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Portfolio Optimzation Using of Metods Multi Objective Genetic Algorithm and Goal Programming: An Application in BIST-30

Author

Listed:
  • Yakut, Emre

    (Osmaniye Korkut Ata University)

  • Çankal, Ahmet

    (Osmaniye Korkut Ata University)

Abstract

Portfolio optimization problem has become one of the related fields of financial engineering since the studies of Markowitz about modern portfolio theory. Selection process of portfolio is carried out by looking at the return and risk relationship of stocks in portfolio in order to create the best portfolio. The main purpose of a financial manager is to ensure an efficient portfolio which provides minimum risk and maximum return. For this purpose, new models and computer technology continue at an accelerated rate. Genetic algorithms are from stochastic algorithm family based on the principles of natural selection. In this study, soft closing prices data of BIST 30 stocks between the periods, 2004-2013 are used. Eight different return and risk portfolios are created by applying goal programming and multi-purpose genetic algorithm methods with Markowitz mean-variance model. Variation coefficient which is a statistical unit of measure used for selection of portfolio is used. The results obtained from the study show that the best portfolios consist of number 7 portfolio for genetic algorithm and 5 stocks of this portfolio ; number 4 portfolio for quadratic goal programming method and 8 stocks of this portfolio. It is concluded that when compared in terms of optimization techniques, quadratic goal programming gives better results than genetic algorithm.

Suggested Citation

  • Yakut, Emre & Çankal, Ahmet, 2016. "Portfolio Optimzation Using of Metods Multi Objective Genetic Algorithm and Goal Programming: An Application in BIST-30," Business and Economics Research Journal, Uludag University, Faculty of Economics and Administrative Sciences, vol. 7(2), pages 43-62, April.
    • Handle: RePEc:ris:buecrj:0223
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    More about this item

    Keywords

    Genetic Algorithm; Multiobjective Genetic Algortihm; Goal Programming; Optimal Portfolio; Portfolio Selection;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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