带有模糊流动性约束的均值-方差-偏度-正弦熵投资组合优化模型

通过引入可信性偏度及模糊流动性约束，分别建立了同时满足随机不确定和模糊不确定情形下的均值-方差-偏度-正弦熵（M-V-S-SE）的投资组合模型和带有模糊流动性约束的均值-方差-偏度-正弦熵（M-V-S-L-SE）投资组合优化模型。然后运用马尔科夫方法求解模糊收益率，利用上海证券交易所数据进行实证研究。结果表明：模糊流动性约束的引入使得模型更加稳定，在提高收益、控制风险等方面更具有优势。
Abstract：By introducing the credibility theory and skewness, a mean-variance-skewness-sine entropy (M-V-S-SE) portfolio selection model considering random uncertainty and fuzzy uncertainty, and a mean-variance-skewness-liquidity-sine entropy (M-V-S-L-SE) portfolio selection model with fuzzy liquidity constraints have been established. We forecasted the fuzzy yields using the Markov method. Empirical research was conducted by employing the 2015 stock price data from the Shanghai stock exchange. The results reveal that the M-V-S-L-SE model which includes fuzzy liquidity constraints is more stable and advantageous in terms of improving the income and controlling the risk.