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The impact of the COVID 19 pandemic on stock market volatility: evidence from a selection of developed and emerging stock markets

Author

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  • Muhammad Niaz Khan

    (University of Science and Technology)

  • Suzanne G. M. Fifield

    (University of Dundee)

  • David M. Power

    (University of Dundee)

Abstract

This study examines the impact of the COVID 19 pandemic on the stock markets of China, India, Pakistan, the UK and the US using Generalised Autoregressive Conditional Heteroscedasticity (GARCH) and Threshold GARCH models with COVID 19 as an exogenous dummy variable in the variance equation. The sample period of 2016–2021 is divided into two sub-periods: the pre-COVID 19 period and the COVID 19 period. The results of the study indicate that there was persistent volatility in these markets and that this volatility increased as a result of the pandemic. In addition, the Threshold GARCH results indicate that the asymmetric term was significant in all markets indicating that bad news, such as the pandemic, had a stronger impact on the conditional variance of the returns as compared to good news. In addition, the results further confirm that the US market had no significant impact on the volatility of the Chinese market during the pandemic. The results have important implications for (1) international investors regarding portfolio management and investment risk minimisation in situations like the COVID 19 pandemic; and (2) policy-makers in terms of how they respond to any future pandemic.

Suggested Citation

  • Muhammad Niaz Khan & Suzanne G. M. Fifield & David M. Power, 2024. "The impact of the COVID 19 pandemic on stock market volatility: evidence from a selection of developed and emerging stock markets," SN Business & Economics, Springer, vol. 4(6), pages 1-26, June.
    • Handle: RePEc:spr:snbeco:v:4:y:2024:i:6:d:10.1007_s43546-024-00659-w
    DOI: 10.1007/s43546-024-00659-w
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    References listed on IDEAS

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    1. Rossetti, Nara & Seido , Marcelo & Faria , Jorge, 2017. "A behavioral analysis of the volatility of interbank interest rates in developed and emerging countries," Journal of Economics, Finance and Administrative Science, Universidad ESAN, vol. 22(42), pages 99-128.
    2. Al-Awadhi, Abdullah M. & Alsaifi, Khaled & Al-Awadhi, Ahmad & Alhammadi, Salah, 2020. "Death and contagious infectious diseases: Impact of the COVID-19 virus on stock market returns," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    3. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    4. Scott R. Baker & Nicholas Bloom & Steven J. Davis & Kyle J. Kost & Marco C. Sammon & Tasaneeya Viratyosin, 2020. "The Unprecedented Stock Market Impact of COVID-19," NBER Working Papers 26945, National Bureau of Economic Research, Inc.
    5. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    6. Aktar, Asikha & Alam, Md. Mahmudul & Al-Amin, Abul Quasem, 2021. "Global Economic Crisis, Energy Use, CO2 Emissions and Policy Roadmap amid COVID-19," OSF Preprints 69kje, Center for Open Science.
    7. Ren, Yi-Shuai & Narayan, Seema & Ma, Chao-qun, 2021. "Air quality, COVID-19, and the oil market: Evidence from China’s provinces," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 58-72.
    8. Muhammad Niaz Khan & Suzanne G. M. Fifield & Nongnuch Tantisantiwong & David M. Power, 2022. "Changes in co-movement and risk transmission between South Asian stock markets amidst the development of regional co-operation," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 36(1), pages 87-117, March.
    9. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    10. Chun-Da Chen & Chin-Chun Chen & Wan-Wei Tang & Bor-Yi Huang, 2009. "The positive and negative impacts of the sars outbreak:a case of the Taiwan industries," Journal of Developing Areas, Tennessee State University, College of Business, vol. 43(1), pages 281-293, September.
    11. Nara Rossetti & Marcelo Seido Nagano & Jorge Luis Faria Meirelles, 2017. "A behavioral analysis of the volatility of interbank interest rates in developed and emerging countries," Journal of Economics, Finance and Administrative Science, Emerald Group Publishing Limited, vol. 22(42), pages 99-128, June.
    12. Alomari, Mohammad & Al Rababa'a, Abdel Razzaq & Ur Rehman, Mobeen & Power, David M., 2022. "Infectious diseases tracking and sectoral stock market returns: A quantile regression analysis," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    13. Baker, Malcolm & Wurgler, Jeffrey & Yuan, Yu, 2012. "Global, local, and contagious investor sentiment," Journal of Financial Economics, Elsevier, vol. 104(2), pages 272-287.
    14. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
    15. Yi-Hsien Wang & Fu-Ju Yang & Li-Je Chen, 2013. "An investor's perspective on infectious diseases and their influence on market behavior," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 14(sup1), pages 112-127, June.
    16. Vuong, Giang Thi Huong & Nguyen, Manh Huu & Huynh, Anh Ngoc Quang, 2022. "Volatility spillovers from the Chinese stock market to the U.S. stock market: The role of the COVID-19 pandemic," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    17. Natarajana, Vinodh & Raja , Azariah & Priyac, Nagarajan, 2014. "Examining mean-volatility spillovers across national stock markets," Journal of Economics, Finance and Administrative Science, Universidad ESAN, vol. 19(36), pages 55-62.
    18. Goodell, John W., 2020. "COVID-19 and finance: Agendas for future research," Finance Research Letters, Elsevier, vol. 35(C).
    19. Ștefan Cristian Gherghina & Daniel Ștefan Armeanu & Camelia Cătălina Joldeș, 2021. "COVID-19 Pandemic and Romanian Stock Market Volatility: A GARCH Approach," JRFM, MDPI, vol. 14(8), pages 1-29, July.
    20. Li, Hong & Majerowska, Ewa, 2008. "Testing stock market linkages for Poland and Hungary: A multivariate GARCH approach," Research in International Business and Finance, Elsevier, vol. 22(3), pages 247-266, September.
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    More about this item

    Keywords

    Stock market volatility; COVID 19; GARCH;
    All these keywords.

    JEL classification:

    • F30 - International Economics - - International Finance - - - General
    • G01 - Financial Economics - - General - - - Financial Crises
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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