Modelling Stock Market Volatility: Evidence from Vietnam

Abstract

This study empirically investigates the volatility pattern of Vietnam stock market based on time series data which consists of daily closing prices of VN-Index during the period 2005-2016. The analysis has been done using both symmetric and asymmetric Generalized Autoregressive Conditional Heteroscedastic (GARCH) models. Based on Akaike Information Criterion (AIC) and Schwarz Information Criterion (SIC) criteria, the study proves that GARCH (1,1) and EGARCH (1,1) are the most appropriate model to measure the symmetric and asymmetric volatility of VN-Index respectively. The study also provides evidence of the existence of asymmetric effects (leverage) via the parameters of the EGARCH (1,1) model that show that negative shocks have significant effects on conditional variance (fluctuation). Meanwhile, in the TGARCH (1,1) model, the findingss are not as expected. This study also provides investors with a tool to forecast the rate of return of the stock market. At the same time, the findings will help investors determine the profitability and volatility of the market so that they can make the right decisions on holding the securities.