IDEAS home Printed from https://ideas.repec.org/a/rsk/journ0/2160424.html
   My bibliography  Save this article

Failure discrimination by semi-definite programming using a maximal margin ellipsoidal surface

Author

Listed:
  • Yohei Okada
  • Hiroshi Konno

Abstract

ABSTRACT We propose a new approach for failure discriminant analysis. The basic idea of the new method is to separate multi dimensional financial data corresponding to ongoing and failed companies by an ellipsoidal surface which is estimated by using a maximal margin hyperplane. We introduce two kinds of norms to construct the surface and compare the precision of prediction with other models including a semi-definite logit model.

Suggested Citation

  • Yohei Okada & Hiroshi Konno, . "Failure discrimination by semi-definite programming using a maximal margin ellipsoidal surface," Journal of Computational Finance, Journal of Computational Finance.
    • Handle: RePEc:rsk:journ0:2160424
    as

    Download full text from publisher

    File URL: https://www.risk.net/journal-of-computational-finance/2160424/failure-discrimination-by-semi-definite-programming-using-a-maximal-margin-ellipsoidal-surface
    Download Restriction: no
    ---><---

    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:rsk:journ0:2160424. 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: Thomas Paine (email available below). General contact details of provider: https://www.risk.net/journal-of-computational-finance .

    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.