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Parameterizing Credit Risk Models
Company: University of Regensburg
Company Url: Click here to open
Year Of Publication: 2003
Month Of Publication: December
Pages: 36
Download Count: 1492
View Count: 7773
Comment Num: 0
Language: EN
Source: article
Who Can Read: Free
Date: 6-18-2004
Publisher: Administrator
Summary
Approaches for modeling and estimating individual credit risk have been considerably improved during the lastyears, and latterly practitioners and researchers in the banking industry increasingly focus on quantification ofportfolio credit risk. The main problem of this task is the lack of adequate time series of default data. Thereforethere is little empirical evidence on the relevant input parameters for the various credit risk modeling approaches.As a consequence calculations of economic capital may yield very different results and internal models will notbe envisaged for the determination of regulatory capital requirements. The present contribution firstly presentsthree popular portfolio credit risk models and shows how they can be comparably parameterized using a likelihoodframework. Then the respective input parameters of all three models are estimated from a large databaseusing a time-series of German corporate bankruptcies. Several restrictions on the available information set areintroduced and compared. At last we analyze the forecasted loss distributions generated by each model. We findthat the differences of the outcomes are very small when our empirical estimates are used. Hence, model riskmay be considerably reduced.
Author(s)
Hamerle, Alfred Sign in to follow this author
Roesch, Daniel Sign in to follow this author
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