重庆理工大学学报（自然科学版）2017，Vol.31Issue(9)：172-181,10.DOI:10.3969/j.issn.1674-8425(z).2017.09.027
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
摘要
Abstract
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Key words
local linear method/nonparametric CARR/semi-parametric CARR/volatility/fitting ability分类
数学引用本文复制引用
郭名媛,韩志楠..基于非参数和半参数CARR模型的上海股票市场波动性研究[J].重庆理工大学学报（自然科学版）,2017,31(9):172-181,10.基金项目
国家社会科学基金资助项目(14CTJ012) （14CTJ012）
