Multivariate stochastic dominance for risk averters and risk seekers

Xu Guo, Wing Keung Wong

Research output: Contribution to journalArticle

15 Scopus citations

Abstract

This paper first extends some well-known univariate stochastic dominance results to multivariate stochastic dominances (MSD) for both risk averters and risk seekers, respectively, to n order for any n ≤ 1 when the attributes are assumed to be independent and the utility is assumed to be additively and separable. Under these assumptions, we develop some properties for MSD for both risk averters and risk seekers. For example, we prove that MSD are equivalent to the expected-utility maximization for both risk averters and risk seekers, respectively. We show that the hierarchical relationship exists for MSD. We establish some dual relationships between the MSD for risk averters and risk seekers. We develop some properties for non-negative combinations and convex combinations random variables of MSD and develop the theory of MSD for the preferences of both risk averters and risk seekers on diversification. At last, we discuss some MSD relationships when attributes are dependent and discuss the importance and the use of the results developed in this paper.

Original languageEnglish (US)
Pages (from-to)575-586
Number of pages12
JournalRAIRO - Operations Research
Volume50
Issue number3
DOIs
StatePublished - Jul 1 2016

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science Applications
  • Management Science and Operations Research

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