This study investigates the effects of global economic policy uncertainty and oil shocks on stock market volatility in Botswana, Mauritius, and South Africa. Datasets from periods preceding and during the COVID-19 pandemic are utilized to provide evidence on the impact of global economic policy uncertainty (GEPU) and oil shocks on stock returns volatility in these countries. The examination employs a mixed data sampling model based on generalized autoregressive conditional heteroskedasticity (GARCH-MIDAS). The GARCH-MIDAS approach allows for combining high-frequency stock data with low-frequency GEPU and oil shock data to forecast the long-term component of volatility. Additionally, this method demonstrates a better fit for that relationship when compared to traditional GARCH. The results indicate that both GEPU and oil consumption demand shocks have positive and significant impacts on stock volatility for the three countries in our in-sample case (which corresponds to the period before the COVID-19 pandemic). The volatility coefficient estimates for Botswana, Mauritius, and South Africa are 0.076, 0.001 and 0.119, respectively, all significant at the 1% level. This suggests that stock returns in these countries react positively to changes in oil demand shocks. Forecasting data during the COVID-19 period also shows that incorporating global economic policy uncertainty and oil shocks using a GARCH-MIDAS approach improves forecasting accuracy. The application of the GARCH-MIDAS approach in this study facilitates the separation of short-term and long-term volatility components effectively, thus enabling us to address a significant shortfall of previous research that has explored the impact of economic policy uncertainty on stock market returns.
Key words: Global economic policy uncertainty, oil consumption demand shock, generalized autoregressive conditional heteroskedasticity (GARCH-MIDAS), Southern African Development Community (SADC) countries, stock market volatility.
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