A Study of Chinese Stock Market: Empirical and Theoretical Explorations by Bayesian and GARCH Models

Ph.D

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Main Author: CHEN HENG
Other Authors: ECONOMICS
Format: Theses and Dissertations
Language:English
Published: 2010
Subjects:
Online Access:http://scholarbank.nus.edu.sg/handle/10635/16246
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Institution: National University of Singapore
Language: English
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spelling sg-nus-scholar.10635-162462015-01-27T16:05:52Z A Study of Chinese Stock Market: Empirical and Theoretical Explorations by Bayesian and GARCH Models CHEN HENG ECONOMICS WONG WING KEUNG Stock Market, IPOs, Cointegration, Bayes, GARCH Ph.D DOCTOR OF PHILOSOPHY 2010-04-08T11:02:40Z 2010-04-08T11:02:40Z 2007-04-11 Thesis CHEN HENG (2007-04-11). A Study of Chinese Stock Market: Empirical and Theoretical Explorations by Bayesian and GARCH Models. ScholarBank@NUS Repository. http://scholarbank.nus.edu.sg/handle/10635/16246 NOT_IN_WOS en
institution National University of Singapore
building NUS Library
country Singapore
collection ScholarBank@NUS
language English
topic Stock Market, IPOs, Cointegration, Bayes, GARCH
spellingShingle Stock Market, IPOs, Cointegration, Bayes, GARCH
CHEN HENG
A Study of Chinese Stock Market: Empirical and Theoretical Explorations by Bayesian and GARCH Models
description Ph.D
author2 ECONOMICS
author_facet ECONOMICS
CHEN HENG
format Theses and Dissertations
author CHEN HENG
author_sort CHEN HENG
title A Study of Chinese Stock Market: Empirical and Theoretical Explorations by Bayesian and GARCH Models
title_short A Study of Chinese Stock Market: Empirical and Theoretical Explorations by Bayesian and GARCH Models
title_full A Study of Chinese Stock Market: Empirical and Theoretical Explorations by Bayesian and GARCH Models
title_fullStr A Study of Chinese Stock Market: Empirical and Theoretical Explorations by Bayesian and GARCH Models
title_full_unstemmed A Study of Chinese Stock Market: Empirical and Theoretical Explorations by Bayesian and GARCH Models
title_sort study of chinese stock market: empirical and theoretical explorations by bayesian and garch models
publishDate 2010
url http://scholarbank.nus.edu.sg/handle/10635/16246
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