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Fit The Base Correlation : Dynamic Model
  • Dynamic Factor Copula Model models an factor copula model is the market standard model for multi-name credit derivatives. Its main drawback is that factor copula models exhibit correlation smiles when calibrating against market tranche quotes. We introduce a multi-period factor copula model to overcome the calibration deficiency of factor copula models by allowing the factor loadings to be time-dependent. Usually, multi-period factor copula models require multi-dimensional integration, typically computed by Monte Carlo simulation, which makes calibration extremely time consuming. In our model, the portfolio loss of a completely homogeneous pool possesses the Markov property, thus we can compute the portfolio loss distribution analytically without multi-dimensional integration. Numerical results demonstrate the efficiency and flexibility of our model to match market quotes. , K.Jackson, A.Kreinin, W.Zhang (2009)
  • A Simple Dynamic Model for Pricing and Hedging Heterogenous CDOs models We present a simple bottom-up dynamic credit model that can be calibrated simultaneously to the market quotes on CDO tranches and individual CDSs constituting the credit portfolio. The model is most suitable for the purpose of evaluating the hedge ratios of CDO tranches with respect to the underlying credit names. Default intensities of individual assets are modeled as deterministic functions of time and the total number of defaults accumulated in the portfolio. To overcome numerical difficulties, we suggest a semi-analytic approximation that is justified by the large number of portfolio members. We calibrate the model to the recent market quotes on CDO tranches and individual CDSs and find the hedge ratios of tranches. Results are compared with those obtained within the static Gaussian Copula model. , A.V. Lopatin (2009)
  • Geometrical Loss Model models , Charaf Ech-Chatbi (2009)
  • Climbing Down from the Top: Single name dynamics in credit top down models models , I.Halperin, P.Tomecek (2008)
  • A simple dynamic model for pricing and hedging heterogenous CDOs models , A. V. Lopatin (2008)
  • Forward Equations for Portfolio Credit Derivatives models , R. Cont, I. A. Savescu (2008)
  • Arbitrage-free Loss Surface Closest to Base Correlations models , A.GreenBerg (2008)
  • Hedging default risks of CDOs in Markovian contagion models models , J.-P. Laurent, A. Cousin, J.-D. Fermanian (2008)
  • The Discrete Gamma Pool model models , P. J?ckel (2008)
  • The Implementation of the Discrete Gamma Pool model models , P. J?ckel (2008)
  • Dynamic Models of Portfolio Credit Risk: A Simplified Approach models , J.Hull, A.White (2008)
  • Calibration of CDO Tranches with the Dynamical Generalized-Poisson Loss Model models , D. Brigo, A. Pallavicini, R. Torresetti (2007)
  • Forwards and European Option On CDO Tranches models , J.Hull, A.White (2007)
  • BSLP: Markovian Bivariate Spread-Loss Model for Portfolio Credit Derivatives models , M. Arnsdorf, I. Halperin (2007)
  • Two-Dimensional Markovian Model for Dynamics of Aggregate Credit Loss models , A.V.Lopatin, T.Misirpashaev (2007)
  • An Implied Loss Model models , M.Van Der Voort (2007)
  • Dynamic Conditioning and Credt Correlation Baskets models , C.Albanese, A.Vidler (2007)
  • Background Filtrations and Canonical Loss Processes for Top-Down Models of Portfolio Credit Risk models , P.Elhers, P.J.Schonbucher (2006)
  • On the term structure of loss distributions - a forward model approach models , J. Sidenius (2006)
  • A New Framework for Dynamic Credit Portfolio Loss Modelling models , J. Sidenius, V. Piterbarg, L. Andersen (2006)
  • Portfolio Losses and the Term Structure of Loss Transition Rates: A New Methodology for the Pricing of Portfolio Credit Derivatives models , P. Sch?nbucher (2006)
  • Portfolio Losses in Factor Models : Term Structures and Intertemporal Loss Dependence models , L. Andersen (2006)
  • The Forward Loss Model: A Dynamic Term Structure Approach For The Pricing of Portfolio Credit Derivatives models , N.Bennani (2005)





















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