Forecasting the volatility of the Moroccan financial market: A comparison between the models of GARCH family and EWMA

Ouael El Jebari, Abdelati Hakmaoui


The aim of this article is to compare the GARCH (Generalised AutoRegressive Conditional Heteroskedasticity) family models of GARCH (1.1), GJR-GARCH, PGARCH, EGARCH, and IGARCH, to the EWMA (Exponentially Weighted Moving Average) model in the hope of finding the best model to forecast the volatility of the Moroccan stock market index MADEX. It proposes an empirical approach based on the assessment and measurement of the forecasting models based on well-known forecasts error metrics such as MRSE, RAE, and TIC. The data used in this study consists of a series of daily returns covering the period between 01/04/1993 and 30/08/2016. The results of the study confirm the superiority of the GARCH family models in terms of volatility forecasting since the asymmetric model of IGARCH, following a normal error distribution, seems to yield the best forecasting performance results thus outperforming the EWMA model. Its conclusions could be of a particular interest to hedge funds and portfolio managers along with investors acting in the Moroccan context. 

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This work is licensed under a Creative Commons Attribution 4.0 International License.