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Algorithm of construction of Optimum Portfolio of stocks using Genetic Algorithm

Author

Listed:
  • Sinha, Pankaj
  • Chandwani, Abhishek
  • Sinha, Tanmay

Abstract

The objective of this paper is to develop an algorithm to create an Optimum Portfolio from a large pool of stocks listed in a single market index SPX 500 Index: USA (for example) using Genetic Algorithm. The algorithm selects stocks on the basis of a priority index function designed on company fundamentals, and then genetically assigns optimum weights to the selected stocks by finding a genetically suitable combination of return and risk on the basis of historical data. The effect of genetic evolution on portfolio optimization has been demonstrated by developing a MATLAB code to implement the genetic application of reproduction, crossover and mutation operators. The effectiveness of the obtained portfolio has been successfully tested by running its performance over a six month holding period. It is found that genetic algorithm is successful in providing the optimum weights to stocks which were initially screened through a predetermined priority index function. The constructed portfolio beats the market for the considered holding period by a significant margin.

Suggested Citation

  • Sinha, Pankaj & Chandwani, Abhishek & Sinha, Tanmay, 2013. "Algorithm of construction of Optimum Portfolio of stocks using Genetic Algorithm," MPRA Paper 48204, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:48204
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    File URL: https://mpra.ub.uni-muenchen.de/48204/1/MPRA_paper_48204.pdf
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    References listed on IDEAS

    as
    1. Slimane Sefiane & Mohamed Benbouziane, 2012. "Portfolio Selection Using Genetic Algorithm," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 2(4), pages 1-9.
    2. Robert Pereira, 2000. "Genetic Algorithm Optimisation for Finance and Investment," Working Papers 2000.02, School of Economics, La Trobe University.
    3. Sinha, Pankaj & Goyal, Lavleen, 2012. "Algorithm for construction of portfolio of stocks using Treynor’s ratio," MPRA Paper 40134, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Optimum Portfolio; Genetic Algorithm; Portfolio Construction; MATLAB;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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