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A dynamic default dependence model

Listed author(s):
  • Sara Cecchetti


    (Bank of Italy)

  • Giovanna Nappo


    (Sapienza, University of Rome)

Registered author(s):

    We develop a dynamic multivariate default model for a portfolio of credit-risky assets in which default times are modelled as random variables with possibly different marginal distributions, and L�vy subordinators are used to model the dependence among default times. In particular, we define a cumulative dynamic hazard process as a L�vy subordinator, which allows for jumps and induces positive probabilities of joint defaults. We allow the main asset classes in the portfolio to have different cumulative default probabilities and corresponding different cumulative hazard processes. Under this heterogeneous assumption we compute the portfolio loss distribution in closed form. Using an approximation of the loss distribution, we calibrate the model to the tranches of the iTraxx Europe. Once the multivariate default distribution has been estimated, we analyse the distress dependence in the portfolio by computing indicators of systemic risk, such as the Stability Index, the Distress Dependence Matrix and the Probability of Cascade Effects.

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    Paper provided by Bank of Italy, Economic Research and International Relations Area in its series Temi di discussione (Economic working papers) with number 892.

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    Date of creation: Nov 2012
    Handle: RePEc:bdi:wptemi:td_892_12
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    1. Elisa Luciano, 2007. "Copula-Based Default Dependence Modelling: Where Do We Stand?," ICER Working Papers - Applied Mathematics Series 21-2007, ICER - International Centre for Economic Research.
    2. Donnelly, Catherine & Embrechts, Paul, 2010. "The Devil is in the Tails: Actuarial Mathematics and the Subprime Mortgage Crisis," ASTIN Bulletin: The Journal of the International Actuarial Association, Cambridge University Press, vol. 40(01), pages 1-33, May.
    3. Barbara Choroś-Tomczyk & Wolfgang Karl Härdle & Ludger Overbeck, 2014. "Copula dynamics in CDOs," Quantitative Finance, Taylor & Francis Journals, vol. 14(9), pages 1573-1585, September.
    4. Viktoriya Masol & Wim Schoutens, 2011. "Comparing alternative Levy base correlation models for pricing and hedging CDO tranches," Quantitative Finance, Taylor & Francis Journals, vol. 11(5), pages 763-773.
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