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Credit Risk Modelling with Shot-noise Processes

by Raquel M. Gaspar of the Technical University of Lisbon, and
Thorsten Schmidt of Chemnitz University of Technology

April 4, 2010

Abstract: In this work we study a form of shot-noise processes which is driven by LÚvy subordinators. The main focus is on applications to portfolios which are subject to credit risk. We show how to augment an arbitrary model for credit risk (e.g. an affine model) with shot-noise processes. This introduces clustering of defaults into the original model, which is an important model feature highlighted by the current credit crisis.

JEL Classification: C02, C51, G12.

AMS Classification: 60E10, 60G09, 60J75, 60H20, 62P05, 91B70, 91G40.

Keywords: credit portfolio risk, shot-noise processes, default dependence, affine models, local intensities, calibration, CDO.

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