Measuring risks in the tail: The extreme VaR and its confidence interval

Dominique Guegan (), Bertrand Hassani () and Kehan Li ()
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Dominique Guegan: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, Labex ReFi - UP1 - Université Paris 1 Panthéon-Sorbonne, IPAG Paris
Bertrand Hassani: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, Labex ReFi - UP1 - Université Paris 1 Panthéon-Sorbonne
Kehan Li: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, Labex ReFi - UP1 - Université Paris 1 Panthéon-Sorbonne

Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) from HAL

Abstract: Contrary to the current regulatory trend regarding extreme risks, the purpose of this paper is to emphasize the necessity of considering the Value-at-Risk (VaR) with extreme confidence levels like 99.9%, as an alternative way of measuring risks in the "extreme tail". Although the mathematical definition of the extreme VaR is trivial, its computation is challenging in practice, because the uncertainty of the extreme VaR may not be negligible for a finite amount of data. We begin to build confidence intervals around the unknown VaR. We build them using two different approaches, the first one uses the asymptotic Gaussian result and the second saddlepoint approach, the latter proves to be more robust when we use finite samples. We compare our approach with other methodologies which are based on bootstrapping techniques, focusing on the estimation of the extreme quantiles of a distribution. Finally, we apply these confidence intervals to perform a stress testing exercice with historical stock returns during the financial crisis, in order to identify potential violations of the VaR during periods of turmoil on financial markets.

Keywords: stress testing; asymptotic theory; extreme risk; Regulation; confidence interval; extreme Value-at-Risk (search for similar items in EconPapers)
Date: 2017-08-28
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Published in Risk and Decision Analysis, 2017, Risk and Decision Analysis, 6 (3), pp.213 - 224. ⟨10.3233/RDA-170128⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:cesptp:halshs-01592736

DOI: 10.3233/RDA-170128

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