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Monetary policy, COVID-19 immunization, and risk in the US stock markets

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  • Seungho Baek
  • Kwan Yong Lee

Abstract

We examine how monetary policy of the Federal Reserve System, COVID-19 mortality cases, and vaccinations are associated with the US stock market volatility during the pandemic period. Using the wavelet coherence analysis, we first find that there is a positive relationship between the volatility and death tolls. Second, while in the short term the sizable interest rate cut causes market instability, in the intermediate term it stabilizes the market. Third, vaccinations and the volatility have a negative relationship. Finally, the monetary policy and the volatility have much stronger coherency than the vaccination and the movements. These findings are consistent with panel regression results. Specifically, we find that the systemic COVID-19 shock in the US stock market is alleviated by an increase in the number of COVID-19 vaccination doses administered and a low and stable change in the effective federal funds rate. Furthermore, our results show that the monetary policy influences the stock market volatility significantly more than the vaccination, regardless of firm size and industry type. Thus, this study helps policymakers cope with possible systemic shocks from other infectious diseases, considering the magnitude of monetary and health policy and their short/intermediate/long-term lagging effectiveness in reducing market volatility.

Suggested Citation

  • Seungho Baek & Kwan Yong Lee, 2022. "Monetary policy, COVID-19 immunization, and risk in the US stock markets," Cogent Economics & Finance, Taylor & Francis Journals, vol. 10(1), pages 2148365-214, December.
  • Handle: RePEc:taf:oaefxx:v:10:y:2022:i:1:p:2148365
    DOI: 10.1080/23322039.2022.2148365
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    Cited by:

    1. Szczygielski, Jan Jakub & Charteris, Ailie & Obojska, Lidia & BrzeszczyƄski, Janusz, 2024. "Capturing the timing of crisis evolution: A machine learning and directional wavelet coherence approach to isolating event-specific uncertainty using Google searches with an application to COVID-19," Technological Forecasting and Social Change, Elsevier, vol. 205(C).

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