Sectoral dependence and contagion in the BRICS grouping: an application of the R-Vine copulas

Hendriks, Johannes Jurgens and Bonga-Bonga, Lumengo (2020): Sectoral dependence and contagion in the BRICS grouping: an application of the R-Vine copulas.

Abstract

Advances in portfolio optimisation techniques have given rise to studies that aim to identify changes in correlation structures between markets in times of economic turmoil. This phenomenon is known as contagion. This article aims at providing a new approach to distinguish between contagion and interdependence, where interdependence occurs when the correlation between two assets is not significantly different in tranquil and turmoil markets. An R-Vine Copula approach is considered to estimate the dependence structures and bivariate copulas between the estimated volatility of different markets. Thereafter, the tail dependence coefficients are estimated and a simulation procedure is used to determine their levels of significance. This article also focuses on contagion and interdependence structures at a sectoral – rather than an aggregated - level of stock exchanges. Thus, this article analyses the contagion and interdependence structures of the Brazilian, Russian, Indian, Chinese, and South African financial, industrial, and resource sectors.The estimated models indicate only a limited amount of contagion and interdependence events. This is in line with other authors who found that the Brazilian, Russian, Indian, Chinese, and South African economies can be seen as a heterogeneous asset class. In cases where there is strong co-movement, interdependence rather than contagion is observed. This suggests that strong market co-movements during periods of financial shock may be a continuation of strong cross-market linkages, i.e. interdependence instead of contagion.

• Item Type: MPRA Paper
• Language: English
• Keywords: contagion, interdependence, R-Vine copula
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C15 - Statistical Simulation Methods: General; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C58 - Financial Econometrics; G - Financial Economics > G1 - General Financial Markets > G15 - International Financial Markets

References

Abad, P., & Chulia, H. (2016). European Government Bond Market Contagion in Turbulent Times. Finance a uver-czech journal of economics and finance, 263-276.

Ahmad, W., Mishra, A. V., & Daly, K. (2018). Heterogeneous dependence and dynamic hedging between sectors of BRIC and global markets. International Review of Financial Analysis, 117–133.

Akhtaruzzaman, M., & Shamsuddin, A. (2018). International contagion through financial versus non-financial firms. Economic Modelling, 143–163.

Alexakis, C., & Pappas, V. (2018). Sectoral dynamics of financial contagion in Europe - The cases of the recent crises episodes. Economic Modelling, 222–239.

Andrew Ang, G. B. (2004). How do Regimes Affect Asset Allocation. Financial Analysts Journal, 86-99.

Ang, A., & Bekaert, G. (2002). International Asset Allocation With Regime Shifts. The Review of Financial Studies, 1137-1187.

Anuoluwapo, D., Abdul-Wasi, M. B., & Edwin, I. (2018). South Africa's inclusion in BRICS: Challenges and Prospects for Development in Africa. International Journal of African Renaissance Studies - Multi-, Inter- and Transdisciplinarity, 27-41.

BanSaida, A. (2018). The contagion effect in European sovereign debt markets: A regime-switching vine copula approach. International Review of Financial Analysis, 153-165.

Bekhaert, G., Harvey, C. R., & Ng, A. (2005). Market Integration and Contagion. Journal of Business, 39-69.

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, 58-69.

Bhaskar, U. (2019). South China Morning Post. Retrieved from South China Morning Post: https://www.scmp.com/comment/opinion/article/3026573/why-indias-relationship-russia-so-special

Billio, M., Duca, M. L., & Pelizzon, L. (2005). Contagion Detection with Switching Regime Models: A Short and Long Run Analysis. SSRN eLibrary.

Bonga-Bonga, L. (2018). Uncovering equity market contagion among BRICS countries: An application of the multivariate GARCH model. The Quarterly Review of Economics and Finance, 36-44.

Boyer, B. H., Gibson, M. S., & Loretan, M. (1999). Pitfalls in Tests for Changes in Correlations. FRB International Finance Discussion Paper No. 597.

Buckley, I., Saunders, D., & Seco, L. (2008). Portfolio optimization when asset returns have the Gaussian mixture distribution. European Journal of Operational Research, 1434-1461.

Campbell, R., Koedijk, K., & Kofman, P. (2002). Increased Correlation in Bear Markets. Financial Analysts Journal, 87-94.

Campbell, R., Koedijk, K., & Kofman, P. (2002). Increased Correlation in Bear Markets. Financial Analysts Journal, 87-94.

Chan-Lau, J. A., Mathieson, D. J., & Yao, J. Y. (2004). Extreme Contagion in Equity Markets. IMF Staff Papers, 386-408.

Chollete, L., Heinen, A., & Valdesogo, A. (2009). Modeling International Financial Returns with a Multivariate Regime-switching Copula. Journal of Financial Econometrics, 437-480.

Corsetti, G., Pericoli, M., & Sbracia, M. (2005). Some contagion, some interdependence: More pitfalls in tests of financial contagion. Journal of International Money and Finance, 1177-1199.

Costinot, A., Roncalli, T., & Teiletche, J. (2000). Revisiting the Dependence between Financial Markets with Copulas. SSRN eLibrary.

Cubillos-Rocha, J. S., Gomez-Gonzalez, J. E., & Melo-Velandia, L. F. (2019). Detecting exchange rate contagion using copula functions. North American Journal of Economics and Finance, 13-22.

Davies, P. (2013). Business Times. Retrieved from Business Times: http://www.bdlive.co.za/businesstimes/2013/03/17/sa-needs-to-justify-its-inclusion-inbrics

De Lira Salvatierra, I., & Patton, A. J. (2015). Dynamic copula models and high frequency data. Journal of Empirical Finance, 120-135.

Dißmann, J., Brechmann, E. C., & C. Czado, D. K. (2013). Selecting and estimating regular vine copulae and application to financial returns. Computational Statistics and Data Analysis, 52-69.

Elton, E. J., Gruber, M. J., & Padberg, M. W. (1976). Simple criteria for optimal portfolio selection. The Journal of Finance, 1341-1357.

Eun, C. S., & Resnick, B. G. (2014). International Financial Management. New York: McGraw-Hill Education.

Feldstein, M. (2003). Economic and financial crises in emerging market economies. Chicago and London: University of Chicago Press: NBER Conference Report series.

Forbes, K. J., & Rigobon, R. (2002). No Contagion, Only Interdependence: Measuring Stock Market Comovements. The Journal of Finance, 2223–2261.

Gambogi, J. (2005). Rare Earths. Reston, Virginia: United States Geological Survey.

Girton, L., & Roper, D. (1977). A Monetary Model of Exchange Market Pressure Applied to the Post-War Canadian Experience. The American Economic Review, 537-548.

Graflund, A., & Nilsson, B. (2002). Dynamic Portfolio Selection: The Relevance of Switching Regimes and Investment Horizon. European Financial Management, 179-200.

Guiso, L., Jappelli, T., Padula, M., & Pagano, M. (2004). Financial market integration and economic growth in the EU. EU FINANCE AND GROWTH, 525-577.

Henry, P. B. (2007). Capital Account Liberalization: Theory, Evidence, and Speculation. Journal of Economic Literature, 887-935.

Horen, N. v., Jager, H., & Klaassen, F. (2006). Foreign Exchange Market Contagion in the Asian Crisis: A Regression-Based Approach. Review of World Economics, 374-401.

Horta, P., Mendes, C., & Vieira, I. (2010). Contagion effects of the subprime cirsis in the European NYSE Euronext markets. Portaguese Economic Journal, 115-140.

Hu, L. (2006). Dependence Patterns across Financial Markets: a Mixed Copula Approach. Applied Financial Economics, 717-729.

India Brand Equity Foundation. (2019, 07 15). Automobile Industry in India. Retrieved from IDEF: https://www.ibef.org/industry/india-automobiles.aspx

Info BRICS (2019). History of BRICS. Retrieved from Info BRICS: http://infobrics.org/page/history-of-brics/

International Monetary Fund. (2018, 4 1). World Economic Outlook Database April 2018.

Jayech, S. (2016). The contagion channels of July–August-2011 stock market crash: A DAG-copula based approach. European Journal of Operational Research, 631-646.

Ji, Q., Bouri, E., & Roubaud, D. (2018). Dynamic network of implied volatility transmission among US equities, strategic commodities, and BRICS equities. International Review of Financial Analysis, 1-12.

Jin, X., & An, X. (2016). Global financial crisis and emerging stock market contagion: A volatility impulse response function approach. Research in International Business and Finance, 179-195.

Jondeau, E., & Rockinger, M. (2006). The copula-GARCH model of conditional dependencies: An international stock market application. Journal of International Money and Finance, 827-853.

Kenourgios, D., & Dimitriou, D. (2015). Contagion of the Global Financial Crisis and the real economy: a regional analysis. Economic Modelling, 283-293.

King, M. A., & Wadhwani, S. (1990). Transmission of Volatility between Stock Markets. The Review of Financial Studies, 5-33.

Ledoit, O., & Wolf, M. (2004). Honey, I shrunk the sample covariance matrix. Journal of Portfolio Management, 110-119.

Lee, S. B., & Kim, K. J. (1993). Does the October 1987 crash strengthen the co-movements among national stock markets? Review of Financial Economics, 89.

Longin, F., & Solnik, B. (2001). Extreme correlations in international equity markets. The journal of Finance, 649-676.

Loretan, M., & English, W. B. (2000). Evaluating "Correlation Breakdowns" during Periods of Market Volatility. In International Financial Markets and the Implication for Monetary and Financial Stability. Basel: Bank for International Settlements.

Lyocsa, S., & Horvath, R. (2018). Stock Market Contagion: a New Approach. Open Economies Review, 547-578.

Markowitz, H. (1952). Portfolio Selection. The Journal of Finance, 77-91.

Mensi, W., Hammoudeh, S., Nguyen, D. K., & al., e. (2016). Global financial crisis and spillover effects among US and BRICS stock markets. International Review of Economics & Finance, 257-276.

Migiro, G. (2019, 7 15). Countries with the most natural resources. Retrieved from World Atlas: https://www.worldatlas.com/articles/countries-with-the-most-natural-resources.html

Muratori, U. (2014). Contagion in the Euro Area Sovereign Bond Market. Social Sciences, 66-82.

New Development Bank. (2019). About Us. Retrieved from NDB: https://www.ndb.int/about-us/essence/history/

Obstfeld, M. (1998). The Global Capital Market: Benefactor or Menace. Journal of Economic Perspectives, 9-30.

Patton, A. J. (2006). Modelling asymmetric exchange rate dependence. International Economic Review, 527-556.

Paul, A., & Gideon, B. (2017). Examining evidence of ‘shift-contagion’ in African stock markets : a CoVaR-copula approach. Review of Development Finance, 142-156.

Pelletier, D. (2006). Regime switching for dynamic correlations. Journal of Econometrics, 445-473.

Phylaktis, K., & Xia, L. (2009). Equity Market Comovement and Contagion: A Sectoral Perspective. Financial Management, 381 - 409.

Rodriguez, J. C. (2007). Measuring financial contagion: A Copula approach. Journal of Empirical Finance, 401-423.

Simoes, H. (2019). The observatory of economic complexity. Retrieved from The observatory of economic complexity: https://oec.world/en/

Sklar, M. (1959). Fonctions de répartition à n dimensions et leurs marges. Publications de l’Institut de statistique de l’Université de Paris, 229–231.

Smith, D. (2013). The Guardian. Retrieved from The Guardian:https://www.theguardian.com/world/2013/mar/24/south-africa-bric-developing-economy

Sundaram, P. (2012). The BRIC Mutual Fund Industry.Procedia - Social and Behavioral Sciences, 324-336.

Tsay, R. (2010). Analysis of Financial Time Series. Chicago: John Wiley & Sons.

Workman, D. (2019, 07 15). Platinum Exports by Country. Retrieved from World's Top Exports: http://www.worldstopexports.com/platinum-exporters/

Ye, W., Luo, K., & Liu, X. (2017). Time-varying quantile association regression model with applications to financial contagion and VaR. European Journal of Operational Research, 1015-1028.

Ye, W., Zhu, Y., Wu, Y., & Miao, B. (2016). Markov regime-switching quantile regression models and financial contagion detection. Insurance: Mathematics and Economics, 21-26.

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, 725-738.