Forecasting credit migration matrices with business cycle effects—a model comparison
AbstractMigration matrices are considered a major determinant for credit risk management. They are widely used for credit value-at-risk determination, portfolio management or derivative pricing. It is well known that migration matrices show strong variations and cyclical behavior through time. We compare a factor model approach and numerical adjustment methods for estimation and forecasting of conditional migration matrices. Our findings show that the methods may lead to quite different forecasting results. Although the numerical adjustment methods fail to outperform the naive approach of taking previous year's migration matrix as an estimator, the one-factor model provides significantly better in-sample and out-of-sample results. Additionally, on the basis of a chosen risk-sensitive goodness-of-fit criteria, we are able to interpret the results in terms of risk.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal The European Journal of Finance.
Volume (Year): 14 (2008)
Issue (Month): 5 ()
Contact details of provider:
Web page: http://www.tandfonline.com/REJF20
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Dimitris Gavalas & Theodore Syriopoulos, 2014. "Bank Credit Risk Management and Rating Migration Analysis on the Business Cycle," International Journal of Financial Studies, MDPI, Open Access Journal, vol. 2(1), pages 122-143, March.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty).
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.