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

Research output: Contribution to journalArticlepeer-review

Abstract

We develop an extension to the GARCHX model - named GARCHX-NL - that captures a key stylised fact for stock market return data seen during the Covid pandemic: an abrupt jump in volatility at the onset of the crisis, followed by a gradual return to its pre-crisis 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 Covid19
Original languageEnglish
Pages (from-to)531-547
Number of pages17
JournalData Science in Finance and Economics
DOIs
Publication statusPublished - 29 Nov 2024

Keywords

  • MARKET VOLATILITY
  • Covid19 Pandemic
  • GARCHX
  • Profile Likelihood

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