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Stress Testing Engineering: The Real Risk Measurement?

In: Future Perspectives in Risk Models and Finance

Author

Listed:
  • Dominique Guégan

    (University Paris 1 Panthéon-Sorbonne et New York University Polytechnic School of Engineering)

  • Bertrand K. Hassani

    (Université Paris 1 Panthéon-Sorbonne CES UMR 8174 and Grupo Santander)

Abstract

Stress testing is used to determine the stability or the resilience of a given financial institution by deliberately submitting the subject to intense and particularly adverse conditions which has not been considered a priori. This exercise does not imply that the entity’s failure is imminent, though its purpose is to address and prepare this potential failure. Consequently, as the focal point is a concept (Risk) the stress testing is the quintessence of risk management. In this chapter we focus on what may lead a bank to fail and how its resilience can be measured. Two families of triggers are analysed: the first stands in the impact of external (and/or extreme) events, the second one stands on the impacts of the choice of inadequate models for predictions or risks measurement; more precisely on models becoming inadequate with time because of not being sufficiently flexible to adapt themselves to dynamical changes. The first trigger needs to take into account fundamental macro-economic data or massive operational risks while the second trigger deals with the limitations of the quantitative models for forecasting, pricing, evaluating capital or managing the risks. It may be argued that if inside the banks-limitations, pitfalls and other drawbacks of models used were correctly identified, understood and handled, and if the associated products were correctly known, priced and insured, then the effects of the crisis may not have had so important impacts on the real economy. In other words, the appropriate model should be able to capture real risks (including in particular extreme events) at any point in time, or ultimately a model management strategy should be considered to switch from a model to another during extreme market conditions.

Suggested Citation

  • Dominique Guégan & Bertrand K. Hassani, 2015. "Stress Testing Engineering: The Real Risk Measurement?," International Series in Operations Research & Management Science, in: Alain Bensoussan & Dominique Guegan & Charles S. Tapiero (ed.), Future Perspectives in Risk Models and Finance, edition 127, pages 89-124, Springer.
  • Handle: RePEc:spr:isochp:978-3-319-07524-2_3
    DOI: 10.1007/978-3-319-07524-2_3
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    Citations

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    Cited by:

    1. Dominique Guegan & Bertrand K. Hassani & Kehan Li, 2015. "The Spectral Stress VaR (SSVaR)," Documents de travail du Centre d'Economie de la Sorbonne 15052, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    2. Dominique Gu�gan & Bertrand Hassani & Kehan Li, 2015. "The Spectral Stress VaR (SSVaR)," Working Papers 2015:17, Department of Economics, University of Venice "Ca' Foscari".
    3. Dominique Guegan & Bertrand K. Hassani & Kehan Li, 2015. "The Spectral Stress VaR (SSVaR)," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01169537, HAL.
    4. Dominique Guegan & Bertrand K. Hassani & Kehan Li, 2015. "The Spectral Stress VaR (SSVaR)," Post-Print halshs-01169537, HAL.

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