A HYBRID MODEL FOR STOCK PORTFOLIO SELECTION: MEAN-VALUE-AT-RISK WITH ANT COLONY OPTIMIZATION - Arief Surya Lesmana; Hadi Satria Ganefi; Dadan Darmawan Muttaqien (INDONESIAN JOURNAL OF BUSINESS AND ECONOMICS, 2025)
The main problem in portfolio selection and management is determining an optimal risk-return balance. Investors strive to obtain maximum return while keeping the level of risk, but such a balance is hard to reach. The objective of this paper is to optimize stock portfolio formation using Ant Colony Optimization (ACO) for stock selection and the Mean-Value-at-Risk (VaR) model for portfolio optimization. By simulating risk aversion coefficients, the cluster of four stocks was computed by the ACO algorithm with asset allocation proportions. The study found a negative relationship existing between risk aversion and VaR or the expected return, while between VaR and expected return, exists a positive correlation. The optimum portfolio for a risk aversion of 3.6 had an expected return of 4.38% and VaR of 9.27% with a ratio of 47.25%. The detailed composition includes 26.61% BRIS, 24.42% ELSA, 46.16% PGAS, and 2.83% TLKM. It shows the efficiency of the ACO algorithm in stock selection and that the investment is acceptable to suit the individual’s risk preference. Results from this study have significant implications for portfolio management in that it provides the necessary guide to construct an optimum portfolio that is balanced according to investor profiles.