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Dependent defaults and losses with factor copula models

Author

Listed:
  • Ackerer Damien

    (Swissquote Bank, Gland, Switzerland)

  • Vatter Thibault

    (Department of Statistics, Columbia University, New York, USA)

Abstract

We present a class of flexible and tractable static factor models for the term structure of joint default probabilities, the factor copula models. These high-dimensional models remain parsimonious with paircopula constructions, and nest many standard models as special cases. The loss distribution of a portfolio of contingent claims can be exactly and efficiently computed when individual losses are discretely supported on a finite grid. Numerical examples study the key features affecting the loss distribution and multi-name credit derivatives prices. An empirical exercise illustrates the flexibility of our approach by fitting credit index tranche prices.

Suggested Citation

  • Ackerer Damien & Vatter Thibault, 2017. "Dependent defaults and losses with factor copula models," Dependence Modeling, De Gruyter, vol. 5(1), pages 375-399, December.
  • Handle: RePEc:vrs:demode:v:5:y:2017:i:1:p:375-399:n:22
    DOI: 10.1515/demo-2017-0022
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    References listed on IDEAS

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    1. Aas, Kjersti & Czado, Claudia & Frigessi, Arnoldo & Bakken, Henrik, 2009. "Pair-copula constructions of multiple dependence," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 182-198, April.
    2. Jan-Frederik Mai & Pablo Olivares & Steffen Schenk & Matthias Scherer, 2014. "A Multivariate Default Model with Spread and Event Risk," Applied Mathematical Finance, Taylor & Francis Journals, vol. 21(1), pages 51-83, March.
    3. Edward Altman & Andrea Resti & Andrea Sironi, 2004. "Default Recovery Rates in Credit Risk Modelling: A Review of the Literature and Empirical Evidence," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 33(2), pages 183-208, July.
    4. Dong Hwan Oh & Andrew J. Patton, 2017. "Modeling Dependence in High Dimensions With Factor Copulas," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 139-154, January.
    5. Marius Hofert & Matthias Scherer, 2011. "CDO pricing with nested Archimedean copulas," Quantitative Finance, Taylor & Francis Journals, vol. 11(5), pages 775-787.
    6. 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.
    7. Alexander J. McNeil & Rüdiger Frey & Paul Embrechts, 2015. "Quantitative Risk Management: Concepts, Techniques and Tools Revised edition," Economics Books, Princeton University Press, edition 2, number 10496.
    8. Ulf Schepsmeier & Jakob Stöber, 2014. "Derivatives and Fisher information of bivariate copulas," Statistical Papers, Springer, vol. 55(2), pages 525-542, May.
    9. Krupskii, Pavel & Joe, Harry, 2015. "Structured factor copula models: Theory, inference and computation," Journal of Multivariate Analysis, Elsevier, vol. 138(C), pages 53-73.
    10. Sancetta, Alessio & Satchell, Stephen, 2004. "The Bernstein Copula And Its Applications To Modeling And Approximations Of Multivariate Distributions," Econometric Theory, Cambridge University Press, vol. 20(3), pages 535-562, June.
    11. Pierre Collin-Dufresne, 2009. "A Short Introduction to Correlation Markets," Journal of Financial Econometrics, Oxford University Press, vol. 7(1), pages 12-29, Winter.
    12. Florence Guillaume & Philippe Jacobs & Wim Schoutens, 2009. "Pricing And Hedging Of Cdo-Squared Tranches By Using A One Factor Lévy Model," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 12(05), pages 663-685.
    13. Daniel Dufresne & Jose Garrido & Manuel Morales, 2009. "Fourier Inversion Formulas in Option Pricing and Insurance," Methodology and Computing in Applied Probability, Springer, vol. 11(3), pages 359-383, September.
    14. Dong Hwan Oh & Andrew J. Patton, 2013. "Simulated Method of Moments Estimation for Copula-Based Multivariate Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(502), pages 689-700, June.
    15. Krupskii, Pavel & Joe, Harry, 2013. "Factor copula models for multivariate data," Journal of Multivariate Analysis, Elsevier, vol. 120(C), pages 85-101.
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