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Journal articles
Nonparametric estimation of the conditional tail copula
Abstract : The tail copula is widely used to describe the dependence in the tail of multivariate distributions. In some situations such as risk management, the dependence structure may be linked with some covariate. The tail copula thus depends on this covariate and is referred to as the conditional tail copula.
The aim of this paper is to propose a nonparametric estimator of the conditional tail copula and to establish its asymptotic normality. Some illustrations are presented both on simulated and real datasets.
Cited literature [40 references]
https://hal.archives-ouvertes.fr/hal-00964514
Contributor : Laurent Gardes <>
Submitted on : Tuesday, January 20, 2015 - 1:28:16 PM
Last modification on : Thursday, March 26, 2020 - 8:49:31 PM
Document(s) archivé(s) le : Friday, September 11, 2015 - 7:45:41 AM
Contributor : Laurent Gardes <>
Submitted on : Tuesday, January 20, 2015 - 1:28:16 PM
Last modification on : Thursday, March 26, 2020 - 8:49:31 PM
Document(s) archivé(s) le : Friday, September 11, 2015 - 7:45:41 AM
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CTDC16.pdf
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