The effect of the Covid pandemic on stock market volatility: Separating initial impact from time-to-recovery

Jin Zeng; Yijia Zhang; Yun Yin; Peter G Moffatt; Jin Zeng; Yijia Zhang; Yun Yin; Peter G Moffatt

doi:10.3934/DSFE.2024022

Data Science in Finance and Economics

2024, Volume 4, Issue 4: 531-547. doi: 10.3934/DSFE.2024022

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The effect of the Covid pandemic on stock market volatility: Separating initial impact from time-to-recovery

1.
Business school, Guangzhou College of Technology and Business, Guangzhou, China
2.
School of Economics, University of East Anglia, Norwich, UK
3.
Faculty of Business, City University of Macau, Macau

Received: 06 August 2024 Revised: 03 November 2024 Accepted: 14 November 2024 Published: 29 November 2024
JEL Codes: C13, C58, G01

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.
- market volatility,
- COVID-19 pandemic,
- GARCH,
- GARCHX,
- profile likelihood
Citation: Jin Zeng, Yijia Zhang, Yun Yin, Peter G Moffatt. The effect of the Covid pandemic on stock market volatility: Separating initial impact from time-to-recovery[J]. Data Science in Finance and Economics, 2024, 4(4): 531-547. doi: 10.3934/DSFE.2024022

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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.

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