IDEAS home Printed from https://ideas.repec.org/a/taf/lstaxx/v47y2018i23p5867-5883.html
   My bibliography  Save this article

On a discrete interaction risk model with delayed claims and stochastic incomes under random discount rates

Author

Listed:
  • Yingchun Deng
  • Juan Liu
  • Ya Huang
  • Man Li
  • Jieming Zhou

Abstract

In this paper, we study a discrete interaction risk model with delayed claims and stochastic incomes in the framework of the compound binomial model. A generalized Gerber-Shiu discounted penalty function is proposed to analyse this risk model in which the interest rates follow a Markov chain with finite state space. We derive an explicit expression for the generating function of this Gerber-Shiu discounted penalty function. Furthermore, we derive a recursive formula and a defective renewal equation for the original Gerber-Shiu discounted penalty function. As an application, the joint distributions of the surplus one period prior to ruin and the deficit at ruin, as well as the probabilities of ruin are obtained. Finally, some numerical illustrations from a specific example are also given.

Suggested Citation

  • Yingchun Deng & Juan Liu & Ya Huang & Man Li & Jieming Zhou, 2018. "On a discrete interaction risk model with delayed claims and stochastic incomes under random discount rates," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 47(23), pages 5867-5883, December.
    • Handle: RePEc:taf:lstaxx:v:47:y:2018:i:23:p:5867-5883
    DOI: 10.1080/03610926.2017.1406518
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03610926.2017.1406518
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/03610926.2017.1406518?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:taf:lstaxx:v:47:y:2018:i:23:p:5867-5883. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/lsta .

    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.