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Asset Allocation And Portfolio Optimization Problems With Metaheuristics: A Literature Survey

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  • Bilel JARRAYA

    (University of Sfax, Sfax, Tunisia)

Abstract

The main objective of Markowitz work is seeking optimal allocation of wealth on a defined number of assets while minimizing risk and maximizing returns of expected portfolio. At the beginning, proposed models in this issue are resolved basing on quadratic programming. Unfortunately, the real state of financial markets makes these problems too complex. Metaheuristics are stochastic methods which aim to solve a large panel of NPhard problems without intervention of users. These methods are inspired from analogies with other fields such as physics, genetics, or ethologic. Already various Metaheuristics approaches have been proposed to solve asset allocation and portfolio optimization problems. In a first time, we survey some approaches on the topic, by categorizing them, describing results and involved techniques. Second part of this paper aims providing a good guide to the application of Metaheuristics to portfolio optimization and asset allocation problems.

Suggested Citation

  • Bilel JARRAYA, 2013. "Asset Allocation And Portfolio Optimization Problems With Metaheuristics: A Literature Survey," Business Excellence and Management, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 3(4), pages 38-56, December.
    • Handle: RePEc:rom:bemann:v:3:y:2013:i:4:p:38-56
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    References listed on IDEAS

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    1. Man-Chung CHAN & Chi-Cheong WONG & Bernard K-S Cheung & Gordon Y-N Tang, 2002. "Genetic Algorithms in Multi-Stage Portfolio Optimization System," Computing in Economics and Finance 2002 165, Society for Computational Economics.
    2. Crama, Y. & Schyns, M., 2003. "Simulated annealing for complex portfolio selection problems," European Journal of Operational Research, Elsevier, vol. 150(3), pages 546-571, November.
    3. Bilel JARRAYA, 2013. "Asset Allocation And Portfolio Optimization Problems With Metaheuristics: A Literature Survey," Business Excellence and Management, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 3(4), pages 38-56, December.
    4. Ardia, David & Boudt, Kris & Carl, Peter & Mullen, Katharine M. & Peterson, Brian, 2010. "Differential Evolution (DEoptim) for Non-Convex Portfolio Optimization," MPRA Paper 22135, University Library of Munich, Germany.
    5. Yu, Tzu-Yi & Tsai, Chenghsien & Huang, Hsiao-Tzu, 2010. "Applying simulation optimization to the asset allocation of a property-casualty insurer," European Journal of Operational Research, Elsevier, vol. 207(1), pages 499-507, November.
    6. Thiemo Krink & Sandra Paterlini, 2011. "Multiobjective optimization using differential evolution for real-world portfolio optimization," Computational Management Science, Springer, vol. 8(1), pages 157-179, April.
    7. Alois Geyer & Michael Hanke & Alex Weissensteiner, 2009. "A stochastic programming approach for multi-period portfolio optimization," Computational Management Science, Springer, vol. 6(2), pages 187-208, May.
    8. Branke, J. & Scheckenbach, B. & Stein, M. & Deb, K. & Schmeck, H., 2009. "Portfolio optimization with an envelope-based multi-objective evolutionary algorithm," European Journal of Operational Research, Elsevier, vol. 199(3), pages 684-693, December.
    9. Friesz, Terry L. & Anandalingam, G. & Mehta, Nihal J. & Nam, Keesung & Shah, Samir J. & Tobin, Roger L., 1993. "The multiobjective equilibrium network design problem revisited: A simulated annealing approach," European Journal of Operational Research, Elsevier, vol. 65(1), pages 44-57, February.
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    1. Bilel JARRAYA, 2013. "Asset Allocation And Portfolio Optimization Problems With Metaheuristics: A Literature Survey," Business Excellence and Management, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 3(4), pages 38-56, December.

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    More about this item

    Keywords

    Portfolio; Asset allocation; Metaheuristics; Mono-objective problems; Multi-objective problem;
    All these keywords.

    JEL classification:

    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management

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