Restricted risk measures and robust optimization
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Vielma_Restricted-Risk-Measures.pdf
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605.54 KB
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Author(s)
Lagos, Guido
Espinoza, Daniel
Moreno, Eduardo
Vielma Centeno, Juan Pablo
Date Issued
October 2014
Journal
European Journal of Operational Research
Publisher
Elsevier
Citation
Lagos, Guido et al. “Restricted Risk Measures and Robust Optimization.” European Journal of Operational Research 241, 3 (March 2015): 771–782 © 2014 Elsevier B.V.
Version
Original manuscript
Abstract
In this paper we consider characterizations of the robust uncertainty sets associated with coherent and distortion risk measures. In this context we show that if we are willing to enforce the coherent or distortion axioms only on random variables that are affine or linear functions of the vector of random parameters, we may consider some new variants of the uncertainty sets determined by the classical characterizations. We also show that in the finite probability case these variants are simple transformations of the classical sets. Finally we present results of computational experiments that suggest that the risk measures associated with these new uncertainty sets can help mitigate estimation errors of the Conditional Value-at-Risk. Keywords: Risk management; Stochastic programming; Uncertainty modeling
MIT Department
Sloan School of Management
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/J.EJOR.2014.09.024
