GARCH Family Models vs EWMA: Which is the best model to forecast volatility of the Moroccan stock exchange market?

Nowadays, modeling and forecasting the volatility of stock markets have become central to the practice of risk management; they have become one of the major topics in financial econometrics and they are principally and continuously used in the pricing of financial assets and the Value at Risk, as well as the pricing of options and derivatives. The aim of this article is to compare the GARCH (Generalised Auto Regressive Conditional Heteroskedasticity) family models -GARCH (1.1), GJR-GARCH, PGARCH, EGARCH, and IGARCH- with the EWMA (Exponentially Weighed Moving Average) model in the hope of finding the best model to forecast the volatility of the Moroccan stock-market index MADEX. We use daily returns covering the period between 01/04/1993 and 30/08/2016. We find that the asymmetric model IGARCH following a normal error distribution yields the best forecasting performance results and therefore, surpasses the EWMA model. Our results could have application in the risk management in Morocco, as well as leading to a better understanding of the Moroccan stock-exchange volatility dynamics, especially with the lack of previous similar studies.