IDEAS home Printed from https://ideas.repec.org/a/eee/finana/v74y2021ics1057521921000144.html
   My bibliography  Save this article

The impact of Covid-19 on G7 stock markets volatility: Evidence from a ST-HAR model

Author

Listed:
  • Izzeldin, Marwan
  • Muradoğlu, Yaz Gülnur
  • Pappas, Vasileios
  • Sivaprasad, Sheeja

Abstract

We investigate the impact of Covid-19 on stock markets across G7 countries and their business sectors. We highlight the synchronicity and severity of this unprecedented crisis. We find strong transition evidence to a crisis regime in all countries and sectors, yet crisis intensity and timings vary. The Health Care and Consumer services sectors were the most severely affected; a reflection of the Covid-19 drug-race and international travel restrictions. The Technology sector was hit the latest and least severely, as imposed lockdown measures forced people to explore various web-based entertainment and distraction options. Country-wise the UK and the US were the most affected with the highest heterogeneity in their business sectors' response; a possible reflection of the ambiguity in the initial response and adoption of lockdown measures. Financial markets' response to Covid-19 is akin to response in previous financial crisis rather than previous pandemics. A series of robustness checks confirms our findings.

Suggested Citation

  • Izzeldin, Marwan & Muradoğlu, Yaz Gülnur & Pappas, Vasileios & Sivaprasad, Sheeja, 2021. "The impact of Covid-19 on G7 stock markets volatility: Evidence from a ST-HAR model," International Review of Financial Analysis, Elsevier, vol. 74(C).
  • Handle: RePEc:eee:finana:v:74:y:2021:i:c:s1057521921000144
    DOI: 10.1016/j.irfa.2021.101671
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1057521921000144
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.irfa.2021.101671?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Buncic, Daniel & Gisler, Katja I.M., 2016. "Global equity market volatility spillovers: A broader role for the United States," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1317-1339.
    2. Ghysels, E. & Harvey, A. & Renault, E., 1995. "Stochastic Volatility," Papers 95.400, Toulouse - GREMAQ.
    3. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
    4. Rioja, Felix & Rios-Avila, Fernando & Valev, Neven, 2017. "Productivity during recessions with banking crises: Inter-Industry evidence," Economics Letters, Elsevier, vol. 152(C), pages 50-53.
    5. Hsiao-I Kuo & Chia-Lin Chang & Bing-Wen Huang & Chi-Chung Chen & Michael McAleer, 2009. "Estimating the Impact of Avian Flu on International Tourism Demand Using Panel Data," Tourism Economics, , vol. 15(3), pages 501-511, September.
    6. Martin S Eichenbaum & Sergio Rebelo & Mathias Trabandt, 2021. "The Macroeconomics of Epidemics [Economic activity and the spread of viral diseases: Evidence from high frequency data]," The Review of Financial Studies, Society for Financial Studies, vol. 34(11), pages 5149-5187.
    7. Bossaerts, P. & Ghysels, E. & Gourieroux, C., 1996. "Arbitrage-Based Pricing when Volatility is Stochastic," Cahiers de recherche 9615, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    8. Ho, Jerry C. & Qiu, Mei & Tang, Xiaojun, 2013. "Do airlines always suffer from crashes?," Economics Letters, Elsevier, vol. 118(1), pages 113-117.
    9. Andersen, Torben G. & Bollerslev, Tim & Huang, Xin, 2011. "A reduced form framework for modeling volatility of speculative prices based on realized variation measures," Journal of Econometrics, Elsevier, vol. 160(1), pages 176-189, January.
    10. 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.
    11. Efthyvoulou, Georgios, 2012. "The impact of financial stress on sectoral productivity," Economics Letters, Elsevier, vol. 116(2), pages 240-243.
    12. Robert J. Barro & José F. Ursúa & Joanna Weng, 2020. "The Coronavirus and the Great Influenza Pandemic: Lessons from the “Spanish Flu” for the Coronavirus’s Potential Effects on Mortality and Economic Activity," NBER Working Papers 26866, National Bureau of Economic Research, Inc.
    13. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
    14. João H. Gonçalves Mazzeu & Helena Veiga & Massimo B. Mariti, 2019. "Modeling and forecasting the oil volatility index," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(8), pages 773-787, December.
    15. Chkili, Walid, 2017. "Is gold a hedge or safe haven for Islamic stock market movements? A Markov switching approach," Journal of Multinational Financial Management, Elsevier, vol. 42, pages 152-163.
    16. Toya, Hideki & Skidmore, Mark, 2007. "Economic development and the impacts of natural disasters," Economics Letters, Elsevier, vol. 94(1), pages 20-25, January.
    17. Stephen J. Taylor, 1994. "Modeling Stochastic Volatility: A Review And Comparative Study," Mathematical Finance, Wiley Blackwell, vol. 4(2), pages 183-204, April.
    18. Ole E. Barndorff‐Nielsen & Neil Shephard, 2002. "Econometric analysis of realized volatility and its use in estimating stochastic volatility models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 253-280, May.
    19. Lahaye, Jerome & Shaw, Philip, 2014. "Can we reject linearity in an HAR-RV model for the S&P 500? Insights from a nonparametric HAR-RV," Economics Letters, Elsevier, vol. 125(1), pages 43-46.
    20. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    21. Fabienne Comte & Eric Renault, 1998. "Long memory in continuous‐time stochastic volatility models," Mathematical Finance, Wiley Blackwell, vol. 8(4), pages 291-323, October.
    22. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    23. Tiwari, Aviral Kumar & Aye, Goodness C. & Gupta, Rangan & Gkillas, Konstantinos, 2020. "Gold-oil dependence dynamics and the role of geopolitical risks: Evidence from a Markov-switching time-varying copula model," Energy Economics, Elsevier, vol. 88(C).
    24. Chuliá, Helena & Martens, Martin & Dijk, Dick van, 2010. "Asymmetric effects of federal funds target rate changes on S&P100 stock returns, volatilities and correlations," Journal of Banking & Finance, Elsevier, vol. 34(4), pages 834-839, April.
    25. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Ebens, Heiko, 2001. "The distribution of realized stock return volatility," Journal of Financial Economics, Elsevier, vol. 61(1), pages 43-76, July.
    26. Ashraf, Badar Nadeem, 2020. "Economic impact of government interventions during the COVID-19 pandemic: International evidence from financial markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    27. repec:aei:rpaper:1008560098 is not listed on IDEAS
    28. Andrew Papanicolaou & Ronnie Sircar, 2014. "A regime-switching Heston model for VIX and S&P 500 implied volatilities," Quantitative Finance, Taylor & Francis Journals, vol. 14(10), pages 1811-1827, October.
    29. Hoffman, S.J. & Silverberg, S.L., 2018. "Delays in global disease outbreak responses: Lessons from H1N1, Ebola, and Zika," American Journal of Public Health, American Public Health Association, vol. 108(3), pages 329-333.
    30. Efraim Benmelech & Nitzan Tzur-Ilan, 2020. "The Determinants of Fiscal and Monetary Policies During the Covid-19 Crisis," NBER Working Papers 27461, National Bureau of Economic Research, Inc.
    31. Humphries, John Eric & Neilson, Christopher A. & Ulyssea, Gabriel, 2020. "Information frictions and access to the Paycheck Protection Program," Journal of Public Economics, Elsevier, vol. 190(C).
    32. Li, Wenlan & Cheng, Yuxiang & Fang, Qiang, 2020. "Forecast on silver futures linked with structural breaks and day-of-the-week effect," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    33. Tse, Yiuman, 2001. "Index arbitrage with heterogeneous investors: A smooth transition error correction analysis," Journal of Banking & Finance, Elsevier, vol. 25(10), pages 1829-1855, October.
    34. František Čech & Jozef Baruník, 2017. "On the Modelling and Forecasting of Multivariate Realized Volatility: Generalized Heterogeneous Autoregressive (GHAR) Model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(2), pages 181-206, March.
    35. Zhang, Lingxiang, 2013. "Revisiting the empirics of inflation in China: A smooth transition error correction approach," Economics Letters, Elsevier, vol. 119(1), pages 68-71.
    36. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2016. "Exploiting the errors: A simple approach for improved volatility forecasting," Journal of Econometrics, Elsevier, vol. 192(1), pages 1-18.
    37. Todorova, Neda, 2017. "The asymmetric volatility in the gold market revisited," Economics Letters, Elsevier, vol. 150(C), pages 138-141.
    38. Nademi, Arash & Nademi, Younes, 2018. "Forecasting crude oil prices by a semiparametric Markov switching model: OPEC, WTI, and Brent cases," Energy Economics, Elsevier, vol. 74(C), pages 757-766.
    39. 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.
    40. Brian M. Lucey & Fergal A. O’Connor, 2013. "Do bubbles occur in the gold price? An investigation of gold lease rates and Markov Switching models," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 13(3), pages 53-63, September.
    41. Moore, Tomoe & Wang, Ping, 2007. "Volatility in stock returns for new EU member states: Markov regime switching model," International Review of Financial Analysis, Elsevier, vol. 16(3), pages 282-292.
    42. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    43. Caggiano, Giovanni & Castelnuovo, Efrem & Figueres, Juan Manuel, 2017. "Economic policy uncertainty and unemployment in the United States: A nonlinear approach," Economics Letters, Elsevier, vol. 151(C), pages 31-34.
    44. Audrino, Francesco & Sigrist, Fabio & Ballinari, Daniele, 2020. "The impact of sentiment and attention measures on stock market volatility," International Journal of Forecasting, Elsevier, vol. 36(2), pages 334-357.
    45. Cheikh, Nidhaleddine Ben & Zaied, Younes Ben & Chevallier, Julien, 2020. "Asymmetric volatility in cryptocurrency markets: New evidence from smooth transition GARCH models," Finance Research Letters, Elsevier, vol. 35(C).
    46. Bradley, Michael D. & Jansen, Dennis W., 2004. "Forecasting with a nonlinear dynamic model of stock returns and industrial production," International Journal of Forecasting, Elsevier, vol. 20(2), pages 321-342.
    47. Go Tamakoshi & Shigeyuki Hamori, 2014. "Greek sovereign bond index, volatility, and structural breaks," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 38(4), pages 687-697, October.
    48. Sumudu W. Watugala, 2019. "Economic uncertainty, trading activity, and commodity futures volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(8), pages 921-945, August.
    49. Salisu, Afees A. & Vo, Xuan Vinh, 2020. "Predicting stock returns in the presence of COVID-19 pandemic: The role of health news," International Review of Financial Analysis, Elsevier, vol. 71(C).
    50. Yudong Wang & Zhiyuan Pan & Chongfeng Wu, 2017. "Time‐Varying Parameter Realized Volatility Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(5), pages 566-580, August.
    51. Robert J. Barro & José F. Ursua & Joanna Weng, 2020. "The Coronavirus and the Great Influenza Epidemic - Lessons from the "Spanish Flu" for the Coronavirus's Potential Effects on Mortality and Economic Activity," CESifo Working Paper Series 8166, CESifo.
    52. Ciarreta, Aitor & Pizarro-Irizar, Cristina & Zarraga, Ainhoa, 2020. "Renewable energy regulation and structural breaks: An empirical analysis of Spanish electricity price volatility," Energy Economics, Elsevier, vol. 88(C).
    53. Sharif, Arshian & Aloui, Chaker & Yarovaya, Larisa, 2020. "COVID-19 pandemic, oil prices, stock market, geopolitical risk and policy uncertainty nexus in the US economy: Fresh evidence from the wavelet-based approach," International Review of Financial Analysis, Elsevier, vol. 70(C).
    54. Taylor, Nick, 2019. "Forecasting returns in the VIX futures market," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1193-1210.
    55. Llussá, Fernanda & Tavares, José, 2011. "Which terror at which cost? On the economic consequences of terrorist attacks," Economics Letters, Elsevier, vol. 110(1), pages 52-55, January.
    56. Ghoshray, Atanu, 2010. "Smooth transition effects in price transmission: The case of international wheat export prices," Economics Letters, Elsevier, vol. 106(3), pages 169-171, March.
    57. Ji, Qiang & Zhang, Dayong & Zhao, Yuqian, 2020. "Searching for safe-haven assets during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 71(C).
    58. Huang, Alex YiHou & Hu, Wen-Cheng, 2012. "Regime switching dynamics in credit default swaps: Evidence from smooth transition autoregressive model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1497-1508.
    59. Adam Blake & M. Thea Sinclair & Guntur Sugiyarto, 2003. "Quantifying the Impact of Foot and Mouth Disease on Tourism and the UK Economy," Tourism Economics, , vol. 9(4), pages 449-465, December.
    60. Robert J. Elliott & Katsumasa Nishide & Carlton‐James U. Osakwe, 2016. "Heston‐Type Stochastic Volatility with a Markov Switching Regime," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(9), pages 902-919, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Izzeldin, Marwan & Muradoğlu, Yaz Gülnur & Pappas, Vasileios & Petropoulou, Athina & Sivaprasad, Sheeja, 2023. "The impact of the Russian-Ukrainian war on global financial markets," International Review of Financial Analysis, Elsevier, vol. 87(C).
    2. Palandri, Alessandro, 2015. "Do negative and positive equity returns share the same volatility dynamics?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 486-505.
    3. Lyócsa, Štefan & Molnár, Peter & Výrost, Tomáš, 2021. "Stock market volatility forecasting: Do we need high-frequency data?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1092-1110.
    4. Hua, Jian & Manzan, Sebastiano, 2013. "Forecasting the return distribution using high-frequency volatility measures," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4381-4403.
    5. Papantonis, Ioannis & Rompolis, Leonidas & Tzavalis, Elias, 2023. "Improving variance forecasts: The role of Realized Variance features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1221-1237.
    6. Santos, Douglas G. & Candido, Osvaldo & Tófoli, Paula V., 2022. "Forecasting risk measures using intraday and overnight information," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    7. Asai, Manabu & McAleer, Michael & Medeiros, Marcelo C., 2012. "Modelling and forecasting noisy realized volatility," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 217-230, January.
    8. Ma, Feng & Wei, Yu & Huang, Dengshi & Chen, Yixiang, 2014. "Which is the better forecasting model? A comparison between HAR-RV and multifractality volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 171-180.
    9. Masato Ubukata & Toshiaki Watanabe, 2013. "Pricing Nikkei 225 Options Using Realized Volatility," Global COE Hi-Stat Discussion Paper Series gd12-273, Institute of Economic Research, Hitotsubashi University.
    10. Yusui Tang & Feng Ma & Yaojie Zhang & Yu Wei, 2022. "Forecasting the oil price realized volatility: A multivariate heterogeneous autoregressive model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4770-4783, October.
    11. Masato Ubukata & Toshiaki Watanabe, 2014. "Pricing Nikkei 225 Options Using Realized Volatility," The Japanese Economic Review, Japanese Economic Association, vol. 65(4), pages 431-467, December.
    12. Ma, Feng & Li, Yu & Liu, Li & Zhang, Yaojie, 2018. "Are low-frequency data really uninformative? A forecasting combination perspective," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 92-108.
    13. Koopman, Siem Jan & Jungbacker, Borus & Hol, Eugenie, 2005. "Forecasting daily variability of the S&P 100 stock index using historical, realised and implied volatility measurements," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 445-475, June.
    14. Bee, Marco & Dupuis, Debbie J. & Trapin, Luca, 2016. "Realizing the extremes: Estimation of tail-risk measures from a high-frequency perspective," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 86-99.
    15. Hiroyuki Kawakatsu, 2022. "Modeling Realized Variance with Realized Quarticity," Stats, MDPI, vol. 5(3), pages 1-25, September.
    16. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    17. Papantonis Ioannis & Tzavalis Elias & Agapitos Orestis & Rompolis Leonidas S., 2023. "Augmenting the Realized-GARCH: the role of signed-jumps, attenuation-biases and long-memory effects," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(2), pages 171-198, April.
    18. Aganin, Artem, 2017. "Forecast comparison of volatility models on Russian stock market," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 48, pages 63-84.
    19. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2014. "Realized volatility models and alternative Value-at-Risk prediction strategies," Economic Modelling, Elsevier, vol. 40(C), pages 101-116.
    20. Masato Ubukata & Toshiaki Watanabe, 2011. "Pricing Nikkei 225 Options Using Realized Volatility," IMES Discussion Paper Series 11-E-18, Institute for Monetary and Economic Studies, Bank of Japan.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finana:v:74:y:2021:i:c:s1057521921000144. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620166 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.