Counter-monotonic Risk Sharing with Heterogeneous Distortion Risk Measures

Mario Ghossoub, Qinghua Ren and Ruodu Wang

Papers from arXiv.org

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.

Date: 2024-11, Revised 2026-03
New Economics Papers: this item is included in nep-rmg and nep-upt
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