Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/10419/19728
Title: Forecasting Credit Portfolio Risk
Keywords: C41
G21
C23
ddc:330
asset correlation
bank regulation
Basel II
credit risk
default correlation
default probability
logit model
probit model
Kreditrisiko
Portfolio-Management
Prognoseverfahren
Makroökonomischer Einfluss
Schätzung
Deutschland
Issue Date: 16-Oct-2013
Description: 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.
URI: http://koha.mediu.edu.my:8181/xmlui/handle/10419/19728
Other Identifiers: http://hdl.handle.net/10419/19728
ppn:391295780
RePEc:zbw:bubdp2:2227
Appears in Collections:EconStor

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