A study on the performance of symmetric and asymmetric GARCH models in estimating stock returns volatility

In this paper we aim to test the usefulness of two variants of Generalized Autoregressive Conditional Heteroscedasticity (GARCH) family-type models in estimating stock returns volatility for three Asian markets namely- Kuala Lumpur Composite Index (KLCI) of Malaysia, Straits Times Index (STI) of Singapore and the Bombay Stock Exchange Index (BSESN) of India. For this paper we have chosen the variants of the GARCH family models: the standard GARCH (1, 1) model represents as the symmetric model and the Threshold GARCH or TGARCH (1, 1) model represents as the asymmetric model. The study covers the period 02/01/2007 – 31/12/2013 comprising daily observations of 1724 for KLCI, 1743 for Singapore and 1725 for BSESN excluding the public holidays. Our results provide strong evidence that the daily stock returns can be characterized by these two models and they are better fit to capture the stylized facts about the index returns such as volatility clustering, leptokurtosis and the leverage effects. The results suggest that asymmetric GARCH performs relatively better for the case of Singapore while in the other two markets the standard GARCH performs better in explaining the data