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Testing For Equality Between Two Copulas

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Author Info

  • Bruno Rémillard

    (HEC Montréal)

  • Olivier Scaillet

    (University of Geneva and Swiss Finance Institute)

Abstract

We develop a test of equality between two dependence structures estimated through empirical copulas. We provide inference for independent or paired samples. The multiplier central limit theorem is used for calculating p-values of the Cram´er-von Mises test statistic. Finite sample properties are assessed with Monte Carlo experiments. We apply the testing procedure on empirical examples in finance, psychology, insurance and medicine.

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Bibliographic Info

Paper provided by Swiss Finance Institute in its series Swiss Finance Institute Research Paper Series with number 07-24.

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Length: 24 pages
Date of creation: Jun 2006
Date of revision:
Handle: RePEc:chf:rpseri:rp0724

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Web page: http://www.SwissFinanceInstitute.ch
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Related research

Keywords: Copula; Cram´er-von Mises statistic; empirical process; pseudo-observations; multiplier central limit theorem; p-value.;

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Cited by:
  1. Ivan Kojadinovic & Jun Yan, . "Modeling Multivariate Distributions with Continuous Margins Using the copula R Package," Journal of Statistical Software, American Statistical Association, vol. 34(i09).
  2. Boris Brodsky & Henry Penikas & Irina Safaryan, 2012. "Copula structural shift identification," HSE Working papers WP BRP 05/FE/2012, National Research University Higher School of Economics.
  3. Boente, Graciela & Cao, Ricardo & González Manteiga, Wenceslao & Rodriguez, Daniela, 2013. "Testing in generalized partially linear models: A robust approach," Statistics & Probability Letters, Elsevier, vol. 83(1), pages 203-212.
  4. Penikas, H., 2010. "Financial Applications of Copula-Models," Journal of the New Economic Association, New Economic Association, issue 7, pages 24-44.
  5. Brodsky, Boris & Penikas, Henry & Safaryan, Irina, 2009. "Detection of Structural Breaks in Copula Models," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 16(4), pages 3-15.
  6. Miguel A. Delgado & Juan Carlos Escanciano, 2011. "Conditional stochastic dominance testing," Economics Working Papers we1138, Universidad Carlos III, Departamento de Economía.
  7. Christian Genest & Johanna Nešlehová & Jean-François Quessy, 2012. "Tests of symmetry for bivariate copulas," Annals of the Institute of Statistical Mathematics, Springer, vol. 64(4), pages 811-834, August.
  8. Jäschke, Stefan, 2014. "Estimation of risk measures in energy portfolios using modern copula techniques," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 359-376.
  9. Jean-David Fermanian, 2012. "An overview of the goodness-of-fit test problem for copulas," Papers 1211.4416, arXiv.org.
  10. Quessy, Jean-François & Éthier, François, 2012. "Cramér–von Mises and characteristic function tests for the two and k-sample problems with dependent data," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 2097-2111.
  11. Berghaus, Betina & Bücher, Axel, 2014. "Nonparametric tests for tail monotonicity," Journal of Econometrics, Elsevier, vol. 180(2), pages 117-126.
  12. Bücher, Axel & Ruppert, Martin, 2013. "Consistent testing for a constant copula under strong mixing based on the tapered block multiplier technique," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 208-229.
  13. Jean-David Fermanian & Dragan Radulovic & Marten Wegkamp, 2013. "A Asymptotic Total Variation Test for Copulas," Working Papers 2013-25, Centre de Recherche en Economie et Statistique.
  14. Bücher, Axel & Volgushev, Stanislav, 2013. "Empirical and sequential empirical copula processes under serial dependence," Journal of Multivariate Analysis, Elsevier, vol. 119(C), pages 61-70.
  15. Bücher, Axel & Dette, Holger, 2010. "A note on bootstrap approximations for the empirical copula process," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1925-1932, December.

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