Скачать или смотреть Carole Bernard - Preference robust distortion risk measures

This lecture was part of the Workshop on "Probabilistic Mass Transport - from Schrödinger to Stochastic Analysis" held at the ESI February 9 - 13, 2026.
We introduce a framework for preference-robust decision making when preferences over risk are modelled through generalized distortion risk measures. Unlike distributional robustness, our approach addresses ambiguity in the risk functional itself. We construct ambiguity sets on distortion (weight) functions using the Wasserstein distance and Bregman divergences, and derive closed-form expressions for the worst- and best-case distortion risk measures. We further extend the framework to Rank-Dependent Expected Utility, yielding preference-robust behavioural models.

This is joint work with Silvana Pesenti (University of Toronto).