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Monte carlo algorithms for default timing problems / Kay Giesecke in Management science, Vol. 57 N° 12 (Décembre 2011) 

Public ISBD [article]  in Management science > Vol. 57 N° 12 (Décembre 2011) . - pp. 2115-2129 Titre : Monte carlo algorithms for default timing problems Type de document : texte imprimé Auteurs : Kay Giesecke, Auteur ; Baeho Kim, Auteur ; Shilin Zhu, Auteur Année de publication : 2012 Article en page(s) : pp. 2115-2129 Note générale : Management Langues : Anglais (eng) Mots-clés : Simulation  Probability  Stochastic  model  applications  Financial  institutions  Banks Résumé : Dynamic, intensity-based point process models are widely used to measure and price the correlated default risk in portfolios of credit-sensitive assets such as loans and corporate bonds. Monte Carlo simulation is an important tool for performing computations in these models. This paper develops, analyzes, and evaluates two simulation algorithms for intensity-based point process models. The algorithms extend the conventional thinning scheme to the case where the event intensity is unbounded, a feature common to many standard model formulations. Numerical results illustrate the performance of the algorithms for a familiar top-down model and a novel bottom-up model of correlated default risk. DEWEY : 658 ISSN : 0025-1909 En ligne : http://mansci.journal.informs.org/content/57/12.toc [article] Monte carlo algorithms for default timing problems [texte imprimé] / Kay Giesecke, Auteur ; Baeho Kim, Auteur ; Shilin Zhu, Auteur . - 2012 . - pp. 2115-2129. Management Langues : Anglais (eng) in Management science > Vol. 57 N° 12 (Décembre 2011) . - pp. 2115-2129 Mots-clés : Simulation  Probability  Stochastic  model  applications  Financial  institutions  Banks Résumé : Dynamic, intensity-based point process models are widely used to measure and price the correlated default risk in portfolios of credit-sensitive assets such as loans and corporate bonds. Monte Carlo simulation is an important tool for performing computations in these models. This paper develops, analyzes, and evaluates two simulation algorithms for intensity-based point process models. The algorithms extend the conventional thinning scheme to the case where the event intensity is unbounded, a feature common to many standard model formulations. Numerical results illustrate the performance of the algorithms for a familiar top-down model and a novel bottom-up model of correlated default risk. DEWEY : 658 ISSN : 0025-1909 En ligne : http://mansci.journal.informs.org/content/57/12.toc