PARTICLE METHODS FOR THE ESTIMATION OF CREDIT PORTFOLIO LOSS DISTRIBUTIONS

René Carmona () and Stéphane Crépey
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René Carmona: Bendheim Center for Finance, ORFE, Princeton University, Princeton, NJ 08544, USA
Stéphane Crépey: Département de Mathématiques, Université d'Évry Val d'Essonne, 91025 Évry Cedex, France

International Journal of Theoretical and Applied Finance (IJTAF), 2010, vol. 13, issue 04, 577-602

Abstract: The goal of the paper is the numerical analysis of the performance of Monte Carlo simulation based methods for the computation of credit-portfolio loss-distributions in the context of Markovian intensity models of credit risk. We concentrate on two of the most frequently touted methods of variance reduction in the case of stochastic processes: importance sampling (IS) and interacting particle systems (IPS) based algorithms. Because the subtle differences between these methods are often misunderstood, as IPS is often regarded as a mere particular case of IP, we describe in detail the two kinds of algorithms, and we highlight their fundamental differences. We then proceed to a detailed comparative case study based on benchmark numerical experiments chosen for their popularity in the quantitative finance circles.

Keywords: Importance sampling; interacting particle systems; rare events; credit portfolios; loss distribution estimation (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (5)

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DOI: 10.1142/S0219024910005905

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