Multivariate GARCH Models for the Greater China Stock Markets

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 es...

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Main Author: SONG, Xiaojun
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Language:English
Published: Institutional Knowledge at Singapore Management University 2009
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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
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spelling sg-smu-ink.etd_coll-10292010-09-08T01:24:04Z Multivariate GARCH Models for the Greater China Stock Markets SONG, Xiaojun 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. 2009-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/etd_coll/30 https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1029&context=etd_coll http://creativecommons.org/licenses/by-nc-nd/4.0/ Dissertations and Theses Collection (Open Access) eng Institutional Knowledge at Singapore Management University GARCH multivariate stock market volatility stock return Asian Studies Econometrics Finance
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic GARCH
multivariate
stock market volatility
stock return
Asian Studies
Econometrics
Finance
spellingShingle GARCH
multivariate
stock market volatility
stock return
Asian Studies
Econometrics
Finance
SONG, Xiaojun
Multivariate GARCH Models for the Greater China Stock Markets
description 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.
format text
author SONG, Xiaojun
author_facet SONG, Xiaojun
author_sort SONG, Xiaojun
title Multivariate GARCH Models for the Greater China Stock Markets
title_short Multivariate GARCH Models for the Greater China Stock Markets
title_full Multivariate GARCH Models for the Greater China Stock Markets
title_fullStr Multivariate GARCH Models for the Greater China Stock Markets
title_full_unstemmed Multivariate GARCH Models for the Greater China Stock Markets
title_sort multivariate garch models for the greater china stock markets
publisher Institutional Knowledge at Singapore Management University
publishDate 2009
url https://ink.library.smu.edu.sg/etd_coll/30
https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1029&context=etd_coll
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