Extremal Mean-Variance Functionals over Wasserstein Balls: Applications to Risk Sharing

Battle Count: 0

Highly relevant for robust portfolio selection and risk management. The mean-variance framework is foundational in quantitative finance, and the Wasserstein ambiguity set provides a rigorous way to handle model uncertainty, which is critical for trading strategies sensitive to estimation errors.

High complexity. Requires solving scalar equations for extremal parameters, constructing convex envelopes for distortion riskmetrics, and handling dual variables in finite-dimensional optimization problems. Not a simple plug-and-play library implementation.

The paper provides full analytical proofs and derivations. However, it is a theoretical paper with limited numerical examples (one illustrative figure for RVaR). Reproduction requires implementing the derived scalar equations and convex envelope constructions.