Estimating volatility of stock index returns by using symmetric Garch models
This paper utilizes Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models to estimate volatility of financial asset returns of three Asian markets namely; Kuala Lumpur Composite Index (KLCI) of Malaysia, Jakarta Stock Exchange Composite Index (JKSE) of Indonesia and Straits Time...
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| Format: | Article |
| Language: | English |
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IDOSI Publications
2013
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| Online Access: | http://irep.iium.edu.my/41039/ http://irep.iium.edu.my/41039/ http://irep.iium.edu.my/41039/ http://irep.iium.edu.my/41039/1/Middle-East_Journal_of_Scientific_Research.pdf |
| Summary: | This paper utilizes Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models to
estimate volatility of financial asset returns of three Asian markets namely; Kuala Lumpur Composite
Index (KLCI) of Malaysia, Jakarta Stock Exchange Composite Index (JKSE) of Indonesia and Straits Times Index
(STI) of Singapore. Two symmetric GARCH models with imposing names such as the GARCH (1, 1) and the
GARCH-in-Mean or GARCH-M (1, 1) are considered in this study. The study covers the period
02/01/2007 – 31/12/2012 comprising daily observations of 1477 for KLCI, 1461 for JKSE and 1493 for STI
excluding the public holidays. We choose to apply GARCH models as they are especially suitable for high
frequency financial market data such as stock returns which has a time-varying variance. Unlike the linear
structural models, GARCH models are found useful in explaining a number of important features commonly
observed in most financial time series such as leptokurtosis, volatility clustering and leverage or asymmetric
effects. In this paper, we applied the symmetric GARCH models to examine their capability in explaining the
volatility clustering and leptokurtic characteristic of the financial data. In addition, we also empirically tested
the positive correlation hypothesis between the expected risk and the expected return usually predicted in
financial application. Our results provide strong evidence that daily stock returns can be characterized by these
two symmetric GARCH models. From the results of risk-return hypothesis test in GARCH-M model, we found
evidence of positive correlation between the risk and return for all markets as expected. However, only for
Indonesian market which is found to be more volatile than the other two 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 two markets are positive but statistically insignificant suggesting that
increased risk does not necessarily produce higher return. |
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