GARCH model for volatility in stock return series of Vietnam stock market

This paper examines the features of the stock return volatility and the presence of structural breaks in return variance of VN-Index in the Vietnam stock market by using the iterated cumulative sums of squares (ICSS) algorithm. The relationship between Vietnam stock market's volatility shifts and impacts of global crisis is also detected. Using a long-span data, the results show that daily stock returns can be characterized by GARCH and GARCH in mean (GARCH-M) models while threshold GARCH (T-GARCH) are not suitable. Further evidence also reveals that when sudden shifts are taken into account in the GARCH models, reduction in the volatility persistence is found. It suggests that many previous studies may have overestimated the degree of volatility persistence existing in financial time series. The small value of coefficients of the dummies representing breakpoints in modified GARCH model implies that the conditional variance of stock return is much affected by past trend of observed shocks and variance. Our results have important implications regarding advising investors on decisions concerning pricing equity, portfolio investment and management, hedging and forecasting. Moreover, it is also helpful for policy-makers in making and promulgating the financial policies.