Credit Risk Modelling with Shot-noise Processes
by Raquel M. Gaspar of the Technical University of Lisbon, and
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.
Keywords: credit portfolio risk, shot-noise processes, default dependence, affine models, local intensities, calibration, CDO.