues such as expert judgment. Because of these constraints, neither approach should be viewed as an attempt to push forward the state of the art in portfolio analysis in the abstract. Instead, they are an attempt to use more stylized, heuristic methods that can provide first-order insights in the DOE institutional context. Both approaches make use of advanced technology scenarios implemented in an integrated assessment modeling framework and then apply expert judgment regarding the likelihood of achieving associated R and D and commercialization goals. The approaches differ in the granularity of the scenarios used and in the definition of the benefits of technological advance: in one approach the benefits are defined as the cumulative emission reduction attributable to a particular technology; in the other approach benefits are defined as the cumulative cost reduction. In both approaches a return on investment (ROI) criterion is established based on benefits divided by federal R and D investment. The ROI is then used to build a first-order approximation of an optimal applied energy R and D investment portfolio. Although these methodologies have been used to inform an actual budget request, the results reflect only one input among many used in budget formulation. The results are therefore not

Portfolio optimization for heavy-tailed assets: Extreme Risk Index vs. Markowitz

OpenAIRE

Mainik, Georg; Mitov, Georgi; Rüschendorf, Ludger

2015-01-01

Using daily returns of the S&P 500 stocks from 2001 to 2011, we perform a backtesting study of the portfolio optimization strategy based on the extreme risk index (ERI). This method uses multivariate extreme value theory to minimize the probability of large portfolio losses. With more than 400 stocks to choose from, our study seems to be the first application of extreme value techniques in portfolio management on a large scale. The primary aim of our investigation is the potential of ERI in p...

Geometrical framework for robust portfolio optimization

OpenAIRE

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.

Performance of the reverse Helmbold universal portfolio

Science.gov (United States)

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.

Hereditary Portfolio Optimization with Taxes and Fixed Plus Proportional Transaction Costs—Part II

Directory of Open Access Journals (Sweden)

Mou-Hsiung Chang

2007-01-01

Full Text Available This paper is the continuation of the paper entitled “Hereditary portfolio optimization with taxes and fixed plus proportional transaction costs I” that treats an infinite-time horizon hereditary portfolio optimization problem in a market that consists of one savings account and one stock account. Within the solvency region, the investor is allowed to consume from the savings account and can make transactions between the two assets subject to paying capital-gain taxes as well as a fixed plus proportional transaction cost. The investor is to seek an optimal consumption-trading strategy in order to maximize the expected utility from the total discounted consumption. The portfolio optimization problem is formulated as an infinite dimensional stochastic classical impulse control problem due to the hereditary nature of the stock price dynamics and inventories. This paper contains the verification theorem for the optimal strategy. It also proves that the value function is a viscosity solution of the QVHJBI.

INVESTMENT PORTFOLIO MANAGEMENT PECULIARITIES OF NON-STATE PENSION FUNDS

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Ivan LUCHIAN

2015-07-01

Full Text Available Non-state pension fund is a institution of social security, the primary purpose of which is the payment of pensions to members of the system of private pension provision. The insurance and pension funds in Republic of Moldova is just beginning. In this regard, a study was conducted in different countries on experience with non-state pension insurance. The results, being generalized, can be used in Republic of Moldova. Non-state pension fund has a multiple core: financial institution, fund, social institution, insurer and institutional investor. Non-governmental pension funds were highly integrated in public policy in most countries around the world aimed at expanding the supplementary pension insurance. Therefore, it becomes very important to solve the issue of formation and investment portfolio management in these financial institutions.

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

Commands for financial data management and portfolio optimization

OpenAIRE

C. Alberto Dorantes

2013-01-01

Several econometric software offer portfolio management tools for practitioners and researchers. For example, MatLab and R offer a great variety of tools for the simulation, optimization, and analysis of financial time series. Stata, together with Mata, offers powerful programming tools for the simulation, optimization, and analysis of financial data. However, related user commands are scarce. In this presentation, commands for online market data collection, data manipulation, and financial a...

The Optimal Portfolio Selection Model under g-Expectation

Directory of Open Access Journals (Sweden)

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.

International Diversification Versus Domestic Diversification: Mean-Variance Portfolio Optimization and Stochastic Dominance Approaches

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Fathi Abid

2014-05-01

Full Text Available This paper applies the mean-variance portfolio optimization (PO approach and the stochastic dominance (SD test to examine preferences for international diversification versus domestic diversification from American investors’ viewpoints. Our PO results imply that the domestic diversification strategy dominates the international diversification strategy at a lower risk level and the reverse is true at a higher risk level. Our SD analysis shows that there is no arbitrage opportunity between international and domestic stock markets; domestically diversified portfolios with smaller risk dominate internationally diversified portfolios with larger risk and vice versa; and at the same risk level, there is no difference between the domestically and internationally diversified portfolios. Nonetheless, we cannot find any domestically diversified portfolios that stochastically dominate all internationally diversified portfolios, but we find some internationally diversified portfolios with small risk that dominate all the domestically diversified portfolios.

The portfolio theory applied to small hydroelectric power plants; Teoria do portfolio aplicada a pequenas centrais hidreletricas

Energy Technology Data Exchange (ETDEWEB)

Bastos, Paulo Roberto Ferreira de Moura

2002-07-01

The 'Portfolio Theory' has been largely employed on stock markets, aiming to improve the relation between risk and return. This theory identifies many possible investment combinations once it's associated with the idea that increasing investment diversification can lower risk. The objective is, thus identify the portfolio that offers the most efficient diversification of capital. The reforms on the energy sector in Brazil have made investments on both generation and commercialization of electric energy easier for medium sized investors. There have been economic incentives to the exploration of wind and bio-mass energy, and to the construction of small hydro-electric power plants (in Portuguese, PCH), as well as many legal and regulatory mechanisms pursuing the maintenance of elevate rates of participation of renewable source in the production of electrical energy in Brazil. Between these options, the PCH are a specially good opportunity taking account of its minimum environment impact, low operational costs and total technologic control. The decision concerning investment options has been based on standard economic analysis like 'Net Present Value', 'Payback Time' or 'Cost/Benefit Relations'. Other techniques such as scenario and sensitivity have been incorporated and, more recently, there has been a search for other methods consider the uncertainty of happenings within the horizon of study. This dissertation will analyse six possibilities of PCH with standard techniques. Of them, the four possibilities considered viable will constitute our examples for the application of Portfolio Theory techniques. Once the active portfolio is determined, the best option is identified using the 'mean-variance efficient' developed by Markowitz, concluding that the theory can give better support to the decision-making in future enterprises on the electric sector. After considering the optimal return/risk combinations, there was

The portfolio theory applied to small hydroelectric power plants; Teoria do portfolio aplicada a pequenas centrais hidreletricas

Energy Technology Data Exchange (ETDEWEB)

Bastos, Paulo Roberto Ferreira de Moura

2002-07-01

The 'Portfolio Theory' has been largely employed on stock markets, aiming to improve the relation between risk and return. This theory identifies many possible investment combinations once it's associated with the idea that increasing investment diversification can lower risk. The objective is, thus identify the portfolio that offers the most efficient diversification of capital. The reforms on the energy sector in Brazil have made investments on both generation and commercialization of electric energy easier for medium sized investors. There have been economic incentives to the exploration of wind and bio-mass energy, and to the construction of small hydro-electric power plants (in Portuguese, PCH), as well as many legal and regulatory mechanisms pursuing the maintenance of elevate rates of participation of renewable source in the production of electrical energy in Brazil. Between these options, the PCH are a specially good opportunity taking account of its minimum environment impact, low operational costs and total technologic control. The decision concerning investment options has been based on standard economic analysis like 'Net Present Value', 'Payback Time' or 'Cost/Benefit Relations'. Other techniques such as scenario and sensitivity have been incorporated and, more recently, there has been a search for other methods consider the uncertainty of happenings within the horizon of study. This dissertation will analyse six possibilities of PCH with standard techniques. Of them, the four possibilities considered viable will constitute our examples for the application of Portfolio Theory techniques. Once the active portfolio is determined, the best option is identified using the 'mean-variance efficient' developed by Markowitz, concluding that the theory can give better support to the decision-making in future enterprises on the electric sector. After considering the optimal return/risk combinations, there was a change on the hierarchy concerning the best options

Portfolio Optimization: A Combined Regime-Switching and Black–Litterman Model

OpenAIRE

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...

Two-Stage Fuzzy Portfolio Selection Problem with Transaction Costs

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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.

Universal portfolios in stochastic portfolio theory

OpenAIRE

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...

Issues in the determination of the optimal portfolio of electricity supply options

International Nuclear Information System (INIS)

Hickey, Emily A.; Lon Carlson, J.; Loomis, David

2010-01-01

In recent years a growing amount of attention has been focused on the need to develop a cost-effective portfolio of electricity supply options that provides society with a measure of protection from such factors as fuel price volatility and supply interruptions. A number of strategies, including portfolio theory, real options theory, and different measures of diversity have been suggested. In this paper we begin by first considering how we might characterize an optimal portfolio of supply options and identify a number of constraints that must be satisfied as part of the optimization process. We then review the strengths and limitations of each approach listed above. The results of our review lead us to conclude that, of the strategies we consider, using the concept of diversity to assess the viability of an electricity supply portfolio is most appropriate. We then provide an example of how a particular measure of diversity, the Shannon-Weiner Index, can be used to assess the diversity of the electricity supply portfolio in the state of Illinois, the region served by the Midwest Independent System Operator (MISO), and the continental United States.

On the non-stationarity of financial time series: impact on optimal portfolio selection

International Nuclear Information System (INIS)

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)

Replica approach to mean-variance portfolio optimization

Science.gov (United States)

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

2016-12-01

We consider the problem of mean-variance portfolio optimization for a generic covariance matrix subject to the budget constraint and the constraint for the expected return, with the application of the replica method borrowed from the statistical physics of disordered systems. We find that the replica symmetry of the solution does not need to be assumed, but emerges as the unique solution of the optimization problem. We also check the stability of this solution and find that the eigenvalues of the Hessian are positive for r  =  N/T  optimal in-sample variance is found to vanish at the critical point inversely proportional to the divergent estimation error.

Portfolio management using value at risk: A comparison between genetic algorithms and particle swarm optimization

NARCIS (Netherlands)

V.A.F. Dallagnol (V. A F); J.H. van den Berg (Jan); L. Mous (Lonneke)

2009-01-01

textabstractIn this paper, it is shown a comparison of the application of particle swarm optimization and genetic algorithms to portfolio management, in a constrained portfolio optimization problem where no short sales are allowed. The objective function to be minimized is the value at risk

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

Science.gov (United States)

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

Identification Of Financial Instruments – Important Step in Building Portfolios

Directory of Open Access Journals (Sweden)

Mădălina-Gabriela Anghel

2013-10-01

Full Text Available Construction of any portfolio is initially identifying financial instruments to be traded, and the timing for entering the capital market (ie the optimal timing of trading . This is the stage in which the market analysis is made in order to collect the necessary information in making investment decision. In this regard it is recommended that investment activity should be based on a thorough evaluation of both the individual performance of the instruments to be purchased and the overall development of the capital market on which the investment is to be made.

A diversified portfolio model of adaptability.

Science.gov (United States)

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).

Optimal Premium Pricing for a Heterogeneous Portfolio of Insurance Risks

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Athanasios A. Pantelous

2009-01-01

Full Text Available The paper revisits the classical problem of premium rating within a heterogeneous portfolio of insurance risks using a continuous stochastic control framework. The portfolio is divided into several classes where each class interacts with the others. The risks are modelled dynamically by the means of a Brownian motion. This dynamic approach is also transferred to the design of the premium process. The premium is not constant but equals the drift of the Brownian motion plus a controlled percentage of the respective volatility. The optimal controller for the premium is obtained using advanced optimization techniques, and it is finally shown that the respective pricing strategy follows a more balanced development compared with the traditional premium approaches.

Comparative Analysis of Investment Decision Models

Directory of Open Access Journals (Sweden)

Ieva Kekytė

2017-06-01

Full Text Available Rapid development of financial markets resulted new challenges for both investors and investment issues. This increased demand for innovative, modern investment and portfolio management decisions adequate for market conditions. Financial market receives special attention, creating new models, includes financial risk management and investment decision support systems.Researchers recognize the need to deal with financial problems using models consistent with the reality and based on sophisticated quantitative analysis technique. Thus, role mathematical modeling in finance becomes important. This article deals with various investments decision-making models, which include forecasting, optimization, stochatic processes, artificial intelligence, etc., and become useful tools for investment decisions.

PEMILIHAN SAHAM YANG OPTIMAL MENGGUNAKAN CAPITAL ASSET PRICING MODEL (CAPM

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Dioda Ardi Wibisono

2017-08-01

Full Text Available Optimal portfolio is the basis for investors to invest in stock. Capital Asset Pricing Model (CAPM is a method to determine the value of the risk and return of a company stock. This research uses a secondary data from the closing price of the monthly stock price (monthly closing price, Stock Price Index (SPI, and the monthly SBI rate. The samples of this research are 41 stocks in LQ45 February-July 2015 on the Indonesian Stock Exchange (ISE. The study period is during 5 year from October 2010 - October 2015. The result of analysis shows that the optimal portfolio consists of 18 companies. The average return of the optimal portfolio is higher than the average risk-free return (SBI rate and the average market return. This proves that investing in stocks is more profitable than a risk-free investment. � Keywords: Stock, CAPM, return, risk�

Using Health Care Utilization and Publication Patterns to Characterize the Research Portfolio and to Plan Future Research Investments.

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Luba Katz

Full Text Available Government funders of biomedical research are under increasing pressure to demonstrate societal benefits of their investments. A number of published studies attempted to correlate research funding levels with the societal burden for various diseases, with mixed results. We examined whether research funded by the Department of Veterans Affairs (VA is well aligned with current and projected veterans' health needs. The organizational structure of the VA makes it a particularly suitable setting for examining these questions.We used the publication patterns and dollar expenditures of VA-funded researchers to characterize the VA research portfolio by disease. We used health care utilization data from the VA for the same diseases to define veterans' health needs. We then measured the level of correlation between the two and identified disease groups that were under- or over-represented in the research portfolio relative to disease expenditures. Finally, we used historic health care utilization trends combined with demographic projections to identify diseases and conditions that are increasing in costs and/or patient volume and consequently represent potential targets for future research investments.We found a significant correlation between research volume/expenditures and health utilization. Some disease groups were slightly under- or over-represented, but these deviations were relatively small. Diseases and conditions with the increasing utilization trend at the VA included hypertension, hypercholesterolemia, diabetes, hearing loss, sleeping disorders, complications of pregnancy, and several mental disorders.Research investments at the VA are well aligned with veteran health needs. The VA can continue to meet these needs by supporting research on the diseases and conditions with a growing number of patients, costs of care, or both. Our approach can be used by other funders of disease research to characterize their portfolios and to plan research

Using Health Care Utilization and Publication Patterns to Characterize the Research Portfolio and to Plan Future Research Investments.

Science.gov (United States)

Katz, Luba; Fink, Rebecca V; Bozeman, Samuel R; McNeil, Barbara J

2014-01-01

Government funders of biomedical research are under increasing pressure to demonstrate societal benefits of their investments. A number of published studies attempted to correlate research funding levels with the societal burden for various diseases, with mixed results. We examined whether research funded by the Department of Veterans Affairs (VA) is well aligned with current and projected veterans' health needs. The organizational structure of the VA makes it a particularly suitable setting for examining these questions. We used the publication patterns and dollar expenditures of VA-funded researchers to characterize the VA research portfolio by disease. We used health care utilization data from the VA for the same diseases to define veterans' health needs. We then measured the level of correlation between the two and identified disease groups that were under- or over-represented in the research portfolio relative to disease expenditures. Finally, we used historic health care utilization trends combined with demographic projections to identify diseases and conditions that are increasing in costs and/or patient volume and consequently represent potential targets for future research investments. We found a significant correlation between research volume/expenditures and health utilization. Some disease groups were slightly under- or over-represented, but these deviations were relatively small. Diseases and conditions with the increasing utilization trend at the VA included hypertension, hypercholesterolemia, diabetes, hearing loss, sleeping disorders, complications of pregnancy, and several mental disorders. Research investments at the VA are well aligned with veteran health needs. The VA can continue to meet these needs by supporting research on the diseases and conditions with a growing number of patients, costs of care, or both. Our approach can be used by other funders of disease research to characterize their portfolios and to plan research investments.

DIFFERENCES BETWEEN MEAN-VARIANCE AND MEAN-CVAR PORTFOLIO OPTIMIZATION MODELS

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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

A Monte Carlo based decision-support tool for assessing generation portfolios in future carbon constrained electricity industries

International Nuclear Information System (INIS)

Vithayasrichareon, Peerapat; MacGill, Iain F.

2012-01-01

This paper presents a novel decision-support tool for assessing future generation portfolios in an increasingly uncertain electricity industry. The tool combines optimal generation mix concepts with Monte Carlo simulation and portfolio analysis techniques to determine expected overall industry costs, associated cost uncertainty, and expected CO 2 emissions for different generation portfolio mixes. The tool can incorporate complex and correlated probability distributions for estimated future fossil-fuel costs, carbon prices, plant investment costs, and demand, including price elasticity impacts. The intent of this tool is to facilitate risk-weighted generation investment and associated policy decision-making given uncertainties facing the electricity industry. Applications of this tool are demonstrated through a case study of an electricity industry with coal, CCGT, and OCGT facing future uncertainties. Results highlight some significant generation investment challenges, including the impacts of uncertain and correlated carbon and fossil-fuel prices, the role of future demand changes in response to electricity prices, and the impact of construction cost uncertainties on capital intensive generation. The tool can incorporate virtually any type of input probability distribution, and support sophisticated risk assessments of different portfolios, including downside economic risks. It can also assess portfolios against multi-criterion objectives such as greenhouse emissions as well as overall industry costs. - Highlights: ► Present a decision support tool to assist generation investment and policy making under uncertainty. ► Generation portfolios are assessed based on their expected costs, risks, and CO 2 emissions. ► There is tradeoff among expected cost, risks, and CO 2 emissions of generation portfolios. ► Investment challenges include economic impact of uncertainties and the effect of price elasticity. ► CO 2 emissions reduction depends on the mix of

The Heterogeneous Investment Horizon and Dynamic Strategies for Asset Allocation

Science.gov (United States)

Xiong, Heping; Xu, Yiheng; Xiao, Yi

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

Portfolio theory in the selection of oil investment projects Teoria de carteiras na seleção de projetos de investimento em petróleo

Directory of Open Access Journals (Sweden)

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

Optimal portfolio strategies under a shortfall constraint | Akume ...

African Journals Online (AJOL)

We impose dynamically, a shortfall constraint in terms of Tail Conditional Expectation on the portfolio selection problem in continuous time, in order to obtain optimal strategies. The nancial market is assumed to comprise n risky assets driven by geometric Brownian motion and one risk-free asset. The method of Lagrange ...

Portfolio optimization with short-selling and spin-glass

NARCIS (Netherlands)

Schianchi, A.; Bongini, L.; Degli Esposti, M.; Giardinà, C.

2002-01-01

n this paper, we solve a general problem of optimizing a portfolio in a futures markets framework, extending the previous work of Galluccio et al. [Physica A 259, 449 (1998)]. We allow for long buying/short selling of a relatively large number of assets, assuming a fixed level of margin requirement.

Consumption-Portfolio Optimization with Recursive Utility in Incomplete Markets

DEFF Research Database (Denmark)

Kraft, Holger; Seifried, Frank Thomas; Steffensen, Mogens

2013-01-01

In an incomplete market, we study the optimal consumption-portfolio decision of an investor with recursive preferences of Epstein–Zin type. Applying a classical dynamic programming approach, we formulate the associated Hamilton–Jacobi–Bellman equation and provide a suitable verification theorem...

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

Energy Technology Data Exchange (ETDEWEB)

Brackney, Larry J. [National Renewable Energy Lab. (NREL), Golden, CO (United States)

2016-02-17

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

Estimating investor preferences towards portfolio return distribution in investment funds

Directory of Open Access Journals (Sweden)

Margareta Gardijan

2015-03-01

Full Text Available Recent research in the field of investor preference has emphasised the need to go beyond just simply analyzing the first two moments of a portfolio return distribution used in a MV (mean-variance paradigm. The suggestion is to observe an investor's utility function as an nth order Taylor approximation. In such terms, the assumption is that investors prefer greater values of odd and smaller values of even moments. In order to investigate the preferences of Croatian investment funds, an analysis of the moments of their return distribution is conducted. The sample contains data on monthly returns of 30 investment funds in Croatia for the period from January 1999 to May 2014. Using the theoretical utility functions (DARA, CARA, CRRA, we compare changes in their preferences when higher moments are included. Moreover, we investigate an extension of the CAPM model in order to find out whether including higher moments can explain better the relationship between the awards and risk premium, and whether we can apply these findings to estimate preferences of Croatian institutional investors. The results indicate that Croatian institutional investors do not seek compensation for bearing greater market risk.

Application of Performance Ratios in Portfolio Optimization

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Aleš Kresta

2015-01-01

Full Text Available The cornerstone of modern portfolio theory was established by pioneer work of Harry Markowitz. Based on his mean-variance framework, Sharpe formulated his well-known Sharpe ratio aiming to measure the performance of mutual funds. The contemporary development in computer’s computational power allowed to apply more complex performance ratios, which take into account also higher moments of return probability distribution. Although these ratios were proposed to help the investors to improve the results of portfolio optimization, we empirically demonstrated in our paper that this may not necessarily be true. On the historical dataset of DJIA components we empirically showed that both Sharpe ratio and MAD ratio outperformed Rachev ratio. However, for Rachev ratio we assumed only one level of parameters value. Different set-ups of parameters may provide different results and thus further analysis is certainly required.

2-Phase NSGA II: An Optimized Reward and Risk Measurements Algorithm in Portfolio Optimization

Directory of Open Access Journals (Sweden)

Seyedeh Elham Eftekharian

2017-11-01

Full Text Available Portfolio optimization is a serious challenge for financial engineering and has pulled down special attention among investors. It has two objectives: to maximize the reward that is calculated by expected return and to minimize the risk. Variance has been considered as a risk measure. There are many constraints in the world that ultimately lead to a non–convex search space such as cardinality constraint. In conclusion, parametric quadratic programming could not be applied and it seems essential to apply multi-objective evolutionary algorithm (MOEA. In this paper, a new efficient multi-objective portfolio optimization algorithm called 2-phase NSGA II algorithm is developed and the results of this algorithm are compared with the NSGA II algorithm. It was found that 2-phase NSGA II significantly outperformed NSGA II algorithm.

Application of an integrated model for evaluation and optimization of business projects portfolios

Directory of Open Access Journals (Sweden)

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

Directory of Open Access Journals (Sweden)

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

A Balanced Investment Portfolio For Equitable Health And Well-Being Is An Imperative, And Within Reach.

Science.gov (United States)

Kindig, David A; Milstein, Bobby

2018-04-01

Health investments, defined as formal expenditures to either produce or care for health, in the US are extremely inefficient and have yet to unlock the country's full potential for equitable health and well-being. A major reason for such poor performance is that the US health investment portfolio is out of balance, with too much spent on certain aspects of health care and not enough spent to ensure social, economic, and environmental conditions that are vital to maintaining health and well-being. This commentary summarizes the evidence for this assertion, along with the opportunities and challenges involved in rebalancing investments in ways that would improve overall population health, reduce health gaps, and help build a culture of health for all Americans.

Optimisation of the securities portfolio as a part of the risk management process

Directory of Open Access Journals (Sweden)

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.

Multi-period mean–variance portfolio optimization based on Monte-Carlo simulation

NARCIS (Netherlands)

F. Cong (Fei); C.W. Oosterlee (Kees)

2016-01-01

htmlabstractWe propose a simulation-based approach for solving the constrained dynamic mean– variance portfolio managemen tproblem. For this dynamic optimization problem, we first consider a sub-optimal strategy, called the multi-stage strategy, which can be utilized in a forward fashion. Then,

Optimal Strategy Analysis of a Competing Portfolio Market with a Polyvariant Profit Function

International Nuclear Information System (INIS)

Bogolubov, Nikolai N. Jr.; Kyshakevych, Bohdan Yu.; Blackmore, Denis; Prykarpatsky, Anatoliy K.

2010-12-01

A competing market model with a polyvariant profit function that assumes 'zeitnot' stock behavior of clients is formulated within the banking portfolio medium and then analyzed from the perspective of devising optimal strategies. An associated Markov process method for finding an optimal choice strategy for monovariant and bivariant profit functions is developed. Under certain conditions on the bank 'promotional' parameter with respect to the 'fee' for a missed share package transaction and at an asymptotically large enough portfolio volume, universal transcendental equations - determining the optimal share package choice among competing strategies with monovariant and bivariant profit functions - are obtained. (author)

PORTFOLIO SELECTION OF INFORMATION SYSTEMS PROJECTS USING PROMETHEE V WITH C-OPTIMAL CONCEPT

Directory of Open Access Journals (Sweden)

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.

Optimizing Eco-Efficiency Across the Procurement Portfolio.

Science.gov (United States)

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

2016-06-07

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

Optimal Investment Control of Macroeconomic Systems

Institute of Scientific and Technical Information of China (English)

ZHAO Ke-jie; LIU Chuan-zhe

2006-01-01

Economic growth is always accompanied by economic fluctuation. The target of macroeconomic control is to keep a basic balance of economic growth, accelerate the optimization of economic structures and to lead a rapid, sustainable and healthy development of national economies, in order to propel society forward. In order to realize the above goal, investment control must be regarded as the most important policy for economic stability. Readjustment and control of investment includes not only control of aggregate investment, but also structural control which depends on economic-technology relationships between various industries of a national economy. On the basis of the theory of a generalized system, an optimal investment control model for government has been developed. In order to provide a scientific basis for government to formulate a macroeconomic control policy, the model investigates the balance of total supply and aggregate demand through an adjustment in investment decisions realizes a sustainable and stable growth of the national economy. The optimal investment decision function proposed by this study has a unique and specific expression, high regulating precision and computable characteristics.

Utility portfolio diversification

International Nuclear Information System (INIS)

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)

Convergence of a Scholtes-type regularization method for cardinality-constrained optimization problems with an application in sparse robust portfolio optimization

Czech Academy of Sciences Publication Activity Database

Branda, Martin; Bucher, M.; Červinka, Michal; Schwartz, A.

2018-01-01

Roč. 70, č. 2 (2018), s. 503-530 ISSN 0926-6003 R&D Projects: GA ČR GA15-00735S Institutional support: RVO:67985556 Keywords : Cardinality constraints * Regularization method * Scholtes regularization * Strong stationarity * Sparse portfolio optimization * Robust portfolio optimization Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Statistics and probability Impact factor: 1.520, year: 2016 http://library.utia.cas.cz/separaty/2018/MTR/branda-0489264.pdf

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

Science.gov (United States)

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

2004-01-01

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

The use of the multi-cumulant tensor analysis for the algorithmic optimisation of investment portfolios

Science.gov (United States)

Domino, Krzysztof

2017-02-01

The cumulant analysis plays an important role in non Gaussian distributed data analysis. The shares' prices returns are good example of such data. The purpose of this research is to develop the cumulant based algorithm and use it to determine eigenvectors that represent investment portfolios with low variability. Such algorithm is based on the Alternating Least Square method and involves the simultaneous minimisation 2'nd- 6'th cumulants of the multidimensional random variable (percentage shares' returns of many companies). Then the algorithm was tested during the recent crash on the Warsaw Stock Exchange. To determine incoming crash and provide enter and exit signal for the investment strategy the Hurst exponent was calculated using the local DFA. It was shown that introduced algorithm is on average better that benchmark and other portfolio determination methods, but only within examination window determined by low values of the Hurst exponent. Remark that the algorithm is based on cumulant tensors up to the 6'th order calculated for a multidimensional random variable, what is the novel idea. It can be expected that the algorithm would be useful in the financial data analysis on the world wide scale as well as in the analysis of other types of non Gaussian distributed data.

Inflation Protected Investment Strategies

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Mirco Mahlstedt

2016-03-01

Full Text Available In this paper, a dynamic inflation-protected investment strategy is presented, which is based on traditional asset classes and Markov-switching models. Different stock market, as well as inflation regimes are identified, and within those regimes, the inflation hedging potential of stocks, bonds, real estate, commodities and gold are investigated. Within each regime, we determine optimal investment portfolios driven by the investment idea of protection from losses due to changing inflation if inflation is rising or high, but decoupling the performance from inflation if inflation is low. The results clearly indicate that these asset classes behave differently in different stock market and inflation regimes. Whereas in the long-run, we agree with the general opinion in the literature that stocks and bonds are a suitable hedge against inflation, we observe for short time horizons that the hedging potential of each asset class, especially of real estate and commodities, depend strongly on the state of the current market environment. Thus, our approach provides a possible explanation for different statements in the literature regarding the inflation hedging properties of these asset classes. A dynamic inflation-protected investment strategy is developed, which combines inflation protection and upside potential. This strategy outperforms standard buy-and-hold strategies, as well as the well-known 1 N -portfolio.

Optimal Energy Mix with Renewable Portfolio Standards in Korea

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Zong Woo Geem

2016-05-01

Full Text Available Korea is a heavily energy-dependent country whose primary energy consumption ranks ninth in the world. However, at the same time, it promised to reduce carbon emission and planned to use more renewable energy. Thus, the objective of this study is to propose an optimal energy mix planning model in electricity generation from various energy sources, such as gas, coal, nuclear, hydro, wind, photovoltaic, and biomass, which considers more renewable and sustainable portions by imposing governmental regulation named renewable portfolio standard (RPS. This optimization model minimizes various costs such as construction cost, operation and management cost, fuel cost, and carbon emission cost while satisfying minimal demand requirement, maximal annual installation potential, and renewable portfolio standard constraints. Results showed that this optimization model could successfully generate energy mix plan from 2012 to 2030 while minimizing the objective costs and satisfying all the constraints. Therefore, this optimization model contributes more efficient and objective method to the complex decision-making process with a sustainability option. This proposed energy mix model is expected to be applied not only to Korea, but also to many other countries in the future for more economical planning of their electricity generation while affecting climate change less.

Decentralized portfolio management

OpenAIRE

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...

Mean-variance portfolio optimization with state-dependent risk aversion

DEFF Research Database (Denmark)

Bjoerk, Tomas; Murgoci, Agatha; Zhou, Xun Yu

2014-01-01

The objective of this paper is to study the mean-variance portfolio optimization in continuous time. Since this problem is time inconsistent we attack it by placing the problem within a game theoretic framework and look for subgame perfect Nash equilibrium strategies. This particular problem has...

Deterministic mean-variance-optimal consumption and investment

DEFF Research Database (Denmark)

Christiansen, Marcus; Steffensen, Mogens

2013-01-01

In dynamic optimal consumption–investment problems one typically aims to find an optimal control from the set of adapted processes. This is also the natural starting point in case of a mean-variance objective. In contrast, we solve the optimization problem with the special feature that the consum......In dynamic optimal consumption–investment problems one typically aims to find an optimal control from the set of adapted processes. This is also the natural starting point in case of a mean-variance objective. In contrast, we solve the optimization problem with the special feature...... that the consumption rate and the investment proportion are constrained to be deterministic processes. As a result we get rid of a series of unwanted features of the stochastic solution including diffusive consumption, satisfaction points and consistency problems. Deterministic strategies typically appear in unit......-linked life insurance contracts, where the life-cycle investment strategy is age dependent but wealth independent. We explain how optimal deterministic strategies can be found numerically and present an example from life insurance where we compare the optimal solution with suboptimal deterministic strategies...

Portfolio optimization using Mean Absolute Deviation (MAD and Conditional Value-at-Risk (CVaR

Directory of Open Access Journals (Sweden)

Lucas Pelegrin da Silva

Full Text Available Abstract This paper investigates the efficiency of traditional portfolio optimization models when the returns of financial assets are highly volatile, e.g., in financial crises periods. We also develop alternative optimization models that combine the mean absolute deviation (MAD and the conditional value at risk (CVaR, attempting to mitigate inefficient, low return and/or high-risk, portfolios. Three methodologies for estimating the probability of the asset’s historical returns are also compared. By using historical data on the Brazilian stock market between 2004 and 2013, we analyze the efficiency of the proposed approaches. Our results show that the traditional models provide portfolios with higher returns, but our propose model are able to generate lower risk portfolios, which might be more attractive in volatile markets. In addition, we find that models that do not use equiprobable scenarios produce better results in terms of return and risk.

Assessing the Value of Information for Identifying Optimal Floodplain Management Portfolios

Science.gov (United States)

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

2014-12-01

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

Reinforcement Learning in Repeated Portfolio Decisions

OpenAIRE

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...

Optimal Portfolio Allocation under a Probabilistic Risk Constraint and the Incentives for Financial Innovation

NARCIS (Netherlands)

J. Daníelsson (Jón); B.N. Jorgensen (Bjørn); C.G. de Vries (Casper); X. Yang (Xiaoguang)

2001-01-01

textabstractWe derive, in a complete markets environment, an investor's optimal portfolio allocation subject to both a budget constraint and a probabilistic risk constraint. We demonstrate that the set of feasible portfolios need not be connected or convex, while the number of local optima increases

Optimising investment performance through international diversification

Directory of Open Access Journals (Sweden)

J. Swart

2014-01-01

Full Text Available International portfolio diversification is often advocated as a way of enhancing portfolio performance particularly through the reduction of portfolio risk. Portfolio managers in Europe have for decades routinely invested a substantial portion of their portfolios in securities that were issued in other countries. During the last decade US investors have held a significant amount of foreign securities with over a trillion dollars invested in foreign assets by 1994. South African institutions have been allowed some freedom to diversify internationally since mid 1995 and individual investors since July 1997. In this paper the potential diversification benefits for South African investors are considered. The stability over time of the correlation structure is investigated and simple ex-ante investment strategies are formulated and evaluated.

Wright meets Markowitz: How standard portfolio theory changes when assets are technologies following experience curves

OpenAIRE

Way, Rupert; Lafond, François; Farmer, J. Doyne; Lillo, Fabrizio; Panchenko, Valentyn

2017-01-01

This paper considers how to optimally allocate investments in a portfolio of competing technologies. We introduce a simple model representing the underlying trade-off - between investing enough effort in any one project to spur rapid progress, and diversifying effort over many projects simultaneously to hedge against failure. We use stochastic experience curves to model the idea that investing more in a technology reduces its unit costs, and we use a mean-variance objective function to unders...

Wavelet evolutionary network for complex-constrained portfolio rebalancing

Science.gov (United States)

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

2012-07-01

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

Portfolio Evaluation Based on Efficient Frontier Superiority Using Center of Gravity

Directory of Open Access Journals (Sweden)

Omar Samat

2010-01-01

Full Text Available Investing in portfolio of assets is the best way to reduce the investment risk. The most desired portfolio can be obtained when investors chose to invest in the portfolios that lay on the portfolio’s efficient frontier. However, the superiorities of the portfolios are difficult to differentiate especially when the efficient frontier curves are overlapping. This paper proposed the portfolio’s efficient frontier center of gravity (CoG and Euclidean distance to identify its superiority. A sample of 49 stocks of large-cap and small-cap were used to construct two hypothetical portfolios and its efficient frontiers. The Euclidean distance showed that the large-cap portfolio is superior and having wider feasible solutions compared to the small-cap portfolio. The results of new tool introduced are consistent with the conventional methods. Here the theoretical and practical implications are provided in light of the findings.

Parametric Portfolio Selection: Evaluating and Comparing to Markowitz Portfolios

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

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.

A Monte Carlo simulation technique to determine the optimal portfolio

Directory of Open Access Journals (Sweden)

Hassan Ghodrati

2014-03-01

Full Text Available During the past few years, there have been several studies for portfolio management. One of the primary concerns on any stock market is to detect the risk associated with various assets. One of the recognized methods in order to measure, to forecast, and to manage the existing risk is associated with Value at Risk (VaR, which draws much attention by financial institutions in recent years. VaR is a method for recognizing and evaluating of risk, which uses the standard statistical techniques and the method has been used in other fields, increasingly. The present study has measured the value at risk of 26 companies from chemical industry in Tehran Stock Exchange over the period 2009-2011 using the simulation technique of Monte Carlo with 95% confidence level. The used variability in the present study has been the daily return resulted from the stock daily price change. Moreover, the weight of optimal investment has been determined using a hybrid model called Markowitz and Winker model in each determined stocks. The results showed that the maximum loss would not exceed from 1259432 Rials at 95% confidence level in future day.

Optimal trading quantity integration as a basis for optimal portfolio management

Directory of Open Access Journals (Sweden)

Saša Žiković

2005-06-01

Full Text Available The author in this paper points out the reason behind calculating and using optimal trading quantity in conjunction with Markowitz’s Modern portfolio theory. In the opening part the author presents an example of calculating optimal weights using Markowitz’s Mean-Variance approach, followed by an explanation of basic logic behind optimal trading quantity. The use of optimal trading quantity is not limited to systems with Bernoulli outcome, but can also be used when trading shares, futures, options etc. Optimal trading quantity points out two often-overlooked axioms: (1 a system with negative mathematical expectancy can never be transformed in a system with positive mathematical expectancy, (2 by missing the optimal trading quantity an investor can turn a system with positive expectancy into a negative one. Optimal trading quantity is that quantity which maximizes geometric mean (growth function of a particular system. To determine the optimal trading quantity for simpler systems, with a very limited number of outcomes, a set of Kelly’s formulas is appropriate. In the conclusion the summary of the paper is presented.

Long-run savings and investment strategy optimization.

Science.gov (United States)

Gerrard, Russell; Guillén, Montserrat; Nielsen, Jens Perch; Pérez-Marín, Ana M

2014-01-01

We focus on automatic strategies to optimize life cycle savings and investment. Classical optimal savings theory establishes that, given the level of risk aversion, a saver would keep the same relative amount invested in risky assets at any given time. We show that, when optimizing lifecycle investment, performance and risk assessment have to take into account the investor's risk aversion and the maximum amount the investor could lose, simultaneously. When risk aversion and maximum possible loss are considered jointly, an optimal savings strategy is obtained, which follows from constant rather than relative absolute risk aversion. This result is fundamental to prove that if risk aversion and the maximum possible loss are both high, then holding a constant amount invested in the risky asset is optimal for a standard lifetime saving/pension process and outperforms some other simple strategies. Performance comparisons are based on downside risk-adjusted equivalence that is used in our illustration.

Long-Run Savings and Investment Strategy Optimization

Directory of Open Access Journals (Sweden)

Russell Gerrard

2014-01-01

Full Text Available We focus on automatic strategies to optimize life cycle savings and investment. Classical optimal savings theory establishes that, given the level of risk aversion, a saver would keep the same relative amount invested in risky assets at any given time. We show that, when optimizing lifecycle investment, performance and risk assessment have to take into account the investor’s risk aversion and the maximum amount the investor could lose, simultaneously. When risk aversion and maximum possible loss are considered jointly, an optimal savings strategy is obtained, which follows from constant rather than relative absolute risk aversion. This result is fundamental to prove that if risk aversion and the maximum possible loss are both high, then holding a constant amount invested in the risky asset is optimal for a standard lifetime saving/pension process and outperforms some other simple strategies. Performance comparisons are based on downside risk-adjusted equivalence that is used in our illustration.

Scenario-informed multiple criteria analysis for prioritizing investments in electricity capacity expansion

International Nuclear Information System (INIS)

Martinez, Lauro J.; Lambert, James H.; Karvetski, Christopher W.

2011-01-01

Planning the expansion and energy security of electricity capacity for a national electricity utility is a complex task in almost any economy. Planning is usually an iterative activity and can involve the use of large scale planning optimization systems accompanied by assessment of uncertain scenarios emerging from economic, technological, environmental, and regulatory developments. This paper applies a multiple criteria decision analysis to prioritize investment portfolios in capacity expansion and energy security while principally studying the robustness of the prioritization to multiple uncertain and emergent scenarios. The scenarios are identified through interaction with decision makers and stakeholders. The approach finds which scenarios most affect the prioritization of the portfolios and which portfolios have the greatest upside and downside potential across scenarios. The approach fosters innovation in the use of robust and efficient technologies, renewable energy sources, and cleaner energy fuels. A demonstration is provided for assessing the performance of technology portfolios constructed from investments in nine electricity generation technologies in Mexico.

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

Science.gov (United States)

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.

Long-term portfolio investments: New insight into return and risk

Directory of Open Access Journals (Sweden)

Alexander Abramov

2015-09-01

Emphasis is placed on the need for regular adjustments to long-term investors’ portfolios. As portfolios get older, those investors see a reduction in the returns’ dispersion, while differences in risk between various portfolios increase. This means that to maintain a fixed risk–return ratio for a portfolio as the horizon increases, an investor needs to increase the share of lower-risk financial assets during asset allocation process. This thesis becomes especially relevant in the context of retirement savings management.

Optimal Priority Structure, Capital Structure, and Investment

OpenAIRE

Dirk Hackbarth; David C. Mauer

2012-01-01

We study the interaction between financing and investment decisions in a dynamic model, where the firm has multiple debt issues and equityholders choose the timing of investment. Jointly optimal capital and priority structures can virtually eliminate investment distortions because debt priority serves as a dynamically optimal contract. Examining the relative efficiency of priority rules observed in practice, we develop several predictions about how firms adjust their priority structure in res...

A Generalized Measure for the Optimal Portfolio Selection Problem and its Explicit Solution

Directory of Open Access Journals (Sweden)

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.

A Quantitative Optimization Framework for Market-Driven Academic Program Portfolios

NARCIS (Netherlands)

Burgher, Joshua; Hamers, Herbert

2017-01-01

We introduce a quantitative model that can be used for decision support for planning and optimizing the composition of portfolios of market-driven academic programs within the context of higher education. This model is intended to enable leaders in colleges and universities to maximize financial

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

Science.gov (United States)

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.

The Canada Pension Plan's experience with investing its portfolio in equities.

Science.gov (United States)

Sarney, M; Preneta, A M

For the past few years, the Canada Pension Plan (CPP) has been investing some of its assets in equities. Without changes, an imbalance between revenues and outlays would exhaust the CPP reserve fund by 2015. Creating an entity that was independent of government was one of several changes the federal and provincial governments enacted to achieve fuller funding. The governments created an independent Investment Board (the CPP Investment Board, or "CPPIB") to oversee the new investments. Because the plan already owned a large government bond portfolio, the CPPIB decided to invest new CPP funds in broad equity indices in March 1999. In 2000, the CPPIB began actively investing a portion of the CPP funds. Key features of that policy and some observations about its implementation include the following: In addition to investing CPP revenues in equities, reform also included contribution rate increases, benefit reductions, and a financing stabilizer. The new investment policy accounted for 25 percent of the total effect of all the reforms. It is premature to know if the investments will achieve their long-term performance objective. The new equity investments are projected by the Chief Actuary, in his most recent Actuarial Report, to earn a 4.5 percent real rate of return on Canadian equity and 5.0 percent real return on foreign equity for a blended real return of 4.65 percent based on an equity mix of 70 percent Canadian and 30 percent non-Canadian. However, it is too early to tell if the equity investments will achieve that goal over the long run. The Investment Board's mandate is to maximize returns. The Investment Board, which oversees the CPP's new investments, has broad discretion to pursue maximum returns on its assets without incurring undue risk of loss while keeping in mind the financial obligations and other assets of the CPP. Furthermore, it has developed into a professional investment organization staffed with private-sector experts in finance and investment

Raising the bar on the foreign portfolio to 25 per cent: Strategic implications for South African investors

Directory of Open Access Journals (Sweden)

David John Bradfield

2015-08-01

Full Text Available Regulation 28 of the Pension Funds Act now permits an increased allocation of 25 per cent to foreign investments. The regulation previously only permitted a 20 per cent allocation. Establishing the optimal foreign allocation for South African portfolio managers given the 25 per cent upper bound is an important consideration for strategic portfolio planning. In this paper we consider two methodological approaches to establish a strategic foreign allocation weight. Our first approach considers the strategic role of foreign investment in South African global balanced portfolios by using a mean-variance efficient frontier framework over a long-term period. We also implement a second assessment methodology that utilises a nonparametric procedure. Both the mean-variance and the non-parametric methodology yield compelling evidence for the foreign allocation to be set at the maximum allowable bound of 25 per cent.

Building a Smart E-Portfolio Platform for Optimal E-Learning Objects Acquisition

Directory of Open Access Journals (Sweden)

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.

Designing Modern Equity Portfolios

OpenAIRE

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.

Gli investimenti di portafoglio nelle economie di mercato emergenti:tendenze, dimensioni e problemi (Portfolio Investment in Emerging Market Economies: Trends, Dimensions and Issues

Directory of Open Access Journals (Sweden)

Dilip K. Das

2012-04-01

Full Text Available Securitised financial flows to emerging market economies have become an important feature of the global capital flows. The principal focus of this paper is on an in-depth analysis of current trends in securitised financial flows. It lays special emphasis on private portfolio equity investment into the emerging market economies. The paper begins with the analysis of the process of stimulation of these flows, and identifies the institutional, structural and non-cyclical factors behind them. One of the points it emphasises is the progressively important role of institutional investors, which is the causal factor behind a significant increase in the quantum of portfolio investment into the emerging market economies. These flows were adversely affected by the financial crises of the 1990s. The subject matter of this paper also includes two of the most important policy issues, namely, the "hot money and cold money" issue and the volatility issue.       JEL Codes: G11, O16, F32, P33Keywords: Capital Flows, Financial Flows, Portfolio

Artificial bee colony algorithm for constrained possibilistic portfolio optimization problem

Science.gov (United States)

Chen, Wei

2015-07-01

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

Behavioral optimization models for multicriteria portfolio selection

Directory of Open Access Journals (Sweden)

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.

Public Project Portfolio Optimization under a Participatory Paradigm

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Eduardo Fernandez

2013-01-01

Full Text Available A new democracy paradigm is emerging through participatory budgeting exercises, which can be defined as a public space in which the government and the society agree on how to adapt the priorities of the citizenship to the public policy agenda. Although these priorities have been identified and they are likely to be reflected in a ranking of public policy actions, there is still a challenge of solving a portfolio problem of public projects that should implement the agreed agenda. This work proposes two procedures for optimizing the portfolio of public actions with the information stemming from the citizen participatory exercise. The selection of the method depends on the information about preferences collected from the participatory group. When the information is sufficient, the method behaves as an instrument of legitimate democracy. The proposal performs very well in solving two real-size examples.

Investment under uncertainty : Timing and capacity optimization

NARCIS (Netherlands)

Wen, Xingang

2017-01-01

This thesis consists of three chapters on analyzing the optimal investment timing and investment capacity for the firm(s) undertaking irreversible investment in an uncertain environment. Chapter 2 studies the investment decision of a monopoly firm when it can adjust output quantity in a market with

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

Science.gov (United States)

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

2018-03-01

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

Large and small baseload power plants: Drivers to define the optimal portfolios

International Nuclear Information System (INIS)

Locatelli, Giorgio; Mancini, Mauro

2011-01-01

Despite the growing interest in Small Medium sized Power Plants (SMPP) international literature provides only studies related to portfolios of large plants in infinite markets/grids with no particular attention given to base load SMPP. This paper aims to fill this gap, investigating the attractiveness of SMPP portfolios respect to large power plant portfolios. The analysis includes nuclear, coal and combined cycle gas turbines (CCGT) of different plant sizes. The Mean Variance Portfolio theory (MVP) is used to define the best portfolio according to Internal Rate of Return (IRR) and Levelised Unit Electricity Cost (LUEC) considering the life cycle costs of each power plant, Carbon Tax, Electricity Price and grid dimension. The results show how large plants are the best option for large grids, while SMPP are as competitive as large plants in small grids. In fact, in order to achieve the highest profitability with the lowest risk it is necessary to build several types of different plants and, in case of small grids, this is possible only with SMPP. A further result is the application of the framework to European OECD countries and the United States assessing their portfolios. - Highlights: ► The literature about power plant portfolios does not consider small grids and IRR. ► We evaluated Base load portfolios respect to IRR and LUEC. ► We assessed the influence of grid and plant size, CO 2 cost and Electricity Price. ► Large plants are optimal for large markets even if small plants have similar IRR. ► Small plants are suitable to diversify portfolios in small grids reducing the risk.

Optimization of a dynamic supply portfolio considering risks and discount’s constraints

Directory of Open Access Journals (Sweden)

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

Portfolio management: Finding growth opportunities in a restructured electricity marketplace. Final report

International Nuclear Information System (INIS)

Staley, J.; Patterson, A.; Gardner, T.

1997-12-01

Energy services companies are rapidly creating a wide array of new products and services for their customers. To penetrate the marketplace most effectively, however, these new offerings should be integrated into cohesive portfolios that meet the needs of key customer segments. This report explores the techniques of portfolio management and describes how this tool can help bring greater balance and focus to an energy provider's product and service portfolios. Portfolio management provides a process for initiating, overseeing, and exiting from diverse investments on the basis of not only the merits of each individual investment, but also the merits of those investments in combination. The principles of portfolio management can be applied to various types of investments, including those involving lines of business, new product initiatives, and project commitments. With the rapid transition to a more competitive environment, these types of market-oriented investments are receiving greater scrutiny in the energy services industry. Accordingly, portfolio management techniques are becoming increasingly important business tools. The project team considers three different categories of portfolio management within the context of the energy services industry. Passive portfolio management focuses on choosing the combination of products/services that will provide the most favorable trade-off of risk and return for a given risk tolerance. Balanced portfolio management provides a more aggressive set of techniques that look broadly at a company's multiple objectives and assist in deploying resources to achieve balance along multiple dimensions. Strategic portfolio management goes even further by helping to define a set of synergistic offerings that reinforce one another and the company's strategic direction. In this report the team also documents case studies of companies that profited from their portfolio management efforts and presents a project design for developing and

Leptokurtic portfolio theory

Science.gov (United States)

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 Deterministic Investment Strategies for Insurers

Directory of Open Access Journals (Sweden)

Ulrich Rieder

2013-11-01

Full Text Available We consider an insurance company whose risk reserve is given by a Brownian motion with drift and which is able to invest the money into a Black–Scholes financial market. As optimization criteria, we treat mean-variance problems, problems with other risk measures, exponential utility and the probability of ruin. Following recent research, we assume that investment strategies have to be deterministic. This leads to deterministic control problems, which are quite easy to solve. Moreover, it turns out that there are some interesting links between the optimal investment strategies of these problems. Finally, we also show that this approach works in the Lévy process framework.

Cross-border Portfolio Investment Networks and Indicators for Financial Crises

Science.gov (United States)

Joseph, Andreas C.; Joseph, Stephan E.; Chen, Guanrong

2014-02-01

Cross-border equity and long-term debt securities portfolio investment networks are analysed from 2002 to 2012, covering the 2008 global financial crisis. They serve as network-proxies for measuring the robustness of the global financial system and the interdependence of financial markets, respectively. Two early-warning indicators for financial crises are identified: First, the algebraic connectivity of the equity securities network, as a measure for structural robustness, drops close to zero already in 2005, while there is an over-representation of high-degree off-shore financial centres among the countries most-related to this observation, suggesting an investigation of such nodes with respect to the structural stability of the global financial system. Second, using a phenomenological model, the edge density of the debt securities network is found to describe, and even forecast, the proliferation of several over-the-counter-traded financial derivatives, most prominently credit default swaps, enabling one to detect potentially dangerous levels of market interdependence and systemic risk.

Reliable Portfolio Selection Problem in Fuzzy Environment: An mλ Measure Based Approach

Directory of Open Access Journals (Sweden)

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.

Universal portfolios generated by the Bregman divergence

Science.gov (United States)

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.

Pedagogical Strategies for Incorporating Behavioral Finance Concepts in Investment Courses

Science.gov (United States)

Adams, Michael; Mullins, Terry; Thornton, Barry

2007-01-01

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

Differentiated risk models in portfolio optimization: a comparative analysis of the degree of diversification and performance in the São Paulo Stock Exchange (BOVESPA

Directory of Open Access Journals (Sweden)

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

Robust Active Portfolio Management

National Research Council Canada - National Science Library

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...

Does Aggregated Returns Disclosure Increase Portfolio Risk Taking?

Science.gov (United States)

Beshears, John; Choi, James J; Laibson, David; Madrian, Brigitte C

2017-06-01

Many experiments have found that participants take more investment risk if they see returns less frequently, see portfolio-level returns (rather than each individual asset's returns), or see long-horizon (rather than one-year) historical return distributions. In contrast, we find that such information aggregation treatments do not affect total equity investment when we make the investment environment more realistic than in prior experiments. Previously documented aggregation effects are not robust to changes in the risky asset's return distribution or the introduction of a multi-day delay between portfolio choice and return realizations.

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

Science.gov (United States)

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

2010-09-01

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

Effective Stock Selection and Portfolio Construction Within US, International, and Emerging Markets

Directory of Open Access Journals (Sweden)

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.

Supply contract and portfolio insurance

Science.gov (United States)

Runsheng Yin; Bob Izlar

2001-01-01

The long-term growth of institutional timberland investments depends on the ability of timberland investment management organizations (TIMO) to deal effectively with securitization, leveraging, arbitraging, supply contracting, portfolio insurance, tax efficiency enhancement, and other issues. Financial engineering holds great promise for many of these issues. This...

INFLUENCE OF REGIME SWITCHING TO RISK IN PORT-MODERN PORTFOLIO MANAGEMENT

OpenAIRE

Cristina Geambaşu; Liviu Geambaşu; Iulia Jianu

2013-01-01

The present financial crises determines an increase in analysing the application of regime switching over portfolio investments. We applied the switching regimes to measurement of risk as presented in post-modern portfolio management theory. Post-modern portfolio theory include investor’s tendency to measure risk as the chance to obtain from the investment performed a return lower than the minimum expected by him. The investor, as presented by behavioural finance, is more concerned about his ...

Investment Strategy and Efficiency of Investment Activity of European Insurers

Directory of Open Access Journals (Sweden)

Zhabynets Olga Yo.

2014-02-01

Full Text Available The article studies investment strategy and efficiency of investment activity of European insurance companies. In particular, it analyses the share of investments of insurance companies of Europe in GDP, investment portfolio of European insurers and its structure, contribution of insurance companies – leaders of investment activity – into the European investment portfolio. It studies influence of the financial crisis upon investment strategy of European insurers and analyses efficiency of investment activity of European insurers in risk insurance and life insurance. The article proves that investment business models of insurance companies are capable of resisting crisis phenomena more efficiently than other financial institutions. It marks out that measures of insurance companies that are directed at increase of profitability of investments require from them both significant expenditures on creation of the system of investment risk management and open access to different categories of financial assets and markets, which influences the general risk level, taken upon by an insurance company. The author draws a conclusion that, taking into account recent developments, European insurers should focus on equity and investment risk management, finding new possibilities for their (investments growth and also adaptation of new systems and operations for solution of these important tasks.

The Experimental Study on.the Risk Convergence of the Entrusted Portfolios of NSSF

Institute of Scientific and Technical Information of China (English)

QU Bao-zhong; PANG Qing

2008-01-01

This paper makes use of statistical tools of parameter correlation,multi-parameter regression,and does experimental analysis on issues of risk diversification of portfolios entrusted by National Social Security Fund (NSSF).The issues are industry related investment fieIds distribution,the trend of capitalization movement,and investment style factors in stock selection.The results show that there are risk problems with portfolios entrusted by NSSF,which include similar investment fields distribution trend,little difference among portfolios,and high risk preference degree.

An Evolutionary Algorithm for Multiobjective Fuzzy Portfolio Selection Models with Transaction Cost and Liquidity

Directory of Open Access Journals (Sweden)

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.

Bayesian emulation for optimization in multi-step portfolio decisions

OpenAIRE

Irie, Kaoru; West, Mike

2016-01-01

We discuss the Bayesian emulation approach to computational solution of multi-step portfolio studies in financial time series. "Bayesian emulation for decisions" involves mapping the technical structure of a decision analysis problem to that of Bayesian inference in a purely synthetic "emulating" statistical model. This provides access to standard posterior analytic, simulation and optimization methods that yield indirect solutions of the decision problem. We develop this in time series portf...

Optimal selling rules for monetary invariant criteria: tracking the maximum of a portfolio with negative drift

OpenAIRE

Elie, Romuald; Espinosa, Gilles-Edouard

2013-01-01

Considering a positive portfolio diffusion $X$ with negative drift, we investigate optimal stopping problems of the form $$ \\inf_\\theta \\Esp{f\\left(\\frac{X_\\theta}{\\Sup_{s\\in[0,\\tau]}{X_s}}\\right)}\\;,$$ where $f$ is a non-increasing function, $\\tau$ is the next random time where the portfolio $X$ crosses zero and $\\theta$ is any stopping time smaller than $\\tau$. Hereby, our motivation is the obtention of an optimal selling strategy minimizing the relative distance between the liquidation val...

Does Aggregated Returns Disclosure Increase Portfolio Risk Taking?

Science.gov (United States)

Beshears, John; Choi, James J.; Laibson, David; Madrian, Brigitte C.

2016-01-01

Many experiments have found that participants take more investment risk if they see returns less frequently, see portfolio-level returns (rather than each individual asset’s returns), or see long-horizon (rather than one-year) historical return distributions. In contrast, we find that such information aggregation treatments do not affect total equity investment when we make the investment environment more realistic than in prior experiments. Previously documented aggregation effects are not robust to changes in the risky asset’s return distribution or the introduction of a multi-day delay between portfolio choice and return realizations. PMID:28553012

Smart Beta Equity Investing Through Calm and Storm

NARCIS (Netherlands)

Boudt, Kris; Darras, Joakim; Ha Nguyen, Giang; Peeters, Benedict

2015-01-01

Smart beta portfolios typically achieve a superior diversification than the benchmark market capitalization-weighted portfolio, but remain vulnerable to broad market downturns. We examine tactical investment decision rules to switch timely between equity and cash investments based on an underlying

A General Framework for Portfolio Theory—Part I: Theory and Various Models

Directory of Open Access Journals (Sweden)

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.

Use of crops and livestock futures contracts in portfolios: an analysis of feasibility

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Mattos Fabio L.

2003-01-01

Full Text Available According to Portfolio Theory, by combining assets that show a correlation inferior to one (1 among their individual returns, it becomes possible to create portfolios that reduce risk without damaging expected return. Crop and livestock futures contracts and company stocks show such a characteristic, which signals potential benefits when forming portfolios combining these two types of assets. This investment strategy is not often utilized in Brazil. The purpose of our research was to assess whether such an asset combination is actually advantageous to those creating investment portfolios in the Brazilian market. Our evaluation used instruments of analysis developed by Markowitz in Portfolio Theory and data about the return from crop and livestock futures contracts and stocks. The data was gathered from the Brazilian Futures and Commodities Exchange (BM&F and Brazil?s National Association of Open Market Institutions (ANDIMA between July 1994 and December 1998. The results of this work showed that the combination of these two types of assets in investment portfolios can be an interesting portfolio management alternative.

The investment strategy of commercial banks on the financial markets

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Ercegovac Dajana

2012-01-01

Full Text Available In contemporary market conditions classical deposit-loan strategy is not enough anymore in order to ensure survival of the commercial banks on the financial market and to reach profit that is high enough. Besides the loan placements strategy, it is necessary to adopt an adequate investment strategy which will contribute to the profitability, liquidity and safety of gross asset portfolio. Commercial banks, unlike investment banks, invest smaller part of their resources into securities of diverse maturity on financial markets. However, with the harsh competition of banks and other non-banking institutions, significance of investment portfolio grows as an alternative that ensures additional sources of revenue, assures liquidity, diversification of placements and decreases risk exposure. Banks have at their disposal vast range of investment strategies that can be combined depending on their investment objectives and risk aversion, such as passive and active strategy, strategy of ladder, weights strategy etc. Therefore, the aim of this paper is to present the significance of investment portfolio in commercial banks and the basic management strategies of investment portfolio that can be used by commercial banks.

Switching portfolios.

Science.gov (United States)

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.

Optimal Portfolio Selection Under Concave Price Impact

International Nuclear Information System (INIS)

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

Energy Technology Data Exchange (ETDEWEB)

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.

Portofolio Optimal dan Pengelompokan Perusahaan Berdasarkan Pengaruh Komoditas Dunia

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