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New Extreme-Value Dependance Measures and Finance Applications

  • POON, Ser-Huang

    (University of Strathclyde)

  • ROCKINGER, Michael
  • TAWN, Jonathan

    (Lancaster University)

In the finance literature, cross-sectional dependence in extreme returns of risky assets is often modeled implicitly assuming an asymptotically dependent structure. If the true dependence structure is asymptotically independent then existing finance models will lead to over-estimation of the risk of simultaneous extreme events. We provide simple techniques for deciding between these dependence classes and for quantifying the degree of dependence in each class. Examples based on daily stock market returns show that there is strong evidence in favor of asymptotically independent models for dependence in extremal stock market returns, and that most of the extremal dependence is due to heteroskedasticity in stock returns processes.

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Paper provided by HEC Paris in its series Les Cahiers de Recherche with number 719.

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Length: 29 pages
Date of creation: 06 Feb 2001
Date of revision:
Handle: RePEc:ebg:heccah:0719
Contact details of provider: Postal: HEC Paris, 78351 Jouy-en-Josas cedex, France
Web page: http://www.hec.fr/

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  1. Dennis Jansen & Casper de Vries, 1988. "On the frequency of large stock returns: putting booms and busts into perspective," Working Papers 1989-006, Federal Reserve Bank of St. Louis.
  2. Longin, Francois M, 1996. "The Asymptotic Distribution of Extreme Stock Market Returns," The Journal of Business, University of Chicago Press, vol. 69(3), pages 383-408, July.
  3. LONGIN, François & SOLNIK, Bruno, 2000. "Extreme correlation of international equity markets," Les Cahiers de Recherche 705, HEC Paris.
  4. Longin, François & Solnik, Bruno H, 2000. "Extreme Correlation of International Equity Markets," CEPR Discussion Papers 2538, C.E.P.R. Discussion Papers.
  5. Terry A. Marsh & Niklas Wagner, 2004. "Return-Volume Dependence and Extremes in International Equity Markets," Finance 0401007, EconWPA.
  6. Harvey, Campbell R. & Siddique, Akhtar, 1999. "Autoregressive Conditional Skewness," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(04), pages 465-487, December.
  7. Philipp Hartmann & Stefan Straetmans & Casper G. de Vries, 2001. "Asset market linkages in crisis periods," Proceedings 727, Federal Reserve Bank of Chicago.
  8. Francis X. Diebold & Til Schuermann & John D. Stroughair, 1998. "Pitfalls and Opportunities in the Use of Extreme Value Theory in Risk Management," Center for Financial Institutions Working Papers 98-10, Wharton School Center for Financial Institutions, University of Pennsylvania.
  9. 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.
  10. Richardson, Matthew & Smith, Tom, 1993. "A Test for Multivariate Normality in Stock Returns," The Journal of Business, University of Chicago Press, vol. 66(2), pages 295-321, April.
  11. ROCKINGER, Michael & JONDEAU, Eric, 2000. "Entropy densities," Les Cahiers de Recherche 709, HEC Paris.
  12. P. Bortot & S. Coles & J. Tawn, 2000. "The multivariate Gaussian tail model: an application to oceanographic data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 49(1), pages 31-049.
  13. Rockinger, Michael & Jondeau, Eric, 2002. "Entropy densities with an application to autoregressive conditional skewness and kurtosis," Journal of Econometrics, Elsevier, vol. 106(1), pages 119-142, January.
  14. Longin, Francois M., 2000. "From value at risk to stress testing: The extreme value approach," Journal of Banking & Finance, Elsevier, vol. 24(7), pages 1097-1130, July.
  15. Starica, Catalin, 1999. "Multivariate extremes for models with constant conditional correlations," Journal of Empirical Finance, Elsevier, vol. 6(5), pages 515-553, December.
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