Abstract
We develop an extension to the GARCHX model-named GARCHX-NL-that captures a key stylized fact for stock market return data seen during the COVID-19 pandemic: an abrupt jump in volatility at the onset of the crisis, followed by a gradual return to its precrisis level. We apply the GARCHX-NL procedure to daily data on various major stock market indexes. The profile likelihood method is used for estimation. The model decomposes the overall impact of the crisis into two measures: the initial impact, and the “half-life” of the shock. We find a strong negative association between these two measures. Moreover, countries with low initial impact but a long half-life tend to be emerging markets, while those with high initial impact and short half-life tend to be developed economies with well-established stock-markets. We attribute these differences to differences in investors’ sensitivity to adverse news, and to differences in the preparedness of stock markets to absorb the effects of crises such as the COVID-19 pandemic.
| Original language | English |
|---|---|
| Pages (from-to) | 531-547 |
| Number of pages | 17 |
| Journal | Data Science in Finance and Economics |
| Volume | 4 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 29 Nov 2024 |
Keywords
- COVID-19 pandemic
- GARCH
- GARCHX
- market volatility
- profile likelihood
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