Multivariate countermonotonicity and the minimal copulas

被引:9
|
作者
Lee, Woojoo [1 ]
Cheung, Ka Chun [2 ]
Ahn, Jae Youn [3 ]
机构
[1] Inha Univ, Dept Stat, 235 Yonghyun Dong, Incheon 402751, South Korea
[2] Univ Hong Kong, Dept Stat & Actuarial Sci, Pokfulam Rd, Hong Kong, Hong Kong, Peoples R China
[3] Ewha Womans Univ, Dept Stat, 11-1 Daehyun Dong, Seoul 120750, South Korea
基金
新加坡国家研究基金会;
关键词
Countermonotonicity; Comonotonicity; Minimal copula; Variance minimization; DEPENDENCE STRUCTURE; CONVEX ORDER; COMONOTONICITY; DISTRIBUTIONS; RISKS;
D O I
10.1016/j.cam.2016.12.032
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Frechet-Hoeffding upper and lower bounds play an important role in various bivariate optimization problems because they are the maximum and minimum of bivariate copulas in concordance order, respectively. However, while the Frechet-Hoeffding upper bound is the maximum of any multivariate copulas, there is no minimum copula available for dimensions d >= 3. Therefore, multivariate minimization problems with respect to a copula are not straightforward as the corresponding maximization problems. When the minimum copula is absent, minimal copulas are useful for multivariate minimization problems. We illustrate the motivation of generalizing the joint mixability to d-countermonotonicity defined in Lee and Ahn (2014) through variance minimization problems and show that d-countermonotonic copulas are minimal copulas. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:589 / 602
页数:14
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