摩擦市场下加权极大-极小随机模糊投资组合模型及实证

考虑投资者面临证券市场随机和模糊的双重不确定性,把证券收益率视为随机模糊变量. 根据前景理论建立符合投资者心理特征的期望收益和目标概率隶属度函数,构建目标权重不等的加权极大- 极小随机模糊投资组合模型. 在含有交易费用和最小交易单位约束的摩擦市场环境下,利用改进动态邻居粒子群算法求解投资组合问题. 采用实证方法把市场分为上升和下降两个阶段,研究模型的表现. 结果表明： 加权极大- 极小随机模糊投资组合模型的收益率优于均值-方差投资组合模型; 利用加权极大- 极小随机模糊投资组合模型能够满足不同风险态度投资者的需求,构建与投资者风险态度一致的投资组合.

Empirical study on portfolio model with random fuzzy variables and weighted max-min operator in frictional market

As investors face the uncertainty of randomness and fuzziness simultaneously in stock market, the paper regarded the security returns as random fuzzy variables, and built the membership functions of expected return and target probability in accordance with the investors' psychological trait based on the prospect theory. A weighted max-min random fuzzy portfolio model with unequal target weights was proposed. In frictional market with transaction cost and minimum trading unit constraints, the improved dynamic neighborhood particle swarm optimization was proposed to solve the portfolio problems. Under the rise and decline states of stock market, the performance of the proposed model was empirically studied. The result shows that the proposed model can outperform the mean-variance model, and construct a portfolio which meets the need of investors with different risk-taking attitudes.