IDEAS home Printed from https://ideas.repec.org/a/eee/jbfina/v37y2013i5p1687-1705.html
   My bibliography  Save this article

Hedging structured credit products during the credit crisis: A horse race of 10 models

Author

Listed:
  • Ascheberg, Marius
  • Bick, Björn
  • Kraft, Holger

Abstract

Pricing and hedging structured credit products poses major challenges to financial institutions. This paper puts several valuation approaches through a crucial test: How did these models perform in one of the worst periods of economic history, September 2008, when Lehman Brothers went under? Did they produce reasonable hedging strategies? We study several bottom-up and top-down credit portfolio models and compute the resulting delta hedging strategies using either index contracts or a portfolio of single-name CDS contracts as hedging instruments. We compute the profit-and-loss profiles and assess the performances of these hedging strategies. Among all 10 pricing models that we consider the Student-t copula model performs best. The dynamical generalized-Poisson loss model is the best top-down model, but this model class has in general problems to hedge equity tranches. Our major finding is however that single-name and index CDS contracts are not appropriate instruments to hedge CDO tranches.

Suggested Citation

  • Ascheberg, Marius & Bick, Björn & Kraft, Holger, 2013. "Hedging structured credit products during the credit crisis: A horse race of 10 models," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1687-1705.
  • Handle: RePEc:eee:jbfina:v:37:y:2013:i:5:p:1687-1705
    DOI: 10.1016/j.jbankfin.2013.01.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378426613000137
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lutz Schloegl & Dominic O’Kane, 2005. "A note on the large homogeneous portfolio approximation with the Student-t copula," Finance and Stochastics, Springer, vol. 9(4), pages 577-584, October.
    2. Rama Cont & Yu Hang Kan, 2011. "Dynamic hedging of portfolio credit derivatives," Post-Print hal-00578008, HAL.
    3. Bakshi, Gurdip & Cao, Charles & Chen, Zhiwu, 1997. " Empirical Performance of Alternative Option Pricing Models," Journal of Finance, American Finance Association, vol. 52(5), pages 2003-2049, December.
    4. Darrell Duffie & Jun Pan & Kenneth Singleton, 2000. "Transform Analysis and Asset Pricing for Affine Jump-Diffusions," Econometrica, Econometric Society, vol. 68(6), pages 1343-1376, November.
    5. Igor Halperin & Pascal Tomecek, 2009. "Climbing Down from the Top: Single Name Dynamics in Credit Top Down Models," Papers 0901.3404, arXiv.org.
    6. Viktoriya Masol & Wim Schoutens, 2011. "Comparing alternative Levy base correlation models for pricing and hedging CDO tranches," Quantitative Finance, Taylor & Francis Journals, vol. 11(5), pages 763-773.
    7. Stephan Höcht & Rudi Zagst, 2010. "Pricing distressed CDOs with stochastic recovery," Review of Derivatives Research, Springer, vol. 13(3), pages 219-244, October.
    8. 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, April.
    9. Instefjord, Norvald, 2005. "Risk and hedging: Do credit derivatives increase bank risk?," Journal of Banking & Finance, Elsevier, vol. 29(2), pages 333-345, February.
    10. Ederington, Louis H, 1979. "The Hedging Performance of the New Futures Markets," Journal of Finance, American Finance Association, vol. 34(1), pages 157-170, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.

    More about this item

    Keywords

    Structured products; P&L analysis; Hedging; Bottom-up models; Top-down models; Copulas; Self-exciting models;

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jbfina:v:37:y:2013:i:5:p:1687-1705. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/jbf .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.