IDEAS home Printed from https://ideas.repec.org/a/bla/jtsera/v13y1992i1p79-94.html
   My bibliography  Save this article

Threshold Time Series Models As Multimodal Distribution Jump Processes

Author

Listed:
  • Vance L. Martin

Abstract

. Recent contributions by Tong and others in modelling time series exhibiting threshold points have generally been based on approximating non‐linear processes by piecewise linear time series models. In this paper we provide an alternative framework in which to model time series displaying jump behaviour by using a multimodal conditional distribution to capture the jump process. Each subordinate model of the distribution is determined by an autoregressive process, and jump behaviour occurs when the relative heights of the modes of the distribution change whilst the threshold points are identified by the antimodes of the distribution. This class of models is referred to as multipredictor autoregressive time series (MATS).

Suggested Citation

  • Vance L. Martin, 1992. "Threshold Time Series Models As Multimodal Distribution Jump Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 13(1), pages 79-94, January.
    • Handle: RePEc:bla:jtsera:v:13:y:1992:i:1:p:79-94
    DOI: 10.1111/j.1467-9892.1992.tb00095.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-9892.1992.tb00095.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1467-9892.1992.tb00095.x?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
    ---><---

    Citations

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


    Cited by:

    1. Tom Pak-wing Fong & Chun-shan Wong, 2008. "Stress Testing Banks' Credit Risk Using Mixture Vector Autoregressive Models," Working Papers 0813, Hong Kong Monetary Authority.

    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:bla:jtsera:v:13:y:1992:i:1:p:79-94. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782 .

    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.