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Large-Scale Portfolio Optimization Using Biogeography-Based Optimization

Author

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  • Wendy Wijaya

    (Department of Mathematics, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Ganesa Street No. 10, Bandung 40132, Indonesia)

  • Kuntjoro Adji Sidarto

    (Department of Mathematics, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Ganesa Street No. 10, Bandung 40132, Indonesia)

Abstract

Portfolio optimization is a mathematical formulation whose objective is to maximize returns while minimizing risks. A great deal of improvement in portfolio optimization models has been made, including the addition of practical constraints. As the number of shares traded grows, the problem becomes dimensionally very large. In this paper, we propose the usage of modified biogeography-based optimization to solve the large-scale constrained portfolio optimization. The results indicate the effectiveness of the method used.

Suggested Citation

  • Wendy Wijaya & Kuntjoro Adji Sidarto, 2023. "Large-Scale Portfolio Optimization Using Biogeography-Based Optimization," IJFS, MDPI, vol. 11(4), pages 1-16, October.
    • Handle: RePEc:gam:jijfss:v:11:y:2023:i:4:p:125-:d:1268092
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    References listed on IDEAS

    as
    1. Mavrotas, George & Florios, Kostas, 2013. "An improved version of the augmented epsilon-constraint method (AUGMECON2) for finding the exact Pareto set in Multi-Objective Integer Programming problems," MPRA Paper 105034, University Library of Munich, Germany.
    2. Andre F. Perold, 1984. "Large-Scale Portfolio Optimization," Management Science, INFORMS, vol. 30(10), pages 1143-1160, October.
    3. M. Bartholomew-Biggs & S. Kane, 2009. "A global optimization problem in portfolio selection," Computational Management Science, Springer, vol. 6(3), pages 329-345, August.
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