IDEAS home Printed from https://ideas.repec.org/a/rsk/journ1/2160587.html
   My bibliography  Save this article

Private firm default probabilities via statistical learning theory and utility maximization

Author

Listed:
  • Xuelong Zhou, Jinggang Huang, Craig Friedman, Robert Cangemi, Sven Sandow

Abstract

ABSTRACT We estimate real-world private firm default probabilities over a fixed time horizon. The default probabilities are conditioned on a vector of explanatory variables which include financial ratios, economic indicators and market prices. To estimate our model we apply a recently developed method from statistical learning theory. This method leads to a model that is particularly appropriate for financial market participants, who would use the model to make financial decisions. We compare our model with various benchmark models with respect to a number of performance measures. In all these tests our model outperformed the benchmark models. We discuss possible reasons for this outperformance.

Suggested Citation

Handle: RePEc:rsk:journ1:2160587
as

Download full text from publisher

File URL: https://www.risk.net/system/files/import/protected/digital_assets/4463/v2n1_zhou.pdf
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:journ1:2160587. 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-credit-risk .

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.