IDEAS home Printed from https://ideas.repec.org/a/gam/jrisks/v12y2024i10p153-d1486192.html
   My bibliography  Save this article

Transmuted Distortion Functions for Measuring Risks

Author

Listed:
  • Muna Alkasasbeh

    (Department of Statistics, Actuarial and Data Sciences, Central Michigan University, Mount Pleasant, MI 48859, USA)

  • Carl Lee

    (Department of Statistics, Actuarial and Data Sciences, Central Michigan University, Mount Pleasant, MI 48859, USA)

  • Felix Famoye

    (Department of Statistics, Actuarial and Data Sciences, Central Michigan University, Mount Pleasant, MI 48859, USA)

Abstract

This paper introduces a new family of distortion functions for measuring risks, developed using transmutation techniques. We identify the parameter spaces where the proposed distortions exhibit concavity. Considering that the choice of distortion parameters can be influenced by political factors or users’ risk aversion levels, we generate plots of the distortion functions to examine how these parameters impact the tasks and users’ attitudes toward risk. The coherent properties of the resulting risk measures are explored, outlining the conditions under which the transmuted Kumaraswamy and transmuted truncated normal distortions ensure coherence. Numerical analyses demonstrate the effects of parameter variations on the derived risk measures, highlighting the effectiveness of the proposed distortion functions in accurately assessing risk.

Suggested Citation

  • Muna Alkasasbeh & Carl Lee & Felix Famoye, 2024. "Transmuted Distortion Functions for Measuring Risks," Risks, MDPI, vol. 12(10), pages 1-17, September.
    • Handle: RePEc:gam:jrisks:v:12:y:2024:i:10:p:153-:d:1486192
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-9091/12/10/153/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-9091/12/10/153/
    Download Restriction: no
    ---><---

    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:gam:jrisks:v:12:y:2024:i:10:p:153-:d:1486192. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.