Simulation of Coherent Risk Measures Based on Generalized Scenarios

Vadim Lesnevski (), Barry L. Nelson () and Jeremy Staum ()
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Vadim Lesnevski: Royal Bank of Scotland, London, United Kingdom
Barry L. Nelson: Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, Illinois 60208
Jeremy Staum: Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, Illinois 60208

Management Science, 2007, vol. 53, issue 11, 1756-1769

Abstract: In financial risk management, coherent risk measures have been proposed as a way to avoid undesirable properties of measures such as value at risk that discourage diversification and do not account for the magnitude of the largest, and therefore most serious, losses. A coherent risk measure equals the maximum expected loss under several different probability measures, and these measures are analogous to "populations" or "systems" in the ranking-and-selection literature. However, unlike in ranking and selection, here it is the value of the maximum expectation under any of the probability measures, and not the identity of the probability measure that attains it, that is of interest. We propose procedures to form fixed-width, simulation-based confidence intervals for the maximum of several expectations, explore their correctness and computational efficiency, and illustrate them on risk-management problems. The availability of efficient algorithms for computing coherent risk measures will encourage their use for improved risk management.

Keywords: simulation; ranking and selection; good deal bounds; coherent risk measures; risk management (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (14)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:53:y:2007:i:11:p:1756-1769

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