Modelling Volatility Influenced by Exogenous Factors using an Improved GARCH-X Model

Abstract

Generalized Autoregressive Conditional Heteroscedastic (GARCH) model has gained popularity since its inception due to its ability to forecast volatility. Usually, GARCH model captures the volatility based on its past volatility and past squared residuals, but does not consider the effect of exogenous variable(s) on the volatility process owing to its univariate nature. In the domain of econometric modelling, where exogenous variables play a crucial role, GARCH model with intervention of exogenous variable(s) is more feasible than the traditional GARCH model. Hence, this study aims to empirically introduce and implement an improved GARCH-X model which can account for the effects of influencing factors (X) both into the mean and variance equation simultaneously of the standard GARCH model. In this manuscript, we have briefly discussed GARCH and GARCH-X models along with their implementation procedure. The proposed model is compared with the traditional GARCH model using domestic price index of edible oils in India along with the influencing factors like foreign exchange rate and international price index of edible oils as exogenous variables (X). Supremacy of using exogenous factors in volatility modelling is concluded from this comparison