Value-At-Risk Optimal Policies for Revenue Management Problems
Matthias Koenig and
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Matthias Koenig: Department of Management Science, Lancaster University Management School, http://www.meiss.com/en/team/matthias-koenig/
No MRG/0018, Working Papers from Department of Management Science, Lancaster University
Consider a single-leg dynamic revenue management problem with fare classes controlled by capacity in a risk-averse setting. The revenue management strategy aims at limiting the down-side risk, and in particular, value-at-risk. A value-at-risk optimised policy offers an advantage when considering applications which do not allow for a large number of reiterations. They allow for specifying a confidence level regarding undesired scenarios. We state the underlying problem as a Markov decision process and provide a computational method for computing policies, which optimise the value-at-risk for a given confidence level. This is achieved by computing dynamic programming solutions for a set of target revenue values and combining the solutions in order to attain the requested multi-stage risk-averse policy. Numerical examples and comparison with other risk-sensitive approaches are discussed.
Keywords: operations research; risk management; capacity control; revenue management; risk; value-at-risk (search for similar items in EconPapers)
JEL-codes: C61 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2010-05, Revised 2014-12
New Economics Papers: this item is included in nep-cmp and nep-rmg
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Journal Article: Value-at-risk optimal policies for revenue management problems (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:lms:mansci:mrg-0018
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