GARCH (1,1) as the Stochastic Underlying Process for Stock Market Returns : Empirical Evidence from Asian Markets - Inder, Shivani; Pasricha, J. S. (Indian Journal of Research in Capital Markets, 2014)
Traditional econometric analysis assumes the financial time series as a random walk process with constant variance. However, returns from financial market variables exhibit the conditionally dependent behaviour which is autoregressive in nature and can be explained by the generally auto regressive conditionally heteroskedastic process. The present study focused on GARCH as the process explaining the behaviour for returns and volatility of indices of the stock markets of 10 Asian countries. This process was estimated by employing the GARCH (1,1) model on stock market returns. The time period considered is from January 2000 to July 2013. The GARCH(1,1) model was found to be a satisfactory model fitting the financial time series.