Cash-Subadditive Risk Measures Without Quasi-Convexity

In the literature on risk measures, cash subadditivity was proposed to replace cash additivity, motivated by the presence of stochastic or ambiguous interest rates and defaultable contingent claims. Cash subadditivity has been traditionally studied together with quasi-convexity, in a way similar to cash additivity with convexity. In this paper, we study cash-subadditive risk measures without quasi-convexity. One of our major results is that a general cash-subadditive risk measure can be represented as the lower envelope of a family of quasi-convex and cash-subadditive risk measures. Representation results of cash-subadditive risk measures with some additional properties are also examined. The notion of quasi-star-shapedness, which is a natural analogue of star-shapedness, is introduced, and we obtain a corresponding representation result via the lower envelope of normalized, quasi-convex, and cash-subadditive risk measures. Funding: J. Xia received financial support of the National Key R&D Program of China [Grant 2018YFA0703900] and the National Natural Science Foundation of China [Grants 12071146, 12431017, and 12471447]. X. Han, Q. Wang, and R. Wang received financial support from the Natural Sciences and Engineering Research Council of Canada [Grants RGPIN-2024-03728 and CRC-2022-00141]. X. Han also received financial support from the National Natural Science Foundation of China [Grants 12301604, 12371471, and 12471449]. Q. Wang also received financial support from the Society of Actuaries through the James C. Hickman Scholar Doctoral Stipend.

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Publication Details

Journal
Mathematics of Operations Research
Published
2025-05-15
DOI
https://doi.org/10.1287/moor.2022.0312
Citations
3
Primary Topic
Risk and Portfolio Optimization
Type
article
Field-Weighted Citation Impact
6.32
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article

Cash-Subadditive Risk Measures Without Quasi-Convexity

Qiuqi Wang, Ruodu Wang, Jianming Xia, Xia Han
3 citations
Mathematics of Operations Research
Risk and Portfolio Optimization
6.32
article

Cash-Subadditive Risk Measures Without Quasi-Convexity

Qiuqi Wang, Ruodu Wang, Jianming Xia, Xia Han
article en
3 citations

Abstract

In the literature on risk measures, cash subadditivity was proposed to replace cash additivity, motivated by the presence of stochastic or ambiguous interest rates and defaultable contingent claims. Cash subadditivity has been traditionally studied together with quasi-convexity, in a way similar to cash additivity with convexity. In this paper, we study cash-subadditive risk measures without quasi-convexity. One of our major results is that a general cash-subadditive risk measure can be represented as the lower envelope of a family of quasi-convex and cash-subadditive risk measures. Representation results of cash-subadditive risk measures with some additional properties are also examined. The notion of quasi-star-shapedness, which is a natural analogue of star-shapedness, is introduced, and we obtain a corresponding representation result via the lower envelope of normalized, quasi-convex, and cash-subadditive risk measures. Funding: J. Xia received financial support of the National Key R&D Program of China [Grant 2018YFA0703900] and the National Natural Science Foundation of China [Grants 12071146, 12431017, and 12471447]. X. Han, Q. Wang, and R. Wang received financial support from the Natural Sciences and Engineering Research Council of Canada [Grants RGPIN-2024-03728 and CRC-2022-00141]. X. Han also received financial support from the National Natural Science Foundation of China [Grants 12301604, 12371471, and 12471449]. Q. Wang also received financial support from the Society of Actuaries through the James C. Hickman Scholar Doctoral Stipend.

Mathematics of Operations Research
University of Waterloo (CA), Georgia State University (US), Chinese Academy of Sciences (CN), Nankai University (CN), National Center for Mathematics and Interdisciplinary Sciences (CN), Academy of Mathematics and Systems Science (CN)
Openalex Percentile: Top 5%
Risk and Portfolio Optimization
6.32
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