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The delivery option in credit default swaps

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  • Jankowitsch, Rainer
  • Pullirsch, Rainer
  • Veza, Tanja

Abstract

Under standard assumptions the reduced-form credit risk model is not capable of accurately pricing the two fundamental credit risk instruments - bonds and credit default swaps (CDS) - simultaneously. Using a data set of euro-denominated corporate bonds and CDS our paper quantifies this mispricing by calibrating such a model to bond data, and subsequently using it to price CDS, resulting in model CDS spreads up to 50% lower on average than observed in the market. An extended model is presented which includes the delivery option implicit in CDS contracts emerging since a basket of bonds is deliverable in default. By using a constant recovery rate standard models assume equal recoveries for all bonds and hence zero value for the delivery option. Contradicting this common assumption, case studies of Chapter 11 filings presented in the paper show that corporate bonds do not necessarily trade at equal levels following default. Our extension models the implied expected recovery rate of the cheapest-to-deliver bond and, applied to data, largely eliminates the mispricing. Calibrated recovery values lie between 8% and 47% for different obligors, exhibiting strong variation among rating classes and industries. A cross-sectional analysis reveals that the implied recovery parameter depends on proxies for the delivery option, primarily the number of available bonds and bond pricing errors. No evidence is found for a direct influence of the bid-ask spread, notional amount, coupon, or rating used as proxies for bond market liquidity.

Suggested Citation

  • Jankowitsch, Rainer & Pullirsch, Rainer & Veza, Tanja, 2008. "The delivery option in credit default swaps," Journal of Banking & Finance, Elsevier, vol. 32(7), pages 1269-1285, July.
  • Handle: RePEc:eee:jbfina:v:32:y:2008:i:7:p:1269-1285
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    References listed on IDEAS

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    1. Francis A. Longstaff & Sanjay Mithal & Eric Neis, 2005. "Corporate Yield Spreads: Default Risk or Liquidity? New Evidence from the Credit Default Swap Market," Journal of Finance, American Finance Association, vol. 60(5), pages 2213-2253, October.
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    4. Roberto Blanco & Simon Brennan & Ian W. Marsh, 2005. "An Empirical Analysis of the Dynamic Relation between Investment-Grade Bonds and Credit Default Swaps," Journal of Finance, American Finance Association, vol. 60(5), pages 2255-2281, October.
    5. Alois Geyer & Stephan Kossmeier & Stefan Pichler, 2004. "Measuring Systematic Risk in EMU Government Yield Spreads," Review of Finance, Springer, vol. 8(2), pages 171-197.
    6. Damiano Brigo & Aurélien Alfonsi, 2005. "Credit default swap calibration and derivatives pricing with the SSRD stochastic intensity model," Finance and Stochastics, Springer, vol. 9(1), pages 29-42, January.
    7. Haibin Zhu, 2006. "An Empirical Comparison of Credit Spreads between the Bond Market and the Credit Default Swap Market," Journal of Financial Services Research, Springer;Western Finance Association, vol. 29(3), pages 211-235, June.
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    Cited by:

    1. Gürtler, Marc & Hibbeln, Martin, 2013. "Improvements in loss given default forecasts for bank loans," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2354-2366.
    2. Alexander Friesenegger & Andreas W. Rathgeber & Stefan Stöckl, 2015. "Recovery Rate in the Event of an Issuer’s Insolvency — Empirical Study on Implications for the Pricing of Credit Default Risks in German Corporate Bonds," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 18(04), pages 1-34, December.
    3. Bastos, João A., 2010. "Forecasting bank loans loss-given-default," Journal of Banking & Finance, Elsevier, vol. 34(10), pages 2510-2517, October.
    4. Ben-Abdallah, Ramzi & Ben-Ameur, Hatem & Breton, Michèle, 2009. "An analysis of the true notional bond system applied to the CBOT T-bond futures," Journal of Banking & Finance, Elsevier, vol. 33(3), pages 534-545, March.
    5. Patrick Augustin, 2012. "Sovereign Credit Default Swap Premia," Working Papers 12-10, New York University, Leonard N. Stern School of Business, Department of Economics.
    6. Xu, Ruxing, 2011. "A lattice approach for pricing convertible bond asset swaps with market risk and counterparty risk," Economic Modelling, Elsevier, vol. 28(5), pages 2143-2153, September.
    7. Feldhütter, Peter & Hotchkiss, Edith & Karakaş, Oğuzhan, 2016. "The value of creditor control in corporate bonds," Journal of Financial Economics, Elsevier, vol. 121(1), pages 1-27.
    8. 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.
    9. Yalin Gündüz & Marliese Uhrig-Homburg, 2014. "Does modeling framework matter? A comparative study of structural and reduced-form models," Review of Derivatives Research, Springer, vol. 17(1), pages 39-78, April.
    10. Calabrese, Raffaella & Zenga, Michele, 2010. "Bank loan recovery rates: Measuring and nonparametric density estimation," Journal of Banking & Finance, Elsevier, vol. 34(5), pages 903-911, May.
    11. Peña Sánchez de Rivera, Juan Ignacio & Mayordomo, Sergio & Romo, Juan, 2009. "Are There Arbitrage Opportunities in Credit Derivatives Markets? A New Test and an Application to the Case of CDS and ASPs," DEE - Working Papers. Business Economics. WB wb096303, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    12. Das, Sanjiv R. & Hanouna, Paul & Sarin, Atulya, 2009. "Accounting-based versus market-based cross-sectional models of CDS spreads," Journal of Banking & Finance, Elsevier, vol. 33(4), pages 719-730, April.
    13. Rubia, Antonio & Sanchis-Marco, Lidia & Serrano, Pedro, 2016. "Market frictions and the pricing of sovereign credit default swaps," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 223-252.
    14. Hibbeln, Martin & Gürtler, Marc, 2011. "Pitfalls in modeling loss given default of bank loans," Working Papers IF35V1, Technische Universität Braunschweig, Institute of Finance.
    15. Biao Guo & Qian Han & Doojin Ryu, 2013. "The Number of State Variables for CDS Pricing," WISE Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.

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