Abstract
This study examines the impact of the COVID 19 pandemic on the stock markets of China, India, Pakistan, the UK and the US using Generalised Autoregressive Conditional Heteroscedasticity (GARCH) and Threshold GARCH models with COVID 19 as an exogenous dummy variable in the variance equation. The sample period of 2016 – 2021 is divided into two sub-periods: the pre-COVID 19 period and the COVID 19 period. The results of the study indicate that the COVID 19 pandemic had a significant impact on the stock market volatility of the sample markets. Results from both the GARCH and Threshold GARCH models further confirm that there was persistent volatility in these markets and that this volatility increased as a result of the pandemic. In addition, the Threshold GARCH results indicate that the asymmetric term was significant in all markets indicating that bad news, such as the pandemic, had a stronger impact on the conditional variance of the returns as compared to good news. In addition, the results further confirm that the US market had no significant impact on the volatility of the Chinese market during the pandemic. The results have important implications for (i) international investors regarding portfolio management and investment risk minimisation in situations like the COVID 19 pandemic; and (ii) policymakers in terms of how they respond to any future pandemic.
| Original language | English |
|---|---|
| Article number | 63 |
| Number of pages | 26 |
| Journal | SN Business and Economics |
| Volume | 4 |
| DOIs | |
| Publication status | Published - 15 May 2024 |
Keywords
- Stock Market Volatility
- COVID 19
- GARCH
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