Measuring risks in the extreme tail: The extreme VaR and its confidence interval
Dominique Guegan (),
Bertrand Hassani () and
Kehan Li ()
Additional contact information
Dominique Guegan: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique
Bertrand 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
Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) from HAL
Abstract:
Contrary to the current regulatory trend concerning 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 to measure 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 using Smirnov's result (Smirnov, 1949 [24]) and the second Zhu and Zhou's result (Zhu and Zhou, 2009 [25]), showing that this last one is robust when we use finite samples. We compare our approach with other methodologies which are based on bootstrapping techniques, Christoffersen et al. (2005) [7], 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 financial crisis, for identifying potential violations of the VaR during turmoil periods on financial markets.
Keywords: Extreme risk; Extreme Value-at-Risk; Confidence interval; Asymptotic theory; Stress testing; Regulation (search for similar items in EconPapers)
Date: 2017-01
New Economics Papers: this item is included in nep-ban and nep-rmg
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-01317391v3
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Published in 2017
Downloads: (external link)
https://shs.hal.science/halshs-01317391v3/document (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:hal:cesptp:halshs-01317391
Access Statistics for this paper
More papers in Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) from HAL
Bibliographic data for series maintained by CCSD ().