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Black swan events and COVID-19 outbreak: Sector level evidence from the US, UK, and European stock markets

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  • Ahmad, Wasim
  • Kutan, Ali M.
  • Gupta, Smarth

Abstract

Studies investigating the impact of coronavirus outbreak at the sector (industry) level are scant and focus on the USA market. We examine this issue for the US, UK, and the European stock markets, using endogenous structural break models and factor-augmented event study methodology by identifying the critical events. We find that the impact of coronavirus outbreak to the extent of black swan events is visible in March and, till the end of March 2020, the investors had limited opportunities for investment except for a few sectors in the US, UK, and Europe due to black swan events. Specifically, we find some stocks in consumer staples, healthcare, telecommunications, utilities, and financials were the attention-seekers and different sectors in our sample countries had different reactions to the outbreak. Overall, the analysis provides the reasons for panic buy and sell.

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  • Ahmad, Wasim & Kutan, Ali M. & Gupta, Smarth, 2021. "Black swan events and COVID-19 outbreak: Sector level evidence from the US, UK, and European stock markets," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 546-557.
    • Handle: RePEc:eee:reveco:v:75:y:2021:i:c:p:546-557
    DOI: 10.1016/j.iref.2021.04.007
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    More about this item

    Keywords

    Stock index; Sectoral returns; Black-swan events; COVID-19; Structural break; Event study;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models

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