Incorporating Contagion in Portfolio Credit Risk Models Using Network Theory

Portfolio credit risk models estimate the range of potential losses due to defaults or deteriorations in credit quality. Most of these models perceive default correlation as fully captured by the dependence on a set of common underlying risk factors. In light of empirical evidence, the ability of su...

Full description

Bibliographic Details
Main Authors: Ioannis Anagnostou, Sumit Sourabh, Drona Kandhai
Format: Article
Language:English
Published: Hindawi-Wiley 2018-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2018/6076173
id doaj-933823d086d449be9e57984ecfff837e
record_format Article
spelling doaj-933823d086d449be9e57984ecfff837e2020-11-24T20:49:14ZengHindawi-WileyComplexity1076-27871099-05262018-01-01201810.1155/2018/60761736076173Incorporating Contagion in Portfolio Credit Risk Models Using Network TheoryIoannis Anagnostou0Sumit Sourabh1Drona Kandhai2Computational Science Lab, University of Amsterdam, Science Park 904, 1098XH Amsterdam, NetherlandsComputational Science Lab, University of Amsterdam, Science Park 904, 1098XH Amsterdam, NetherlandsComputational Science Lab, University of Amsterdam, Science Park 904, 1098XH Amsterdam, NetherlandsPortfolio credit risk models estimate the range of potential losses due to defaults or deteriorations in credit quality. Most of these models perceive default correlation as fully captured by the dependence on a set of common underlying risk factors. In light of empirical evidence, the ability of such a conditional independence framework to accommodate for the occasional default clustering has been questioned repeatedly. Thus, financial institutions have relied on stressed correlations or alternative copulas with more extreme tail dependence. In this paper, we propose a different remedy—augmenting systematic risk factors with a contagious default mechanism which affects the entire universe of credits. We construct credit stress propagation networks and calibrate contagion parameters for infectious defaults. The resulting framework is implemented on synthetic test portfolios wherein the contagion effect is shown to have a significant impact on the tails of the loss distributions.http://dx.doi.org/10.1155/2018/6076173
collection DOAJ
language English
format Article
sources DOAJ
author Ioannis Anagnostou
Sumit Sourabh
Drona Kandhai
spellingShingle Ioannis Anagnostou
Sumit Sourabh
Drona Kandhai
Incorporating Contagion in Portfolio Credit Risk Models Using Network Theory
Complexity
author_facet Ioannis Anagnostou
Sumit Sourabh
Drona Kandhai
author_sort Ioannis Anagnostou
title Incorporating Contagion in Portfolio Credit Risk Models Using Network Theory
title_short Incorporating Contagion in Portfolio Credit Risk Models Using Network Theory
title_full Incorporating Contagion in Portfolio Credit Risk Models Using Network Theory
title_fullStr Incorporating Contagion in Portfolio Credit Risk Models Using Network Theory
title_full_unstemmed Incorporating Contagion in Portfolio Credit Risk Models Using Network Theory
title_sort incorporating contagion in portfolio credit risk models using network theory
publisher Hindawi-Wiley
series Complexity
issn 1076-2787
1099-0526
publishDate 2018-01-01
description Portfolio credit risk models estimate the range of potential losses due to defaults or deteriorations in credit quality. Most of these models perceive default correlation as fully captured by the dependence on a set of common underlying risk factors. In light of empirical evidence, the ability of such a conditional independence framework to accommodate for the occasional default clustering has been questioned repeatedly. Thus, financial institutions have relied on stressed correlations or alternative copulas with more extreme tail dependence. In this paper, we propose a different remedy—augmenting systematic risk factors with a contagious default mechanism which affects the entire universe of credits. We construct credit stress propagation networks and calibrate contagion parameters for infectious defaults. The resulting framework is implemented on synthetic test portfolios wherein the contagion effect is shown to have a significant impact on the tails of the loss distributions.
url http://dx.doi.org/10.1155/2018/6076173
work_keys_str_mv AT ioannisanagnostou incorporatingcontagioninportfoliocreditriskmodelsusingnetworktheory
AT sumitsourabh incorporatingcontagioninportfoliocreditriskmodelsusingnetworktheory
AT dronakandhai incorporatingcontagioninportfoliocreditriskmodelsusingnetworktheory
_version_ 1716806366303092736