EconPapers    
Economics at your fingertips  
 

An Intensity Based Non-Parametric Default Model for Residential Mortgage Portfolios

Enrico De Giorgi ()

Risk and Insurance from University Library of Munich, Germany

Abstract: In April 2001 Swiss banks held over CHF 500 billion in mortgages. This important segment accounts for about 63\% of all the loan portfolios of Swiss banks. In this paper we restrict our attention to residential mortgages held by private clients, i.e. borrowers who finance their property by the loan and we model the probability distribution of the number of defaults using a non-parametric intensity based approach. We consider the time-to-default and, by conditioning on a set of predictors for the default event, we obtain a log-additive model for the conditional intensity process of the time-to-default, where the contribution of each predictor is described by a smooth function. We estimate the model by using a local scoring algorithm coming from the generalized additive model.

Keywords: default risk; default intensity; mortgages; generalized additive model. (search for similar items in EconPapers)
JEL-codes: C14 G11 G33 (search for similar items in EconPapers)
Date: 2002-09-04, Revised 2002-09-09
New Economics Papers: this item is included in nep-rmg and nep-ure
Note: Type of Document - Acrobat PDF; prepared on IBM PC; figures: included. RiskLab report
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://econwpa.ub.uni-muenchen.de/econ-wp/ri/papers/0209/0209001.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpri:0209001

Access Statistics for this paper

More papers in Risk and Insurance from University Library of Munich, Germany
Bibliographic data for series maintained by EconWPA ( this e-mail address is bad, please contact ).

 
Page updated 2025-03-20
Handle: RePEc:wpa:wuwpri:0209001