Tails of multivariate Archimedean copulas

被引:94
作者
Charpentier, Arthur [2 ]
Segers, Johan [1 ]
机构
[1] Catholic Univ Louvain, Inst Stat, B-1348 Louvain, Belgium
[2] Univ Rennes 1, CREM, Fac Sci Econ 7, F-35065 Rennes, France
关键词
Archimedean copula; Asymptotic independence; Clayton copula; Coefficient of tail dependence; Complete monotonicity; Domain of attraction; Extreme value distribution; Frailty model; Regular variation; Survival copula; Tail dependence copula; BIVARIATE; DEPENDENCE; MODELS; DISTRIBUTIONS; ASSOCIATION;
D O I
10.1016/j.jmva.2008.12.015
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
070103 [概率论与数理统计]; 140311 [社会设计与社会创新];
摘要
A complete and user-friendly directory of tails of Archimedean copulas is presented which can be used in the selection and construction of appropriate models with desired properties. The results are synthesized in the form of a decision tree: Given the values of some readily computable characteristics of the Archimedean generator, the upper and lower tails of the copula are classified into one of three classes each, one corresponding to asymptotic dependence and the other two to asymptotic independence. For a long list of single-parameter families, the relevant tail quantities are computed so that the corresponding classes in the decision tree can easily be determined. In addition, new models with tailor-made upper and lower tails can be constructed via a number of transformation methods. The frequently occurring category of asymptotic independence turns out to conceal a surprisingly rich variety of tail dependence structures. (c) 2009 Elsevier Inc. All rights reserved.
引用
收藏
页码:1521 / 1537
页数:17
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