Dependence and Value at Risk in the Stock Markets from the Americas: A Copula Approach

Edgar Ortiz, Christian Bucio, Alejandra Cabello

Abstract


This work applies copula modeling to estimate the degree of dependence among the nine major equity markets from the Western Hemisphere, seven emerging markets from Latin America (Argentina, Brazil, Chile, Colombia, Peru, Venezuela, Mexico) and the two mature markets from North America (Canada, United States). The relevance of copula-measured dependence is assessed estimating Value at Risk for bilateral portfolio investments, comparing it with conventional VaR methodologies. The data encompass daily time series for the 1992-2009 period.

Keywords


Copula; Value at Risk; Stock Markets North America; Stock Markets Latin America.

Full Text:

PDF

References


Best, P. (1998). Implementing value at risk. John Wiley and Sons. England.

Bob, N. K. (2013). Value-at risk Estimation. A GARCH-EVT-Copula Approach. Master Thesis, Mathematical Statistics, University of Stockholm.

Boubaker, H., and Sghaier, N. (2014). On the dynamic dependence between U.S. and other developed markets. Working Paper. PAG Business School, Paris.

Brockwell, P. J. and Davis, R.A. (2009). Time Series: Theory and Methods. Springer. Series in Statistics. USA.

Chan-Lau, J. A., Mathieson, D. J., and Yao, J Y. (2004). Extreme contagion in equity markets. IMF Working Paper. International Monetary Fund.

Chebbi, A., and Hedhli, A. (2014). Dynamic dependence between the Tunisian stock market and other international stock markets: GARCH-EVT approach. Applied Financial Economics, vol. 24, issue 18, pp. 1215.1228.

Dall’Aglio, G. (1956). Sugli estremi dei moment delle funzione id repartizione doppia. AnnbScola Norm Sup Pisa. Cl Sci. (3) 10, 35-74.

De Lara, A.. (2009). Medición y control de riesgos financieros. Limusa. Mexico.

Dowd, K.. (1998). Beyond Value at Risk: The New Science of Risk Management, Frontiers in Finance Series. John Wiley and Sons. England.

Embrechts, P., H., A., and Puccetti, G. (2005). Worst VaR Scenarios Insurance. Mathematics and Economics. 37(1). pp. 115-134.

Fantazzini, D. (2008). Dynamic Copula Modelling for Value at Risk. Frontiers in Finance and Economics. Vol. 5, No. 2, pp. 72-108.

Frétchet, M. (1951) . (1951) Sur les tableaux de corr´elation dont les marges sont donn´ees. Ann. Univ. Lyon Sect. A 9, 53-77.

Gonzalo, J., and Olmo, J. (2005). Contagion Versus Flight To Quality in Financial Markets. Working Paper. Economic series. Universidad Carlos III de Madrid.

Hamilton, J. D. (1994). Time Series Analysis. Princeton University Press. USA.

Hoedfing, W. (1940) Masstabinvariante Korrelationtheorie. Schiften des Mathemastischen .

Instituts und des Instituts für Angewandie Mathematic der Univers. Berlin 5, Heft 3, pp. 179--233.

Hoedfing, W. (1941). Masstabinvariante Korrelationsmasse für diskontinuerliche veriteinlungen.

Archive für Matemathschen Wirtshaften und Sozialforschung 7, pp. 49-70.

Holton, G.A. (2016). Value at Risk: Theory and Practice. Academic Press.

Hotta, L.K., Lucas, E. C., and Palaro, H.P. (2008). Estimation of VaR using Copula and Extreme Value Theory. Multinational Finance Journal. 12 (3/4). pp. 205-218.

Hsu, C-P., Huang, C.-W, and Chiou, W-J. P.l (2012). Effectiveness of copula-extreme value theory in estimating value at risk: empirical evidence from Asian emerging markets. Review of Quantitative Finance and Accounting, vol 39, issues 4, pp. 447-468.

Hu, L.. (2003). Dependence Patterns Across Financial Markets: Methods and Evidence. Mimeo. Department of Economics. Ohio State University. USA.

Hussain, S.I., and Li, S. (2015). Modeling international diversification between the Chinise stock maket and others. 2015 Financial Markets & Corporate Governance Conference. The University of Western Australia.

Johnson, N. and Kotz, S. (1972). Distributions in Statistics: Continuous Multivariate Distributions. Wiley. USA.

Jorion, P. (2010). Valor en Riesgo. Limusa. Mexico.

Kole, E., Koedijk, K. and Verbeek, M. (2005). Testing copulas to model financial dependence. Erasmus University. Holland.

Kresta, A.,, and Tichy, T. (2012).. International portfolio risk modeling: The case of NIG model and ordinary copula functions. Finance a Uver – Czech Journal of Economics and Finance, vol. 62, num.2, pp. 141-161.

Krzemienowski, A., and SZymczyk, S. (2016). Annals of Operations Research, vol. 237, issues 1, pp. 219-236.

López, D. N. (2006). Crisis de mercados de bonos emergentes y contagio: dependencia extrema. Working Paper. Universidad de los Andes. Colombia.

Lopez-Herrera, F., Santillan Salgado, R.J., and Cruz Ake, S. (2015). Volatility dependence structure between the mexican stock Exchange and the world capital market. Investigación Económica, ,vol.. LXXIV, núm. 293, pp. 69-97.

Messaud, S.B., and Aloui, C. (2015). Measuring interdependency and contagion: A copula approach. International Review of Business Research Papers, vol. 11, num. 1, pp. 60-77.

Nguyen, V.-L, and Huynh, V.-N. (2015). Using conditional copula to estimate value-at-risk in Vietnam´s foreign exchange market. In Econometrics of risk, Huynh, V.-N,, Kreinovich, V., Scroboonchitta, ,S,, and Suriya, K., eds. Elsevier.

Ozun, Alper and Cifter, A.. (2011). Portfolio Value-at-Risk with Time-Varying Copula: Evidence from the Americas. MPRA Paper. University Library of Munich, Germany.

Penza, P. and Bansal, V. K. (2001). Measuring market risk with value at risk. John Wiley and Sons.New York.

Rank, J. (2007). Copulas: From theory to application in finance. Risk Books. United Kingdom.

Reyes, F. and Ortiz, Edgar (2013). VaR- GARCH y Portafolios de Inversión Trinacionales enlos mercados accionarios del TLCAN. Revista mexicana de Economía y Finanzas, vol. 8, num. 2, pp. 129-155.

Romano, C.. (2002). Applying Copula Function to Risk Management. Working Paper. University ofRome, La Sapienza.

Samitas, A., Kenourgios, D., and Paltalidis, N. (2007). Financial crises and stock market dependence.

European Financial Management Association. 16th Annual Meeting (EFMA). Vienna, 27-30.

Sanchez, A., and Reyes, O. (2005). Regularidades probabilisticas de las series financieras y la familia de de modelos GARCH. Ciencia Ergo Sum, vol. 13, num. 002, pp. 149-156.

Shim, J., and Lee, S., and MacMinn, R.D., (2011). Measuring Economic Capital: Value-at-Risk,Expected Shortfall and Copula Approach (May 12, 2011). Available at SSRN: http://ssrn.com/abstract=1840124 or http://dx.doi.org/10.2139/ssrn.1840124

Sklar, A. (1959). Fonctions de repartition a n dimensions et leurs marges. Publications de l’Institut de Sta s ue de l’ niversit e de Paris, 8: 229–231.

Torres, G. and Olarte A. (2009). Valor en riesgo desde un enfoque de cópulas. AD-MINISTER Universidad EAFIT. 15. pp. 113-136.

Yingying, H., Pu, G., and Xiang, Z. (2016). Correlations and risk contagion between mixed assets and mixed-asset portfolio VaR measurements in a dynamic view: An application based on time varying copula models. Physica A. Statiscal Mechanics and its Applications, vol. 444., pp. 940-953.


Refbacks

  • There are currently no refbacks.


 

Copyright© 2015 Journal of Research in Business, Economics and Management. All rights reserved.

ISSN 2395-2210

For any help/support contact us at editorial@scitecresearch.com, jrbem@scitecresearch.com.