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The pricing of correlated default risk: evidence from the credit derivatives market

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  • Zhu, Haibin
  • Tarashev, Nikola A.

Abstract

In order to analyze the pricing of portfolio credit risk – as revealed by tranche spreads of a popular credit default swap (CDS) index – we extract risk-neutral probabilities of default (PDs) and physical asset return correlations from single-name CDS spreads. The time profile and overall level of index spreads validate our PD measures. At the same time, the physical asset return correlations are too low to account for the spreads of index tranches and, thus, point to a large correlation risk premium. This premium, which covaries negatively with current realized correlations and positively with future realized correlations, sheds light on market perceptions of and attitude towards correlation risk. -- Das Portfoliokreditrisiko setzt sich aus drei Hauptkomponenten zusammen: der Ausfallwahrscheinlichkeit (probability of default, PD), der Verlustquote (loss given default, LGD) und der Wahrscheinlichkeitsverteilung für gemeinsame Ausfälle. Mit der rasanten Entwicklung innovativer Produkte im Bereich der strukturierten Finanzierung ist die Bedeutung der dritten Komponente zusehends gestiegen. Allerdings herrscht keine Einigkeit darüber, wie die Marktteilnehmer diese schätzen. Im vorliegenden Arbeitspapier schlagen wir zunächst einen auf CDSMarktdaten beruhenden Ansatz zur Ableitung der Wahrscheinlichkeitsverteilung für gemeinsame Ausfälle vor. Mit diesem Ansatz werden risikoneutrale PDs und physische Asset-Return-Korrelationen aus der Höhe der Preise und dem Gleichlauf (Co-movement) von Single-name-CDS-Spreads abgeleitet. Anschließend benutzen wir diese Schätzungen in einer konkreten Anwendung unseres Ansatzes zur Berechnung von Prognosen für Tranchenspreads eines bekannten CDS-Index (Dow Jones CDX North America Investment Grade Index) und vergleichen diese mit empirischen Spreads am CDS-Indexmarkt.

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Bibliographic Info

Paper provided by Deutsche Bundesbank, Research Centre in its series Discussion Paper Series 2: Banking and Financial Studies with number 2008,09.

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Date of creation: 2008
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Handle: RePEc:zbw:bubdp2:7319

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Keywords: Portfolio credit risk; Correlation risk premium; CDS index; Tranche spread; Copula;

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References

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  1. Sanjiv Das & Darrell Duffie & Nikunj Kapadia & Leandro Saita, 2006. "Common Failings: How Corporate Defaults are Correlated," NBER Working Papers 11961, National Bureau of Economic Research, Inc.
  2. Darrell Duffie & Leandro Siata & Ke Wang, 2006. "Multi-Period Corporate Default Prediction With Stochastic Covariates," NBER Working Papers 11962, National Bureau of Economic Research, Inc.
  3. Koopman, Siem Jan & Lucas, André, 2008. "A Non-Gaussian Panel Time Series Model for Estimating and Decomposing Default Risk," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 510-525.
  4. Francis A. Longstaff & Arvind Rajan, 2008. "An Empirical Analysis of the Pricing of Collateralized Debt Obligations," Journal of Finance, American Finance Association, vol. 63(2), pages 529-563, 04.
  5. Zhou, Chunsheng, 2001. "An Analysis of Default Correlations and Multiple Defaults," Review of Financial Studies, Society for Financial Studies, vol. 14(2), pages 555-76.
  6. Daniel Covitz & Song Han, 2004. "An empirical analysis of bond recovery rates: exploring a structural view of default," Finance and Economics Discussion Series 2005-10, Board of Governors of the Federal Reserve System (U.S.).
  7. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-70, May.
  8. Jeffery D Amato & Jacob Gyntelberg, 2005. "CDS index tranches and the pricing of credit risk correlations," BIS Quarterly Review, Bank for International Settlements, March.
  9. Siem Jan Koopman & André Lucas & Robert Daniels, 2005. "A Non-Gaussian Panel Time Series Model for Estimating and Decomposing Default Risk," Tinbergen Institute Discussion Papers 05-060/4, Tinbergen Institute.
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Cited by:
  1. Nikola Tarashev, 2009. "Measuring portfolio credit risk correctly: why parameter uncertainty matters," BIS Working Papers 280, Bank for International Settlements.
  2. Mutl, Jan & Sögner, Leopold, 2013. "Parameter Estimation and Inference with Spatial Lags and Cointegration," Economics Series 296, Institute for Advanced Studies.

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