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 Parametric tail copula estimation and model testing
Please use this identifier to cite or link to this item http://hdl.handle.net/10773/6549

title: Parametric tail copula estimation and model testing
authors: 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.
URI: http://hdl.handle.net/10773/6549
ISSN: 0047-259X
publisher version/DOI: dx.doi.org/10.1016/j.jmva.2007.08.003
source: Journal of Multivariate Analysis
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