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An Econometric Study of Vine Copulas

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  • Dominique Guegan

    ()
    (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris I - Panthéon-Sorbonne, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris)

  • Pierre-André Maugis

    ()
    (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris I - Panthéon-Sorbonne)

Abstract

We present a new recursive algorithm to construct vine copulas based on an underlying tree structure. This new structure is interesting to compute multivariate distributions for dependent random variables. We proove the asymptotic normality of the vine copula parameter estimator and show that all vine copula parameter estimators have comparable variance. Both results are crucial to motivate any econometrical work based on vine copulas. We provide an application of vine copulas to estimate the VaR of a portfolio, and show they offer significant improvement as compared to a benchmark estimator based on a GARCH model.

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Paper provided by HAL in its series Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) with number halshs-00492124.

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Date of creation: May 2010
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Handle: RePEc:hal:cesptp:halshs-00492124

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Keywords: Vines; multivariate copulas; risk management.;

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  1. Loran , CHOLLETTE & Andreas , HEINEN & Alfonso , VALDESOGO, 2008. "Modelling international financial returns with a multivariate regime switching copula," Discussion Papers (ECON - Département des Sciences Economiques), Université catholique de Louvain, Département des Sciences Economiques 2008011, Université catholique de Louvain, Département des Sciences Economiques.
  2. Xiaohong Chen & Yanqin Fan & Andrew J. Patton, 2004. "Simple tests for models of dependence between multiple financial time series, with applications to U.S. equity returns and exchange rates," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library 24681, London School of Economics and Political Science, LSE Library.
  3. Dominique Guegan & Pierre-André Maugis, 2010. "New Prospects on Vines," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00348884, HAL.
  4. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.) 95-24, Board of Governors of the Federal Reserve System (U.S.).
  5. Aas, Kjersti & Czado, Claudia & Frigessi, Arnoldo & Bakken, Henrik, 2009. "Pair-copula constructions of multiple dependence," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 182-198, April.
  6. Andrew J. Patton, 2008. "Copula-Based Models for Financial Time Series," OFRC Working Papers Series, Oxford Financial Research Centre 2008fe21, Oxford Financial Research Centre.
  7. Andrew Patton, 2004. "Modelling Asymmetric Exchange Rate Dependence," Working Papers, Warwick Business School, Finance Group wp04-04, Warwick Business School, Finance Group.
  8. Fischer, Matthias J. & Köck, Christian & Schlüter, Stephan & Weigert, Florian, 2007. "Multivariate Copula Models at Work: Outperforming the desert island copula?," Discussion Papers 79/2007, Friedrich-Alexander-University Erlangen-Nuremberg, Chair of Statistics and Econometrics.
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Cited by:
  1. Dominique Guegan & Bertrand Hassani, 2014. "Stress Testing Engineering: the real risk measurement?," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00951593, HAL.
  2. Dominique Guegan & Bertrand Hassani, 2011. "Multivariate VaRs for Operational Risk Capital Computation: a Vine Structure Approach," Documents de travail du Centre d'Economie de la Sorbonne, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne 11017, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.

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