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Cited by 92Financial Risk and Volatility ModelingMarket Dynamics and VolatilityCOVID-19 Pandemic Impacts

The source of financial contagion and spillovers: An evaluation of the covid-19 pandemic and the global financial crisis

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Gunay, Samet, Can, Gokberk·2022·PLOS ONE
DOI 10.1371/journal.pone.0261835PMC PMC8759666
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Abstract

This study investigates the reaction of stock markets to the Covid-19 pandemic and the Global Financial Crisis of 2008 (GFC) and compares their influence in terms of risk exposures. The empirical investigation is conducted using the modified ICSS test, DCC-GARCH, and Diebold-Yilmaz connectedness analysis to examine financial contagion and volatility spillovers. To further reveal the impact of these two crises, the statistical features of tranquil and crisis periods under different time intervals are also compared. The test results show that although the outbreak’s origin was in China, the US stock market is the source of financial contagion and volatility spillovers during the pandemic, just as it was during the GFC. The propagation of shocks is considerably higher between developed economies compared to emerging markets. Additionally, the results show that the COVID-19 pandemic induced a more severe contagious effect and risk transmission than the GFC. The study provides an extensive examination of the COVID-19 pandemic and the GFC in terms of financial contagion and volatility spillovers. The results suggest the presence of strong co-movements of world stock markets with the US equity market, especially in periods of financial turmoil.

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  • Institutional asymmetries between developed and emerging economies increased the asymmetric effect of the crisis, exposing weaknesses in global financial governance.

    “Besides, institutional asymmetries between the developed and emerging economies increased the asymmetric effect of the crisis, exposing weaknesses in the global financial governance (Gunay & Can, 2022).”

    From The Interactions Between Political Economy and Global Financial Crises: A Case Study of the 2008 Global Recession (2026) · cites this paper as Gunay & Can, 2022

    The Conclusion (section 5; page unavailable) finds greater financial-contagion and spillover transmission among developed economies, supporting a difference in crisis effects. It does not establish that institutional asymmetries caused that difference or that the findings exposed weaknesses in global financial governance. (LLM, conf=0.86)

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Research works printed but not linked: 55

  1. [3]Pradhan RP. Development of stock market and economic growth: the G-20 evidence. Eurasian Econ Rev. 2018; 8: 161– 181. doi: 10.1007/s40822-018-0094-4 · DOI
  2. [4]Billio M, Caporin M. Market linkages, variance spillovers, and correlation stability: Empirical evidence of financial contagion. Comput Stat Data Anal. 2010; 54: 2443– 2458. doi: 10.1016/j.csda.2009.03.018 · DOI
  3. [5]Chun D, Cho H, Ryu D. Economic indicators and stock market volatility in an emerging economy. Econ Syst. 2020; 44: 100788. doi: 10.1016/j.ecosys.2020.100788 · DOI
  4. [6]Guo Y, Li P, Li A. Tail risk contagion between international financial markets during COVID-19 pandemic. Int Rev Financ Anal. 2021; 73: 101649. doi: 10.1016/j.irfa.2020.101649 · DOI
  5. [7]Milani F. Learning about the interdependence between the macroeconomy and the stock market. Int Rev Econ Financ. 2017; 49: 223– 242. doi: 10.1016/j.iref.2017.01.028 · DOI
  6. [8]Jebran K, Chen S, Ullah I, Mirza SS. Does volatility spillover among stock markets varies from normal to turbulent periods? Evidence from emerging markets of Asia. J Financ Data Sci. 2017; 3: 20– 30. doi: 10.1016/j.jfds.2017.06.001 · DOI
  7. [9]Cakan E, Doytch N, Upadhyaya KP. Does U.S. macroeconomic news make emerging financial markets riskier? Borsa Istanbul Rev. 2015; 15: 37– 43. doi: 10.1016/j.bir.2014.10.002 · DOI
  8. [10]Kim BH, Kim H, Lee BS. Spillover effects of the U.S. financial crisis on financial markets in emerging Asian countries. Int Rev Econ Financ. 2015; 39: 192– 210. doi: 10.1016/j.iref.2015.04.005 · DOI
  9. [13]Coşkun Y, Seven Ü, Ertuğrul HM, Ulussever T. Capital market and economic growth nexus: Evidence from Turkey. Cent Bank Rev. 2017; 17: 19– 29. doi: 10.1016/j.cbrev.2017.02.003 · DOI · Paper page
  10. [14]Aali-Bujari A, Venegas-Martínez F, Pérez-Lechuga G. Impact of the stock market capitalization and the banking spread in growth and development in Latin American: A panel data estimation with System GMM. Contaduria y Adm. 2017; 62: 1427– 1441. doi: 10.1016/j.cya.2017.09.005 · DOI
  11. [15]Belda PR. Transmission between Stock Markets and Financial Crisis: The Case of Spain. Estud Econ Apl. 2014; 32: 789– 812.
  12. [16]Amar A Ben, Belaid F, Youssef A Ben, Chiao B, Guesmi K. The unprecedented reaction of equity and commodity markets to COVID-19. Financ Res Lett. 2021; 38: 101853. doi: 10.1016/j.frl.2020.101853 PMC9761192 36569653 · DOI
  13. [17]Shahzad SJH, Bouri E, Kang SH, Saeed T. Regime specific spillover across cryptocurrencies and the role of COVID-19. Financ Innov. 2021; 7. doi: 10.1186/s40854-020-00210-4 PMC7786164 35024270 · DOI
  14. [18]Günay S, Can G, Ocak M. Forecast of China’s Economic Growth During the COVID-19 Pandemic: A MIDAS Regression Analysis. J Chinese Econ Foreign Trade Stud. 2021. doi: 10.1108/JCEFTS-08-2020-0053 · DOI
  15. [19]Yousfi M, Ben Zaied Y, Ben Cheikh N, Ben Lahouel B, Bouzgarrou H. Effects of the COVID-19 pandemic on the US stock market and uncertainty: A comparative assessment between the first and second waves. Technol Forecast Soc Change. 2021; 167. doi: 10.1016/j.techfore.2021.120710 PMC9753217 36536660 · DOI
  16. [20]Corbet S, Larkin C, Lucey B. The contagion effects of the COVID-19 pandemic: Evidence from gold and cryptocurrencies. Financ Res Lett. 2020; 35: 101554. doi: 10.1016/j.frl.2020.101554 PMC7224668 38620241 · DOI
  17. [21]Szczygielski JJ, Bwanya PR, Charteris A, Brzeszczyński J. The only certainty is uncertainty: An analysis of the impact of COVID-19 uncertainty on regional stock markets. Financ Res Lett. 2021; 101945. doi: 10.1016/j.frl.2021.101945 33519309 PMC7835099 · DOI
  18. [22]Sharif A, Aloui C, Yarovaya L. COVID-19 pandemic, oil prices, stock market, geopolitical risk and policy uncertainty nexus in the US economy: Fresh evidence from the wavelet-based approach. Int Rev Financ Anal. 2020; 70: 101496. doi: 10.1016/j.irfa.2020.101496 PMC7227524 38620230 · DOI
  19. [23]Akhtaruzzaman M, Boubaker S, Sensoy A. Financial contagion during COVID–19 crisis. Financ Res Lett. 2021; 38: 101604. doi: 10.1016/j.frl.2020.101604 32837363 PMC7245292 · DOI
  20. [24]Abuzayed B, Bouri E, Al-Fayoumi N, Jalkh N. Systemic risk spillover across global and country stock markets during the COVID-19 pandemic. Econ Anal Policy. 2021; 71: 180– 197. doi: 10.1016/j.eap.2021.04.010 · DOI
  21. [25]Yong HHA, Laing E. Stock market reaction to COVID-19: Evidence from U.S. Firms’ International exposure. Int Rev Financ Anal. 2021; 76: 101656. doi: 10.1016/j.irfa.2020.101656 PMC9759750 36569818 · DOI
  22. [26]Banerjee AK. Futures market and the contagion effect of COVID-19 syndrome. Financ Res Lett. 2021; 102018. doi: 10.1016/j.frl.2021.102018 34803533 PMC8596880 · DOI
  23. [27]Balcilar M, Demirer R, Hammoudeh S. Quantile relationship between oil and stock returns: Evidence from emerging and frontier stock markets. Energy Policy. 2019; 134: 110931. doi: 10.1016/j.enpol.2019.110931 · DOI
  24. [28]Gunay S. Comparing COVID-19 with the GFC: A shockwave analysis of currency markets. Res Int Bus Financ. 2021; 56: 101377. doi: 10.1016/J.RIBAF.2020.101377 PMC9756040 36540770 · DOI
  25. [29]Huang YS, Chen CR, Kato I. Different strokes by different folks: The dynamics of hedge fund systematic risk exposure and performance. Int Rev Econ Financ. 2017; 48: 367– 388. doi: 10.1016/j.iref.2017.01.001 · DOI
  26. [30]Yoshino N, Taghizadeh-Hesary F, Otsuka M. Covid-19 and Optimal Portfolio Selection for Investment in Sustainable Development Goals. Financ Res Lett. 2021; 38: 101695. doi: 10.1016/j.frl.2020.101695 32837379 PMC7354763 · DOI
  27. [31]Bouri E, Cepni O, Gabauer D, Gupta R. Return connectedness across asset classes around the COVID-19 outbreak. Int Rev Financ Anal. 2021; 73: 101646. doi: 10.1016/j.irfa.2020.101646 · DOI
  28. [32]Raiher AP, Stege AL, Do Carmos ASS. COVID-19 and employment in Brazilian microregions: A spatial analysis. Stud Appl Econ. 2021; 39. doi: 10.25115/EEA.V39I2.3709 · DOI
  29. [33]Shahzad SJH, Bouri E, Kristoufek L, Saeed T. Impact of the COVID-19 outbreak on the US equity sectors: Evidence from quantile return spillovers. Financ Innov. 2021; 7. doi: 10.1186/s40854-021-00228-2 PMC7920753 35024275 · DOI
  30. [34]Bouri E, Naeem MA, Nor SM, Mbarki I, Saeed T. Government responses to COVID-19 and industry stock returns. Econ Res Istraz. 2021; 1– 24. doi: 10.1080/1331677X.2021.1929374 · DOI
  31. [35]Gunay S, Kurtulmuş BE. COVID-19 social distancing and the US service sector: What do we learn? Res Int Bus Financ. 2021; 56: 101361. doi: 10.1016/J.RIBAF.2020.101361 PMC9756044 36540768 · DOI
  32. [36]Shahzad SJH, Naeem MA, Peng Z, Bouri E. Asymmetric volatility spillover among Chinese sectors during COVID-19. Int Rev Financ Anal. 2021; 75: 101754. doi: 10.1016/j.irfa.2021.101754 PMC9760082 36568735 · DOI
  33. [37]Mensi W, Maitra D, Vo XV, Kang SH. Asymmetric volatility connectedness among main international stock markets: A high frequency analysis. Borsa Istanbul Rev. 2021. doi: 10.1016/j.bir.2020.12.003 · DOI
  34. [38]Gazdar K, Cherif M. Institutions and the finance-growth nexus: Empirical evidence from MENA countries. Borsa Istanbul Rev. 2015; 15: 137– 160. doi: 10.1016/j.bir.2015.06.001 · DOI · Paper page
  35. [39]Chevallier J. COVID-19 Pandemic and Financial Contagion. J Risk Financ Manag. 2020; 13: 309. doi: 10.3390/jrfm13120309 · DOI
  36. [40]Aslam F, Mohmand YT, Ferreira P, Memon BA, Khan M, Khan M. Network analysis of global stock markets at the beginning of the coronavirus disease (Covid-19) outbreak. Borsa Istanbul Rev. 2020; 20: S49– S61. doi: 10.1016/j.bir.2020.09.003 · DOI
  37. [42]Bollerslev T. Modelling the Coherence in Short-Run Nominal Exchange Rates: A Multivariate Generalized Arch Model. Rev Econ Stat. 1990; 72: 498. doi: 10.2307/2109358 · DOI
  38. [43]Diebold FX, Yilmaz K. Better to give than to receive: Predictive directional measurement of volatility spillovers. Int J Forecast. 2012; 28: 57– 66. doi: 10.1016/J.IJFORECAST.2011.02.006 · DOI
  39. [44]Diebold FX, Yilmaz K. Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets. Econ J. 2009; 119: 158– 171. doi: 10.1111/J.1468-0297.2008.02208.X · DOI
  40. [45]Koop G, Pesaran MH, Potter SM. Impulse response analysis in nonlinear multivariate models. J Econom. 1996; 74: 119– 147. doi: 10.1016/0304-4076(95)01753-4 · DOI
  41. [46]Pesaran HH, Shin Y. Generalized impulse response analysis in linear multivariate models. Econ Lett. 1998; 58: 17– 29. doi: 10.1016/S0165-1765(97)00214-0 · DOI
  42. [47]Corsetti G, Pesenti P, Roubini N. What caused the Asian currency and financial crisis? Japan World Econ. 1999; 11: 305– 373. doi: 10.1016/S0922-1425(99)00019-5 · DOI
  43. [48]Chiodo AJ, Owyang MT. A Case Study of a Currency Crisis: The Russian Default of 1998. Review. 2002; 84. doi: 10.20955/R.84.7-18 · DOI
  44. [49]Gulzar S, Mujtaba Kayani G, Xiaofeng H, Ayub U, Rafique A. Financial cointegration and spillover effect of global financial crisis: a study of emerging Asian financial markets. http://www.tandfonline.com/action/authorSubmission?journalCode=rero20&page=instructions. 2019; 32: 187– 218.
  45. [50]Akhtaruzzaman M, Abdel-Qader W, Hammami H, Shams S. Is China a source of financial contagion? Financ Res Lett. 2021; 38: 101393. doi: 10.1016/J.FRL.2019.101393 PMC7245292 32837363 · DOI
  46. [51]Karoglou M. Breaking down the non-normality of stock returns. Eur J Financ. 2010; 16: 79– 95. doi: 10.1080/13518470902872343 · DOI
  47. [52]Cross J, Poon A. Forecasting structural change and fat-tailed events in Australian macroeconomic variables. Econ Model. 2016; 58: 34– 51. doi: 10.1016/J.ECONMOD.2016.04.021 · DOI
  48. [54]Leiss M, Nax HH, Sornette D. Super-exponential growth expectations and the global financial crisis. J Econ Dyn Control. 2015; 55: 1– 13. doi: 10.1016/J.JEDC.2015.03.005 · DOI
  49. [55]Kapetanios G. Unit-root testing against the alternative hypothesis of up to m structural breaks. J Time Ser Anal. 2005; 26: 123– 133. doi: 10.1111/J.1467-9892.2005.00393.X · DOI
  50. [56]Sansó A, Aragó V, Carrion JL. Testing for changes in the unconditional variance of financial time series. Rev Econ Financ. 2004; 4: 32– 53.
  51. [57]Inclán C, Tiao GC. Use of Cumulative Sums of Squares for Retrospective Detection of Changes of Variance. J Am Stat Assoc. 1994; 89: 913– 923. doi: 10.1080/01621459.1994.10476824 · DOI
  52. [58]Chen M, Hong Y. Has Chinese Stock Market Become Efficient? Evidence from a New Approach. LNCS. 2003; 2658: 90– 98.
  53. [59]Li XM. China: Further Evidence on the Evolution of Stock Markets in Transition Economies. Scott J Polit Econ. 2003; 50: 341– 358. doi: 10.1111/1467-9485.5003006 · DOI
  54. [60]Quintos C, Fan Z, Philips PCB. Structural Change Tests in Tail Behaviour and the Asian Crisis. Rev Econ Stud. 2001; 68: 633– 663. doi: 10.1111/1467-937X.00184 · DOI
  55. [61]Gunay S, Bakry W, Al-Mohamad S. The Australian Stock Market’s Reaction to the First Wave of the COVID-19 Pandemic and Black Summer Bushfires: A Sectoral Analysis. J Risk Financ Manag 2021, Vol 14, Page 175. 2021;14: 175. doi: 10.3390/JRFM14040175 · DOI

Cited by

Sorted by citations

Authors
Gunay, S., & Can, G.
Venue
PLOS ONE
Publisher
Public Library of Science (PLoS)
Published
2022-01-14
Volume
17
Issue
1
Pages
e0261835
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0261835
PMC
PMC8759666
OpenAlex
W4206248381
Cited by
92
References
2
Citations by year
2026: 12 · 2025: 18 · 2024: 27 · 2023: 25 · 2022: 9 · 2020: 1
FWCI
13.71
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Social Sciences › Economics, Econometrics and Finance › Finance › Financial Risk and Volatility Modeling
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Market Dynamics and Volatility
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › COVID-19 Pandemic Impacts
Keywords
financial contagion, volatility spillovers, COVID-19 pandemic, 2008 financial crisis, stock market co-movement, risk transmission, emerging markets, developed countries, shock wave propagation
MeSH terms
COVID-19, China, Commerce, Humans, Investments, United States, Pandemics

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