Vector-valued multivariate conditional value-at-risk

被引：6
|
作者：
Merakli, Merve [1 ]
Kucukyavuz, Simge [1 ]
机构：
[1] Univ Washington, Ind & Syst Engn, Seattle, WA 98195 USA
来源：
OPERATIONS RESEARCH LETTERS | 2018年 / 46卷 / 03期
基金：
美国国家科学基金会;
关键词：
Conditional value-at-risk; Multivariate risk; Value-at-risk; STOCHASTIC-PROGRAMMING-MODELS; CONSTRAINTS; DISTRIBUTIONS; OPTIMIZATION; EXTENSIONS;
D O I：
10.1016/j.orl.2018.02.006
中图分类号：
C93 [管理学]; O22 [运筹学];
学科分类号：
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要：
In this study, we propose a new definition of multivariate conditional value-at-risk (MCVaR) as a set of vectors for arbitrary probability spaces. We explore the properties of the vector-valued MCVaR (VMCVaR) and show the advantages of VMCVaR over the existing definitions particularly for discrete random variables. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码：300 / 305
页数：6
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