IDEAS home Printed from https://ideas.repec.org/a/taf/lstaxx/v46y2017i18p9075-9085.html
   My bibliography  Save this article

Some novel results on pairwise quasi-asymptotical independence with applications to risk theory

Author

Listed:
  • Shijie Wang
  • Cen Chen
  • Xuejun Wang

Abstract

In this article we obtain some novel results on pairwise quasi-asymptotically independent (pQAI) random variables. Concretely speaking, let X1, …, Xn be n real-valued pQAI random variables, and W1, …, Wn be another n non negative and arbitrarily dependent random variables, but independent of X1, …, Xn. Under some mild conditions, we prove that W1X1, …, WnXn are still pQAI as well. Our result is in a general setting whether the primary random variables X1, …, Xn are heavy-tailed or not. Finally, a special case of above result is applied to risk theory for investigating the finite-time ruin probability for a discrete-time risk model with a wide type of dependence structure.

Suggested Citation

  • Shijie Wang & Cen Chen & Xuejun Wang, 2017. "Some novel results on pairwise quasi-asymptotical independence with applications to risk theory," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(18), pages 9075-9085, September.
  • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:18:p:9075-9085
    DOI: 10.1080/03610926.2016.1202287
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03610926.2016.1202287
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/03610926.2016.1202287?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mantas Dirma & Saulius Paukštys & Jonas Šiaulys, 2021. "Tails of the Moments for Sums with Dominatedly Varying Random Summands," Mathematics, MDPI, vol. 9(8), pages 1-26, April.
    2. Jaunė, Eglė & Šiaulys, Jonas, 2022. "Asymptotic risk decomposition for regularly varying distributions with tail dependence," Applied Mathematics and Computation, Elsevier, vol. 427(C).
    3. Leipus, Remigijus & Paukštys, Saulius & Šiaulys, Jonas, 2021. "Tails of higher-order moments of sums with heavy-tailed increments and application to the Haezendonck–Goovaerts risk measure," Statistics & Probability Letters, Elsevier, vol. 170(C).

    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:46:y:2017:i:18:p:9075-9085. 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.