Stock Portfolio Optimization on JII Index using Multi-Objective Mean-Absolute Deviation-Entropy

Abstract

Stock portfolio optimization is allocating stock assets from investors to manage return and risk. Investors need a high return portfolio with a given level of risk, and portfolio optimization can help to find the feasible one. The data used for this problem are stocks listed on the Jakarta Islamic Index (JII). The portfolio optimization methods are applied Mean-Absolute Deviation (MAD) and Entropy. MAD is used because it can solve the portfolio optimization problem for the nonnormal distribution of data. Meanwhile, entropy is used because it can better diversify the weight of stocks in the MAD portfolio. Experiment results in this study show that MAD-Entropy and Equal Weight portfolio outperform the MAD portfolio in Sharpe Ratio and Performance Ratio. MAD only excels in one period, influenced by a stock that has a fantastic return in a certain period.