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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/9810

Title: Modelling consumer credit risk via survival analysis
Authors: Cao, Ricardo
Vilar, Juan M.
Devia, Andres
VERAVERBEKE, Noel
Boucher, Jean-Philippe
Beran, Jan
Issue Date: 2009
Publisher: INST ESTADISTICA CATALUNYA-IDESCAT
Citation: SORT-STATISTICS AND OPERATIONS RESEARCH TRANSACTIONS, 33(1). p. 31-+ & 47
Abstract: Credit risk models are used by financial companies to evaluate in advance the insolvency risk caused by credits that enter into default. Many models for credit risk have been developed over the past few decades. In this paper, we focus on those models that can be formulated in terms of the probability of default by using survival analysis techniques. With this objective three different mechanisms are proposed based on the key idea of writing the default probability in terms of the conditional distribution function of the time to default. The first method is based on a Cox's regression model, the second approach uses generalized linear models under censoring and the third one is based on nonparametric kernel estimation, using the product-limit conditional distribution function estimator by Beran. The resulting nonparametric estimator of the default probability is proved to be consistent and asymptotically normal. An empirical study, based on modified real data, illustrates the three methods.
Notes: Cao, Ricardo - Univ Coruna, Fac Informat, Dept Matemat, La Coruna 15071, Spain. Veraverbeke, Noel - Univ Hasselt, Ctr Stat, Hasselt, Belgium. Boucher, Jean-Philippe - Univ Quebec, Dept Math, Montreal, PQ H3C 3P8, Canada. Beran, Jan - Univ Konstanz, Dept Math & Stat, D-7750 Constance, Germany.
URI: http://hdl.handle.net/1942/9810
Link to publication: http://www.idescat.cat/sort/sort331/33.1.1.cao-etal.pdf
ISI #: 000267358700001
ISSN: 1696-2281
Category: A1
Type: Journal Contribution
Validation: ecoom, 2010
Appears in Collections: Research publications

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