Distortion Risk Measures or the Transformation of Unimodal Distributions into Multimodal Functions

Dominique Guegan () and Bertrand Hassani ()
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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 Hassani: 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 particular subject of this paper, is to construct a general framework that can consider and analyse in the same time upside and downside risks. This paper offers a comparative analysis of concept risk measures, we focus on quantile based risk measure (ES and VaR), spectral risk measure and distortion risk measure. After introducing each measure, we investigate their interest and limit. Knowing that quantile based risk measure cannot capture correctly the risk aversion of risk manager and spectral risk measure can be inconsistent to risk aversion, we propose and develop a new distortion risk measure extending the work of Wang (2000) [38] and Sereda et al (2010) [34]. Finally, we provide a comprehensive analysis of the feasibility of this approach using the S&P500 data set from o1/01/1999 to 31/12/2011.

Keywords: Risk; distorsion measures; Risques; VaR; mesure de distorsion (search for similar items in EconPapers)
Date: 2014-02
New Economics Papers: this item is included in nep-rmg and nep-upt
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Citations: View citations in EconPapers (6)

Published in 2014

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Working Paper: Distortion Risk Measures or the Transformation of Unimodal Distributions into Multimodal Functions (2014)
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