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

Dominique Guegan () and Bertrand K. Hassani ()
Additional contact information
Dominique Guegan: Centre d'Economie de la Sorbonne - Paris School of Economics, https://cv.archives-ouvertes.fr/dominique-guegan
Bertrand K. Hassani: Centre d'Economie de la Sorbonne et Grupo Santander

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

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; VaR; distortion measures (search for similar items in EconPapers)
JEL-codes: C1 C6 (search for similar items in EconPapers)
Pages: 22 pages
Date: 2014-02
New Economics Papers: this item is included in nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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ftp://mse.univ-paris1.fr/pub/mse/CES2014/14008.pdf (application/pdf)

Related works:
Working Paper: Distortion Risk Measures or the Transformation of Unimodal Distributions into Multimodal Functions (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:mse:cesdoc:14008

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