---
title: Stochastic Non-Dominance Measures
url: https://www.ml-quant.com/papers/repec/eee-ejores-v-321-y-2025-i-1-p-269-283/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:eee:ejores:v:321:y:2025:i:1:p:269-283
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0377221724006714%3Bh%3Drepec%3Aeee%3Aejores%3Av%3A321%3Ay%3A2025%3Ai%3A1%3Ap%3A269-283
featured: 2025-01-01
citations: unknown
topic: Other
---


# Stochastic Non-Dominance Measures

The research introduces measures of stochastic non-dominance to analyze scenarios where stochastic dominance rules are not applicable, using the Wasserstein distance as the measure.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0377221724006714%3Bh%3Drepec%3Aeee%3Aejores%3Av%3A321%3Ay%3A2025%3Ai%3A1%3Ap%3A269-283
- Identifier: RePEc:eee:ejores:v:321:y:2025:i:1:p:269-283
- Released: 2025-01-01
- First featured: Quant Letter No. 80 (2025-01-01): https://www.ml-quant.com/issues/2025-01-01/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Other

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