Capturing the intrinsic uncertainty of the VaR: Spectrum representation of a saddlepoint approximation for an estimator of the VaR

Dominique Guegan (), Bertrand K. Hassani () and Kehan Li ()
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Dominique Guegan: Centre d'Economie de la Sorbonne, https://cv.archives-ouvertes.fr/dominique-guegan
Bertrand K. Hassani: Grupo Santander et Centre d'Economie de la Sorbonne, https://centredeconomiesorbonne.univ-paris1.fr
Kehan Li: Centre d'Economie de la Sorbonne, https://centredeconomiesorbonne.univ-paris1.fr

Documents de travail du Centre d'Economie de la Sorbonne from Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne

Abstract: Though risk measurement is the core of most regulatory document, in both financial and insurance industries, risk managers and regulators pay little attention to the random behaviour of risk measures. To address this uncertainty, we provide a novel way to build a robust parametric confidence interval (CI) of Value-at-Risk (VaR) for different lengths of samples. We compute this CI from a saddlepoint approximation of the distribution of an estimator of VaR. Based on the CI, we create a spectrum representation that represents an area that we use to define a risk measure. We apply this methodology to risk management and stress testing providing an indicator of threats caused by events uncaptured in the traditional VaR methodology which can lead to dramatic failures

Keywords: Financial regulation; Value-at-Risk; Order statistic; Uncertainty; Saddlepoint approximation; Stress testing (search for similar items in EconPapers)
JEL-codes: C14 D81 G28 G32 (search for similar items in EconPapers)
Date: 2016-04, Revised 2016-07
New Economics Papers: this item is included in nep-rmg
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Persistent link: https://EconPapers.repec.org/RePEc:mse:cesdoc:16034r

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