Multi-Objective Stock Portfolio Optimization Using NSGA-II: A Comparative Analysis of Conventional and Shariah Stocks in the U.S. Market

Novita Sari (Faculty of Economics and Business, Dian Nuswantoro University, Indonesia)
Dwi Eko Waluyo (Faculty of Economics and Business, Dian Nuswantoro University, Indonesia)
Usman (Faculty of Economics and Business, Dian Nuswantoro University, Indonesia)
Amalia Nur Chasanah (Faculty of Economics and Business, Dian Nuswantoro University, Indonesia)

JURNAL ECONOMINA
Vol. 5 No. 6 (2026): JURNAL ECONOMINA, Juni 2026

This study analyzes and compares the performance of Conventional, Shariah, Intersection, and Combination stock portfolios in the United States stock market using the Non- dominated Sorting Genetic Algorithm II (NSGA-II). The study employs a quantitative empirical approach using daily stock closing price data from January 2022 to December 2025 obtained from Yahoo Finance. Portfolio optimization was conducted in Python and evaluated using the Efficient Frontier, Sharpe Ratio, Sortino Ratio, and Omega Ratio. The results show that the Combination portfolio achieved the best overall performance, followed by the Intersection portfolio. These findings indicate that broader diversification improves portfolio efficiency and supports Modern Portfolio Theory.