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Modelling Dependence in Latin American Markets Using Copula Functions

Author

Listed:
  • Canela Miguel-Angel

    (Miguel-Angel Canela, Department of Managerial Decision Sciences, IESE Business School, Av. Pearson 21, 08034 Barcelona, Spain. E-mail: mcanela@iese.edu)

  • Pedreira Eduardo

    (Eduardo Pedreira, ‘la Caixa’ Research Department, Av. Diagonal 629, 08028 Barcelona, Spain. E-mail: epedreira@lacaixa.es)

Abstract

Two important issues in the analysis of association among financial markets are the degree of dependence and the underlying shape commanding the cross-market dependencies, so that any model used to describe this association must cope with both the issues. In the study presented in this article, we approach the modelling of dependence in two stages. The first stage is based on modelling the dependence between the returns of two assets by means of a single Archimedean copula, whereas the second one takes advantage of the mixture between copulas to gain the necessary flexibility to capture different tail dependence patterns. Both stages have been followed in modelling the dependence among the daily returns of seven Latin American country indices, a regional index and a worldwide index. Our findings have important implications for portfolio risk management. JEL Classification: G11, G15

Suggested Citation

  • Canela Miguel-Angel & Pedreira Eduardo, 2012. "Modelling Dependence in Latin American Markets Using Copula Functions," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 11(3), pages 231-270, December.
    • Handle: RePEc:sae:emffin:v:11:y:2012:i:3:p:231-270
    DOI: 10.1177/0972652712466493
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    References listed on IDEAS

    as
    1. Hayette Gatfaoui, 2003. "How Does Systematic Risk Impact US Credit Spreads? A Copula Study," Risk and Insurance 0308002, University Library of Munich, Germany.
    2. Prakash, Arun J. & Chang, Chun-Hao & Pactwa, Therese E., 2003. "Selecting a portfolio with skewness: Recent evidence from US, European, and Latin American equity markets," Journal of Banking & Finance, Elsevier, vol. 27(7), pages 1375-1390, July.
    3. Lorán Chollete & Andréas Heinen & Alfonso Valdesogo, 2009. "Modeling International Financial Returns with a Multivariate Regime-switching Copula," Journal of Financial Econometrics, Oxford University Press, vol. 7(4), pages 437-480, Fall.
    4. Bekaert, Geert & Harvey, Campbell R., 1997. "Emerging equity market volatility," Journal of Financial Economics, Elsevier, vol. 43(1), pages 29-77, January.
    5. Fujii, Eiji, 2005. "Intra and inter-regional causal linkages of emerging stock markets: evidence from Asia and Latin America in and out of crises," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 15(4), pages 315-342, October.
    6. Fisher N. I. & Switzer P., 2001. "Graphical Assessment of Dependence: Is a Picture Worth 100 Tests?," The American Statistician, American Statistical Association, vol. 55, pages 233-239, August.
    7. Pagan, Jose A. & Soydemir, Gokce A., 2001. "Response asymmetries in the Latin American equity markets," International Review of Financial Analysis, Elsevier, vol. 10(2), pages 175-185.
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    Cited by:

    1. Boubaker, Heni & Raza, Syed Ali, 2016. "On the dynamic dependence and asymmetric co-movement between the US and Central and Eastern European transition markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 459(C), pages 9-23.

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    More about this item

    Keywords

    Emerging markets; tail dependence; copulas; mixture copulas; dependence structure;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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