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Stocks Vote with Their Feet: Can a Piece of Paper Document Fights the COVID-19 Pandemic?

Author

Listed:
  • J. Su
  • Q. Zhong

Abstract

Assessing the trend of the COVID-19 pandemic and policy effectiveness is essential for both policymakers and stock investors, but challenging because the crisis has unfolded with extreme speed and the previous index was not suitable for measuring policy effectiveness for COVID-19. This paper builds an index of policy effectiveness on fighting COVID-19 pandemic, whose building method is similar to the index of Policy Uncertainty, based on province-level paper documents released in China from Jan.1st to Apr.16th of 2020. This paper also studies the relationships among COVID-19 daily confirmed cases, stock market volatility, and document-based policy effectiveness in China. This paper uses the DCC-GARCH model to fit conditional covariance's change rule of multi-series. This paper finally tests four hypotheses, about the time-space difference of policy effectiveness and its overflow effect both on the COVID-19 pandemic and stock market. Through the inner interaction of this triad structure, we can bring forward more specific and scientific suggestions to maintain stability in the stock market at such exceptional times.

Suggested Citation

  • J. Su & Q. Zhong, 2020. "Stocks Vote with Their Feet: Can a Piece of Paper Document Fights the COVID-19 Pandemic?," Papers 2005.02034, arXiv.org.
    • Handle: RePEc:arx:papers:2005.02034
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    References listed on IDEAS

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    1. Rosa, Carlo, 2014. "The high-frequency response of energy prices to U.S. monetary policy: Understanding the empirical evidence," Energy Economics, Elsevier, vol. 45(C), pages 295-303.
    2. Engle, Robert F & Sheppard, Kevin K, 2001. "Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH," University of California at San Diego, Economics Working Paper Series qt5s2218dp, Department of Economics, UC San Diego.
    3. Fabrizio Gilardi, 2010. "Who Learns from What in Policy Diffusion Processes?," American Journal of Political Science, John Wiley & Sons, vol. 54(3), pages 650-666, July.
    4. Engle, Robert F & Sheppard, Kevin K, 2001. "Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH," University of California at San Diego, Economics Working Paper Series qt5s2218dp, Department of Economics, UC San Diego.
    5. Warwick McKibbin & Roshen Fernando, 2021. "The Global Macroeconomic Impacts of COVID-19: Seven Scenarios," Asian Economic Papers, MIT Press, vol. 20(2), pages 1-30, Summer.
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    Cited by:

    1. Fu Qiao & Yan Yan, 2020. "How does stock market reflect the change in economic demand? A study on the industry-specific volatility spillover networks of China's stock market during the outbreak of COVID-19," Papers 2007.07487, arXiv.org.

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