A Characterization of Law-Invariant and Coherent Risk Measures through Optimal Transport

TL;DR

This paper introduces a new way to characterize law-invariant and coherent risk measures using a generalized optimal transport framework, providing a unified representation and duality formulas.

Contribution

It offers a novel representation formula for such risk measures based on a flexible optimal transport problem, extending classical results like Kusuoka's theorem.

Findings

Derived a general duality formula for convex target sets.

Explicitly computed target sets for CVaR and higher moment measures.

Unified framework for law-invariant coherent risk measures.

Abstract

In this article, we propose a novel characterization of law-invariant and coherent risk measures, based on a generalized optimal transport problem in which the second marginal of the admissible plans is not fixed, but required to lie within a target set of probability measures. One of the main contributions of this work is a general representation formula for such risk measures, which is closely related to Kusuoka's theorem. When the aforementioned target set is convex, our representation result allows for the systematic derivation of general duality formulas. To illustrate our findings, we explicitly compute the target sets associated with several classical law-invariant coherent risk measures, including the prototypical conditional value at risk and higher moment measures.