基于EEMD与模糊回归的投资组合选择模型及实证

随着模糊理论的不断发展与其在证券市场的广泛应用,越来越多的学者关注到参数模糊化对投资组合优化具有重要作用。本文利用集合经验模态分解(EEMD)和模糊线性回归相结合的预测方法,构建了基于对称三角模糊数的投资组合模型。并将提出的模型与集合经验模态分解和普通最小二乘结合的方法、单一模糊线性回归方法进行了对比分析,结果表明基于集合经验模态分解和模糊线性回归建立的投资组合模型最优,这对构建最优投资组合具有参考意义。

Portfolio Selection Model and Empirical Study Based on EEMD and Fuzzy Regression

With the continuous development of fuzzy theory and its extensive application in the securities market, more and more scholars have paid attention to the importance of fuzzy parameters for portfolio optimization. In this paper, a combination of ensemble empirical mode decomposition (EEMD) and fuzzy linear regression method is proposed to construct a portfolio selection model based on symmetric triangular fuzzy numbers. Compared with the method of ensemble empirical mode decomposition combined with ordinary least squares and single fuzzy linear regression method, the results of empirical study show that the portfolio model based on ensemble empirical mode decomposition and fuzzy linear regression is optimal, which is of reference significance for constructing the optimal portfolio.