IDEAS home Printed from
   My bibliography  Save this paper

Transformation kernel density estimation of actuarial loss functions


  • Catalina Bolance (Universitat de Barcelona)
  • Montserrat Guillen (Universitat de Barcelona)
  • Jens Perch Nielsen (City University London)

    (Universitat de Barcelona)


A transformation kernel density estimator that is suitable for heavy-tailed distributions is discussed. Using a truncated Beta transformation, the choice of the bandwidth parameter becomes straightforward. An application to insurance data and the calculation of the value-at-risk are presented.

Suggested Citation

  • Catalina Bolance (Universitat de Barcelona) & Montserrat Guillen (Universitat de Barcelona) & Jens Perch Nielsen (City University London), 2009. "Transformation kernel density estimation of actuarial loss functions," Working Papers in Economics 219, Universitat de Barcelona. Espai de Recerca en Economia.
  • Handle: RePEc:bar:bedcje:2009219

    Download full text from publisher

    File URL:
    Download Restriction: no

    More about this item

    JEL classification:

    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    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:bar:bedcje:2009219. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Espai de Recerca en Economia). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.