A Random Matrix Approach to Credit Risk

We estimate generic statistical properties of a structural credit risk model by considering an ensemble of correlation matrices. This ensemble is set up by Random Matrix Theory. We demonstrate analytically that the presence of correlations severely limits the effect of diversification in a credit po...

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Detalles Bibliográficos
Autores principales: Münnix, Michael C., Schäfer, Rudi, Guhr, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4031172/
https://www.ncbi.nlm.nih.gov/pubmed/24853864
http://dx.doi.org/10.1371/journal.pone.0098030
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author Münnix, Michael C.
Schäfer, Rudi
Guhr, Thomas
author_facet Münnix, Michael C.
Schäfer, Rudi
Guhr, Thomas
author_sort Münnix, Michael C.
collection PubMed
description We estimate generic statistical properties of a structural credit risk model by considering an ensemble of correlation matrices. This ensemble is set up by Random Matrix Theory. We demonstrate analytically that the presence of correlations severely limits the effect of diversification in a credit portfolio if the correlations are not identically zero. The existence of correlations alters the tails of the loss distribution considerably, even if their average is zero. Under the assumption of randomly fluctuating correlations, a lower bound for the estimation of the loss distribution is provided.
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spelling pubmed-40311722014-05-28 A Random Matrix Approach to Credit Risk Münnix, Michael C. Schäfer, Rudi Guhr, Thomas PLoS One Research Article We estimate generic statistical properties of a structural credit risk model by considering an ensemble of correlation matrices. This ensemble is set up by Random Matrix Theory. We demonstrate analytically that the presence of correlations severely limits the effect of diversification in a credit portfolio if the correlations are not identically zero. The existence of correlations alters the tails of the loss distribution considerably, even if their average is zero. Under the assumption of randomly fluctuating correlations, a lower bound for the estimation of the loss distribution is provided. Public Library of Science 2014-05-22 /pmc/articles/PMC4031172/ /pubmed/24853864 http://dx.doi.org/10.1371/journal.pone.0098030 Text en © 2014 Münnix et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Münnix, Michael C.
Schäfer, Rudi
Guhr, Thomas
A Random Matrix Approach to Credit Risk
title A Random Matrix Approach to Credit Risk
title_full A Random Matrix Approach to Credit Risk
title_fullStr A Random Matrix Approach to Credit Risk
title_full_unstemmed A Random Matrix Approach to Credit Risk
title_short A Random Matrix Approach to Credit Risk
title_sort random matrix approach to credit risk
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4031172/
https://www.ncbi.nlm.nih.gov/pubmed/24853864
http://dx.doi.org/10.1371/journal.pone.0098030
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