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An empirical comparison of alternative credit default swap pricing models


  • Michele Leonardo Bianchi

    () (Bank of Italy)


Most of the important models in finance rest on the assumption that randomness is explained through a normal random variable because, in general, the use of alternative models is obstructed by the difficulty of calibrating and simulating them. In this paper, we empirically study models for pricing credit default swaps under a reduced-form framework, assuming different dynamics for the default intensity process. After reviewing the most recent results on this subject, we explore both pricing performance and parameter stability during the highly volatile period from 30 June 2008 to 31 December 2010 for different classes of processes: one driven by the Brownian motion, three driven by non-Gaussian L�vy processes, and the last one driven by a Sato process. The models are analysed from both a static and dynamic perspective.

Suggested Citation

  • Michele Leonardo Bianchi, 2012. "An empirical comparison of alternative credit default swap pricing models," Temi di discussione (Economic working papers) 882, Bank of Italy, Economic Research and International Relations Area.
  • Handle: RePEc:bdi:wptemi:td_882_12

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    References listed on IDEAS

    1. Sergio Mayordomo & Juan Ignacio Peña & Eduardo S. Schwartz, 2010. "Are all Credit Default Swap Databases Equal?," NBER Working Papers 16590, National Bureau of Economic Research, Inc.
    2. Robert A. Jarrow, 2009. "Credit Risk Models," Annual Review of Financial Economics, Annual Reviews, vol. 1(1), pages 37-68, November.
    3. Robert A. Jarrow & David Lando & Fan Yu, 2008. "Default Risk And Diversification: Theory And Empirical Implications," World Scientific Book Chapters,in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 19, pages 455-480 World Scientific Publishing Co. Pte. Ltd..
    4. repec:dau:papers:123456789/1380 is not listed on IDEAS
    5. Duan, Jin-Chuan & Simonato, Jean-Guy, 1999. "Estimating and Testing Exponential-Affine Term Structure Models by Kalman Filter," Review of Quantitative Finance and Accounting, Springer, vol. 13(2), pages 111-135, September.
    6. Kwamie Dunbar, 2008. "US corporate default swap valuation: the market liquidity hypothesis and autonomous credit risk," Quantitative Finance, Taylor & Francis Journals, vol. 8(3), pages 321-334.
    7. 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, Reading University.
    8. Duan, Jin-Chuan & Fulop, Andras, 2009. "Estimating the structural credit risk model when equity prices are contaminated by trading noises," Journal of Econometrics, Elsevier, vol. 150(2), pages 288-296, June.
    9. Helyette Geman & C. Peter M. Dilip Y. Marc, 2007. "Self decomposability and option pricing," Post-Print halshs-00144193, HAL.
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    More about this item


    credit default swap; Cox-Ingersoll-Ross; non-Gaussian Ornstein-Uhlenbeck processes; L�vy processes; Sato processes; filtering methods; unscented Kalman filter; particle filter;

    JEL classification:

    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis


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