{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T07:49:04Z","timestamp":1791618544170,"version":"4.3.4"},"posted":{"date-parts":[[2026]]},"group-title":"SSRN","reference-count":0,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.uspto.gov\/ip-policy\/copyright-policy\/copyright-basics"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>Stochastic dominance is a well-established tool both for the comparison of two random variables and as a constraint in optimization problems. However, it can be unnecessarily strict. This has motivated the introduction of concepts like almost stochastic dominance and measures of stochastic non-dominance, which have been previously applied mainly to pairwise comparison between two given random variables. To allow a relaxation of stochastic dominance during the optimization process, this paper introduces tractable formulations of optimization problems where the measures of stochastic non-dominance are used in the constraints. This widens the feasible sets by allowing the variables to differ from those that dominate the benchmark by a specified level of Wasserstein distance. The relationship between such relaxation and the expected utility is also explored. The benefits of stochastic non-dominance constraints are demonstrated through an application to a portfolio selection problem using daily return data from 49 U.S. industry representative portfolios. The out-of-sample moving window analysis over 96 years shows that allowing small measures of second-degree stochastic non-dominance, especially when the Wasserstein distance of order two is considered, results in significantly higher out-of-sample returns while maintaining a similar level of risk when compared to the classical second-degree or third-degree stochastic dominance constraints.<\/jats:p>","DOI":"10.2139\/ssrn.7589423","type":"posted-content","created":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T07:07:24Z","timestamp":1791616044000},"source":"Crossref","is-referenced-by-count":0,"title":["Optimization Problems with Stochastic Non-dominance Constraints: Application to Portfolio Selection"],"prefix":"10.2139","author":[{"given":"Jana","family":"Junova","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Milos","family":"Kopa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sebastiano","family":"Vitali","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","container-title":[],"original-title":[],"deposited":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T07:07:24Z","timestamp":1791616044000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ssrn.com\/abstract=7589423"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":0,"URL":"https:\/\/doi.org\/10.2139\/ssrn.7589423","relation":{},"subject":[],"published":{"date-parts":[[2026]]},"subtype":"preprint"}}