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Extremes

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An estimator of the stable tail dependence function based on the empirical beta copula

  • Anna Kiriliouk
  • Johan Segers
  • Laleh Tafakori
Article
  • 54 Downloads

Abstract

The replacement of indicator functions by integrated beta kernels in the definition of the empirical tail dependence function is shown to produce a smoothed version of the latter estimator with the same asymptotic distribution but superior finite-sample performance. The link of the new estimator with the empirical beta copula enables a simple but effective resampling scheme.

Keywords

Bernstein polynomial Brown–Resnick process Bootstrap Copula Empirical process Max-linear model Tail copula Tail dependence Weak convergence 

Mathematics Subject Classification (2010)

62G32 62G30 

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Notes

Acknowledgments

A. Kiriliouk gratefully acknowledges support from the Fonds de la Recherche Scientifique (FNRS).

J. Segers gratefully acknowledges funding by contract “Projet d’Actions de Recherche Concertées” No. 12/17-045 of the “Communauté française de Belgique” and by IAP research network Grant P7/06 of the Belgian government (Belgian Science Policy).

L. Tafakori would like to thank the Australian Research Council for supporting this work through Laureate Fellowship FL130100039.

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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of EconometricsErasmus University RotterdamRotterdamThe Netherlands
  2. 2.Institut de Statistique, Biostatistique et Sciences ActuariellesUniversité Catholique de LouvainLouvain-la-NeuveBelgium
  3. 3.School of Mathematics and StatisticsThe University of MelbourneMelbourneAustralia

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