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Pricing Synthetic CDOs Using a Three Regime Random-Factor-Loading Model

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  • Philip Messow

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    Abstract

    Synthetic Collateralized Debt Obligations (CDOs) were among the driving forces of the rapid growth of the market for credit derivatives in recent years. Possibly the most popular model beside the Gaussian copula for pricing CDO tranches is the Random-Factor-Loading-Model of Andersen and Sidenius (2005). We extend this model by allowing more than two regimes of default correlations. The model is calibrated to market spreads at times of financial distress and during calm periods. For both points in time the model correlation skews are similar to the steep skews observed in the market and lead to an improvement to the standard Random-Factor-Loading-Model.

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    File URL: http://repec.rwi-essen.de/files/REP_12_317.pdf
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    Bibliographic Info

    Paper provided by Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen in its series Ruhr Economic Papers with number 0317.

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    Length: 28 pages
    Date of creation: Feb 2012
    Date of revision:
    Handle: RePEc:rwi:repape:0317

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    Related research

    Keywords: Collateralized debt obligation; random-factor-loading; pricing; financial dependence; factor model; default risk; correlated defaults;

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    1. Koedijk, Kees & Kole, Erik & Verbeek, Marno, 2006. "Selecting Copulas for Risk Management," CEPR Discussion Papers 5652, C.E.P.R. Discussion Papers.
    2. Glasserman, Paul & Suchintabandid, Sira, 2007. "Correlation expansions for CDO pricing," Journal of Banking & Finance, Elsevier, vol. 31(5), pages 1375-1398, May.
    3. Ping Li & Housheng Chen & Xiaotie Deng & Shunming Zhang, 2006. "On Default Correlation And Pricing Of Collateralized Debt Obligation By Copula Functions," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 5(03), pages 483-493.
    4. Merton, Robert C., 1973. "On the pricing of corporate debt: the risk structure of interest rates," Working papers 684-73., Massachusetts Institute of Technology (MIT), Sloan School of Management.
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