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COVID-19 Impact on Stock Markets: A Multiscale Event Analysis Perspective

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Abstract

The existing literature primarily examined the impact of unexpected events on the stock market at a single scale, posing the challenge of a lack of multiscale analysis. This paper investigates the impact of COVID-19 on stock markets (China, the U.S., and Hong Kong) from a multiscale perspective using an improved ensemble empirical mode decomposition (EEMD)-based event analysis method. First, the stock price series is decomposed into several independent intrinsic mode functions (IMFs) and a residue. Second, a novel composition method is proposed to reconstruct the IMFs into three components: high-frequency, low-frequency, and long-term trend. We find that the composition of low-frequency and long-term trend components is dominant, which is used to estimate the strength of COVID-19 impact on the stock markets. In addition, the outbreak of COVID-19 significantly increased the intensity of short-term fluctuations in stock prices. Finally, the high-frequency component is analyzed to capture the volatility spillover effects among the three stock markets by the BEKK(Baba-Engle-Kraft-Kroner)-GARCH model. The results show that before the outbreak, there are two-way volatility spillovers between any two of the three markets. After the outbreak, there is no spillover effect between China and Hong Kong, and Hong Kong has no spillover effect on the U.S. However, volatility in the U.S. market still has a significant spillover effect on the other two markets, implying that a mature market can absorb new information more quickly.

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Notes

  1. https://www.who.int/.

  2. The news comes from the People’s Daily, one of the largest official media in China. http://en.people.cn/n3/2020/0123/c90000-9651334.html.

  3. Thanks for the referee’s helpful advice.

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Acknowledgements

This research is supported by the Key project of the National Social Science Fund (22AZD039), the Guangzhou Philosophy and Social Science Planning project (2022GZYB08), the Fundamental Research Funds for the Central Universities (ZDPY202209). We would like to thank Editor-in-chief Hans Amman and the anonymous reviewers for their valuable suggestions and feedback.

Funding

This research is supported by the Key project of the National Social Science Fund (22AZD039), the Guangzhou Philosophy and Social Science Planning project (2022GZYB08), the Fundamental Research Funds for the Central Universities (ZDPY202209).

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Authors and Affiliations

  1. School of Economics and Finance, South China University of Technology, Guangzhou, 510006, People’s Republic of China

    Helong Li, Guanglong Xu, Qin Huang & Rubin Ruan

  2. School of Business Administration, South China University of Technology, Guangzhou, 510641, People’s Republic of China

    Weiguo Zhang

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  1. Helong Li
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  2. Guanglong Xu
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  3. Qin Huang
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Contributions

HL designed the algorithms, wrote the paper. GX wrote the code and carried out the experiments. Material preparation, data collection and analysis were performed by QH, RR. WZ is responsible for ensuring that the descriptions are accurate and agreed by all authors. All authors discussed the results and contributed to the final manuscript.

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Correspondence to Helong Li.

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Li, H., Xu, G., Huang, Q. et al. COVID-19 Impact on Stock Markets: A Multiscale Event Analysis Perspective. Comput Econ 63, 1191–1212 (2024). https://doi.org/10.1007/s10614-023-10448-6

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