@techreport{Hamerle2004Forecasting,
abstract = {The main challenge of forecasting credit default risk in loan portfolios is forecasting the
default probabilities and the default correlations. We derive a Merton-style threshold-value
model for the default probability which treats the asset value of a firm as unknown and uses a
factor model instead. In addition, we demonstrate how default correlations can be easily
modeled. The empirical analysis is based on a large data set of German firms provided by
Deutsche Bundesbank. We find that the inclusion of variables which are correlated with the
business cycle improves the forecasts of default probabilities. Asset and default correlations
depend on the factors used to model default probabilities. The better the point-in-time
calibration of the estimated default probabilities, the smaller the estimated correlations. Thus,
correlations and default probabilities should always be estimated simultaneously.},
author = {Alfred Hamerle and Thilo Liebig and Harald Scheule},
copyright = {http://www.econstor.eu/dspace/Nutzungsbedingungen},
keywords = {C41; G21; C23; 330; asset correlation; bank regulation; Basel II; credit risk; default correlation; default probability; logit model; probit model; Kreditrisiko; Portfolio-Management; Prognoseverfahren; Makro\"{o}konomischer Einfluss; Sch\"{a}tzung; Deutschland},
language = {eng},
number = {2004,01},
title = {Forecasting Credit Portfolio Risk},
type = {Discussion Paper, Series 2: Banking and Financial Supervision},
url = {http://hdl.handle.net/10419/19728},
year = {2004}
}
