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Joe, Harry, Li, Haijun and Nikoloulopoulos, Aristidis K 
ORCID: https://orcid.org/0000-0003-0853-0084
(2010)
Tail dependence functions and vine copulas.
Journal of Multivariate Analysis, 101 (1).
pp. 252-270.
Abstract
Tail dependence and conditional tail dependence functions describe, respectively, the tail probabilities and conditional tail probabilities of a copula at various relative scales. The properties as well as the interplay of these two functions are established based upon their homogeneous structures. The extremal dependence of a copula, as described by its extreme value copulas, is shown to be completely determined by its tail dependence functions. For a vine copula built from a set of bivariate copulas, its tail dependence function can be expressed recursively by the tail dependence and conditional tail dependence functions of lower-dimensional margins. The effect of tail dependence of bivariate linking copulas on that of a vine copula is also investigated.
| Item Type: | Article |
|---|---|
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| UEA Research Groups: | Faculty of Science > Research Groups > Data Science and AI Faculty of Science > Research Groups > Statistics (former - to 2024) Faculty of Science > Research Groups > Numerical Simulation, Statistics & Data Science |
| Depositing User: | Vishal Gautam |
| Date Deposited: | 04 Mar 2011 08:58 |
| Last Modified: | 07 Nov 2024 12:32 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/22918 |
| DOI: | 10.1016/j.jmva.2009.08.002 |
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