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V-Shaped BAS: Applications on Large Portfolios Selection Problem

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  • Spyridon D. Mourtas

    (National and Kapodistrian University of Athens)

  • Vasilios N. Katsikis

    (National and Kapodistrian University of Athens)

Abstract

The beetle antennae search (BAS) algorithm is a memetic meta-heuristic optimization algorithm capable of solving combinatorial optimization problems. In this paper, the binary version of BAS (BBAS) is modified by adding a V-shaped transfer function. In this way, we introduce the V-shaped transfer function-based binary BAS (VSBAS) algorithm, which is a more effective and efficient version of BBAS in the case of large input data. Applications using real-world data sets on a binary Markowitz-based portfolio selection (BMPS) problem validate the excellent performance of VSBAS on large input data and demonstrate that it is a marvelous alternative against other ordinary memetic meta-heuristic optimization algorithms. Note that, because the meta-heuristic algorithms compared in this paper are directly applicable only to unconstrained optimization, the penalty function method was used to keep their solutions in the feasible district. In order to support and promote the findings of this work, we have constructed a complete MATLAB package for the interested user, which is freely available through GitHub.

Suggested Citation

  • Spyridon D. Mourtas & Vasilios N. Katsikis, 2022. "V-Shaped BAS: Applications on Large Portfolios Selection Problem," Computational Economics, Springer;Society for Computational Economics, vol. 60(4), pages 1353-1373, December.
    • Handle: RePEc:kap:compec:v:60:y:2022:i:4:d:10.1007_s10614-021-10184-9
    DOI: 10.1007/s10614-021-10184-9
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    References listed on IDEAS

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    1. Panos Xidonas & George Mavrotas, 2014. "Comparative issues between linear and non-linear risk measures for non-convex portfolio optimization: evidence from the S&P 500," Quantitative Finance, Taylor & Francis Journals, vol. 14(7), pages 1229-1242, July.
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