Risk Measures in the Form of Infimal Convolution

被引：2
|
作者：
Kirilyuk, V. S. [1 ]
机构：
[1] Natl Acad Sci Ukraine, VM Glushkov Inst Cybernet, Kiev, Ukraine
来源：
CYBERNETICS AND SYSTEMS ANALYSIS | 2021年 / 57卷 / 01期
关键词：
infimal convolution; convex risk measure; coherent risk measure; conditional value-at-risk; dual representation; subdifferential; expected utility; deterministic equivalent; OPTIMAL PORTFOLIOS; EXPECTED UTILITY; COHERENT;
D O I：
10.1007/s10559-021-00327-z
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
The properties of risk measures in the form of infimal convolution are analyzed. The dual representation of such measures, their subdifferential, extremum conditions, representation for optimization and use in constraints are described. The results of the study are demonstrated by examples of known risk measures of such structure. This allows systematization of the available results and facilitates a potential search for new variants of risk measures.
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页码：30 / 46
页数：17
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