基于非参数和半参数CARR模型的上海股票市场波动性研究  

Nonparametric and Semiparametric CARR Models for Shanghai Stock Market Volatility

作　　者：郭名媛[1] 韩志楠 GUO Mingyuan HAN Zhinan(College of Management and Economics, Tianjin University, Tianjin 300072, Chin)

机构地区：[1]天津大学管理与经济学部,天津300072

出　　处：《重庆理工大学学报（自然科学）》2017年第9期172-181,共10页Journal of Chongqing University of Technology：Natural Science

基　　金：国家社会科学基金资助项目(14CTJ012)

摘　　要：以上证综指日对数价格的极差为研究对象,分别建立参数、半参数和非参数CARR(1,1)模型来研究上海股票市场的波动性。采用MSE、MAE两种误差度量指标比较参数、非参数、半参数CARR(1,1)模型的拟合能力。结果表明:半参数CARR(1,1)模型在对上海股市波动性的拟合方面表现最优,非参数CARR(1,1)模型次之,GCARR(1,1)模型最差。Previous empirical results reveal that CARR significantly outperforms GARCH in the prediction of volatility.As we all know,the estimation of CARR is based on the function form and the residual＇s distribution.It is because the estimation of the nonparametric and semi-paremetric CARR ignores the hypothesis,and the two models can reduce the error obviously.By using the daily range data of Shanghai composite index,we establish the parametric,nonparametric and semi-paremetric CARR to study Shanghai stock market＇s volatility.We select MSE and MAE to compare the fitting ability of the three models.The results show that among the three models,the best one to feature shanghai stock market＇s volatility is semi-parametric CARR,and the nonparametric CARR is inferior and the weak one is parametric CARR.

关 键 词：局部线性估计 非参数CARR模型 半参数CARR模型 波动性 拟合能力 

分 类 号：O21[理学—概率论与数理统计] F830[理学—数学]