Modeling and Forecasting Time Varying Stock Return Volatility in the Egyptian Stock Market

This study investigates the performance of five models for forecasting the Egyptian stock market return volatility. We used the period from 1 January, 1998 until 31 December, 2009 as an in-sample period. We used also the next 30 days after the in-sample period to be our out-of-sample period. The competing models are: EWMA, ARCH, GARCH, GJR, and EGARCH. We examined also the ARCH effect to test the validity of using GARCH family to predict the volatility of market indices. The empirical results show that EGARCH is the best model between the examined models according to the usual evaluating statistical metrics (RMSN, MAE, and MAPE). When we used Diebold and Mariano (DM) test to examine the significance of the difference between errors of volatility forecasting models, we found no significance difference between the errors of competing models. The results also reject the null hypothesis of homoscedastic normal process for both EGX30 and CIBC100 indices