IDEAS home Printed from https://ideas.repec.org/a/bla/irvfin/v5y2005i1-2p55-74.html
   My bibliography  Save this article

The SCoD Model: Analyzing Durations with a Semiparametric Copula Approach

Author

Listed:
  • CORNELIA SAVU
  • WING LON NG

Abstract

This paper applies a new methodology for modeling order durations of ultra‐high‐frequency data using copulas. While the class of common Autoregressive Conditional Duration models are characterized by strict parameterizations and high computational burden, the semiparametric copula approach proposed here offers more flexibility in modeling the dynamic duration process by separating the marginal distributions of waiting times from their temporal dependence structure. Comparing both frameworks as to their density forecast abilities, the Semiparametric Copula Duration model clearly shows a better performance.

Suggested Citation

  • Cornelia Savu & Wing Lon Ng, 2005. "The SCoD Model: Analyzing Durations with a Semiparametric Copula Approach," International Review of Finance, International Review of Finance Ltd., vol. 5(1‐2), pages 55-74, March.
    • Handle: RePEc:bla:irvfin:v:5:y:2005:i:1-2:p:55-74
    DOI: 10.1111/j.1468-2443.2006.00051.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1468-2443.2006.00051.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1468-2443.2006.00051.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. Wing Lon Ng, 2006. "Overreaction and Multiple Tail Dependence at the High-frequency Level — The Copula Rose," SFB 649 Discussion Papers SFB649DP2006-086, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Brendan K. Beare & Juwon Seo, 2015. "Vine Copula Specifications for Stationary Multivariate Markov Chains," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(2), pages 228-246, March.
    3. Penikas, H., 2010. "Financial Applications of Copula-Models," Journal of the New Economic Association, New Economic Association, issue 7, pages 24-44.

    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:irvfin:v:5:y:2005:i:1-2:p:55-74. 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=1369-412X .

    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.