Forecasting The Volatilities of Stock Market Returns in Sudan and The Kingdom of Saudi Arabia during The Period 2000-2022

Abstract

The study tested the ability of GARRCH models to forecast the volatilities of stock markets returns in Sudan and Kingdom of Saudi Arabia during the period 2000-2022, it used the descriptive analytical approach based on Generalized Autoregressive Conditional Heteroskedasticity model GARCH, the empirical results show that the best model is EGARCH (1, 1), the conditional variance has exponential function, this confirmed the existence of asymmetric shocks, positive financial leverage effect and risk premium parameter, which mean the increasing in volatilities would increase returns, and the significant of model parameters with a complete independence between estimation residuals indicate to removal ARCH effect on the stock exchanges residuals during a specified period, there is a positive relationship between returns and risk, that means the average returns depends on the past innovation and conditional variance, EGARCH (1, 1) model abled to forecast the volatilities of stock markets returns, and it recommended that Expanding the scope of stock markets implementing effective control systems that reduced risks and achieve the safety of financial transactions, and depending on research and development to forecast volatilities in the developing countries stock markets to improve and promote financial services.