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The impact of the SARS-CoV-2 pandemic on financial markets: a seismologic approach

Author

Listed:
  • Alessandro Spelta

    (University of Pavia)

  • Nicolò Pecora

    (Catholic University)

  • Andrea Flori

    (Polytechnic of Milan)

  • Paolo Giudici

    (University of Pavia)

Abstract

This work investigates financial volatility cascades generated by SARS-CoV-2 related news using concepts developed in the field of seismology. We analyze the impact of socio-economic and political announcements, as well as of financial stimulus disclosures, on the reference stock markets of the United States, United Kingdom, Spain, France, Germany and Italy. We quantify market efficiency in processing SARS-CoV-2 related news by means of the observed Omori power-law exponents and we relate these empirical regularities to investors’ behavior through the lens of a stylized Agent-Based financial market model. The analysis reveals that financial markets may underreact to the announcements by taking a finite time to re-adjust prices, thus moving against the efficient market hypothesis. We observe that this empirical regularity can be related to the speculative behavior of market participants, whose willingness to switch toward better performing investment strategies, as well as their degree of reactivity to price trend or mispricing, can induce long-lasting volatility cascades.

Suggested Citation

  • Alessandro Spelta & Nicolò Pecora & Andrea Flori & Paolo Giudici, 2023. "The impact of the SARS-CoV-2 pandemic on financial markets: a seismologic approach," Annals of Operations Research, Springer, vol. 330(1), pages 639-664, November.
    • Handle: RePEc:spr:annopr:v:330:y:2023:i:1:d:10.1007_s10479-021-04115-y
    DOI: 10.1007/s10479-021-04115-y
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    1. Noemi Schmitt & Frank Westerhoff, 2017. "Heterogeneity, spontaneous coordination and extreme events within large-scale and small-scale agent-based financial market models," Journal of Evolutionary Economics, Springer, vol. 27(5), pages 1041-1070, November.
    2. Sandrine Jacob Leal & Mauro Napoletano & Andrea Roventini & Giorgio Fagiolo, 2016. "Rock around the clock: An agent-based model of low- and high-frequency trading," Journal of Evolutionary Economics, Springer, vol. 26(1), pages 49-76, March.
    3. Hens, Thorsten & Schenk-Hoppe, Klaus Reiner (ed.), 2009. "Handbook of Financial Markets: Dynamics and Evolution," Elsevier Monographs, Elsevier, edition 1, number 9780123742582.
    4. Matthias Lengnick & Hans-Werner Wohltmann, 2013. "Agent-based financial markets and New Keynesian macroeconomics: a synthesis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 1-32, April.
    5. Scott R. Baker & Nicholas Bloom & Steven J. Davis & Stephen J. Terry, 2020. "COVID-Induced Economic Uncertainty," NBER Working Papers 26983, National Bureau of Economic Research, Inc.
    6. Hommes, Cars & Huang, Hai & Wang, Duo, 2005. "A robust rational route to randomness in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 29(6), pages 1043-1072, June.
    7. Maurizio Bovi & Roy Cerqueti, 2016. "Forecasting macroeconomic fundamentals in economic crises," Annals of Operations Research, Springer, vol. 247(2), pages 451-469, December.
    8. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    9. Tian, Shuairu & Hamori, Shigeyuki, 2016. "Time-varying price shock transmission and volatility spillover in foreign exchange, bond, equity, and commodity markets: Evidence from the United States," The North American Journal of Economics and Finance, Elsevier, vol. 38(C), pages 163-171.
    10. Spelta, A. & Flori, A. & Pecora, N. & Pammolli, F., 2021. "Financial crises: Uncovering self-organized patterns and predicting stock markets instability," Journal of Business Research, Elsevier, vol. 129(C), pages 736-756.
    11. Alexander M. Petersen & Fengzhong Wang & Shlomo Havlin & H. Eugene Stanley, 2009. "Quantitative law describing market dynamics before and after interest-rate change," Papers 0903.0010, arXiv.org, revised Oct 2010.
    12. William A. Brock & Cars H. Hommes, 2001. "A Rational Route to Randomness," Chapters, in: W. D. Dechert (ed.), Growth Theory, Nonlinear Dynamics and Economic Modelling, chapter 16, pages 402-438, Edward Elgar Publishing.
    13. Avdjiev, S. & Giudici, P. & Spelta, A., 2019. "Measuring contagion risk in international banking," Journal of Financial Stability, Elsevier, vol. 42(C), pages 36-51.
    14. Barberis, Nicholas & Shleifer, Andrei & Vishny, Robert, 1998. "A model of investor sentiment," Journal of Financial Economics, Elsevier, vol. 49(3), pages 307-343, September.
    15. Siokis, Fotios M., 2012. "The dynamics of a complex system: The exchange rate crisis in Southeast Asia," Economics Letters, Elsevier, vol. 114(1), pages 98-101.
    16. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    17. Day, Richard H. & Huang, Weihong, 1990. "Bulls, bears and market sheep," Journal of Economic Behavior & Organization, Elsevier, vol. 14(3), pages 299-329, December.
    18. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    19. Alexander M. Petersen & Fengzhong Wang & Shlomo Havlin & H. Eugene Stanley, 2010. "Market dynamics immediately before and after financial shocks: quantifying the Omori, productivity and Bath laws," Papers 1006.1882, arXiv.org, revised Oct 2010.
    20. Alessandro Spelta & Andrea Flori & Nicolò Pecora & Sergey Buldyrev & Fabio Pammolli, 2020. "A behavioral approach to instability pathways in financial markets," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    21. Nowak, Sylwia & Andritzky, Jochen & Jobst, Andreas & Tamirisa, Natalia, 2011. "Macroeconomic fundamentals, price discovery, and volatility dynamics in emerging bond markets," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2584-2597, October.
    22. LeBaron, Blake & Arthur, W. Brian & Palmer, Richard, 1999. "Time series properties of an artificial stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 23(9-10), pages 1487-1516, September.
    23. Noemi Schmitt & Frank Westerhoff, 2017. "Herding behaviour and volatility clustering in financial markets," Quantitative Finance, Taylor & Francis Journals, vol. 17(8), pages 1187-1203, August.
    24. Fabrizio Lillo & Rosario N. Mantegna, 2001. "Power law relaxation in a complex system: Omori law after a financial market crash," Papers cond-mat/0111257, arXiv.org, revised Jun 2003.
    25. Jon Danielsson & Hyun Song Shin & Jean-Pierre Zigrand, 2012. "Endogenous Extreme Events and the Dual Role of Prices," Annual Review of Economics, Annual Reviews, vol. 4(1), pages 111-129, July.
    26. Lux, Thomas, 1995. "Herd Behaviour, Bubbles and Crashes," Economic Journal, Royal Economic Society, vol. 105(431), pages 881-896, July.
    27. Ascari, G. & Pecora, N. & Spelta, A., 2018. "Booms And Busts In A Housing Market With Heterogeneous Agents," Macroeconomic Dynamics, Cambridge University Press, vol. 22(7), pages 1808-1824, October.
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    More about this item

    Keywords

    SARS covid-2; Financial markets; Omori law; Agent-based modeling;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

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