arXiv · 2607.01229
Multidimensional Risk Made Easy
Abstract
Suppose we want to assign a certainty equivalent--one number--to a multivariate risk. Which such assignments are law-invariant, monotone with respect to vector stochastic dominance, and invariant to independent background risk? I show that every such certainty equivalent is a positive mixture of scalar entropic certainty equivalents applied to positive projections of the vector risk. The same representation yields a robust-order characterization: unanimity across such certainty equivalents is equivalent, up to closure, to dominance after adding independent multidimensional background risk. In a social-welfare specialization, the corresponding shadow valuations are welfare weights.
Explore related subjects
Keep this discovery
Mark Whitmeyer. 2026-07-01. Multidimensional Risk Made Easy. https://arxiv.org/abs/2607.01229
Cite the original work for its findings. Save a collection to share your selection of sources.