Uncertainty in historical Value-at-Risk: an alternative quantile-based risk measure

Dominique Guegan (), Bertrand K. 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
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

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

Abstract: The financial industry has extensively used quantile-based risk measures relying on the Value-at-Risk (VaR). They need to be estimated from relevant historical data set. Consequently, they contain uncertainty. We propose an alternative quantile-based risk measure (the Spectral Stress VaR) to capture the uncertainty in the historical VaR approach. This one provides flexibility to the risk manager to implement prudential regulatory framework. It can be a VaR based stressed risk measure. In the end we propose a stress testing application for it.

Keywords: Historical method; Uncertainty; Value-at-Risk; Stress risk measure; Tail risk measure; Prudential financial regulation; Stress testing (search for similar items in EconPapers)
Date: 2016-01
New Economics Papers: this item is included in nep-ban and nep-rmg
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Published in 2016

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