EconPapers    
Economics at your fingertips  
 

Prediction of bank rating transition probabilities

Paraskevi Dimou, Alistair Milne () and Francesca Campolongo

No 520, Computing in Economics and Finance 2006 from Society for Computational Economics

Abstract: The objective of this paper is to determine whether information from equity markets, as summarized in the distance to default measure derived from Merton-MKMV, is useful for modeling and predicting bank credit ratings. We use the BankScope database and Bloomberg to build a data set comprising of 98 equity listed banks, from 8 English-speaking and Scandinavian countries, with annual accounting and daily ratings and equity price data from 1997 to 2004. We divide bank ratings into four broad credit risk classes. We then build an ordered-probit model of the current credit rating class, incorporating both accounting ratios and a Merton-type measure of distance to default. We find distance to default has no additional explanatory power for modeling current ratings, or predicting credit rating changes over a 6-month or 12-month horizon. We find some evidence that changes in distance-to-default, have some additional explanatory power for changes in ratings

Date: 2006-07-04
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sce:scecfa:520

Access Statistics for this paper

More papers in Computing in Economics and Finance 2006 from Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F. Baum ().

 
Page updated 2025-04-03
Handle: RePEc:sce:scecfa:520