Investigation of the Return and Volatility Clustering Effects in China Stock Markets

This dissertation examines the return and volatility in Shanghai Stock Exchange (SSE); Shenzhen Stock Exchange (SZSE); Hong Kong Stock Exchange (HKEx) and Taiwan Stock Exchange (TWSE) in China for the period Jan 2002-Dec 2008 employing the GARCH models. GARCH-M; TGARCH-M and EGARCH-M model are estim...

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Main Author: Mei, Lirong
Format: Dissertation (University of Nottingham only)
Language:English
Published: 2009
Online Access:https://eprints.nottingham.ac.uk/24552/
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author Mei, Lirong
author_facet Mei, Lirong
author_sort Mei, Lirong
building Nottingham Research Data Repository
collection Online Access
description This dissertation examines the return and volatility in Shanghai Stock Exchange (SSE); Shenzhen Stock Exchange (SZSE); Hong Kong Stock Exchange (HKEx) and Taiwan Stock Exchange (TWSE) in China for the period Jan 2002-Dec 2008 employing the GARCH models. GARCH-M; TGARCH-M and EGARCH-M model are estimated using three return intervaldaily; weekly and monthly. The results confirmed the leverage effects in these stock markets; but the significance of the estimation are questioned partly for the insufficient data in low frequency intervals. Comparison between the three models concluded with the superiority of the EGARCH over the other two models. Misspecification testing and Granger Causality Test are employed for modification of the model and examination of the spillover effect in the markets. ARMA lag specification in mean equations are suggested for the modification of the models; inclusion of GARCH variance lag terms in the variance equation also recommended for the models of the markets that have spillover effect between or from other markets.
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institution University of Nottingham Malaysia Campus
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language English
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spelling nottingham-245522018-03-11T17:27:46Z https://eprints.nottingham.ac.uk/24552/ Investigation of the Return and Volatility Clustering Effects in China Stock Markets Mei, Lirong This dissertation examines the return and volatility in Shanghai Stock Exchange (SSE); Shenzhen Stock Exchange (SZSE); Hong Kong Stock Exchange (HKEx) and Taiwan Stock Exchange (TWSE) in China for the period Jan 2002-Dec 2008 employing the GARCH models. GARCH-M; TGARCH-M and EGARCH-M model are estimated using three return intervaldaily; weekly and monthly. The results confirmed the leverage effects in these stock markets; but the significance of the estimation are questioned partly for the insufficient data in low frequency intervals. Comparison between the three models concluded with the superiority of the EGARCH over the other two models. Misspecification testing and Granger Causality Test are employed for modification of the model and examination of the spillover effect in the markets. ARMA lag specification in mean equations are suggested for the modification of the models; inclusion of GARCH variance lag terms in the variance equation also recommended for the models of the markets that have spillover effect between or from other markets. 2009 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/24552/1/meilirong.pdf Mei, Lirong (2009) Investigation of the Return and Volatility Clustering Effects in China Stock Markets. [Dissertation (University of Nottingham only)] (Unpublished)
spellingShingle Mei, Lirong
Investigation of the Return and Volatility Clustering Effects in China Stock Markets
title Investigation of the Return and Volatility Clustering Effects in China Stock Markets
title_full Investigation of the Return and Volatility Clustering Effects in China Stock Markets
title_fullStr Investigation of the Return and Volatility Clustering Effects in China Stock Markets
title_full_unstemmed Investigation of the Return and Volatility Clustering Effects in China Stock Markets
title_short Investigation of the Return and Volatility Clustering Effects in China Stock Markets
title_sort investigation of the return and volatility clustering effects in china stock markets
url https://eprints.nottingham.ac.uk/24552/