融入信息熵及多渠道信息的投资组合优化研究

Research on Portfolio Optimization with Information Entropy and Multi-Channel Information

摘要: 考虑到投资者预期的异质性，本文结合金融市场的历史信息及前瞻性信息，且引入信息熵替代传统模型的风险度量方法，由此确定出反映金融市场不确定性及投资者行为非理性的最优投资决策。本文以中国股票市场为研究对象，对比分析不同投资策略的样本外绩效及投资收益。研究结果表明，融入信息熵及多渠道信息的投资策略表现稳健，能获得较高的夏普比率、投资收益以及较低的换手率。

Abstract: Considering the heterogeneity of investors’ expectations, this paper combines the historical information and forward-looking information of financial markets, and introduces information entropy to replace the traditional model of risk measurement, so as to determine the optimal investment decision reflecting the uncertainty of financial markets and the irrational behavior of investors. This paper takes the Chinese stock market as the research object and compares and analyzes the out-of-sample performance and investment returns of different investment strategies. The results show that the investment strategy with information entropy and multi-channel information has a stable performance and can obtain higher Sharpe ratio, investment return and lower turnover rate.