Parameterizing Credit Risk Models with Rating Data

By Mark Carey, Mark Hrycay. 2001

226 citations recorded by the source corpus.

Estimates of average default probabilities for borrowers assigned to each of a financial institution's internal credit risk rating grades are crucial inputs to portfolio credit risk models. Such models are increasingly used in setting financial institution capital structure, in internal control and compensation systems, in asset-backed security design, and are being considered for use in setting regulatory capital requirements for banks. This paper empirically examines properties of the major methods currently used to estimate average default probabilities by grade. Evidence of potential problems of bias, instability, and gaming is presented. With care, and perhaps judicious application of multiple methods, satisfactory estimates may be possible. In passing, evidence is presented about other properties of internal and rating-agency ratings.

Subfields: Accounting, Finance

View Paper: https://www.semanticscholar.org/paper/48978e6ab31f5eb2e3e330d076240a529a950d21

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Citations in the corpus

Procyclicality of the financial system and financial stability: issues and policy options (2001, methodology): “BIS Papers No 1 21 Box 2 Point-in-time and through-the-cycle measurement systems Figure 1 depicts the behaviour of a point-in-time system and a through-the-cycle risk measurement system and has been adapted from Carey and Hrycay (2000).”
Measuring and Managing Credit Risk (2004, background): “The question then is how many years should be required to perform such a complete analysis? Based on Moody’s database, Carey and Hrycay (2001) estimate that a historical sample between 11 and 18 years should be necessary20 in order to test the validity of internal ratings.”
Avoiding the rating bounce: why rating agencies are slow to react to new information (2005, background): “Carey and Hrycay (2001) and Kealhofer et al. (1998) find that agency ratings are relatively stable compared to alternative rating systems.”
On comparing the accuracy of default predictions in the rating industry (2006, unknown): “…of default are what is needed in modern capital allocation models and in setting reserves in the banking industry, so there is an enormous interest in correctly mapping letter grades into probabilities (Falkenstein 2000, Carey and Hrycay 2001, Carey 2002, Bluhm et al. 2003 11 and many others).”
Credit Ratings as Coordination Mechanisms (2006, unknown): “See Nickell, Perraudin and Varotto (1999), Carey and Hrycay (2001) , Altman, Bharath and Saunders (2002), and Saunders (2002) for some interesting work on the issue of credit-risk models.”