BSLP: Markovian Bivariate Spread-Loss Model for Portfolio Credit Derivatives

By M. Arnsdorf, Igor Halperin. 2008

99 citations recorded by the source corpus.

BSLP is a two-dimensional dynamic model of interacting portfolio-level loss and spread (more exactly, loss intensity) processes. The model is similar to the top-down HJM-like frameworks developed by Schonbucher (2005) and Sidenius-Peterbarg-Andersen (SPA) (2005), however is constructed as a Markovian, short-rate intensity model. This property of the model enables fast lattice methods for pricing various portfolio credit derivatives such as tranche options, forward-starting tranches, leveraged super-senior tranches etc. A non-parametric model specification is used to achieve nearly perfect calibration to liquid tranche quotes across strikes and maturities. A non-dynamic version of the model obtained in the zero volatility limit of stochastic intensity is useful on its own as an arbitrage-free interpolation model to price non-standard index tranches off the standard ones.

View Paper: https://www.semanticscholar.org/paper/892af910e4db55d6daed87e54190c2da3ea55c72

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Citations in the corpus

Dynamic hedging of synthetic CDO tranches with spread risk and default contagion (2010, methodology): “…the the aggregate loss L is the modelling primitive and information related to credit quality and default state of individual names is ignored; see for instance Giesecke & Goldberg (2007), Schönbucher (2006), Arnsdorf & Halperin (2007), Lopatin & Misirpashaev (2007) or Cont & Minca (2008).”
Affine Point Processes and Portfolio Credit Risk (2010, unknown): “Arnsdorf and Halperin [2] describe arrivals by a nonlinear death process and its generalizations.”
Two-Dimensional Markovian Model for Dynamics of Aggregate Credit Loss (2008, unknown): “(4) for the stochastic intensity model.”
RECOVERING PORTFOLIO DEFAULT INTENSITIES IMPLIED BY CDO QUOTES (2013, unknown): “Ding et al. [15] construct the default process by starting from a linear birth process with immigration = 𝑐 + and applying a time change, while Arnsdorﬀ & Halperin [1] use a two factor speciﬁcation: = 𝜆 0 ( 𝑁 0 − 𝑁 𝑡 ) 𝑌 𝑡 where is a non-negative stochastic process (see also [26]).”
Up and down credit risk (2010, methodology): “Examples of this approach are Bennani (2006), Ehlers and Schönbucher (2006), Schönbucher (2006), Sidenius et al. (2006), and Arnsdorf and Halperin (2007).”