Modelling Stock Market Return Volatility: Evidence from Moroccan stock market

Abstract

Generally speaking, the Moroccan all-share index (MASI), or the Moroccan stock market's daily returns, are being estimated and forecasted by the research and which is using General Autoregressive Conditional Heteroscedastic (GARCH) type models on a worldwide scale. The conditional variance was also evaluated using data from January 2007 to December 2021. Additionally, two of the most prevalent stock market characteristics namely the leverage effect, and volatility clustering, are both modeled by symmetric and asymmetric frameworks in this study.

In a similar vein, the research had been carried out for this paper demonstrates that the returns' variance was not steady. Nevertheless, it varied with time, which is a conditional heteroskedasticity operation. Additionally, the returns on the Moroccan stock market have also been computed using a variety of methods, including GARCH, GJR GARCH, EGARCH, and M- GARCH models. These strategies also display the leverage effect, volatility persistency, clustering effects, and last but not least, an asymmetric response to external shocks. Proving that, there is a risk premium for the MASI return series.

Keywords: ARCH effect, GARCH Models, leverage effect, volatility clustering, asymmetric GARCH models, symmetric GARCH models.

JEL Classification: G10, G14, C58

Paper type: Empirical Research