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A Copula-Based Autoregressive Conditional Dependence Model of International Stock Markets

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  • Rob van den Goorbergh

Abstract

This paper investigates the level and development of cross-country stock market dependence using daily returns on stock indices. The use of copulas allows us to build exible models of the joint distribution of stock index returns. In particular, we apply univariate AR(p)-GARCH(1,1) models to the margins with possibly skewed and fat tailed return innovations, while modelling the dependence between markets using parametric families of copulas which offer various alternatives to the commonly assumed normal dependence structure. Moreover, the dependence across stock markets is allowed to vary over time through a GARCH-like autoregressive conditional copula model. Using synchronous daily returns on U.S., U.K., and French stock indices, we find strong evidence that the conditional dependence between pairs of each of these markets varies over time. All market pairs show high levels of dependence persistence. The performance of the copula-based approach is compared with Engle's (2002) dynamic conditional correlation model and found to be superior.

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Bibliographic Info

Paper provided by Netherlands Central Bank, Research Department in its series DNB Working Papers with number 022.

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Date of creation: Dec 2004
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Handle: RePEc:dnb:dnbwpp:022

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Keywords: stock markets; dependence; copulas; synchronicity;

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References

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  1. Andrew J. Patton, 2002. "On the out-of-sample importance of skewness and asymetric dependence for asset allocation," LSE Research Online Documents on Economics 24951, London School of Economics and Political Science, LSE Library.
  2. Joshua Rosenberg, 1999. "Semiparametric Pricing of Multivariate Contingent Claims," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-028, New York University, Leonard N. Stern School of Business-.
  3. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. " On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
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  7. U. Cherubini & E. Luciano, 2002. "Bivariate option pricing with copulas," Applied Mathematical Finance, Taylor & Francis Journals, vol. 9(2), pages 69-85.
  8. Joshua Rosenberg, 1996. "Pricing Multivariate Contingent Claims Using Estimated Risk-neutral Density Functions," New York University, Leonard N. Stern School Finance Department Working Paper Seires 96-36, New York University, Leonard N. Stern School of Business-.
  9. repec:cup:etheor:v:11:y:1995:i:1:p:122-50 is not listed on IDEAS
  10. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(01), pages 122-150, February.
  11. BAUWENS, Luc & LAURENT, Sébastien & ROMBOUTS, Jeroen, 2003. "Multivariate GARCH models: a survey," CORE Discussion Papers 2003031, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  12. Martens, Martin & Poon, Ser-Huang, 2001. "Returns synchronization and daily correlation dynamics between international stock markets," Journal of Banking & Finance, Elsevier, vol. 25(10), pages 1805-1827, October.
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  14. Engle, Robert F & Manganelli, Simone, 1999. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," University of California at San Diego, Economics Working Paper Series qt06m3d6nv, Department of Economics, UC San Diego.
  15. Baele, Lieven, 2005. "Volatility Spillover Effects in European Equity Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 40(02), pages 373-401, June.
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  17. Engle, Robert F & Sheppard, Kevin K, 2001. "Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH," University of California at San Diego, Economics Working Paper Series qt5s2218dp, Department of Economics, UC San Diego.
  18. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-50, July.
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  22. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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  24. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
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Cited by:
  1. Jacek Leskow & Justyna Mokrzycka & Krzysztof Krawiec, 2011. "Modeling Stock Market Indexes With Copula Functions," "e-Finanse", University of Information Technology and Management, Institute of Financial Research and Analysis, vol. 7(2), pages 1-16, August.
  2. Grundke, Peter & Polle, Simone, 2012. "Crisis and risk dependencies," European Journal of Operational Research, Elsevier, vol. 223(2), pages 518-528.

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