Multivariate GARCH Models for the Greater China Stock Markets

• Main Author: SONG, Xiaojun
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2009
• Subjects: GARCH; multivariate; stock market volatility; stock return; Asian Studies; Econometrics; Finance
• Online Access: https://ink.library.smu.edu.sg/etd_coll/30; https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1029&context=etd_coll
• Institution: Singapore Management University

This paper reviews the commonly used multivariate GARCH models and uses the daily data of the four Greater China region stock markets, namely Hongkong, Shanghai,Shenzhen, and Singapore, and data of Japan as one ex-ogenous variable to investigate the volatility and shocks spillover behavior and to establish the market linkage among the four markets. We find that the volatility spillover between Shanghai and Shenzhen is obvious and correlation contagion is detected. Conditional variance and conditional correlations are time varying and dynamic which conforms to the arguments in most of the literature. Shanghai and Shenzhen present a very high correlation level during the sampling period,varying from 0.75 to 0.98, at some point even near linear correlation, which is not uncommon due to the close interlink between the two markets. Hongkong and Singapore presents a mildly high correlation, varying from 0.25 to 0.9, with an average of 0.62. However, the correlation is very volatile. Results present the convincing evidence that Chinese stock markets are more and more integrated to the global markets and the Greater China region markets are more integrated to each other. There are many obvious correlation breaks,when all the correlations suddenly drop to a drastically low level. The drop corresponds to the actual economic event as we discover.