Tree Structured DC_Cmultivariate GARCH Model and Its Application in Volatility Correlation Analysis of Shanghai, Shenzhen and Hong Kong Stock Markets
In oder to analyze the volatility asymmetry and volatility correlation of Mainland stock market and Hong Kong stock market, this paper attempts to apply MCMC algorithm to estimating the most probable tree structured DCC_Multivariate GARCH(1,1,1,1) model for daily returns of Shanghai, Shenzhen and Hong Kong stock markets. In the paper, the prediction performance of the most probable tree structured and general DCCmultivariate GARCH models were compared. The results show that the most probable tree structured DCC multivariate GARCH model has better prediction performance. Whats more, the predicted graphs of volatility and volatility correlation were analyzed, which indicates that asymmetry in the volatility of the three stock markets and volatility correlation among them does exist, Mainland stock market fluctuates more frequently than Hong Kong stock market and the correlation between Mainland stock market and Hong Kong stock market has been increasing since 2005.
tree structure dcc_multivariate garch model markov chain monte carlo
Shaofu Zhou Xiuxia Zuo
School of Economics, Huazhong University of Science and Technology Huazhong University of Science and Technology Wuhan, P.R.China
国际会议
成都
英文
595-599
2010-07-09（万方平台首次上网日期，不代表论文的发表时间）