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

Werry Febrianti (), Kuntjoro Adji Sidarto and Novriana Sumarti ()
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Werry Febrianti: 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
Novriana Sumarti: Department of Mathematics, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Ganesa Street No. 10, Bandung 40132, Indonesia

IJFS, 2022, vol. 11, issue 1, 1-12

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.

Keywords: constrained portfolio optimization; mixed integer nonlinear programming; spiral optimization algorithm (search for similar items in EconPapers)
JEL-codes: F2 F3 F41 F42 G1 G2 G3 (search for similar items in EconPapers)
Date: 2022
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