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Simulation of Coherent Risk Measures Based on Generalized Scenarios

Author

Listed:
  • 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)

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.

Suggested Citation

  • Vadim Lesnevski & Barry L. Nelson & Jeremy Staum, 2007. "Simulation of Coherent Risk Measures Based on Generalized Scenarios," Management Science, INFORMS, vol. 53(11), pages 1756-1769, November.
    • Handle: RePEc:inm:ormnsc:v:53:y:2007:i:11:p:1756-1769
    DOI: 10.1287/mnsc.1070.0734
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    References listed on IDEAS

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    1. Jeremy Staum, 2004. "Fundamental Theorems of Asset Pricing for Good Deal Bounds," Mathematical Finance, Wiley Blackwell, vol. 14(2), pages 141-161, April.
    2. Justin Boesel & Barry L. Nelson & Seong-Hee Kim, 2003. "Using Ranking and Selection to “Clean Up” after Simulation Optimization," Operations Research, INFORMS, vol. 51(5), pages 814-825, October.
    3. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    4. Stefan Jaschke & Uwe Küchler, 2001. "Coherent risk measures and good-deal bounds," Finance and Stochastics, Springer, vol. 5(2), pages 181-200.
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    Citations

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    Cited by:

    1. Grechuk, Bogdan & Zabarankin, Michael, 2016. "Inverse portfolio problem with coherent risk measures," European Journal of Operational Research, Elsevier, vol. 249(2), pages 740-750.
    2. Tsai, Shing Chih & Chu, I-Hao, 2012. "Controlled multistage selection procedures for comparison with a standard," European Journal of Operational Research, Elsevier, vol. 223(3), pages 709-721.
    3. Hai Lan & Barry L. Nelson & Jeremy Staum, 2010. "A Confidence Interval Procedure for Expected Shortfall Risk Measurement via Two-Level Simulation," Operations Research, INFORMS, vol. 58(5), pages 1481-1490, October.
    4. Shing Chih Tsai & Chen Hao Kuo, 2012. "Screening and selection procedures with control variates and correlation induction techniques," Naval Research Logistics (NRL), John Wiley & Sons, vol. 59(5), pages 340-361, August.
    5. Michael B. Gordy & Sandeep Juneja, 2010. "Nested Simulation in Portfolio Risk Measurement," Management Science, INFORMS, vol. 56(10), pages 1833-1848, October.
    6. Grechuk, Bogdan, 2015. "The center of a convex set and capital allocation," European Journal of Operational Research, Elsevier, vol. 243(2), pages 628-636.
    7. Roger J. A. Laeven & John G. M. Schoenmakers & Nikolaus F. F. Schweizer & Mitja Stadje, 2020. "Robust Multiple Stopping -- A Pathwise Duality Approach," Papers 2006.01802, arXiv.org, revised Sep 2021.
    8. Mark Broadie & Yiping Du & Ciamac C. Moallemi, 2011. "Efficient Risk Estimation via Nested Sequential Simulation," Management Science, INFORMS, vol. 57(6), pages 1172-1194, June.
    9. Lawrence Haar & Andros Gregoriou, 2023. "Regulation and De-Risking: Theoretical and Empirical Insights," Risks, MDPI, vol. 11(6), pages 1-23, June.
    10. Volker Krätschmer & Marcel Ladkau & Roger J. A. Laeven & John G. M. Schoenmakers & Mitja Stadje, 2018. "Optimal Stopping Under Uncertainty in Drift and Jump Intensity," Mathematics of Operations Research, INFORMS, vol. 43(4), pages 1177-1209, November.
    11. Andrzej Ruszczynski & Jianing Yao, 2017. "A Dual Method For Backward Stochastic Differential Equations with Application to Risk Valuation," Papers 1701.06234, arXiv.org, revised Aug 2020.
    12. Shing Chih Tsai, 2013. "Rapid Screening Procedures for Zero-One Optimization via Simulation," INFORMS Journal on Computing, INFORMS, vol. 25(2), pages 317-331, May.
    13. Grechuk, Bogdan & Zabarankin, Michael, 2018. "Direct data-based decision making under uncertainty," European Journal of Operational Research, Elsevier, vol. 267(1), pages 200-211.

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