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On modeling credit defaults: A probabilistic Boolean network approach

On modeling credit defaults: A probabilistic Boolean network approach One of the central issues in credit risk measurement and management is modeling and predicting correlated defaults. In this paper we introduce a novel model to investigate the relationship between correlated defaults of different industrial sectors and business cycles as well as the impacts of business cycles on modeling and predicting correlated defaults using the Probabilistic Boolean Network (PBN). The key idea of the PBN is to decompose a transition probability matrix describing correlated defaults of different sectors into several BN matrices which contain information about business cycles. An efficient estimation method based on an entropy approach is used to estimate the model parameters. Using real default data, we build a PBN for explaining the default structure and making reasonably good predictions of joint defaults in different sectors. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Risk and Decision Analysis IOS Press

On modeling credit defaults: A probabilistic Boolean network approach

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References (39)

Publisher
IOS Press
Copyright
Copyright © 2013 by IOS Press, Inc
ISSN
1569-7371
eISSN
1875-9173
DOI
10.3233/RDA-2012-0086
Publisher site
See Article on Publisher Site

Abstract

One of the central issues in credit risk measurement and management is modeling and predicting correlated defaults. In this paper we introduce a novel model to investigate the relationship between correlated defaults of different industrial sectors and business cycles as well as the impacts of business cycles on modeling and predicting correlated defaults using the Probabilistic Boolean Network (PBN). The key idea of the PBN is to decompose a transition probability matrix describing correlated defaults of different sectors into several BN matrices which contain information about business cycles. An efficient estimation method based on an entropy approach is used to estimate the model parameters. Using real default data, we build a PBN for explaining the default structure and making reasonably good predictions of joint defaults in different sectors.

Journal

Risk and Decision AnalysisIOS Press

Published: Jan 1, 2013

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