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Empirical Copulas For Cdo Tranche Pricing Using Relative Entropy

In: Credit Correlation Life After Copulas

Author

Listed:
  • MICHAEL A. H. DEMPSTER

    (Centre for Financial Research, Judge Business School, University of Cambridge, United Kingdom and Cambridge Systems Associates Limited, Cambridge, United Kingdom)

  • ELENA A. MEDOVA

    (Centre for Financial Research, Judge Business School, University of Cambridge, United Kingdom and Cambridge Systems Associates Limited, Cambridge, United Kingdom)

  • SEUNG W. YANG

    (Centre for Financial Research, Judge Business School, University of Cambridge, United Kingdom and Cambridge Systems Associates Limited, Cambridge, United Kingdom)

Abstract

We discuss the general optimization problem of choosing a copula with minimum entropy relative to a specified copula and a computationally intensive procedure to solve its dual. These techniques are applied to constructing an empirical copula for CDO tranche pricing. The empirical copula is chosen to be as close as possible to the industry standard Gaussian copula while ensuring a close fit to market tranche quotes. We find that the empirical copula performs noticeably better than the base correlation approach in pricing non-standard tranches and that the market view of default dependence is influenced by maturity.

Suggested Citation

  • Michael A. H. Dempster & Elena A. Medova & Seung W. Yang, 2007. "Empirical Copulas For Cdo Tranche Pricing Using Relative Entropy," World Scientific Book Chapters, in: Alexander Lipton & Andrew Rennie (ed.), Credit Correlation Life After Copulas, chapter 5, pages 87-109, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789812709509_0005
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    Citations

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    Cited by:

    1. Alexander Veremyev & Peter Tsyurmasto & Stan Uryasev & R. Rockafellar, 2014. "Calibrating probability distributions with convex-concave-convex functions: application to CDO pricing," Computational Management Science, Springer, vol. 11(4), pages 341-364, October.
    2. Cassio Neri & Lorenz Schneider, 2011. "A Family of Maximum Entropy Densities Matching Call Option Prices," Papers 1102.0224, arXiv.org.
    3. Cassio Neri & Lorenz Schneider, 2012. "Maximum entropy distributions inferred from option portfolios on an asset," Finance and Stochastics, Springer, vol. 16(2), pages 293-318, April.
    4. Ba Chu & Stephen Satchell, 2016. "Recovering the Most Entropic Copulas from Preliminary Knowledge of Dependence," Econometrics, MDPI, vol. 4(2), pages 1-21, March.

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