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Concurrent credit portfolio losses

We consider the problem of concurrent portfolio losses in two non-overlapping credit portfolios. In order to explore the full statistical dependence structure of such portfolio losses, we estimate their empirical pairwise copulas. Instead of a Gaussian dependence, we typically find a strong asymmetr...

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Detalles Bibliográficos
Autores principales: Sicking, Joachim, Guhr, Thomas, Schäfer, Rudi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5806874/
https://www.ncbi.nlm.nih.gov/pubmed/29425246
http://dx.doi.org/10.1371/journal.pone.0190263
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author Sicking, Joachim
Guhr, Thomas
Schäfer, Rudi
author_facet Sicking, Joachim
Guhr, Thomas
Schäfer, Rudi
author_sort Sicking, Joachim
collection PubMed
description We consider the problem of concurrent portfolio losses in two non-overlapping credit portfolios. In order to explore the full statistical dependence structure of such portfolio losses, we estimate their empirical pairwise copulas. Instead of a Gaussian dependence, we typically find a strong asymmetry in the copulas. Concurrent large portfolio losses are much more likely than small ones. Studying the dependences of these losses as a function of portfolio size, we moreover reveal that not only large portfolios of thousands of contracts, but also medium-sized and small ones with only a few dozens of contracts exhibit notable portfolio loss correlations. Anticipated idiosyncratic effects turn out to be negligible. These are troublesome insights not only for investors in structured fixed-income products, but particularly for the stability of the financial sector. JEL codes: C32, F34, G21, G32, H81.
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spelling pubmed-58068742018-02-23 Concurrent credit portfolio losses Sicking, Joachim Guhr, Thomas Schäfer, Rudi PLoS One Research Article We consider the problem of concurrent portfolio losses in two non-overlapping credit portfolios. In order to explore the full statistical dependence structure of such portfolio losses, we estimate their empirical pairwise copulas. Instead of a Gaussian dependence, we typically find a strong asymmetry in the copulas. Concurrent large portfolio losses are much more likely than small ones. Studying the dependences of these losses as a function of portfolio size, we moreover reveal that not only large portfolios of thousands of contracts, but also medium-sized and small ones with only a few dozens of contracts exhibit notable portfolio loss correlations. Anticipated idiosyncratic effects turn out to be negligible. These are troublesome insights not only for investors in structured fixed-income products, but particularly for the stability of the financial sector. JEL codes: C32, F34, G21, G32, H81. Public Library of Science 2018-02-09 /pmc/articles/PMC5806874/ /pubmed/29425246 http://dx.doi.org/10.1371/journal.pone.0190263 Text en © 2018 Sicking 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 (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Sicking, Joachim
Guhr, Thomas
Schäfer, Rudi
Concurrent credit portfolio losses
title Concurrent credit portfolio losses
title_full Concurrent credit portfolio losses
title_fullStr Concurrent credit portfolio losses
title_full_unstemmed Concurrent credit portfolio losses
title_short Concurrent credit portfolio losses
title_sort concurrent credit portfolio losses
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5806874/
https://www.ncbi.nlm.nih.gov/pubmed/29425246
http://dx.doi.org/10.1371/journal.pone.0190263
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