Stochastically weighted stochastic dominance concepts with an application in capital budgeting

Jian Hu, Tito Homem-De-Mello, Sanjay Mehrotra

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

The problem of comparing random vectors arises in many applications. We propose three new concepts of stochastically weighted dominance for comparing random vectors X and Y. The main idea is to use a random vector V to scalarize X and Y as VTX and VTY, and subsequently use available concepts from stochastic dominance and stochastic optimization for comparison. For the case where the distributions of X, Y and V have finite support, we give (mixed-integer) linear inequalities that can be used for random vector comparison as well as for modeling of optimization problems where one of the random vectors depends on decisions to be optimized. Some advantages of the proposed new concepts are illustrated with the help of a capital budgeting example.

Original languageEnglish
Pages (from-to)572-583
Number of pages12
JournalEuropean Journal of Operational Research
Volume232
Issue number3
DOIs
StatePublished - 1 Feb 2014
Externally publishedYes

Keywords

  • Chance constraint
  • Integer programming
  • Risk management
  • Stochastic dominance
  • Stochastic programming

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