Connectivity between the Latin American and U.S. stock markets in the presence of the Covid-19 pandemic
DOI:
https://doi.org/10.5902/1983465969467Keywords:
Stock markets, Dynamic connectedness, COVID-19 pandemic, TVP-VAR model, Latin AmericanAbstract
Objective - This paper aims to revisit the relationship between the Latin American and U.S. stock markets during the Covid-19 pandemic.
Methodology- The dynamic connectivity between these markets was estimated by implementing the time-varying VAR model (TVP-VAR) for daily data from January 2010 to June 2021.
Results - There are three main results. First, although spillovers from each market accounted for most of their variance, exchanges were not entirely independent of each other. Second, the U.S. and Brazil were net transmitters of spillovers, while Argentina and Chile were net receivers. Finally, the magnitude of net spillovers is not high enough to characterize a contagion effect.
Practical implications - The inclusion of Latin American stock markets in the scope of Covid-19 studies is an important contribution to the literature that often neglects Latin American markets in its samples.
Originality - The study of the connection between markets in the presence of Covid-19 differs from most that focus exclusively on the impact of Covid-19. Understanding the relationship between Latin American and U.S. markets in the presence of a crisis unlike any that has occurred before can help investors in their investment strategies and policymakers, governments, and monetary authorities interested in the integration or disintegration between markets.
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References
Akhtaruzzaman, M., Boubaker, S., & Sensoy, A. (2021). Financial contagion during COVID – 19 crisis. Finance Research Letters, 38(January), 1–20.
Alvarez, R. P., & Harris, P. R. (2020). Covid-19 in latin america: Challenges and opportunities. Revista Chilena de Pediatria, 91(2), 179–182. https://doi.org/10.32641/rchped.vi91i2.2157
Antonakakis, N., Gabauer, D., & Gupta, R. (2019). International monetary policy spillovers: Evidence from a time-varying parameter vector autoregression. International Review of Financial Analysis, 65(July), 101382. https://doi.org/10.1016/j.irfa.2019.101382
Ashraf, B. N. (2020). Stock markets’ reaction to COVID-19: Cases or fatalities? Research in International Business and Finance, 54, 101249. https://doi.org/10.1016/j.ribaf.2020.101249
Azimli, A. (2020). The impact of COVID-19 on the degree of dependence and structure of risk-return relationship: A quantile regression approach. Finance Research Letters, 36. https://doi.org/10.1016/j.frl.2020.101648
Bai, Y. (2014). Cross-border sentiment: An empirical analysis on EU stock markets. Applied Financial Economics, 24(4), 259–290. https://doi.org/10.1080/09603107.2013.864035
Baker, S. R., Bloom, N., Davis, S. J., & Terry, S. J. (2020). Covid-Induced Economic Uncertainty. Ssrn. https://doi.org/10.3386/w26983
Bekaert, G., Ehrmann, M., Fratzscher, M., & Mehl, A. (2011). Global Crises and Equity Market Contagion. ECB Working Paper Serices, 1381. Retrieved from https://www.ecb.europa.eu/pub/pdf/scpwps/ecbwp1381.pdf
Bosch, J. C., Eckard, E. W., & Singal, V. (1998). The competitive impact of air crashes: Stock market evidence. Journal of Law and Economics, 41(2), 503–519. https://doi.org/10.1086/467399
Cardona, L., Gutiérrez, M., & Agudelo, D. A. (2017). Volatility transmission between US and Latin American stock markets: Testing the decoupling hypothesis. Research in International Business and Finance, 39, 115–127. https://doi.org/10.1016/j.ribaf.2016.07.008
Cavallo, E., Galiani, S., Noy, I., & Pantano, J. (2013). Catastrophic natural disasters and economic growth. Review of Economics and Statistics, 95(5), 1549–1561. https://doi.org/10.1162/REST_a_00413
Cepoi, C. O. (2020). Asymmetric dependence between stock market returns and news during COVID-19 financial turmoil. Finance Research Letters, 36, 101658. https://doi.org/10.1016/j.frl.2020.101658
Chuliá, H., Guillén, M., & Uribe, J. M. (2017). Spillovers from the United States to Latin American and G7 stock markets: A VAR quantile analysis. Emerging Markets Review, 31, 32–46. https://doi.org/10.1016/j.ememar.2017.01.001
Corbet, S., Hou, Y., Hu, Y., Lucey, B., & Oxley, L. (2021). Aye Corona! The contagion effects of being named Corona during the COVID-19 pandemic. Finance Research Letters, 38(May), 101591. https://doi.org/10.1016/j.frl.2020.101591
Davidson, S. N. (2020). Interdependence or contagion: A model switching approach with a focus on Latin America. Economic Modelling, 85(March), 166–197. https://doi.org/10.1016/j.econmod.2019.05.015
Dickey, D. A., & Fuller, W. A. (1981). Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root. Econometrica, 49(4), 1057–1072.
Diebold, F. X., & Yilmaz, K. (2014). On the network topology of variance decompositions: Measuring the connectedness of financial firms. Journal of Econometrics, 182(1), 119–134. https://doi.org/10.1016/j.jeconom.2014.04.012
Dimitriou, D., Kenourgios, D., & Simos, T. (2013). Global financial crisis and emerging stock market contagion: A multivariate FIAPARCH-DCC approach. International Review of Financial Analysis, 30, 46–56. https://doi.org/10.1016/j.irfa.2013.05.008
Dornbusch, R. (1976). Expectations and Exchange Rate Dynamics. Journal of Political Economy, 84(61), 1167–1176. https://doi.org/10.1016/0261-5606(84)90029-9
Fan, V. Y., Jamison, D. T., & Summers, L. H. (2018). Pandemic risk: How large are the expected losses? Bulletin of the World Health Organization, 96(2), 129–134. https://doi.org/10.2471/BLT.17.199588
Goodell, J. W. (2020). COVID-19 and finance: Agendas for future research. Finance Research Letters, 35(April). https://doi.org/10.1016/j.frl.2020.101512
Guo, L., Ren, L., Yang, S., Xiao, M., Chang, D., Yang, F., … Wang, J. (2020). Profiling early humoral response to diagnose novel coronavirus disease (COVID-19). Clinical Infectious Diseases, 71(15), 778–785. https://doi.org/10.1093/cid/ciaa310
Hasan, M. B., Mahi, M., Hassan, M. K., & Bhuiyan, A. B. (2021). Impact of COVID-19 pandemic on stock markets: Conventional vs. Islamic indices using wavelet-based multi-timescales analysis. North American Journal of Economics and Finance, 58(February), 101504. https://doi.org/10.1016/j.najef.2021.101504
Karolyi, G. A., & Martell, R. (2011). Terrorism and the Stock Market. SSRN Electronic Journal, (June). https://doi.org/10.2139/ssrn.823465
King, M. A., & Wadhwani, S. (1990). Transmission of Volatility between Stock Markets. The Review of Financial Studies, 3(1), 5–33.
Koop, G., & Korobilis, D. (2014). A new index of financial conditions. European Economic Review, 71, 101–116. https://doi.org/10.1016/j.euroecorev.2014.07.002
Kwiatkowski, D., Phillips, P. C. B., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root. How sure are we that economic time series have a unit root? Journal of Econometrics, 54(1–3), 159–178. https://doi.org/10.1016/0304-4076(92)90104-Y
Macciocchi, D., Lanini, S., Vairo, F., Zumla, A., Figueiredo, L. T. M., Lauria, F. N., … Ippolito, G. (2016). Short-term economic impact of the Zika virus outbreak. New Microbiologica, 39(4), 287–289.
Manzi, R. H. D., & Viola, E. (2020). A desaceleração da economia da China e a transição para um “novo normal” no século 21. Carta Internacional, 15(2), 5–27. https://doi.org/10.21530/ci.v15n2.2020.1018
Marçal, E. F., Pereira, P. L. V., Martin, D. M. L., & Nakamura, W. T. (2011). Evaluation of contagion or interdependence in the financial crises of Asia and Latin America, considering the macroeconomic fundamentals. Applied Economics, 43(19), 2365–2379. https://doi.org/10.1080/00036840903194204
Moretti, A. R., Vaz, B., & Mendes, D. M. (2005). Medindo a Influêencia do Mercado Americano nas Interdependêencias Observadas na América Latina. Revista Brasileira de Financ¸as, 3(1), 123–137.
Pesaran, H. H., & Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics Letters, 58(1), 17–29. https://doi.org/10.1016/s0165-1765(98)00214-6
Pimenta, T. (2004). Uma mensuração do fenômeno da interdependência entre os principais mercados acionários da América Latina e a Nasdaq. Revista de Administração USP, 39(2), 177–185.
Ribeiro, A. L. P., & Hotta, L. K. (2013). An analysis of contagion among Asian countries using the canonical model of contagion. International Review of Financial Analysis, 29, 62–69. https://doi.org/10.1016/j.irfa.2013.03.014
Salisu, A. A., & Vo, X. V. (2020). Predicting stock returns in the presence of COVID-19 pandemic: The role of health news. Internacional Review of Financial Analysis, 70(January), 1–10.
Sharif, A., Aloui, C., & Yarovaya, L. (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, 70(April), 101496. https://doi.org/10.1016/j.irfa.2020.101496
Silva, G. D. (2016). Efeito Spillover do crescimento dos principais pólos comerciais do mundo sobre as economias Sul-Americanas. Universidade Federal de Viçosa.
So, M. K. P., Chu, A. M. Y., & Chan, T. W. C. (2021). Impacts of the COVID-19 pandemic on financial market connectedness. Finance Research Letters, 38, 101864. https://doi.org/10.1016/j.frl.2020.101864
Yarovaya, L., Brzeszczynski, J., Goodell, J. W., Lucey, B., & Lau, C. (2020). Rethinking Financial Contagio: Information Transmission Mechanism during the COVID-19 pandemic.
Youssef, M., Mokni, K., & Ajmi, A. N. (2021). Dynamic connectedness between stock markets in the presence of the COVID-19 pandemic: does economic policy uncertainty matter? Financial Innovation, 7(1). https://doi.org/10.1186/s40854-021-00227-3
Zhang, D., Hu, M., & Ji, Q. (2020). Financial markets under the global pandemic of COVID-19. Finance Research Letters, 36(April), 101528. https://doi.org/10.1016/j.frl.2020.101528
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