<![CDATA[The limitations of traditional portfolio models in capturing multi-factor risks in the Indonesian capital market underlie the need for a framework that integrates a realistic return estimation model with a reliable optimization technique. Traditional portfolios do not utilize multi-factor risk and assume that market conditions depend only on a single factor; therefore, a method combining other factors, such as macroeconomic factors, is required. The research method used is the Arbitrage Pricing Theory (APT) to estimate expected stock returns based on three macroeconomic factors (CPI, Rupiah exchange rate against USD, and M2 Money Supply) and the Genetic Algorithm (GA) to determine optimal stock weights, where the resulting portfolio is then evaluated using the Sharpe Ratio to find the best portfolio composition with the highest Sharpe Ratio. The data used in this study are LQ45 stocks of the basic-materials sector in 2025. The research results show that there are four stocks selected in the formation of the optimal portfolio: ANTM, BRPT, INCO, and MDKA. Based on optimization using the Genetic Algorithm, the obtained fund allocation weight composition is 34.82% for ANTM, 16.92% for BRPT, 23.57% for INCO, and 24.69% for MDKA. The formed optimal portfolio yields a Sharpe Ratio of 0.6582, which indicates that although the portfolio generates a positive return.]]>
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