Artikel

Extreme portfolio loss correlations in credit risk

The stability of the financial system is associated with systemic risk factors such as the concurrent default of numerous small obligors. Hence, it is of utmost importance to study the mutual dependence of losses for different creditors in the case of large, overlapping credit portfolios. We analytically calculate the multivariate joint loss distribution of several credit portfolios on a non-stationary market. To take fluctuating asset correlations into account, we use an random matrix approach which preserves, as a much appreciated side effect, analytical tractability and drastically reduces the number of parameters. We show that, for two disjoint credit portfolios, diversification does not work in a correlated market. Additionally, we find large concurrent portfolio losses to be rather likely. We show that significant correlations of the losses emerge not only for large portfolios with thousands of credit contracts, but also for small portfolios consisting of a few credit contracts only. Furthermore, we include subordination levels, which were established in collateralized debt obligations to protect the more senior tranches from high losses. We analytically corroborate the observation that an extreme loss of the subordinated creditor is likely to also yield a large loss of the senior creditor.

Sprache
Englisch

Erschienen in
Journal: Risks ; ISSN: 2227-9091 ; Volume: 6 ; Year: 2018 ; Issue: 3 ; Pages: 1-25 ; Basel: MDPI

Klassifikation
Wirtschaft
Thema
portfolio credit risk
systemic risk
diversification
portfolio loss correlation
collateralized debt obligations
non-stationarity

Ereignis
Geistige Schöpfung
(wer)
Mühlbacher, Andreas
Guhr, Thomas
Ereignis
Veröffentlichung
(wer)
MDPI
(wo)
Basel
(wann)
2018

DOI
doi:10.3390/risks6030072
Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Mühlbacher, Andreas
  • Guhr, Thomas
  • MDPI

Entstanden

  • 2018

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