Keywords
COVID-19 pandemic
DCC model
emerging markets
financial contagion
JEL: C51, C58, G15
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Abstract
This paper investigates financial contagion between the US and emerging European markets during recent turbulent periods, including the COVID-19 pandemic, the Russia-Ukraine war, the US presidential election, and changes in US tariff policy in 2025. The S&P 500 and STOXX Europe 50 indices are employed to capture global and regional factors affecting emerging markets in Europe. Using daily returns from January 2013 to April 2025, I conduct a structural break test and endogenously determine the start date of the COVID-19 pandemic. This approach avoids the arbitrary selection of crisis dates, allowing event timings and their market impact to be determined empirically. The paper then estimates returns models for individual emerging markets using the Bayesian approach. The results indicate that emerging countries’ stock markets are more affected by regional factors than the US market. Moreover, there is a significant increase in the influence of the STOXX Europe 50 on emerging markets during periods of turmoil. Finally, the paper evaluates whether there is contagion across markets based on Bayesian estimation in the dynamic conditional correlation DCC model. To account for the heavy tails associated with financial returns, this paper assumes that the corresponding error terms follow a skewed Student’s t-distributions. The findings also confirm stronger evidence of contagion from regional factors to the examined emerging markets during the episodes of market turmoil. Additionally, the results indicate interdependence, but no contagion, from the US market to emerging European markets.
References
Adesanya, O. (2020). Crisis date identification and testing for contagion across stock markets with regime switching models using Bayesian estimation approach. SSRN. https://ssrn.com/abstract=3618011
Agyei, S. K. (2023). Emerging markets equities’ response to geopolitical risk: Time-frequency evidence from the Russian-Ukrainian conflict era. Heliyon, 9(2).
Akhtaruzzaman, M., Boubaker, S., Chiah, M., & Angel Zhong. (2021). COVID−19 and oil price risk exposure. Finance Research Letters, 42, 101882.
Akhtaruzzaman, M., Sensoy, A., & Corbet, S. (2019). The influence of bitcoin on portfolio diversification and design. Finance Research Letters, 101344.
Deniz, E. & Elif, E. (2021). The Impact of COVID-19 on the Financial Contagion of Real Economy: A Sectoral Analysis. In B. Akkaya, K. Jermsittiparsert, M. A. Malik, & Y. Kocyigit (Eds.), Emerging trends in and strategies for industry 4.0 during and beyond COVID-19 (pp. 101–116). De Gruyter.
Akyildirim, E., Corbet, S., Katsiampa, P., Kellard, N., & Sensoy, A. (2020). The development of bitcoin futures: Exploring the interactions between cryptocurrency derivatives. Finance Research Letters, 34, 101234.
Allen, F., & Gale, D. (2000). Financial contagion. Journal of Political Economy, 108(1), 1–33.
Aloui, R., Aïssa, M., & Nguyen, D. (2011). Global financial crisis, extreme interdependences, and contagion effects: The role of economic structure? Journal of Banking & Finance, 35(1), 130–141.
Amar, A. B., Hachicha, N., & Halouani, N. (2021). Is there a shift contagion among stock markets during the COVID-19 crisis? Further insights from TYDL causality test. International Review of Applied Economics, 35(2), 188–209.
Ardia, D. (2006). Bayesian estimation of the GARCH(1, 1) model with normal innovations. Student 5, 3(4), 283–298
Bai, J., & Perron, P. (2003). Computation and analysis of multiple structural change models. Journal of Applied Econometrics, 18, 1–22.
Baker, S., Bloom, N., Davis, S., Kost, K., Sammon, M., & Viratyosin, T. (2020). The unprecedented stock market impact of COVID-19. NBER Working paper, 26945. https://www.nber.org/papers/w26945.
Baur, D. G. (2012). Financial contagion and the real economy. Journal of Banking & Finance, 36, 2680–2692.
Bauwens, L., & Laurent, S. (2005). A new class of multivariate skew densities, with application to generalized autoregressive conditional heteroscedasticity models. Journal of Business & Economic Statistics, 23(3), 346–354.
Bekaert, G., & Ang, A. (1999). International asset allocation with time-varying correlations. NBER Working Paper No. w7056. SSRN. https://ssrn.com/abstract=227422
Bekaert, G., & Mehl, A. (2019). On the global financial market integration “swoosh” and the trilemma. Journal of International Money and Finance, 94, 227–245.
Bekaert, G., Ehrmann, M., Fratzscher, M., & Mehl, A. (2014). The global crisis and equity market contagion. The Journal of Finance, 69, 2597–2649.
Bekiros, S. D. (2014). Contagion, decoupling and the spillover effects of the US financial crisis: Evidence from the BRIC markets. International Review of Financial Analysis, 33, 58–69.
Belaid, F., Ben Amar, A., Goutte, S., & Guesmi, K. (2021). Emerging and advanced economies markets behaviour during the COVID-19 crisis era. International Journal of Finance and Economics, 28(2), 1563–1581.
Bernardo, J. M. (2011). Philosophy of statistics, modern Bayesian inference: Foundations and objective methods. In M. R. Prasanta & S. Bandyopadhyay (Eds.), Handbook of the philosophy of science (pp. 263–306). North-Holland.
Bissoondoyal-Bheenick, E., Hung, D., Xiaolu, H., & Angle, Z. (2021). Learning from SARS: Return and volatility connectedness in COVID-19. Finance Research Letters, 41, 101796.
Bittlingmayer, G. (1998). Output, stock volatility, and political uncertainty in a natural experiment: Germany, 1880–1940. Journal of Finance, 53(6), 2243–2257.
Bloom, E., Wit, V. d., & Jose, M. J.-S. (2005). Potential economic impact of an avian flu pandemic on Asia. ERD Policy Briefs, Asia Development Bank. https://scispace.com/pdf/potential-economic-impact-of-an-avian-flu-pandemic-on-asia-4uev5xqjcb.pdf
Carrieri, F., Errunza, V., & Hogan, K. (2007). Characterizing world market integration through time. Journal of Financial and Quantitative Analysis, 42(04), 915–940. https://www.jstor.org/stable/27647329
Celık, S. (2012). The more contagion effect on emerging markets: The evidence of DCC-GARCH model. Economic Modelling, 29(5), 1946–1959.
Chen, X., Hao, A., & Li, Y. (2020). The impact of financial contagion on real economy: An empirical research based on combination of complex network technology and spatial econometrics model. PLoS ONE, 15(3).
Chiṭu, L., & Quint, D. (2018). Emerging market vulnerabilities – A comparison with previous crises. ECB Economic Bulletin, 8. https://www.ecb.europa.eu/press/economic-bulletin/focus/2018/html/ecb.ebbox201808_01.en.html
Chou, J., & Kuo, N.-F. (2004). Potential impacts of the SARS outbreak on Taiwan’s economy. Asian Economic Papers, 3(1), 84–112. https://scispace.com/pdf/potential-impacts-of-the-sarsoutbreak-on-taiwan-s-economy-1dvw51hemd.pdf
Claessens, S., & Forbes, K. (2013). International financial contagion. Springer Science & Business Media.
Conlon, T., Corbet, S., & McGee, R. (2020). Are cryptocurrencies a safe haven for equity markets? An international perspective from the COVID-19 pandemic. Research in International Business and Finance, 54.
Corbet, S., C., L., & B., L. (2020). The contagion effects of the COVID-19 pandemic: Evidence from gold and cryptocurrencies. Finance Research Letters, 35.
Das, S. R., & Uppal, R. (2004). Systemic risk and international portfolio choice. The Journal of Finance, 59(6), 2809–2834. https://www.jstor.org/stable/3694790
Dungey, M., & Gajurel, D. (2014). Equity market contagion during the global financial crisis: Evidence from the world’s eight largest economies. Economic Systems, 38(2), 161–177.
Engle, R. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business & Economic Statistics, 20(3), 339–350.
Fioruci, J. A., Ehlers, R. S., & Filho, M. G. (2014). Bayesian multivariate GARCH models with dynamic correlations and asymmetric error distributions. Journal of Applied Statistics, 41(2), 320–331.
Forbes, K. J., & Rigobon, R. (2002). No contagion, only interdependence: Measuring stock market comovements. Journal of Finance, 57(5), 2223–2261. https://www.jstor.org/stable/3094510
Gunay, S. (2021). Comparing COVID-19 with the GFC: A shockwave analysis of currency markets. Research in International Business and Finance, 56.
Guo, F., Chen, C., & Huang, Y. (2011). Markets contagion during financial crisis: A regime-switching approach. International Review of Economics & Finance, 20(1), 95–109.
Hardouvelis, G., Malliaropulos, D., & Priestley, R. (2006). EMU and European equity market integration. Journal of Business, 79, 365–392.
Hwang, E., Min, H.-G., Kim, B.-H., & Kim, H. (2013). Determinants of stock market comovements among US and emerging economies during the US financial crisis. Economic Modelling, 35, 338–348.
Iloskics, Z., Sebestyén, T., & Braun, E. (2021). Shock propagation channels behind the global economic contagion network. The role of economic sectors and the direction of trade. PloS ONE, 16(10).
International Monetary Fund. (2020). Global financial stability report: Bridge to recovery.
Kenourgios, D., & Dimitriou, D. (2015). Contagion of the global financial crisis and the real economy: A regional analysis. Economic Modelling, 44, 283–293.
Kiss, G. D., Alipanah, S., & Sallai, D. (2024). The relevance of network effects on the Central-Eastern European (CEE) stock market indices, 2008 Q1-2022 Q1. Regional Statistics, 14(2).
Kumari, V., Kumar, G., & Pandey, D. K. (2023). Are the European Union stock markets vulnerable to the Russia–Ukraine war? Journal of Behavioral and Experimental Finance, 37.
Lenart, Ł., Pajor, A., & Kwiatkowski, Ł. (2021). A locally both leptokurtic and fat-tailed distribution with application in a Bayesian Stochastic Volatility Model. Entropy, 23(6), 689.
Ligocká, M. (2023). The relationship between macroeconomic variables and stock market indices: Evidence from Central and Eastern European countries. Eastern Journal of European Studies, 14(2), 76–107.
Luchtenberg, K. F., & Vu, Q. V. (2015). The 2008 financial crisis: Stock market contagion and its determinants. Research in International Business and Finance, 33, 178–203.
Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77–91.
McKibbin, W. J., & Fernando, R. (2020). The global macroeconomic impacts of COVID-19: Seven scenarios. CAMA Working Paper No. 19/2020. SSRN.
Modrzejewska, A., & Pajor, A. (2017). The short-term relationships among the US, German and Greek bond markets in times of financial crises: A Bayesian analysis of exogeneity in the VAR-SV model. Argumenta Oeconomica, 1(38), 257–283. https://www.dbc.wroc.pl/dlibra/publication/40517/edition/36710
Mokrzycka, J. (2019). Bayesian comparison of bivariate Copula-GARCH and MGARCH Models. Central European Journal of Economic Modelling and Econometrics, 11, 47–71. https://journals.pan.pl/Content/112902/PDF/mainFile.pdf
Mollah, S., Quoreshi, A., & Zafirov, G. (2016). Equity market contagion during global financial and Eurozone crises: Evidence from a dynamic correlation analysis. Journal of International Financial Markets, Institutions and Money, 41, 151–167.
Muth, C., Oravecz, Z., & Gabry, J. (2018). User-friendly Bayesian regression modeling: A tutorial with rstanarm and shinystan. The Quantitative Methods for Psychology, 14(2), 99–119.
Nguyen, T. N., Phan, T. K., & Nguyen, T. L. (2022). Financial contagion during Global Financial Crisis and Covid-19 pandemic: The evidence from DCC–Garch Model. Cogent Economics & Finance, 10(1).
Okorie, D., & Lin, B. (2021). Stock markets and the COVID-19 fractal contagion effects. Finance Research Letters, 38.
Osiewalski, J., & Pajor, A. (2019). On sensitivity of inference in Bayesian MSF-MGARCH Models. Central European Journal of Economic Modelling and Econometric, 11, 173–197.
Osiewalski, J., & Pipień, M. (2005). Bayesian analysis of dynamic conditional correlation using Bivariate GARCH Models. Acta Universitatis Lodziensis. Folia Oeconomica, 192, 213–227. http://hdl.handle.net/11089/17944
Osiewalski, J., Wróblewska, J., & Makieła, K. (2020). Bayesian comparison of production function-based and time-series GDP models. Empirical Economics, 58, 1355–1380.
Pajor, A., & Wróblewska, J. (2017). VEC-MSF models in Bayesian analysis of short- and longrun relationships. Studies in Nonlinear Dynamics and Econometrics, 21(3).
Permai, S. D., & Tanty, H. (2018). Linear regression model using Bayesian approach for energy performance of residential building. Procedia Computer Science, 135, 671–677.
Pesaran, B., & Pesaran, M. H. (2007). Modelling volatilities and conditional correlations in futures markets with a multivariate t distribution. Cambridge Working Papers in Economics 0734, University of Cambridge. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1000888
Ruiz-Tagle, E. F. (2000). Financial markets and globalization: The perspective of Emerging Economies. In J. A. Ocampo, S. Zamagni, R. Ffrench-Davis & C. Pietrobelli (Eds.), Financial globalization and the Emerging Economies (pp. 31–37). The Economic Commission for Latin America and the Caribbean (ECLAC) and the International Jacques Maritain Institute. https://repositorio.cepal.org/server/api/core/bitstreams/051e2174-4a97-4dda-98eba6e3a4d980c5/content
Samarakoon, L. (2011). Stock market interdependence, contagion, and the U.S. financial crisis: The case of emerging and frontier markets. Journal of International Financial Markets, Institutions and Money, 21(5), 724–742.
Schwarz, G. E. (1978). Estimating the dimension of a model. Annals of Statistics, 6(2), 461–464.
Smith, R. D. (2006). Responding to global infectious disease outbreaks: Lessons from SARS on the role of risk perception, communication and management. Social Science and Medicine, 63(12), 3113–3123.
So, M., Chu, A., & Chan, T. (2021). Impacts of the COVID-19 pandemic on financial market connectedness. Finance Research Letters, 38.
Stiglitz, J. (1998). Distinguished lecture on economics in government: The private uses of public interest: Incentives and institutions. Journal of Economic Perspectives, 12(2), 3–22.
Țilică, E. V. (2021). Financial contagion patterns in individual economic sectors: The day-of-the-week effect from the Polish, Russian and Romanian markets. Journal of Risk and Financial Management, 14(9), 1–28.
Vo, D.-V. (2019). Contagion in the global banking system during the U.S and eurozone crisis. Lund University.
Voronkova, S. (2004). Equity market integration in Central European emerging markets: A cointegration analysis with shifting regimes. International Review of Financial Analysis, 13(5), 633–647.
Wróblewska, J., & Pajor, A. (2019). One-period joint forecasts of Polish inflation, unemployment and interest rate using Bayesian VEC-MSF Models. Central European Journal of Economic Modelling and Econometrics, 1, 23–45.
Yarovaya, L., Brzeszczynski, J., Goodell, J. W., Lucey, B. M., & Lau, C. K. (2020). Rethinking financial contagion: Information transmission mechanism during the COVID-19 pandemic. Journal of International Financial Markets, Institutions and Money, 79, 101589.
Yousfi, M., Zaied, Y. B., Cheikh, N. B., Lahouel, B. B., & Bouzgarrou, H. (2021). Effects of the COVID-19 pandemic on the US stock market and uncertainty: A comparative assessment between the first and second waves. Technological Forecasting and Social Change, 167, 120710.
Zeileis, A., Kleiber, C., Kramer, W., & Hornik, K. (2004). Testing and dating of structural changes in practice. Computational Statistics and Data Analysis, 44(1–2), 109–123.
Zhang, B., Li, X., & Yu, H. (2013). Has recent financial crisis changed permanently the correlations between BRICS and developed stock markets? North American Journal of Economics and Finance, 26, 725–738.
Zhang, D., Min H., & Qiang, J. (2020). Financial markets under the global pandemic of COVID-19. Finance Research Letters, 36, 101528.
Zyznarska-Dworczak, B. (2018). The development perspectives of sustainable management accounting in Central and Eastern European countries. Sustainability, 10(5).
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