| Autor: |
Adeboye, Nureni Olawale, Folorunso, Sakinat Oluwabukonla, Abimbola, Olawale Victor, Akinbo, Rasaki Yinka |
| Předmět: |
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| Zdroj: |
Statistics in Transition. New Series; Mar2023, Vol. 24 Issue 2, p17-36, 21p |
| Abstrakt: |
The growing concern over the global effects of the COVID-19 pandemic on every aspect of human endeavour has necessitated a continuous modelling of its impact on socio-economic phenomena, allowing the formulation of policies aimed at sustaining future economic growth and mitigating the looming recession. The study employed Exponential Generalised Autoregressive Conditional Heteroscedasticity (EGARCH) procedures to develop stock volatility models for the pre- and COVID-19 era. The Fixed-Effects Two Stage Least Square (TSLS) technique was utilised to establish an empirical relationship between capital market volatility and the COVID-19 occurrence based on equity market indices and COVID-19 reported cases of five emerging African economies: Nigeria, Egypt, South Africa, Gabon and Tanzania. The stock series was made stationary at the first order differencing and the model results indicated that the stock volatility of all the countries responded sharply to the outbreak of COVID-19 with the average stock returns of Nigeria and Gabon suffering the most shocks. The forecast values indicated a constant trend of volatility shocks for all the countries in the continuous presence of the COVID-19 pandemic. Additionally, the confirmed and death cases of COVID-19 were found to increase stock prices while recovered cases bring about a reduction in the stock prices in the studied periods. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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