Parametric tail copula estimation and model testing

18Citations
Citations of this article
11Readers
Mendeley users who have this article in their library.

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. © 2007 Elsevier Inc. All rights reserved.

Cite

CITATION STYLE

APA

de Haan, L., Neves, C., & Peng, L. (2008). Parametric tail copula estimation and model testing. Journal of Multivariate Analysis, 99(6), 1260–1275. https://doi.org/10.1016/j.jmva.2007.08.003

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free