Parameterizing Credit Risk Models with Rating Data

93 Pages Posted: 25 Jan 2001

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Mark Hrycay

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Mark Carey

Board of Governors of the Federal Reserve - Division of International Finance (IFDP) - International Banking Section

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Date Written: October 18, 2000

Abstract

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.

Suggested Citation

Hrycay, Mark and Carey, Mark, Parameterizing Credit Risk Models with Rating Data (October 18, 2000). FEDS Working Paper No. 2000-47. Available at SSRN: https://ssrn.com/abstract=249294 or http://dx.doi.org/10.2139/ssrn.249294

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