Summary
We consider optimization problems involving coherent measures of risk. We derive necessary and sufficient conditions of optimality for these problems, and we discuss the nature of the nonanticipativity constraints. Next, we introduce dynamic measures of risk, and formulate multistage optimization problems involving these measures. Conditions similar to dynamic programming equations are developed. The theoretical considerations are illustrated with many examples of mean-risk models applied in practice.
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© 2006 Springer-Verlag London Limited
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RuszczyĆski, A., Shapiro, A. (2006). Optimization of Risk Measures. In: Calafiore, G., Dabbene, F. (eds) Probabilistic and Randomized Methods for Design under Uncertainty. Springer, London. https://doi.org/10.1007/1-84628-095-8_4
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DOI: https://doi.org/10.1007/1-84628-095-8_4
Publisher Name: Springer, London
Print ISBN: 978-1-84628-094-8
Online ISBN: 978-1-84628-095-5
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