Modelling Stock Market Volatility: Evidence from Vietnam

This study empirically investigates the volatility pattern of Indian stock market based on time series data which consists of daily closing prices of VN-Index for period 2005 - 2016. The analysis has been done using both symmetric and asymmetric models of Generalized Autoregressive Conditional Heteroscedastic (GARCH). According to Akaike Information Criterion (AIC) and Schwarz Information Criterion (SIC) criteria, the study proves that GARCH (1,1) and TGARCH (1,1) estimations are found to be most appropriate model to capture the symmetric and asymmetric volatility respectively. The study also provides evidence for the existence of asymmetric effects (leverage) by the parameters of the EGARCH(1,1) model that show that negative shocks have significant effects on Conditionally (fluctuate), but in the TGARCH(1.1) model the results are not as expected. This topic also provides investors with a tool to forecast the return of the stock market. At the same time, the results of the study will help investors and policymakers determine the profitability and volatility of the market so that they make the right decision to hold the securities.