BERNOULLI AND TAIL-DEPENDENCE COMPATIBILITY
成果类型：
Article
署名作者：
Embrechts, Paul; Hofert, Marius; Wang, Ruodu
署名单位：
Swiss Federal Institutes of Technology Domain; ETH Zurich; Swiss Finance Institute (SFI); Swiss Federal Institutes of Technology Domain; ETH Zurich; University of Waterloo
刊物名称：
ANNALS OF APPLIED PROBABILITY
ISSN/ISSBN：
1050-5164
DOI：
10.1214/15-AAP1128
发表日期：
2016
页码：
1636-1658
关键词：
摘要：
The tail-dependence compatibility problem is introduced. It raises the question whether a given d x d-matrix of entries in the unit interval is the matrix of pairwise tail-dependence coefficients of a d-dimensional random vector. The problem is studied together with Bernoulli-compatible matrices, that is, matrices which are expectations of outer products of random vectors with Bernoulli margins. We show that a square matrix with diagonal entries being 1 is a tail-dependence matrix if and only if it is a Bernoulli-compatible matrix multiplied by a constant. We introduce new copula models to construct tail-dependence matrices, including commonly used matrices in statistics.