IDEAS home Printed from https://ideas.repec.org/h/spr/isochp/978-3-319-07524-2_2.html
   My bibliography  Save this book chapter

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

In: Future Perspectives in Risk Models and Finance

Author

Listed:
  • Dominique Guégan

    (University Paris 1 Panthéon-Sorbonne et New York University Polytechnic School of Engineering)

  • Bertrand Hassani

    (University Paris 1 Panthéon-Sorbonne)

Abstract

The particular subject of this paper, is to construct a general framework that can consider and analyse in the same time the 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 (J Risk Insurance 67, 2000) and Sereda et al. (Handbook of Portfolio Construction 2012). Finally we provide a comprehensive analysis of the feasibility of this approach using the S&P500 data set from 01/01/1999 to 31/12/2011.

Suggested Citation

  • Dominique Guégan & Bertrand Hassani, 2015. "Distortion Risk Measure or the Transformation of Unimodal Distributions into Multimodal Functions," International Series in Operations Research & Management Science, in: Alain Bensoussan & Dominique Guegan & Charles S. Tapiero (ed.), Future Perspectives in Risk Models and Finance, edition 127, pages 71-88, Springer.
    • Handle: RePEc:spr:isochp:978-3-319-07524-2_2
    DOI: 10.1007/978-3-319-07524-2_2
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Matyska, Branka, 2021. "Salience, systemic risk and spectral risk measures as capital requirements," Journal of Economic Dynamics and Control, Elsevier, vol. 125(C).
    2. Dominique Guegan & Bertrand Hassani & Kehan Li, 2017. "An alternative class of distortion operators alternative tools to generate asymmetrical multimodal distributions," Documents de travail du Centre d'Economie de la Sorbonne 17030, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    3. Bertrand K. Hassani & Wei Yang, 2016. "The Lila distribution and its applications in risk modelling," Documents de travail du Centre d'Economie de la Sorbonne 16068, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    4. Dominique Guegan & Bertrand Hassani & Kehan Li, 2017. "An alternative class of distortion operators," Post-Print halshs-01543251, HAL.
    5. Dominique Guegan & Bertrand Hassani & Kehan Li, 2017. "Impact of multimodality of distributions on VaR and ES calculations," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01491990, HAL.
    6. Dominique Guegan & Bertrand Hassani, 2016. "More Accurate Measurement for Enhanced Controls: VaR vs ES?," Post-Print halshs-01281940, HAL.
    7. Dominique Guegan & Bertrand Hassani, 2016. "More Accurate Measurement for Enhanced Controls: VaR vs ES?," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01281940, HAL.
    8. Dominique Guegan & Bertrand K. Hassani, 2019. "Risk Measurement," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02119256, HAL.
    9. Dominique Guegan & Bertrand Hassani & Kehan Li, 2017. "An alternative class of distortion operators," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01543251, HAL.
    10. Soren Bettels & Sojung Kim & Stefan Weber, 2022. "Multinomial Backtesting of Distortion Risk Measures," Papers 2201.06319, arXiv.org, revised Jan 2024.
    11. Inés Jiménez & Andrés Mora-Valencia & Trino-Manuel Ñíguez & Javier Perote, 2020. "Portfolio Risk Assessment under Dynamic (Equi)Correlation and Semi-Nonparametric Estimation: An Application to Cryptocurrencies," Mathematics, MDPI, vol. 8(12), pages 1-24, November.
    12. Dominique Guegan & Bertrand Hassani & Kehan Li, 2017. "Impact of multimodality of distributions on VaR and ES calculations," Post-Print halshs-01491990, HAL.
    13. Dominique Guegan & Bertrand Hassani & Kehan Li, 2017. "Impact of multimodality of distributions on VaR and ES calculations," Documents de travail du Centre d'Economie de la Sorbonne 17019, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    14. Bertrand K. Hassani & Wei Yang, 2016. "The Lila distribution and its applications in risk modelling," Post-Print halshs-01400186, HAL.
    15. Dominique Guegan & Bertrand K. Hassani, 2016. "More Accurate Measurement for Enhanced Controls: VaR vs ES?," Documents de travail du Centre d'Economie de la Sorbonne 16015, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:isochp:978-3-319-07524-2_2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.