GCPM: A ?exible package to explore credit portfolio risk

In this article we introduce the novel GCPM package, which represents a generalized credit portfolio model framework. The package includes two of the most popular mod- eling approaches in the banking industry namely the CreditRisk+ and the CreditMetrics model and allows to perform several sensitivit...

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Main Authors: Kevin Jakob, Matthias Fischer
Format: Article
Language:English
Published: Austrian Statistical Society 2016-02-01
Series:Austrian Journal of Statistics
Online Access:http://www.ajs.or.at/index.php/ajs/article/view/87
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spelling doaj-f716e7dafb644547858fcd696540b92b2021-04-22T12:34:26ZengAustrian Statistical SocietyAustrian Journal of Statistics1026-597X2016-02-0145110.17713/ajs.v45i1.87GCPM: A ?exible package to explore credit portfolio riskKevin Jakob0Matthias Fischer1Universität AugsburgDepartment of Statistics and Econometric Universität Erlangen-Nürnberg 90402 Nürnberg, GermanyIn this article we introduce the novel GCPM package, which represents a generalized credit portfolio model framework. The package includes two of the most popular mod- eling approaches in the banking industry namely the CreditRisk+ and the CreditMetrics model and allows to perform several sensitivity analysis with respect to distributional or functional assumptions. Therefore, besides the pure quanti?cation of credit portfolio risk, the package can be used to explore certain aspects of model risk individually for every arbitrary credit portfolio. In order to guarantee maximum ?exibility, most of the models utilize a Monte Carlo simulation, which is implemented in C++, to achieve the loss dis- tribution. Furthermore, the package also o?ers the possibilities to apply simple pooling techniques to speed up calculations for large portfolios as well as a general importance sample approach. The article concludes with a comprehensive example demonstrating the ?exibility of the package.http://www.ajs.or.at/index.php/ajs/article/view/87
collection DOAJ
language English
format Article
sources DOAJ
author Kevin Jakob
Matthias Fischer
spellingShingle Kevin Jakob
Matthias Fischer
GCPM: A ?exible package to explore credit portfolio risk
Austrian Journal of Statistics
author_facet Kevin Jakob
Matthias Fischer
author_sort Kevin Jakob
title GCPM: A ?exible package to explore credit portfolio risk
title_short GCPM: A ?exible package to explore credit portfolio risk
title_full GCPM: A ?exible package to explore credit portfolio risk
title_fullStr GCPM: A ?exible package to explore credit portfolio risk
title_full_unstemmed GCPM: A ?exible package to explore credit portfolio risk
title_sort gcpm: a ?exible package to explore credit portfolio risk
publisher Austrian Statistical Society
series Austrian Journal of Statistics
issn 1026-597X
publishDate 2016-02-01
description In this article we introduce the novel GCPM package, which represents a generalized credit portfolio model framework. The package includes two of the most popular mod- eling approaches in the banking industry namely the CreditRisk+ and the CreditMetrics model and allows to perform several sensitivity analysis with respect to distributional or functional assumptions. Therefore, besides the pure quanti?cation of credit portfolio risk, the package can be used to explore certain aspects of model risk individually for every arbitrary credit portfolio. In order to guarantee maximum ?exibility, most of the models utilize a Monte Carlo simulation, which is implemented in C++, to achieve the loss dis- tribution. Furthermore, the package also o?ers the possibilities to apply simple pooling techniques to speed up calculations for large portfolios as well as a general importance sample approach. The article concludes with a comprehensive example demonstrating the ?exibility of the package.
url http://www.ajs.or.at/index.php/ajs/article/view/87
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AT matthiasfischer gcpmaexiblepackagetoexplorecreditportfoliorisk
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