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Systematic and Idiosyncratic Default Risk in Synthetic Credit Markets

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  • Peter Feldhütter
  • Mads Stenbo Nielsen

Abstract

We present a new estimation approach that allows us to extract from spreads in synthetic credit markets the contribution of systematic and idiosyncratic default risk to total default risk. Using an extensive dataset of 90,600 credit default swap and collateralized debt obligation (CDO) tranche spreads on the North American Investment Grade CDX index, we conduct an empirical analysis of an intensity-based model for correlated defaults. Our results show that systematic default risk is an explosive process with low volatility, while idiosyncratic default risk is more volatile but less explosive. Also, we find that the model is able to capture both the level and time series dynamics of CDO tranche spreads. Copyright The Author 2012. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com., Oxford University Press.

Suggested Citation

  • Peter Feldhütter & Mads Stenbo Nielsen, 2012. "Systematic and Idiosyncratic Default Risk in Synthetic Credit Markets," Journal of Financial Econometrics, Oxford University Press, vol. 10(2), pages 292-324, 2012 05.
    • Handle: RePEc:oup:jfinec:v:10:y:2012:i:2:p:292-324
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbr011
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    Cited by:

    1. Junye Li & Gabriele Zinna, 2014. "How much of bank credit risk is sovereign risk? Evidence from the eurozone," Temi di discussione (Economic working papers) 990, Bank of Italy, Economic Research and International Relations Area.
    2. Augustin, Patrick & Subrahmanyam, Marti G. & Tang, Dragon Yongjun & Wang, Sarah Qian, 2014. "Credit Default Swaps: A Survey," Foundations and Trends(R) in Finance, now publishers, vol. 9(1-2), pages 1-196, December.
    3. Andrew Carverhill & Dan Luo, 2020. "Pricing and integration of credit default swap index tranches," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(4), pages 503-526, April.
    4. Barbara Choroś-Tomczyk & Wolfgang Karl H�rdle & Ludger Overbeck, 2014. "Copula dynamics in CDOs," Quantitative Finance, Taylor & Francis Journals, vol. 14(9), pages 1573-1585, September.
    5. Nickerson, Jordan & Griffin, John M., 2017. "Debt correlations in the wake of the financial crisis: What are appropriate default correlations for structured products?," Journal of Financial Economics, Elsevier, vol. 125(3), pages 454-474.
    6. Rainer Jobst & Daniel Rösch & Harald Scheule & Martin Schmelzle, 2015. "A Simple Econometric Approach for Modeling Stress Event Intensities," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(4), pages 300-320, April.
    7. Christian Koziol & Philipp Koziol & Thomas Schön, 2015. "Do correlated defaults matter for CDS premia? An empirical analysis," Review of Derivatives Research, Springer, vol. 18(3), pages 191-224, October.
    8. Junye Li & Gabriele Zinna, 2018. "How Much of Bank Credit Risk Is Sovereign Risk? Evidence from Europe," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(6), pages 1225-1269, September.
    9. Junye Li & Gabriele Zinna, 2014. "On bank credit risk: systemic or bank-specific? Evidence from the US and UK," Temi di discussione (Economic working papers) 951, Bank of Italy, Economic Research and International Relations Area.
    10. Dan Luo & Dragon Yongjun Tang & Sarah Qian Wang, 2018. "Model specification and collateralized debt obligation (mis)pricing," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(11), pages 1284-1312, November.
    11. Tomohiro Ando & Matthew Greenwood-Nimmo & Yongcheol Shin, 2022. "Quantile Connectedness: Modeling Tail Behavior in the Topology of Financial Networks," Management Science, INFORMS, vol. 68(4), pages 2401-2431, April.
    12. Gabriele Zinna, 2014. "Price pressures in the UK index-linked market: an empirical investigation," Temi di discussione (Economic working papers) 968, Bank of Italy, Economic Research and International Relations Area.

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