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Fit The Base Correlation : Dynamic Model
  • Analytical Pricing of CDOs in a Multi-Factor Setting by a Moment Matching Approach We try and apply the single-scenario version of the general model in Castagna, Mercurio and Mosconi (2010) to the pricing of CDOs. We are able to establish a unified approach to both evaluate the Credit VaR and the risk of structured products, and thus evaluate on a consistent and uniform basis the Economic Capital required to face unexpected credit losses, and the risk transferred out of the balance sheet via the securitisation activity. The approach avoids to resort to cumbersome numerical procedure, by retaining a closed-form feature that allows a quick and accurate pricing of CDO structures. , Fabio Mercurio, Paola Mosconi (2012)
  • Dynamic Factor Copula Model 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 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 , Charaf Ech-Chatbi (2009)
  • Climbing Down from the Top: Single name dynamics in credit top down models , I.Halperin, P.Tomecek (2008)
  • A simple dynamic model for pricing and hedging heterogenous CDOs , A. V. Lopatin (2008)
  • Forward Equations for Portfolio Credit Derivatives , R. Cont, I. A. Savescu (2008)
  • Arbitrage-free Loss Surface Closest to Base Correlations , A.GreenBerg (2008)
  • Hedging default risks of CDOs in Markovian contagion models , J.-P. Laurent, A. Cousin, J.-D. Fermanian (2008)
  • The Discrete Gamma Pool model We present a model for the dynamics of losses and spreads on portfolios for the purpose of pricing exotic variations of synthetic collateralised tranche obligations such as Loss Triggered Leveraged Super-Senior notes, multi-callable CDOs, and, by implication of the latter, options on forward starting CDOs. Also, we discuss how features such as the counterparty’s right to deleverage upon a loss trigger event in a leveraged super senior can be understood as an embedded Bermudan swaption, and how this can be catered for in a numerical implementation. , P. Jackel (2008)
  • The Implementation of the Discrete Gamma Pool model We discuss implementation details of the Discrete Gamma Pool model , P. Jackel (2008)
  • Dynamic Models of Portfolio Credit Risk: A Simplified Approach , J.Hull, A.White (2008)
  • Calibration of CDO Tranches with the Dynamical Generalized-Poisson Loss Model , D. Brigo, A. Pallavicini, R. Torresetti (2007)
  • Forwards and European Option On CDO Tranches , J.Hull, A.White (2007)
  • BSLP: Markovian Bivariate Spread-Loss Model for Portfolio Credit Derivatives , M. Arnsdorf, I. Halperin (2007)
  • Two-Dimensional Markovian Model for Dynamics of Aggregate Credit Loss , A.V.Lopatin, T.Misirpashaev (2007)
  • An Implied Loss Model , M.Van Der Voort (2007)
  • Dynamic Conditioning and Credt Correlation Baskets , C.Albanese, A.Vidler (2007)
  • Background Filtrations and Canonical Loss Processes for Top-Down Models of Portfolio Credit Risk , P.Elhers, P.J.Schonbucher (2006)
  • On the term structure of loss distributions - a forward model approach , J. Sidenius (2006)
  • A New Framework for Dynamic Credit Portfolio Loss Modelling , 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 , P. Sch?nbucher (2006)
  • Portfolio Losses in Factor Models : Term Structures and Intertemporal Loss Dependence , L. Andersen (2006)
  • The Forward Loss Model: A Dynamic Term Structure Approach For The Pricing of Portfolio Credit Derivatives , N.Bennani (2005)

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