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Maximality and numeraires in convex sets of nonnegative random variables

2012/02/21 by Constantinos Kardaras, Kardaras, Constantinos
Decision Sciences · Mathematics · #46A16 #46E30 #60A10 #FOS: Mathematics #Functional Analysis (math.FA) #Limits and Structures in Graph Theory #Point processes and geometric inequalities #Probability (math.PR) #Risk and Portfolio Optimization #math.FA #math.PR #msc:46A16 #msc:46E30 #msc:60A10

paper · pdf · doi:10.48550/arxiv.1202.4703

12 pages; (most probably) final version

openalex publication_date 2012/02/21 · arxiv created 2014/10/03 · arxiv updated 2014/10/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We introduce the concepts of max-closedness and numeraires of convex subsets in the nonnegative orthant of the topological vector space of all random variables built over a probability space, equipped with a topology consistent with convergence in probability. Max-closedness asks that maximal elements of the closure of a set already lie on the set. We discuss how numeraires arise naturally as strictly positive optimisers of certain concave monotone maximisation problems. It is further shown that the set of numeraires of a convex, max-closed and bounded set of of nonnegative random variables that contains at least one strictly positive element is dense in the set of its maximal elements.

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