Vol. 16 No. 33 (2021)

Artículos

Contagion effect in the BRIC+M block: a MS-copula approach

Published 2021-06-20 — Updated on 2021-06-21

  • Miriam Sosa
    • ,
  • Christian Bucio
    • ,
  • Alejandra Cabello

Miriam Sosa
Metropolitan Autonomous University image/svg+xml

Christian Bucio
Autonomous University of Mexico State image/svg+xml

Alejandra Cabello
National Autonomous University of Mexico image/svg+xml

Abstract

This paper aims to analyze the contagion effect among the stock markets of the BRIC+M block (Brazil, Russia, India, China plus Mexico). The dependence is estimated through a dynamic bivariate copula approach over the period july, 1997 – december, 2015. Once the dependence is estimated, univariate (MS-AR) is used to determine whether dynamic dependence evolves according to different regimes: a low dependence regime and a high dependence regime. The high dependence regime indicates contagion effect. Empirical results show strong evidence of time-varying dependence among the BRIC+M markets and an increasing dependence relation, above all, during financial crisis episodes.

Keywords

copula approach, markov switching- AR, BRIC, Mexico, stock Markets

PDF (Spanish)

References

  1. Ang, Andrew and Geert Bekaert (2002). “International Asset Allocation with Regime Shifts”. Review of Financial Studies 15, 1137-1187.
  2. Bekaert, G.; M. Ehrmann; M. Fratzscher & A. Mehl (2014). The global crisis and equity market contagion. The Journal of Finance, 69(6), 2597-2649.
  3. Bergmann, D. R.; J. R. Securato; J. R. F. Savoia & E. A. D. R. Contani (2015). US subprime financial crisis contagion on BRIC and European Union stock markets. Revista de Administração (São Paulo), 50(2), 229-240.
  4. Bianconi, M.; J. A. Yoshino & M. O. M. De Sousa (2013). BRIC and the US financial crisis: An empirical investigation of stock and bond markets. Emerging Markets Review, 14, 76-109.
  5. Chittedi, K. R. (2014). Global Financial Crisis and Contagion: Evidence for the’BRIC’Economies. The Journal of Developing Areas, 48(4), 243-264.
  6. Chkili, W., & D. K. Nguyen (2014). Exchange rate movements and stock market returns in a regime-switching environment: Evidence for BRICS countries. Research in International Business and Finance, 31, 46-56.
  7. Dai, Qiang; Kenneth J. Singleton and Wei Yang (2003), “Regime Shifts in a Dynamic Term Structure Model of U.S. Treasury Bonds”, working paper, Stanford University.
  8. Davies, R. B. (1987). Hypothesis testing when a nuisance parameter is present only under the
  9. alternative. Biometrika, 74 (1987), pp. 3-43.
  10. Dimitriou, D.; D. Kenourgios & T. Simos (2013). Global financial crisis and emerging stock market contagion: A multivariate FIAPARCH–DCC approach. International Review of Financial Analysis, 30, 46-56.
  11. Forbes, K. J., & R. Rigobon (2002). No contagion, only interdependence: measuring stock market comovements. The journal of Finance, 57(5), 2223-2261.
  12. Garcia, R., & P. Perron (1996). An analysis of the real interest rate under regime shifts. The Review of Economics and Statistics, 111-125.
  13. Garcia, R.; R. Luger & E. Renault (2003). Empirical assessment of an intertemporal option pricing model with latent variables. Journal of Econometrics, 116(1), 49-83.
  14. Grover, V. (2015). Identifying Dependence Structure among Equities in Indian Markets using Copulas.
  15. Hamilton, J. D. (2005). Regime-Switching Models. Palgrave Dictionary of Economics.
  16. Hemche, O.; F. Jawadi; S. B. Maliki & A. I. Cheffou (2016). On the study of contagion in the context of the subprime crisis: A dynamic conditional correlation–multivariate GARCH approach. Economic Modelling, 52, 292-299.
  17. Jin, X. & X. An (2016). Global financial crisis and emerging stock market contagion: A volatility impulse response function approach. Research in International Business and Finance, 36, 179-195.
  18. Kanas, A. (2005). Nonlinearity in the stock price-dividend relation. Journal of International Money and Finance, 24(4), 583-606.
  19. Kenourgios, D.; A. Samitas & N. Paltalidis (2011). Financial crises and stock market contagion
  20. in a multivariate time-varying asymmetric framework. Journal of International Financial Markets, Institutions and Money, 21(1), 92-106.
  21. Kim, K. & K. S. Park (1994). Phased-mission system reliability under Markov environment. IEEE Transactions on reliability, 43(2), 301-309.
  22. Kocaarslan, B.; U. Soytas; R. Sari & E. Ugurlu (2018). The changing role of financial stress, oil price, and gold price in financial contagion among US and BRIC markets. International Review of Finance.
  23. Mostafa, M. Z. P. & S. Stavroyiannis (2016). BRIC dynamic conditional correlations, portfolio diversification and rebalancing after the global financial crisis of 2008-2009. Global Business and Economics Review, 18(1), 28-40.
  24. Nelsen, R. B. (1999); An Introduction to Copulas. Springer, New York.
  25. Ortiz, E.; C. Bucio & A. Cabello (2016). Dependence and Value at Risk in the Stock Markets from the Americas: A Copula Approach. Journal of Research in Business, Economics and Management, 5(5), 761-780.
  26. Patel, R. J. (2019). BRICS emerging markets linkages: Evidence from the 2008 Global Financial Crisis. The Journal of Private Equity, 22(4), 42-59.
  27. Singh, A. & P. Kaur (2016). Do BRIC Countries’ Equity Markets Co-Move in Long Run?. Theoretical Economics Letters, 6(02), 119.
  28. Sosa, M.; C. Bucio & A. Cabello (2015). Mercados de Capitales del Bloque Bric México: Dependencia Estimada con un Enfoque de Cópulas. Investigación Administrativa, 44(115).
  29. Verma, R. P. & P. Rani (2016). Emerging Stock Market Integration in the Post Financial Crises Era: An Empirical Analysis of the Short-term and Long-term Linkages. Emerging Economy Studies, 2(1), 91-109.
  30. Wang, P. & M. Theobald (2008). Regime-switching volatility of six East Asian emerging markets. Research in International Business and Finance, 22(3), 267-283.
  31. Zouhair, M.; C. Lanouar & A. N. Ajmi (2014). Contagion versus Interdependence: The Case of the BRIC Countries During the Subprime Crises in Emerging Markets and the Global Economy, pp. 555-582.

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