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Devil in the Parameters

by H. Ugur Koyluoglu of Oliver, Wyman & Company,
Anil Bangia of Oliver, Wyman & Company, and
Thomas Garside of Oliver, Wyman & Company

July 26, 1999

Abstract: Several different credit portfolio models have been recently developed, and proposed for use as tools in measuring and managing credit risk. These models differ in both their calculation techniques and their parameters. Koyluoglu and Hickman (1998) reveal that all of the proposed models share the same underlying intuition, and their calculation techniques yield very similar results if the estimates for their input parameters are harmonized. This paper studies the effect of parameter inconsistency by employing parameter estimates for three commercially available software packages - JP Morgan's CreditMetrics, KMV's Portfolio Manager and CSFP's CreditRisk+ - which are generated from their "natural" data sets for CreditMetrics and Portfolio Manager, and from historical default rate volatility for CreditRisk+. Two single factor/single parameter models are also included for comparison. The results demonstrate that, under these conditions, the models produce significantly different results for identical portfolios, at both the aggregate and contributory risk levels. Obviously, such differences imply different recommendations for credit risk management, risk-based pricing and portfolio optimization. In combination with the earlier Koyluoglu/Hickman paper, the results of this study suggest that users seeking to select a model should focus more on the comparative quality of a model's parameter estimates than the nature of its calculation procedures.

Published in: RISK, Vol. 13, No. 3, (March 2002), pp. 26-30.

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