Comparison of single distribution and mixture distribution models for modelling LGD
Comparison of single distribution and mixture distribution models for modelling LGD
Estimating Recovery Rate and Recovery Amount has taken a more importance in consumer credit because of both the new Basel Accord regulation and the increase in number of defaulters due to the recession.
We examine whether it is better to estimate Recovery Rate (RR) or Recovery amounts. We use linear regression and survival analysis models to model Recovery rate and Recovery amount, thus to predict Loss Given Default (LGD) for unsecured personal loans. We also look at the advantages and disadvantages of using single distribution model or mixture distribution models for default
recovery rate, linear regression, survival analysis, mixture distribution
University of Southampton
Zhang, Jie
21de2303-4727-4097-9b0f-ae43d95d052a
Thomas, Lyn C.
a3ce3068-328b-4bce-889f-965b0b9d2362
2009
Zhang, Jie
21de2303-4727-4097-9b0f-ae43d95d052a
Thomas, Lyn C.
a3ce3068-328b-4bce-889f-965b0b9d2362
Zhang, Jie and Thomas, Lyn C.
(2009)
Comparison of single distribution and mixture distribution models for modelling LGD
(Discussion Papers in Centre for Risk Research, CRR-09-04)
Southampton, UK.
University of Southampton
19pp.
Record type:
Monograph
(Discussion Paper)
Abstract
Estimating Recovery Rate and Recovery Amount has taken a more importance in consumer credit because of both the new Basel Accord regulation and the increase in number of defaulters due to the recession.
We examine whether it is better to estimate Recovery Rate (RR) or Recovery amounts. We use linear regression and survival analysis models to model Recovery rate and Recovery amount, thus to predict Loss Given Default (LGD) for unsecured personal loans. We also look at the advantages and disadvantages of using single distribution model or mixture distribution models for default
Text
CRR-09-04.pdf
- Version of Record
More information
Published date: 2009
Keywords:
recovery rate, linear regression, survival analysis, mixture distribution
Identifiers
Local EPrints ID: 71383
URI: http://eprints.soton.ac.uk/id/eprint/71383
PURE UUID: 7a3c16f1-ce1c-472a-91bf-f7b9c01a9d84
Catalogue record
Date deposited: 09 Feb 2010
Last modified: 13 Mar 2024 20:26
Export record
Contributors
Author:
Jie Zhang
Author:
Lyn C. Thomas
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics