IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this article

Dependent discrete risk processes –calculation of the probability of ruin

Listed author(s):
  • Stanislaw Heilpern


    (Department of Statistics, Wroclaw University of Economics)

Registered author(s):

    This paper is devoted to discrete processes of dependent risks. The random variables describing the time between claims can be dependent in such processes, unlike under the classical approach. The ruin problem is investigated and the probability of ruin is computed. The relation between the degree of dependence and the probability of ruin is studied. Three cases are presented. Different methods of characterizing the dependency structure are examined. First, strictly dependent times between claims are investigated. Next, the dependency structure is described using an Archimedean copula or using Markov chains. In the last case, three situations in which the probability of ruin can be exactly computed are presented. Numerical examples in which the claims have a geometric distribution are investigated. A regular relation between the probability of ruin and the degree of dependence is only observed in the Markov chain case.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL:
    Download Restriction: no

    Article provided by Wroclaw University of Technology, Institute of Organization and Management in its journal Operations Research and Decisions.

    Volume (Year): 2 (2010)
    Issue (Month): ()
    Pages: 59-76

    in new window

    Handle: RePEc:wut:journl:v:2:y:2010:p:59-76
    Contact details of provider: Web page:

    More information through EDIRC

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

    in new window

    1. Dickson, David C.M. & dos Reis, Alfredo D. Egídio & Waters, Howard R., 1995. "Some Stable Algorithms in Ruin Theory and Their Applications," ASTIN Bulletin: The Journal of the International Actuarial Association, Cambridge University Press, vol. 25(02), pages 153-175, November.
    2. Gerber, Hans U., 1988. "Mathematical Fun with the Compound Binomial Process," ASTIN Bulletin: The Journal of the International Actuarial Association, Cambridge University Press, vol. 18(02), pages 161-168, November.
    Full references (including those not matched with items on IDEAS)

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:wut:journl:v:2:y:2010:p:59-76. 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: (Piotr Wawrzynowski)

    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.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 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.

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.