Nonparametric rank-based tests of bivariate extreme-value dependence

Authors:
Ivan Kojadinovic;Jun Yan
Affiliations:
Laboratoire de Mathématiques et Applications, UMR CNRS 5142, Université de Pau et des Pays de l'Adour, B.P. 1155, 64013 Pau Cedex, France;Department of Statistics, University of Connecticut, 215 Glenbrook Road, U-4120, Storrs, CT 06269, USA
Venue:
Journal of Multivariate Analysis
Year:
2010

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Abstract

A new class of tests of extreme-value dependence for bivariate copulas is proposed. It is based on the process comparing the empirical copula with a natural nonparametric rank-based estimator of the unknown copula under extreme-value dependence. A multiplier technique is used to compute approximate p-values for several candidate test statistics. Extensive Monte Carlo experiments were carried out to compare the resulting procedures with the tests of extreme-value dependence recently studied in Ben Ghorbal et al. (2009) [1] and Kojadinovic and Yan (2010) [19]. The finite-sample performance study of the tests is complemented by local power calculations.