Notice of RetractionTree structured DCC_multivariate GARCH model and its application in volatility correlation analysis of Shanghai, Shenzhen and Hong Kong stock markets

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

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 DCC_multivariate GARCH models were compared. The results show that the most probable tree structured DCC_multivariate GARCH model has better prediction performance. What´s 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.