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The Spectral Stress VaR (SSVaR)

Author

Listed:
  • Dominique Guegan

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Bertrand K. Hassani

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Kehan Li

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

Abstract
One of the key lessons of the crisis which began in 2007 has been the need to strengthen the risk coverage of the capital framework. In response, the Basel Committee in July 2009 completed a number of critical reforms to the Basel II framework which will raise capital requirements for the trading book and complex securitisation exposures, a major source of losses for many international active banks. One of the reforms is to introduce a stressed value-at-risk (VaR) capital requirement based on a continuous 12-month period of significant financial stress (Basel III (2011) [1]. However the Basel framework does not specify a model to calculate the stressed VaR and leaves it up to the banks to develop an appropriate internal model to capture material risks they face. Consequently we propose a forward stress risk measure "spectral stress VaR" (SSVaR) as an implementation model of stressed VaR, by exploiting the asymptotic normality property of the distribution of estimator of VaR p. In particular to allow SSVaR incorporating the tail structure information we perform the spectral analysis to build it. Using a data set composed of operational risk factors we fit a panel of distributions to construct the SSVaR in order to stress it. Additionally we show how the SSVaR can be an indicator regarding the inner model robustness for the bank.

Suggested Citation

  • Dominique Guegan & Bertrand K. Hassani & Kehan Li, 2015. "The Spectral Stress VaR (SSVaR)," Post-Print halshs-01169537, HAL.
    • Handle: RePEc:hal:journl:halshs-01169537
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-01169537
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    References listed on IDEAS

    as
    1. Glenn Hoggarth & Steffen Sorensen & Lea Zicchino, 2005. "Stress tests of UK banks using a VAR approach," Bank of England working papers 282, Bank of England.
    2. Dominique Guegan & Bertrand Hassani, 2015. "Stress Testing Engineering: The Real Risk Measurement?," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01310469, HAL.
    3. Carol Alexander & Daniel Ledermann, 2012. "ROM Simulation: Applications to Stress Testing and VaR," ICMA Centre Discussion Papers in Finance icma-dp2012-09, Henley Business School, University of Reading.
    4. Azamat Abdymomunov & Sharon Blei & Bakhodir Ergashev, 2015. "Integrating Stress Scenarios into Risk Quantification Models," Journal of Financial Services Research, Springer;Western Finance Association, vol. 47(1), pages 57-79, February.
    5. Dominique Guegan & Bertrand Hassani, 2015. "Stress Testing Engineering: The Real Risk Measurement?," Post-Print hal-01310469, HAL.
    6. Tom Pak-wing Fong & Chun-shan Wong, 2008. "Stress Testing Banks' Credit Risk Using Mixture Vector Autoregressive Models," Working Papers 0813, Hong Kong Monetary Authority.
    7. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Dominique Guegan & Bertrand K. Hassani & Kehan Li, 2016. "A robust confidence interval of historical Value-at-Risk for small sample," Documents de travail du Centre d'Economie de la Sorbonne 16034, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    2. Dominique Guegan & Bertrand K. Hassani & Kehan Li, 2016. "Uncertainty in historical Value-at-Risk: an alternative quantile-based risk measure," Post-Print halshs-01277880, HAL.
    3. Dominique Guegan & Bertrand K. Hassani & Kehan Li, 2016. "Uncertainty in historical Value-at-Risk: an alternative quantile-based risk measure," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01277880, HAL.
    4. Dominique Guegan & Bertrand K. Hassani & Kehan Li, 2016. "Uncertainty in historical Value-at-Risk: an alternative quantile-based risk measure," Documents de travail du Centre d'Economie de la Sorbonne 16006, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    5. Dominique Guegan & Bertrand Hassani & Kehan Li, 2017. "Measuring risks in the extreme tail: The extreme VaR and its confidence interval," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01317391, HAL.
    6. Dominique Guegan & Bertrand K. Hassani & Kehan Li, 2016. "Capturing the intrinsic uncertainty of the VaR: Spectrum representation of a saddlepoint approximation for an estimator of the VaR," Documents de travail du Centre d'Economie de la Sorbonne 16034r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Jul 2016.

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    Keywords

    value at risk; asymptotic theory; distribution; spectral analysis; stress; risk measure; regulation;
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