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Dynamic hedging of portfolio credit derivatives

Author

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  • Rama Cont

    (LPMA - Laboratoire de Probabilités et Modèles Aléatoires - UPMC - Université Pierre et Marie Curie - Paris 6 - UPD7 - Université Paris Diderot - Paris 7 - CNRS - Centre National de la Recherche Scientifique, IEOR Department (Industrial Engineering & Operations Research) - Columbia University [New York])

  • Yu Hang Kan

    (IEOR Department (Industrial Engineering & Operations Research) - Columbia University [New York])

Abstract

We compare the performance of various hedging strategies for index collateralized debt obligation (CDO) tranches across a variety of models and hedging methods during the recent credit crisis. Our empirical analysis shows evidence for market incompleteness: a large proportion of risk in the CDO tranches appears to be unhedgeable. We also show that, unlike what is commonly assumed, dynamic models do not necessarily perform better than static models, nor do high-dimensional bottom-up models perform better than simpler top-down models. When it comes to hedging, top-down and regression-based hedging with the index provide significantly better results during the credit crisis than bottom-up hedging with single-name credit default swap (CDS) contracts. Our empirical study also reveals that while significantly large moves—"jumps"—do occur in CDS, index, and tranche spreads, these jumps do not necessarily occur on the default dates of index constituents, an observation which shows the insufficiency of some recently proposed portfolio credit risk models.

Suggested Citation

  • Rama Cont & Yu Hang Kan, 2011. "Dynamic hedging of portfolio credit derivatives," Post-Print hal-00578008, HAL.
  • Handle: RePEc:hal:journl:hal-00578008
    DOI: 10.1137/090750937
    Note: View the original document on HAL open archive server: https://hal.science/hal-00578008
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    References listed on IDEAS

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    1. Tomasz Bielecki & Stephane Crepey & Monique Jeanblanc, 2010. "Up and down credit risk," Quantitative Finance, Taylor & Francis Journals, vol. 10(10), pages 1137-1151.
    2. Massimo Morini & Damiano Brigo, 2008. "Arbitrage-free Pricing of Credit Index Options: The no-armageddon pricing measure and the role of correlation after the subprime crisis," Papers 0812.4156, arXiv.org.
    3. Frey, Rüdiger & Backhaus, Jochen, 2010. "Dynamic hedging of synthetic CDO tranches with spread risk and default contagion," Journal of Economic Dynamics and Control, Elsevier, vol. 34(4), pages 710-724, April.
    4. Rama Cont, 2006. "Model Uncertainty And Its Impact On The Pricing Of Derivative Instruments," Mathematical Finance, Wiley Blackwell, vol. 16(3), pages 519-547, July.
    5. Rama Cont, 2006. "Model uncertainty and its impact on the pricing of derivative instruments," Post-Print halshs-00002695, HAL.
    6. Rama Cont & Romain Deguest & Yu Hang Kan, 2010. "Default Intensities implied by CDO Spreads: Inversion Formula and Model Calibration," Post-Print hal-00545744, HAL.
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    Cited by:

    1. Chan, Kam Fong & Bowman, Robert G. & Neely, Christopher J., 2017. "Systematic cojumps, market component portfolios and scheduled macroeconomic announcements," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 43-58.
    2. Chamizo, Álvaro & Novales, Alfonso, 2021. "Evaluation of market risk associated with hedging a credit derivative portfolio," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 411-430.
    3. Buse, Rebekka & Schienle, Melanie, 2019. "Measuring connectedness of euro area sovereign risk," International Journal of Forecasting, Elsevier, vol. 35(1), pages 25-44.
    4. 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.
    5. Wen-Qiong Liu & Wen-Li Huang, 2019. "Hedging Of Synthetic Cdo Tranches With Spread And Default Risk Based On A Combined Forecasting Approach," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(02), pages 1-17, March.
    6. Peter Sinka & Peter J. Zeitsch, 2022. "Hedge Effectiveness of the Credit Default Swap Indices: a Spectral Decomposition and Network Topology Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 60(4), pages 1375-1412, December.
    7. Areski Cousin & Stéphane Crépey & Yu Kan, 2012. "Delta-hedging correlation risk?," Review of Derivatives Research, Springer, vol. 15(1), pages 25-56, April.
    8. 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.
    9. Srikanth Iyer & Seema Nanda & Swapnil Kumar, 2013. "An Empirical Comparison of Two Stochastic Volatility Models using Indian Market Data," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 20(3), pages 243-259, September.
    10. Johannes Ruf & Weiguan Wang, 2020. "Hedging with Linear Regressions and Neural Networks," Papers 2004.08891, arXiv.org, revised Jun 2021.
    11. Bielecki, Tomasz R. & Cousin, Areski & Crépey, Stéphane & Herbertsson, Alexander, 2011. "Dynamic Hedging of Portfolio Credit Risk in a Markov Copula Model (Previous title: Dynamic Modeling of Portfolio Credit Risk with Common Shocks)," Working Papers in Economics 502, University of Gothenburg, Department of Economics, revised 12 Oct 2012.
    12. Lei, Lei & Peng, Yijie & Fu, Michael C. & Hu, Jian-Qiang, 2023. "Copula sensitivity analysis for portfolio credit derivatives," European Journal of Operational Research, Elsevier, vol. 308(1), pages 455-466.
    13. Zehra Eksi & Damir Filipovi'c, 2020. "Affine Pricing and Hedging of Collateralized Debt Obligations," Papers 2011.10101, arXiv.org.

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