基于马尔科夫状态转换下的高阶矩CAPM-GARCH模型的实证研究  

Empirical Research on the High-Order Moment CAPMGARCH Model Based on Markov Regime Switching

作　　者：段静静 王沁 欧攀 DUAN Jingjing;WANG Qin;OU Pan(Department of Statistics,College of Mathematics,Southwest Jiaotong University,Chengdu 611756,China)

机构地区：[1]西南交通大学数学学院统计系,成都611756

出　　处：《重庆理工大学学报（自然科学）》2020年第6期224-231,共8页Journal of Chongqing University of Technology：Natural Science

基　　金：国家自然科学基金项目(71371157)。

摘　　要：为了反映资产组合风险在不同状态下对收益率的影响,从动态的角度提出基于马尔科夫状态转换下的高阶矩CAPM-GARCH模型,即高阶矩CAPM-MSGARCH模型。以上证180指数样本股的10支不同行业的股票为研究对象,实证分析结果表明:高阶矩系统风险对资本资产定价有显著的影响,并且高阶矩CAPM-MSGARCH模型能够较好地刻画风险的时变特征,显著优于传统的高阶矩CAPM-GARCH模型。In order to reflect the impact of portfolio risk on return rates under different regimes,a high-order moment CAPM-GARCH model based on Markov regime switching is proposed from a dynamic perspective,namely the high-order moment CAPM-MSGARCH model.Regarding the 10 different industrial sectors of the stock in the Shanghai 180 index sample stocks as the objects of studying,the empirical analysis results show that the high-order moment systematic risk has a marked impact on the capital asset pricing,and the high-order moment CAPM-MSGARCH model can better describe the time-varying characteristics of risk,which is significantly better than the traditional highorder moment CAPM-GARCH model.

关 键 词：高阶矩CAPM模型 高阶矩CAPM-GARCH模型 马尔科夫状态转换 

分 类 号：F224[经济管理—国民经济] F830.91