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基于MRS-GARCH模型的中国股市波动率估计与预测
引用本文:赵华,蔡建文. 基于MRS-GARCH模型的中国股市波动率估计与预测[J]. 数理统计与管理, 2011, 30(5): 912-921
作者姓名:赵华  蔡建文
作者单位:厦门大学经济学院,福建厦门,361005
基金项目:教育部人文社会科学研究项目(08JC790089); 福建省重点科技项目(2009R0079); 中国博士后基金(20090450006); 中央高校基本科研业务费专项资金资助(2010221055)
摘    要:基于误差项服从正态分布、t分布、广义误差分布的GARCH族模型和MRS-GARCH模型对中国股市波动的结构变化特征进行了实证研究。结果表明,中国股市存在显著的高、低波动状态,两种波动状态的ARCH和GARCH项系数存在较大差异;高、低波动状态均具有较长的持续时间,低波动状态的持续时间长于高波动状态的持续时间,且中国股市更易于从高波动状态转向低波动状态;MRS-GARCH模型预测效果总体上优于GARCH族模型,基于正态分布的MRS-GARCH模型短期预测效果较好。

关 键 词:MRS-GARCH模型  DM检验  结构变化

Estimation and Forecasting of Volatility in China's Stock Markets with Markov Regime-switching GARCH Model
ZHAO Hua CAI Jian-won. Estimation and Forecasting of Volatility in China's Stock Markets with Markov Regime-switching GARCH Model[J]. Application of Statistics and Management, 2011, 30(5): 912-921
Authors:ZHAO Hua CAI Jian-won
Affiliation:ZHAO Hua CAI Jian-won (School of Economics,Xiamen University,Fujian Xiamen 361005,China)
Abstract:Based on GARCH models and Markov regime-switching GARCH model with normal,t and generalized error distributions,the paper studied empirically the structural break characteristics of volatility in China's stock markets.The results show that in the China's stock market there are significant high and low volatility states,and the ARCH and GARCH coefficients differ substantially between the two states.Furthermore,the high and low volatility states all have long durations,the duration for the low volatility stat...
Keywords:Markov regime-switching GARCH model  Diebold and Mariano test  structural break  
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