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Abstract
Investment refers to allocating funds into financial assets, including stocks, to increase future value. To reduce potential losses, investors apply diversification through portfolio formation. This study optimizes stock portfolio construction within the IDXESGL index, which comprises 30 stocks, by combining Partitioning Around Medoids clustering and multi-objective optimization. Clustering employed 2024 financial ratios Return on Assets, Earnings per Share, and Debt to Equity Ratio while considering outliers. Portfolio optimization used daily closing prices from June 20 to November 30, 2025. The multi-objective approach balanced expected return and risk based on investor preferences, with risk measured using Value at Risk under the Historical Simulation method. PAM produced three optimal clusters with a higher silhouette coefficient. MAPA and BBNI represented Clusters 1 and 2, while Cluster 3 was excluded due to negative expected return. For risk seekers, the portfolio was dominated by MAPA (0.939) and BBNI (0.061), generating an expected return of 0.001155026 and a 1-day VaR of -4.9182%. Risk neutral investors obtained more balanced weights, yielding an average expected return of 0.000617052 and a 1-day VaR between -3.0614% and -2.2197%. For risk averters, BBNI (0.759) and MAPA (0.241) produced an expected return of 0.000534355 and a 1-day VaR of -2.218%.
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References
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