Stochastically weighted stochastic dominance concepts with an application in capital budgeting |
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Authors: | Jian Hu Tito Homem-de-Mello Sanjay Mehrotra |
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Institution: | 1. Dept of IMSE, University of Michigan, Dearborn, United States;2. School of Business, Universidad Adolfo Iban?ez, Chile;3. Dept of IEMS, Northwestern University, United States |
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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. |
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Keywords: | Stochastic programming Stochastic dominance Risk management Chance constraint Integer programming |
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