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Solving Constrained Mean-Variance Portfolio Optimization Problems Using Spiral Optimization Algorithm

Author

Listed:
  • Werry Febrianti

    (Department of Mathematics, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Ganesa Street No. 10, Bandung 40132, Indonesia
    Mathematics, Department of Sciences, Institut Teknologi Sumatera, Terusan Ryacudu Street, Way Huwi, South Lampung 35365, Indonesia)

  • Kuntjoro Adji Sidarto

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

  • Novriana Sumarti

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

Abstract

Portfolio optimization is an activity for balancing return and risk. In this paper, we used mean-variance (M-V) portfolio models with buy-in threshold and cardinality constraints. This model can be formulated as a mixed integer nonlinear programming (MINLP) problem. To solve this constrained mean-variance portfolio optimization problem, we propose the use of a modified spiral optimization algorithm (SOA). Then, we use Bartholomew-Biggs and Kane’s data to validate our proposed algorithm. The results show that our proposed algorithm can be an efficient tool for solving this portfolio optimization problem.

Suggested Citation

  • Werry Febrianti & Kuntjoro Adji Sidarto & Novriana Sumarti, 2022. "Solving Constrained Mean-Variance Portfolio Optimization Problems Using Spiral Optimization Algorithm," IJFS, MDPI, vol. 11(1), pages 1-12, December.
    • Handle: RePEc:gam:jijfss:v:11:y:2022:i:1:p:1-:d:1009300
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