Credit Risk Models - Do They Deliver Their Promises? A Quantitative Assessment
AbstractWe develop a framework to assess the statistical significance of expected default frequency as calculated by credit risk models. This framework is then used to analyze the quality of two commercially available models that have become popular among practitioners: KMV Credit Monitor and RiskCalc from Moody's. Using a unique database of expected default probability from both vendors, we study both the consistency of predictions and their timeliness. We introduce the concept of cumulative accuracy profile (CAP), which allows to see in one curve the percentage of companies whose defualts were captured by the models one year in advance. We also use the Miller's information test to see if the models add information to the S&P rating. The result of the analysis indicates that these models indeed add relevant information not accounted for by rating alone. Moreover, with respect to rating agencies, the models predict defaults more than ten months in advance on average.
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.
Bibliographic InfoPaper provided by EconWPA in its series Risk and Insurance with number 0306003.
Length: 18 pages
Date of creation: 19 Jun 2003
Date of revision:
Note: Type of Document - Acrobat PDF; prepared on IBM PC; to print on HP A4; pages: 18 ; figures: included
Contact details of provider:
Web page: http://184.108.40.206
credit risk models; cumulative accuracy profile; risk modeling;
Other versions of this item:
- Gianluca Oderda & Michel M. Dacorogna & Tobias Jung, 2003. "Credit Risk Models - Do They Deliver Their Promises? A Quantitative Assessment," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 32(2), pages 177-195, 07.
- G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies
This paper has been announced in the following NEP Reports:
- NEP-ALL-2003-06-25 (All new papers)
- NEP-CFN-2003-06-25 (Corporate Finance)
- NEP-CMP-2003-06-25 (Computational Economics)
- NEP-FIN-2003-06-25 (Finance)
- NEP-MAC-2003-06-25 (Macroeconomics)
- NEP-RMG-2003-06-25 (Risk Management)
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.:
- Merton, Robert C, 1974.
"On the Pricing of Corporate Debt: The Risk Structure of Interest Rates,"
Journal of Finance,
American Finance Association, vol. 29(2), pages 449-70, May.
- Merton, Robert C., 1973. "On the pricing of corporate debt: the risk structure of interest rates," Working papers 684-73., Massachusetts Institute of Technology (MIT), Sloan School of Management.
- Nidhi Aggarwal & Manish Singh & Susan Thomas, 2012. "Do changes in distance-to-default anticipate changes in the credit rating?," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2012-010, Indira Gandhi Institute of Development Research, Mumbai, India.
- Denzler, Stefan M. & Dacorogna, Michel M. & Muller, Ulrich A. & McNeil, Alexander J., 2006.
"From default probabilities to credit spreads: Credit risk models do explain market prices,"
Finance Research Letters,
Elsevier, vol. 3(2), pages 79-95, June.
- Stefan Denzler & Michel M. Dacorogna & Ulrich A. Mueller & Alexander McNeil, 2005. "From Default Probabilities To Credit Spreads: Credit Risk Models Do Explain Market Prices," Finance 0504011, EconWPA.
- Li, Ming-Yuan Leon & Miu, Peter, 2010. "A hybrid bankruptcy prediction model with dynamic loadings on accounting-ratio-based and market-based information: A binary quantile regression approach," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 818-833, September.
- Agarwal, Vineet & Taffler, Richard, 2008. "Comparing the performance of market-based and accounting-based bankruptcy prediction models," Journal of Banking & Finance, Elsevier, vol. 32(8), pages 1541-1551, August.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (EconWPA).
If references are entirely missing, you can add them using this form.