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Devil In the Parameters
Company: Oliver, Wyman & Company
Year Of Publication: 1999
Month Of Publication: July
Pages: 30
Download Count: 734
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Comment Num: 0
Language: EN
Source:
Who Can Read: Free
Date: 3-26-2005
Publisher: Administrator
Summary
Several different credit portfolio models have been recently developed, andproposed for use as tools in measuring and managing credit risk. These modelsdiffer in both their calculation techniques and their parameters. Koyluoglu andHickman (1998) reveal that all of the proposed models share the same underlyingintuition, and their calculation techniques yield very similar results if the estimatesfor their input parameters are harmonized. This paper studies the effect ofparameter inconsistency by employing parameter estimates for three commerciallyavailable software packages – JP Morgan’s CreditMetrics, KMV’s Portfolio Managerand CSFP’s CreditRisk+ – which are generated from their “natural” data sets forCreditMetrics and Portfolio Manager, and from historical default rate volatility forCreditRisk+. Two single factor/single parameter models are also included forcomparison. The results demonstrate that, under these conditions, the modelsproduce significantly different results for identical portfolios, at both the aggregateand contributory risk levels. Obviously, such differences imply differentrecommendations for credit risk management, risk-based pricing and portfoliooptimization. In combination with the earlier Koyluoglu/Hickman paper, the resultsof this study suggest that users seeking to select a model should focus more on thecomparative quality of a model’s parameter estimates than the nature of itscalculation pro
Author(s)
Koyluoglu, H. Ugur Sign in to follow this author
Bangia, Anil Sign in to follow this author
Garside, Thomas Sign in to follow this author
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