IDEAS home Printed from https://ideas.repec.org/p/osf/inarxi/wg7qa_v1.html
   My bibliography  Save this paper

Univariate Credibility as a Boundary-Value Problem, A Symbolic Green’s Function Method (Regular Case)

Author

Listed:

    Abstract

    Current formulas in credibility theory often calculate net premium as a weighted sum of the average experience of the policyholder and the average experience of the entire collection of policyholders. Because these formulas are linear, they are easy to use. Another advantage of linear formulas is that the estimate changes a fixed amount per change in claim experience, if an insurer uses which a formal, then the policyholder can predict the change in premium. In a series of writing, Young(1997,1998,2000) apply decision theory to develop a credibility formula that minimizes a loss function that is linear combination of a squared-error term and a second-derivative term or first order term. This loss function as a variational forms, is equivalent to fourth order or second order linear differential equation, respectively. This allows us for evaluation to Green's function computation via symbolic calculation to compute details of Green's function to obtain the solution.

    Suggested Citation

  • , 2017. "Univariate Credibility as a Boundary-Value Problem, A Symbolic Green’s Function Method (Regular Case)," INA-Rxiv wg7qa_v1, Center for Open Science.
  • Handle: RePEc:osf:inarxi:wg7qa_v1
    DOI: 10.31219/osf.io/wg7qa_v1
    as

    Download full text from publisher

    File URL: https://osf.io/download/5a10c001594d900263ca3f84/
    Download Restriction: no

    File URL: https://libkey.io/10.31219/osf.io/wg7qa_v1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    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:osf:inarxi:wg7qa_v1. 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: OSF (email available below). General contact details of provider: https://ios.io/preprints/inarxiv/discover .

    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.