2022/03/04 by Yuanying Guan, Guan, Yuanying, Zhanyi Jiao +3 · 1 citation
Decision Sciences · Economics, Econometrics and Finance · Social Sciences · #FOS: Economics and business #Health Systems, Economic Evaluations, Quality of Life #Insurance, Mortality, Demography, Risk Management #Mathematical Finance (q-fin.MF) #Risk Management (q-fin.RM) #Risk and Portfolio Optimization
paper · pdf · doi:10.48550/arxiv.2203.02599
openalex publication_date 2022/03/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The celebrated Expected Shortfall (ES) optimization formula implies that ES at a fixed probability level is the minimum of a linear real function plus a scaled mean excess function. We establish a reverse ES optimization formula, which says that a mean excess function at any fixed threshold is the maximum of an ES curve minus a linear function. Despite being a simple result, this formula reveals elegant symmetries between the mean excess function and the ES curve, as well as their optimizers. The reverse ES optimization formula is closely related to the Fenchel-Legendre transforms, and our formulas are generalized from ES to optimized certainty equivalents, a popular class of convex risk measures. We analyze worst-case values of the mean excess function under two popular settings of model uncertainty to illustrate the usefulness of the reverse ES optimization formula, and this is further demonstrated with an application using insurance datasets.