Journal article
Counter-monotonic risk sharing with heterogeneous distortion risk measures
Insurance, mathematics & economics, Vol.128, p.103236
05/01/2026
DOI: 10.1016/j.insmatheco.2026.103236
Abstract
We study risk sharing among agents with preferences modeled by heterogeneous distortion risk measures, who are not necessarily risk averse. Pareto optimality for agents using risk measures is often studied through the lens of inf-convolutions, because allocations that attain the inf-convolution are Pareto optimal, and the converse holds true under translation invariance. Our main focus is on groups of agents who exhibit varying levels of risk seeking. Under mild assumptions, we derive explicit solutions for the unconstrained inf-convolution and the counter-monotonic inf-convolution, which can be represented by a generalization of distortion risk measures.
Details
- Title: Subtitle
- Counter-monotonic risk sharing with heterogeneous distortion risk measures
- Creators
- Mario Ghossoub - University of WaterlooQinghua Ren - University of WaterlooRuodu Wang - University of Waterloo
- Resource Type
- Journal article
- Publication Details
- Insurance, mathematics & economics, Vol.128, p.103236
- DOI
- 10.1016/j.insmatheco.2026.103236
- ISSN
- 0167-6687
- eISSN
- 1873-5959
- Publisher
- Elsevier
- Number of pages
- 9
- Grant note
- RGPIN-2024-03728; CRC-2022-00141; RGPIN-2024-03744 / Natural Sciences and Engineering Research Council of Canada; Natural Sciences and Engineering Research Council of Canada (NSERC); CGIAR
- Language
- English
- Date published
- 05/01/2026
- Academic Unit
- Statistics and Actuarial Science
- Record Identifier
- 9985179849502771
Metrics
1 Record Views