Erschienen:
Institute for Operations Research and the Management Sciences (INFORMS), 2012
Erschienen in:Operations Research
Sprache:
Englisch
DOI:
10.1287/opre.1110.1008
ISSN:
0030-364X;
1526-5463
Entstehung:
Anmerkungen:
Beschreibung:
<jats:p>We provide a sequential Monte Carlo method for estimating rare-event probabilities in dynamic, intensity-based point process models of portfolio credit risk. The method is based on a change of measure and involves a resampling mechanism. We propose resampling weights that lead, under technical conditions, to a logarithmically efficient simulation estimator of the probability of large portfolio losses. A numerical analysis illustrates the features of the method and contrasts it with other rare-event schemes recently developed for portfolio credit risk, including an interacting particle scheme and an importance sampling scheme.</jats:p>