Applying generalized autoregressive conditional heteroscedasticity models to model univariate volatility

This paper aims to model volatility of daily index returns for four Asian markets namely; Kuala Lumpur Composite Index of Malaysia, Jakarta Stock Exchange Composite Index of Indonesia, Straits Times Index of Singapore and the Stock Index of Korea over the period 03/01/2007 – 31/07/2013 excluding the...

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Main Author: Islam, Mohd Aminul
Format: Article
Language:English
English
Published: Asian Network for Scientific Information 2014
Subjects:
Online Access:http://irep.iium.edu.my/36034/
http://irep.iium.edu.my/36034/
http://irep.iium.edu.my/36034/
http://irep.iium.edu.my/36034/1/59767-59767_JAS.pdf
http://irep.iium.edu.my/36034/4/JAS_Published_Article.pdf
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spelling iium-360342015-04-29T05:21:09Z http://irep.iium.edu.my/36034/ Applying generalized autoregressive conditional heteroscedasticity models to model univariate volatility Islam, Mohd Aminul HG4501 Stocks, investment, speculation This paper aims to model volatility of daily index returns for four Asian markets namely; Kuala Lumpur Composite Index of Malaysia, Jakarta Stock Exchange Composite Index of Indonesia, Straits Times Index of Singapore and the Stock Index of Korea over the period 03/01/2007 – 31/07/2013 excluding the public holidays. We utilized generalized autoregressive conditional heteroskedasticity models as these models are particularly suitable for high frequency financial time series such as the daily stock returns which has a time-varying variance. Unlike the linear structural models, these models are found very useful in explaining the most stylized facts about index returns such as leptokurtosis, volatility clustering and asymmetric or leverage effects. The key results of this study are as follows. Firstly, the conditional variance process is highly persistent in all markets. Secondly, the relationship between the expected risk and the expected return is positive as expected but the relationship is not statistically significant for all markets except Indonesia. For Indonesian market which is found to be more volatile than the other three markets, the estimated coefficient of risk premium appeared to be statistically significant indicating that increased risk leads to a rise in the returns. The risk-premium coefficients for other three markets are although positive but not statistically significant suggesting that increased risk does not necessarily produce higher return for those three markets. Finally, the asymmetric effects is exist in all cases signifying that negative shock produces higher impact on future volatility than the positive shock of the same magnitude. Asian Network for Scientific Information 2014 Article PeerReviewed application/pdf en http://irep.iium.edu.my/36034/1/59767-59767_JAS.pdf application/pdf en http://irep.iium.edu.my/36034/4/JAS_Published_Article.pdf Islam, Mohd Aminul (2014) Applying generalized autoregressive conditional heteroscedasticity models to model univariate volatility. Journal of Applied Sciences, 14 (7). pp. 641-650. ISSN 1812-5662 (O), 1812-5654 (P) http://scialert.net/abstract/?doi=jas.0000.59767.59767 10.3923/jas.2014.641.650
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
English
topic HG4501 Stocks, investment, speculation
spellingShingle HG4501 Stocks, investment, speculation
Islam, Mohd Aminul
Applying generalized autoregressive conditional heteroscedasticity models to model univariate volatility
description This paper aims to model volatility of daily index returns for four Asian markets namely; Kuala Lumpur Composite Index of Malaysia, Jakarta Stock Exchange Composite Index of Indonesia, Straits Times Index of Singapore and the Stock Index of Korea over the period 03/01/2007 – 31/07/2013 excluding the public holidays. We utilized generalized autoregressive conditional heteroskedasticity models as these models are particularly suitable for high frequency financial time series such as the daily stock returns which has a time-varying variance. Unlike the linear structural models, these models are found very useful in explaining the most stylized facts about index returns such as leptokurtosis, volatility clustering and asymmetric or leverage effects. The key results of this study are as follows. Firstly, the conditional variance process is highly persistent in all markets. Secondly, the relationship between the expected risk and the expected return is positive as expected but the relationship is not statistically significant for all markets except Indonesia. For Indonesian market which is found to be more volatile than the other three markets, the estimated coefficient of risk premium appeared to be statistically significant indicating that increased risk leads to a rise in the returns. The risk-premium coefficients for other three markets are although positive but not statistically significant suggesting that increased risk does not necessarily produce higher return for those three markets. Finally, the asymmetric effects is exist in all cases signifying that negative shock produces higher impact on future volatility than the positive shock of the same magnitude.
format Article
author Islam, Mohd Aminul
author_facet Islam, Mohd Aminul
author_sort Islam, Mohd Aminul
title Applying generalized autoregressive conditional heteroscedasticity models to model univariate volatility
title_short Applying generalized autoregressive conditional heteroscedasticity models to model univariate volatility
title_full Applying generalized autoregressive conditional heteroscedasticity models to model univariate volatility
title_fullStr Applying generalized autoregressive conditional heteroscedasticity models to model univariate volatility
title_full_unstemmed Applying generalized autoregressive conditional heteroscedasticity models to model univariate volatility
title_sort applying generalized autoregressive conditional heteroscedasticity models to model univariate volatility
publisher Asian Network for Scientific Information
publishDate 2014
url http://irep.iium.edu.my/36034/
http://irep.iium.edu.my/36034/
http://irep.iium.edu.my/36034/
http://irep.iium.edu.my/36034/1/59767-59767_JAS.pdf
http://irep.iium.edu.my/36034/4/JAS_Published_Article.pdf
first_indexed 2023-09-18T20:51:36Z
last_indexed 2023-09-18T20:51:36Z
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