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Title: Parametric tail copula estimation and model testing
Author: Haan, Laurens de
Neves, Cláudia
Peng, Liang
Keywords: Empirical tail copula
Extreme values
Maximum likelihood estimation
Tail copula
Issue Date: Jul-2008
Publisher: Elsevier
Abstract: Parametric models for tail copulas are being used for modeling tail dependence and maximum likelihood estimation is employed to estimate unknown parameters. However, two important questions seem unanswered in the literature: (1) What is the asymptotic distribution of the MLE and (2) how does one test the parametric model? In this paper, we answer these two questions in the case of a single parameter for ease of illustration. A simulation study is provided to investigate the finite sample performance of the proposed estimator and test.
Peer review: yes
DOI: 10.1016/j.jmva.2007.08.003
ISSN: 0047-259X
Appears in Collections:DMat - Artigos

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