可信性测度下基于均值–方差–VaR–偏度–正弦熵的模糊投资组合分析

Fuzzy Portfolio Analysis Based on Mean-Variance-VaR-Skewness-Sine Entropy under Credibility Measure

本文在可信性理论的基础上,将资产收益率视为模糊变量,建立了均值–方差–VaR–偏度–正弦熵的多目标模糊投资组合模型,利用遗传算法求解最优投资策略。研究表明:模糊VaR的引入及新模型的构建,有助于更好地刻画资产收益率的风险特征,从而发现更优的投资组合策略。

In this paper, a new fuzzy multi-objective mean-variance-VaR-skewness-sine entropy portfolio model is proposed by assuming the rate of return on the risky asset is a fuzzy variable, based on the credibility theory. In order to solve the proposed model, we design a genetic algorithm. Then, nu-merical examples show that the extension of the model and the introduction of fuzzy VaR are help-ful to characterize the risk characteristics of asset returns and make a contribution to the invest-ment portfolio strategies.