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Relative Stock Market Performance during the Coronavirus Pandemic: Virus vs. Policy Effects in 80 Countries

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  • Richard C. K. Burdekin

    (Robert Day School of Economics & Finance, Claremont McKenna College, 500 E. Ninth Street, Claremont, CA 91711, USA)

  • Samuel Harrison

    (Robert Day School of Economics & Finance, Claremont McKenna College, 500 E. Ninth Street, Claremont, CA 91711, USA)

Abstract

This paper examines relative stock market performance following the onset of the coronavirus pandemic for a sample of 80 stock markets. Weekly data on coronavirus cases and deaths are employed alongside Oxford indices on each nation’s stringency and government support intensity. The results are broken down both by month and by geographical region. The full sample results show that increased coronavirus cases exert the expected overall effect of worsening relative stock market performance, but with little consistent impact of rising deaths. There is some evidence of significantly negative stock market effects arising from lockdowns as reflected in the Oxford stringency index. There are also positive reactions to government support in March and December in the overall sample—combined with some additional pervasive effects seen in mid-2020 in Latin America.

Suggested Citation

  • Richard C. K. Burdekin & Samuel Harrison, 2021. "Relative Stock Market Performance during the Coronavirus Pandemic: Virus vs. Policy Effects in 80 Countries," JRFM, MDPI, vol. 14(4), pages 1-18, April.
    • Handle: RePEc:gam:jjrfmx:v:14:y:2021:i:4:p:177-:d:534337
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    References listed on IDEAS

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    Cited by:

    1. Molla Ramizur Rahman & Arun Kumar Misra, 2021. "Bank Competition Using Networks: A Study on an Emerging Economy," JRFM, MDPI, vol. 14(9), pages 1-18, August.
    2. Sabeeh Ullah, 2023. "Impact of COVID-19 Pandemic on Financial Markets: a Global Perspective," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 14(2), pages 982-1003, June.
    3. Hsio-Yi Lin & Bin-Wei Hsu, 2023. "Empirical Study of ESG Score Prediction through Machine Learning—A Case of Non-Financial Companies in Taiwan," Sustainability, MDPI, vol. 15(19), pages 1-19, September.
    4. Park, Dojoon & Kang, Yong Joo & Eom, Young Ho, 2024. "Asset pricing tests for pandemic risk," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 1314-1334.

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