Modeling univariate volatility of stock returns using stochastic GARCH models:Evidence from 4-Asian markets

This paper applies the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models to the financial time series (stock index returns) in four Asian markets namely; Kuala Lumpur Composite Index (KLCI) of Malaysia, the Straits Times Index (STI) of Singapore, Nikkei Indices (N225) of Japan...

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Main Author:	Islam, Mohd Aminul
Format:	Article
Language:	English
Published:	INSI Publications 2013
Subjects:	HG4501 Stocks, investment, speculation
Online Access:	http://irep.iium.edu.my/33419/ http://irep.iium.edu.my/33419/ http://irep.iium.edu.my/33419/1/AJBAS_Published_294-303.pdf

id	iium-33419
recordtype	eprints
spelling	iium-334192013-12-13T03:15:02Z http://irep.iium.edu.my/33419/ Modeling univariate volatility of stock returns using stochastic GARCH models:Evidence from 4-Asian markets Islam, Mohd Aminul HG4501 Stocks, investment, speculation This paper applies the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models to the financial time series (stock index returns) in four Asian markets namely; Kuala Lumpur Composite Index (KLCI) of Malaysia, the Straits Times Index (STI) of Singapore, Nikkei Indices (N225) of Japan and the Hang Seng Index (HSI) of Hong Kong. We included six years of data covering the period from January 2007 to December 2012. This comprises daily observations of 1477 for KLCI, 1493 for STI, 1469 for N225 and 1481 for HSI excluding the public holidays. Closing values for stock indices are used. We included most commonly used variations of conditional volatility models with imposing names such as Generalized Autoregressive Conditional Heteroscedasticity best known as the GARCH (1, 1), GARCH-in-Mean, Thresh-hold GARCH (TGARCH), Exponential GARCH (EGARCH) and Power GARCH models. We aim to empirically examine the use of GARCH models in capturing the stylized facts such as volatility clustering and leverage effects commonly observed in high frequency financial time series data. We found strong empirical evidence of volatility clustering and leverage effects in the daily stock index returns of all four markets showing that the daily stock index returns can be characterized by the GARCH models. The results from GARCH-in-Mean model, we find evidence of positive relationship between the expected risk and expected return in all four markets which is often predicted in investment theory. INSI Publications 2013-09 Article PeerReviewed application/pdf en http://irep.iium.edu.my/33419/1/AJBAS_Published_294-303.pdf Islam, Mohd Aminul (2013) Modeling univariate volatility of stock returns using stochastic GARCH models:Evidence from 4-Asian markets. Australian Journal of Basic and Applied Sciences, 7 (11). pp. 294-303. ISSN 1991-8178 http://www.ajbasweb.com/
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	HG4501 Stocks, investment, speculation
spellingShingle	HG4501 Stocks, investment, speculation Islam, Mohd Aminul Modeling univariate volatility of stock returns using stochastic GARCH models:Evidence from 4-Asian markets
description	This paper applies the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models to the financial time series (stock index returns) in four Asian markets namely; Kuala Lumpur Composite Index (KLCI) of Malaysia, the Straits Times Index (STI) of Singapore, Nikkei Indices (N225) of Japan and the Hang Seng Index (HSI) of Hong Kong. We included six years of data covering the period from January 2007 to December 2012. This comprises daily observations of 1477 for KLCI, 1493 for STI, 1469 for N225 and 1481 for HSI excluding the public holidays. Closing values for stock indices are used. We included most commonly used variations of conditional volatility models with imposing names such as Generalized Autoregressive Conditional Heteroscedasticity best known as the GARCH (1, 1), GARCH-in-Mean, Thresh-hold GARCH (TGARCH), Exponential GARCH (EGARCH) and Power GARCH models. We aim to empirically examine the use of GARCH models in capturing the stylized facts such as volatility clustering and leverage effects commonly observed in high frequency financial time series data. We found strong empirical evidence of volatility clustering and leverage effects in the daily stock index returns of all four markets showing that the daily stock index returns can be characterized by the GARCH models. The results from GARCH-in-Mean model, we find evidence of positive relationship between the expected risk and expected return in all four markets which is often predicted in investment theory.
format	Article
author	Islam, Mohd Aminul
author_facet	Islam, Mohd Aminul
author_sort	Islam, Mohd Aminul
title	Modeling univariate volatility of stock returns using stochastic GARCH models:Evidence from 4-Asian markets
title_short	Modeling univariate volatility of stock returns using stochastic GARCH models:Evidence from 4-Asian markets
title_full	Modeling univariate volatility of stock returns using stochastic GARCH models:Evidence from 4-Asian markets
title_fullStr	Modeling univariate volatility of stock returns using stochastic GARCH models:Evidence from 4-Asian markets
title_full_unstemmed	Modeling univariate volatility of stock returns using stochastic GARCH models:Evidence from 4-Asian markets
title_sort	modeling univariate volatility of stock returns using stochastic garch models:evidence from 4-asian markets
publisher	INSI Publications
publishDate	2013
url	http://irep.iium.edu.my/33419/ http://irep.iium.edu.my/33419/ http://irep.iium.edu.my/33419/1/AJBAS_Published_294-303.pdf
first_indexed	2023-09-18T20:48:18Z
last_indexed	2023-09-18T20:48:18Z
_version_	1777409823303794688

Modeling univariate volatility of stock returns using stochastic GARCH models:Evidence from 4-Asian markets

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