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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.
Considering the random uncertainty and fuzzy ambiguity of the securities market, the stock returns are regarded as the random fuzzy variables.According to the prospect theory, the expectation return and the target probability membership function are established according to the psychological characteristics of investors, and the objective weight is constructed Weighted max-min stochastic fuzzy portfolio model.Under the friction market environment which contains the transaction cost and the minimum transaction unit constraints, the improved dynamic neighbor particle swarm optimization algorithm is used to solve the portfolio problem.The empirical method is used to divide the market into two groups: rising and falling The results show that the weighted maximum-minimum stochastic fuzzy portfolio model yields better than the average-variance portfolio model, and the weighted max-minimal stochastic fuzzy portfolio model can meet different risk Attitude The investor’s need to build a portfolio that is consistent with the investor’s risk attitude.