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Credit models and the crisis, or: how I learned to stop worrying and love the CDOs

Author

Listed:
  • Damiano Brigo
  • Andrea Pallavicini
  • Roberto Torresetti

Abstract

We follow a long path for Credit Derivatives and Collateralized Debt Obligations (CDOs) in particular, from the introduction of the Gaussian copula model and the related implied correlations to the introduction of arbitrage-free dynamic loss models capable of calibrating all the tranches for all the maturities at the same time. En passant, we also illustrate the implied copula, a method that can consistently account for CDOs with different attachment and detachment points but not for different maturities. The discussion is abundantly supported by market examples through history. The dangers and critics we present to the use of the Gaussian copula and of implied correlation had all been published by us, among others, in 2006, showing that the quantitative community was aware of the model limitations before the crisis. We also explain why the Gaussian copula model is still used in its base correlation formulation, although under some possible extensions such as random recovery. Overall we conclude that the modeling effort in this area of the derivatives market is unfinished, partly for the lack of an operationally attractive single-name consistent dynamic loss model, and partly because of the diminished investment in this research area.

Suggested Citation

  • Damiano Brigo & Andrea Pallavicini & Roberto Torresetti, 2009. "Credit models and the crisis, or: how I learned to stop worrying and love the CDOs," Papers 0912.5427, arXiv.org, revised Feb 2010.
  • Handle: RePEc:arx:papers:0912.5427
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    References listed on IDEAS

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    1. Damiano Brigo & Andrea Pallavicini & Vasileios Papatheodorou, 2009. "Bilateral counterparty risk valuation for interest-rate products: impact of volatilities and correlations," Papers 0911.3331, arXiv.org, revised Feb 2010.
    2. Breeden, Douglas T & Litzenberger, Robert H, 1978. "Prices of State-contingent Claims Implicit in Option Prices," The Journal of Business, University of Chicago Press, vol. 51(4), pages 621-651, October.
    3. Balakrishna, B S, 2007. "Delayed Default Dependency and Default Contagion," MPRA Paper 14921, University Library of Munich, Germany, revised 15 May 2007.
    4. Torresetti, Roberto & Pallavicini, Andrea, 2007. "Stressing rating criteria allowing for default clustering: the CPDO case," MPRA Paper 17104, University Library of Munich, Germany, revised 04 Sep 2009.
    5. Damiano Brigo & Kyriakos Chourdakis, 2009. "Counterparty Risk For Credit Default Swaps: Impact Of Spread Volatility And Default Correlation," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 12(07), pages 1007-1026.
    6. Damiano Brigo & Naoufel El-Bachir, 2007. "An exact formula for default swaptions' pricing in the SSRJD stochastic intensity model," ICMA Centre Discussion Papers in Finance icma-dp2007-14, Henley Business School, University of Reading.
    7. 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.
    8. 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.
    9. Unknown, 2005. "Forward," 2005 Conference: Slovenia in the EU - Challenges for Agriculture, Food Science and Rural Affairs, November 10-11, 2005, Moravske Toplice, Slovenia 183804, Slovenian Association of Agricultural Economists (DAES).
    10. Lindskog, Filip & McNeil, Alexander J., 2003. "Common Poisson Shock Models: Applications to Insurance and Credit Risk Modelling," ASTIN Bulletin, Cambridge University Press, vol. 33(2), pages 209-238, November.
    11. Rosen, Dan & Saunders, David, 2009. "Analytical methods for hedging systematic credit risk with linear factor portfolios," Journal of Economic Dynamics and Control, Elsevier, vol. 33(1), pages 37-52, January.
    12. Robert Jarrow, 2017. "Derivatives," World Scientific Book Chapters, in: THE ECONOMIC FOUNDATIONS OF RISK MANAGEMENT Theory, Practice, and Applications, chapter 3, pages 19-28, World Scientific Publishing Co. Pte. Ltd..
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    Cited by:

    1. Balakrishna, B S, 2010. "Levy Subordinator Model of Default Dependency," MPRA Paper 21386, University Library of Munich, Germany.
    2. Tim J. Brereton & Dirk P. Kroese & Joshua C. Chan, 2012. "Monte Carlo Methods for Portfolio Credit Risk," ANU Working Papers in Economics and Econometrics 2012-579, Australian National University, College of Business and Economics, School of Economics.
    3. Balakrishna, B S, 2010. "Levy Subordinator Model: A Two Parameter Model of Default Dependency," MPRA Paper 26274, University Library of Munich, Germany.
    4. Vanini, Paolo, 2012. "Fiancial Innovation, Structuring and Risk Transfer," MPRA Paper 42536, University Library of Munich, Germany.

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