基于多目标均值-绝对偏差-熵的JII指数股票组合优化

D. Saepudin, Dimas Rizqi Guintana
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引用次数: 0

摘要

股票投资组合优化是对投资者的股票资产进行配置,进行收益和风险管理。投资者需要在给定风险水平下获得高收益的投资组合,而投资组合优化可以帮助找到可行的投资组合。用于此问题的数据是雅加达伊斯兰指数(JII)上列出的股票。采用平均绝对偏差法和熵法进行组合优化。之所以使用MAD,是因为它可以解决数据非正态分布的投资组合优化问题。同时,利用熵可以更好地分散MAD投资组合中股票的权重。本研究的实验结果表明,MAD-熵等权组合在夏普比和绩效比上都优于MAD组合。MAD只在某一时期表现出色,受某一时期回报率极高的股票的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stock Portfolio Optimization on JII Index using Multi-Objective Mean-Absolute Deviation-Entropy
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.
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