期刊名称：International Research Journal of Finance and Economics
印刷版ISSN：1450-2887
电子版ISSN：1450-2887
出版年度：2021
卷号：181
页码：44-64
语种：English
出版社：European Journals Inc.
摘要：The purpose of this paper is to evaluate the forecasting performance of linear and non-linear (GARCH) models in terms of their in-sample and out-of-sample forecasting accuracy for EGX30 and Nikkei225 indices as an example of an emerging and developed markets respectively.We employ GARCH, GARCH-IN-MEAN, EGARCH, GJR-GARCH, Multivariate GARCH, and Nelson's EGARCH for forecasting using daily price data of the indices for the period of 2001 to 2019. We find that the volatility shocks on the indices returns are quite persistent. Furthermore, our findings show that the indices have leverage effect, and the impact of shocks is asymmetric, and consequently it can be stated that the impact of negative shocks on volatility are higher than positive shocks.The results suggest that the Nelson's EGARCH model is the most accurate model in the GARCH class for forecasting, as this model outperforms the other models. Additionally, we find that emerging stock markets have higher volatilities than those in developed markets. Further, these results imply that the EGARCH model might be more useful than other models when implementing risk management strategies and developing stock pricing model.This paper contributes to the literature by comparing two significant global markets; one of the largest developed economies in the world, Japan, and one of Africa’s largest developing economies, Egypt.
