基于犹豫模糊语言环境的投资组合优化研究

Research on Portfolio Optimization Based on Hesitant Fuzzy Linguistic Environment

跟传统模糊投资组合相比,基于犹豫模糊语言环境的投资组合不仅可以使用自然语言对金融资产及其不确定程度进行评价,还可以避免评价过程中信息的丢失。本文根据犹豫模糊语言投资组合综合评价系统,对不同金融产品计算得分。通过设置不同的语言尺度函数的参数值及犹豫模糊语言优化模型的临界值,针对激进型、稳健型和保守型三类投资者分别提出了收益最大化和风险最小化犹豫模糊语言投资组合模型,对建立的非线性模型进行求解,得到犹豫模糊语言投资组合的最优解。最后,用数值仿真验证了模型的合理性和有效性。

Compared with traditional fuzzy portfolio, portfolio selection based on hesitant fuzzy linguistic can not only use natural linguistic to evaluate financial assets and their uncertainties, but also avoid the loss of information during the evaluation process. The scores of different financial products are calculated based on the hesitant fuzzy linguistic portfolio comprehensive evaluation system. By setting the parameter values of different semantic scale functions and the thresholds of the hesitant fuzzy linguistic optimization models, maximum returns and minimum risks hesitant fuzzy linguistic portfolio models are proposed for the three types of investors: aggressive, moderate and conservative. The optimal solutions of hesitant fuzzy language portfolio are obtained by solving the proposed nonlinear models. Finally, numerical simulations are used to verify the rationalities and validities of the proposed models.