Multiperiod Stochastic Optimization Problems with Time-Consistent Risk Constraints

Martin Densing and J. Mayer ()
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J. Mayer: University of Zurich

A chapter in Operations Research Proceedings 2011, 2012, pp 521-526 from Springer

Abstract: Abstract Coherent risk measures play an important role in building and solving optimization models for decision problems under uncertainty. We consider an extension to multiple time periods, where a risk-adjusted value for a stochastic process is recursively defined over the time steps, which ensures time consistency. A prominent example of a single-period coherent risk measure that is widely used in applications is Conditional-Value-at-Risk (CVaR). We show that a recursive calculation of CVaR leads to stochastic linear programming formulations. For the special case of the risk-adjusted value of a random variable at the time horizon, a lower bound is given. The possible integration of the risk-adjusted value into multi-stage mean-risk optimization problems is outlined.

Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-642-29210-1_83

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DOI: 10.1007/978-3-642-29210-1_83

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