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作 者:张高勋[1,2] 张洪华 ZHANG Gaoxun;ZHANG Honghua(School of Mathematics and Physics,Southwest University of Science and Technology,Mianyang 621000,Sichuan,China;School of Economics and Management,Southwest University of Science and Technology,Mianyang 621000,Sichuan,China)
机构地区:[1]西南科技大学数理学院,四川绵阳621000 [2]西南科技大学经济管理学院,四川绵阳621000
出 处:《科技和产业》2024年第5期32-39,共8页Science Technology and Industry
基 金:国家社会科学基金(19BGL006)。
摘 要:随着全球经济不稳定性的增强和我国利率市场化的深入推进,金融资产的波动性不断加剧,资产组合优化配置问题依然是金融投资理论研究和实务领域的核心问题。Black-Litterman模型因其解决了传统均值方差模型对参数敏感的问题,且允许将投资者观点融入模型中,已被广泛应用于资产配置实践中。然而投资者观点矩阵的确定一直是Black-Litterman模型理论和应用研究的难点。将宏观因子融入投资者观点矩阵,应用基于主成分分析法的支持向量回归(SVR)模型实现观点矩阵的估计,构建融入宏观因子的SVR-Black-Litterman资产配置模型。为检验模型的有效性,将该模型与经典模型进行比较。实证结果表明,所构建的模型具有较好的市场表现。With the enhancement of global economic instability and the deepening of China’s interest rate liberalization,the volatility of financial assets has been increasing.The optimal allocation of asset portfolio is still the core issue in the field of financial investment theory research and practice.Black-Litterman model has been widely used in asset allocation practice because it solves the problem that traditional mean-variance model is sensitive to parameters and allows investors’views to be incorporated into the model.However,the determination of investor perspective matrix has always been a difficulty in the theoretical and applied research of Black-Litterman model.Based on this,macro factors are integrated into the construction of investor perspective matrix.Support vector regression(SVR)model based on principal component analysis is used to estimate the viewpoint matrix,and the SVR-Black-Litterman asset allocation model with macro factors is constructed.To test the validity of this model,the model is compared with other common asset allocation models.The empirical results show that the model constructed has a good market performance.
关 键 词:宏观因子 主成分分析法 观点矩阵 SVR-Black-Litterman模型
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