Estimating Probabilities of Default
36 Pages Posted: 28 Jul 2004
Date Written: July 2004
Abstract
In this paper we conduct a systematic comparison of confidence intervals around estimated probabilities of default (PD) using several analytical approaches from large sample theory as well as bootstrapped small-sample confidence intervals. We do so for two different PD estimation methods, cohort and duration (intensity), using 22 years of credit ratings data. We find that the bootstrapped intervals for the duration based estimates are surprisingly tight when compared to the more commonly used (asymptotic) Wald interval. We find that even with these relatively tight confidence intervals, it is impossible to distinguish notch-level PDs for investment grade ratings, e.g. a PD(AA-) from a PD(A+). However, once the speculative grade barrier is crossed, we are able to distinguish quite cleanly notch-level estimated default probabilities. Conditioning on the state of the business cycle helps: It is easier to distinguish adjacent PDs in recessions than in expansions.
Keywords: Risk management, credit risk, bootstrap, confidence intervals
JEL Classification: G21, G28, C16
Suggested Citation: Suggested Citation
Do you have a job opening that you would like to promote on SSRN?
Recommended Papers
-
Confidence Sets for Continuous-Time Rating Transition Probabilities
-
Measurement and Estimation of Credit Migration Matrices
By Yusuf Jafry and Til Schuermann
-
Rating Transitions and Defaults Conditional on Watchlist, Outlook and Rating History
-
Credit Rating Dynamics and Markov Mixture Models
By Halina Frydman and Til Schuermann
-
Credit Rating Dynamics and Markov Mixture Models
By Halina Frydman and Til Schuermann
-
Pricing Credit Derivatives with Rating Transitions
By Viral V. Acharya, Sanjiv Ranjan Das, ...
-
Pricing Credit Derivatives with Rating Transitions
By Viral V. Acharya, Sanjiv Ranjan Das, ...
-
Pricing Credit Derivatives with Rating Transitions
By Viral V. Acharya, Sanjiv Ranjan Das, ...