引入条件异方差效应的CAPM模型簇改进

Improvement of CAPM Model Cluster with Conditional Heteroscedastiaty Effect

资本资产定价(CAPM)模型簇假设扰动项为同方差,不能有效刻画金融资产收益率波动呈现出的条件异方差特点。为在实际应用中正确使用此类模型,给出两点改进:引入GARCH模型刻画扰动项波动规律,替代传统的正态分布假设;将条件异方差作为风险因素引入模型。以美国银行业实际数据进行实证研究,检验结果表明了本文改进方案的合理性,为实证分析中正确使用此类模型提供了有益参考。

CAPM model cluster assume that the stochastic error term is homoscedasticity,which can not effectively characterize the conditional heteroscedasticity of financial asset return volatility.In order to use this kind of model correctly in empirical research,two improvements are proposed:GARCH model is introduced to describe the fluctuation law of disturbance term,instead of the traditional assumption of normal distribution;Conditional heteroscedasticity is combined into the model as a risk factor.Empirical research is also developed on the actual data set of American banking industry,and the results show that the improvement of this paper is reasonable,which provides a useful reference for empirical analysis of using such models.