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Discrete Credit Barrier Models

by Claudio Albanese of Imperial College, London, and
Oliver X. Chen of the National University of Singapore

November 2004

Abstract: The model introduced in this article is designed to provide a consistent representation for both the real-world and pricing measures for the credit process. We find that good agreement with historical and market data can be achieved across all credit ratings simultaneously. The model is characterized by an underlying stochastic process that takes on values on a discrete lattice and represents credit quality. Rating transitions are associated to barrier crossings and default events are associated with an absorbing state. The stochastic process has state dependent volatility and jumps which are estimated by using empirical migration and default rates. A risk-neutralizing drift is estimated to consistently match the average spread curves corresponding to all the various ratings.

Keywords: Discrete Credit Barrier Models.

Published in: Quantitative Finance, Vol. 5, No. 3, (June 2005), pp. 247-256.

Previously titled: Credit Barrier Models

Download paper (369K PDF) 17 pages