Survival Analysis in LGD Modeling
The paper proposes an application of the survival time analysis methodology to estimations of the Loss Given Default (LGD) parameter. The main advantage of the survival analysis approach compared to classical regression methods is that it allows exploiting partial recovery data. The model is also modified in order to improve performance of the appropriate goodness of fit measures. The empirical testing shows that the Cox proportional model applied to LGD modeling performs better than the linear and logistic regressions. In addition a significant improvement is achieved with the modified “pseudo” Cox LGD model.
|Date of creation:||Feb 2010|
|Date of revision:||Feb 2010|
|Contact details of provider:|| Postal: Opletalova 26, CZ-110 00 Prague|
Phone: +420 2 222112330
Fax: +420 2 22112304
Web page: http://ies.fsv.cuni.cz/
More information through EDIRC
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Edward Altman & Andrea Resti & Andrea Sironi, 2004. "Default Recovery Rates in Credit Risk Modelling: A Review of the Literature and Empirical Evidence," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 33(2), pages 183-208, 07.
- Sudheer Chava & Catalina Stefanescu & Stuart Turnbull, 2011. "Modeling the Loss Distribution," Management Science, INFORMS, vol. 57(7), pages 1267-1287, July.
- Greg M. Gupton, 2005. "Advancing Loss Given Default Prediction Models: How the Quiet Have Quickened," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 34(2), pages 185-230, 07.
- Jiří Witzany, 2009. "Unexpected Recovery Risk and LGD Discount Rate Determination," European Financial and Accounting Journal, University of Economics, Prague, vol. 2009(1), pages 61-84.
When requesting a correction, please mention this item's handle: RePEc:fau:wpaper:wp2010_02. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Lenka Herrmannova)
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.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.