Asymptotically unbiased estimation of the coefficient of tail dependence

Yuri Goegebeur, Armelle Guillou

Research output: Contribution to journalJournal articleResearchpeer-review


We introduce and study a class of weighted functional estimators for the coefficient of tail dependence in bivariate extreme value statistics. Asymptotic normality of these estimators is established under a second-order condition on the joint tail behaviour, some conditions on the weight function and for appropriately chosen sequences of intermediate order statistics. Asymptotically unbiased estimators are constructed by judiciously chosen linear combinations of weighted functional estimators, and variance optimality within this class of asymptotically unbiased estimators is discussed. The finite sample performance of some specific examples from our class of estimators and some alternatives from the recent literature are evaluated with a small simulation experiment.

Original languageEnglish
JournalScandinavian Journal of Statistics
Pages (from-to)174-189
Publication statusPublished - 2013


  • Bias-correction
  • Coefficient of tail dependence
  • Multivariate extremes
  • Second-order condition


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