Parametric tail copula estimation and model testing

Laurens de Haan, Cláudia Neves and Liang Peng

Journal of Multivariate Analysis, 2008, vol. 99, issue 6, 1260-1275

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.

Keywords: Empirical; tail; copula; Extreme; values; Maximum; likelihood; estimation; Tail; copula (search for similar items in EconPapers)
Date: 2008
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Citations: View citations in EconPapers (19)

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