Portofolio Optimization of Mean-Variance Model Using Tabu Search Algorithm with Cardinality Constraints

Lutfi Praditia Ma’mur; Riaman Riaman; Sukono Sukono

doi:10.46336/ijqrm.v6i2.1010

Portofolio Optimization of Mean-Variance Model Using Tabu Search Algorithm with Cardinality Constraints

Lutfi Praditia Ma’mur, Riaman Riaman, Sukono Sukono

Abstract

Stock investment is increasingly attractive to Indonesians, especially through the IDX30 index, which is known to have high liquidity and solid company fundamentals. In forming an optimal stock portfolio, investors are faced with the challenge of maximizing return and minimizing risk simultaneously. An optimal portfolio is defined as a combination of assets that provides the highest expected return at a certain level of risk, or the lowest risk for the expected level of return. This study aims to form an optimal portfolio on the IDX30 index by considering cardinality constraints, which limit the maximum number of stocks in the portfolio. From 30 IDX30 stocks, 20 stocks were selected based on consistency of existence during the period February 1, 2023 to January 31, 2025. Next, 8 stocks that have positive expected return values are selected, and from these 8, 4 efficient stocks are selected using cardinality constraints. Selection is done with the Tabu Search algorithm, a memory-based metaheuristic optimization method used to find the best solution by avoiding previously explored solutions. The portfolio is formed using the Mean-Variance model, resulting in an allocation of BMRI (30,02%), PTBA (35,18%), INDF (2,48%), and BRPT (32,32%), with an expected return of 0,00207 and a variance of 0,001587.

Keywords

stock; return; risk; IDX30; Mean-Variance; Tabu Search algorithm; optimal

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DOI: https://doi.org/10.46336/ijqrm.v6i2.1010