The Spectral Stress VaR (SSVaR)

23 Pages Posted: 25 Jun 2015

See all articles by Dominique Guegan

Dominique Guegan

Université Paris I Panthéon-Sorbonne

Bertrand Hassani

Université Paris I Panthéon-Sorbonne; University College London - Department of Computer Science

Kehan Li

Université Paris I Panthéon-Sorbonne

Date Written: June 18, 2015

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)).

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.

Keywords: Value at Risk, Asymptotic theory, Distribution, Spectral analysis, Stress, Risk measure, Regulation

JEL Classification: C1, C6

Suggested Citation

Guegan, Dominique and Hassani, Bertrand and Li, Kehan, The Spectral Stress VaR (SSVaR) (June 18, 2015). University Ca' Foscari of Venice, Dept. of Economics Research Paper Series No. 17/WP/2015, Available at SSRN: https://ssrn.com/abstract=2622391 or http://dx.doi.org/10.2139/ssrn.2622391

Dominique Guegan (Contact Author)

Université Paris I Panthéon-Sorbonne ( email )

106 avenue de lhopital
75634 Paris Cedex 13
Paris, IL
France

Bertrand Hassani

Université Paris I Panthéon-Sorbonne ( email )

17, rue de la Sorbonne
Paris, IL 75005
France

University College London - Department of Computer Science ( email )

United Kingdom

Kehan Li

Université Paris I Panthéon-Sorbonne ( email )

12 place du Panthéon
Paris, 75005
France

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