Interacting path systems for credit portfolios risk analysis
نویسندگان
چکیده
This Note introduces an algorithm (referred to as interacting path systems algorithm, IPaS) based on the first Author multilevel splitting technique [5] and suited to the analysis of multiple defaults in credit portfolios. A full development of this Note incorporating technical details and a survey of the use of Interacting Particle Systems in the field of credit risk, Interacting path systems for credit risk, is submitted for publication in Recent Advancements in the Theory and Practice of Credit Derivatives, Eds T. Bielecki, D. Brigo, F. Patras, Bloomberg Press (2011). The reader is referred to this article for further details. Key-words: Credit portfolios risk analysis, rare event simulation, interacting particle systems, stochastic particle methods, genetic algorithms. ∗ Centre INRIA Bordeaux et Sud-Ouest & Institut de Mathématiques de Bordeaux , Université de Bordeaux I, 351 cours de la Libération 33405 Talence cedex, France, [email protected] † CNRS UMR 6621, Université de Nice, Laboratoire de Mathématiques J.-A. Dieudonné, Parc Valrose, 06108 Nice Cedex 2, France in ria -0 04 54 00 5, v er si on 1 7 Fe b 20 10 Systèmes de trajectoires en interaction pour l’analyse de risque de portefeuilles de crédit Résumé : Cette Note présente un algorithme (que nous nommerons systèmes de trajectoires en interaction, en abrégé IPaS) fondé sur des techniques de branchement multi-niveaux développées par le premier auteur [5], et qui s’appliquent de façon naturelle à l’analyse de défauts multiples de portefeuilles de crédit. La version complète de cette Note contenant les détails techniques ainsi qu’un survey sur l’utilisation des algorithmes fondés sur des systèmes de particules en interaction dans le domaine du risque de crédit est soumise pour publication dans l’ouvrage Recent Advancements in the Theory and Practice of Credit Derivatives, Eds T. Bielecki, D. Brigo, F. Patras, Bloomberg Press (2011). Nous renvoyons le lecteur à cet article pour une étude plus approfondie. Mots-clés : Portefeuilles de crédits, analyse de risque, simulation d’événements rares, systèmes de particules en interaction, méthodes particulaires stochastiques, algorithmes génétiques. in ria -0 04 54 00 5, v er si on 1 7 Fe b 20 10 Interacting path systems for credit portfolios risk analysis 3
منابع مشابه
Importance Sampling and Interacting Particle Systems for the Estimation of Markovian Credit Portfolios Loss Distribution
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 s...
متن کاملAnalytical Methods for Hedging Systematic Credit Risk with Linear Factor Portfolios
This paper is part of a series explaining various methodologies for defining and measuring the contributions of systematic factors to economic capital as well as for hedging systematic risk in credit portfolios. Multi-factor credit portfolio models are used widely today for measuring and managing economic capital as well as for pricing credit portfolio instruments such as collateralized debt ob...
متن کاملInvestigating the missing data effect on credit scoring rule based models: The case of an Iranian bank
Credit risk management is a process in which banks estimate probability of default (PD) for each loan applicant. Data sets of previous loan applicants are built by gathering their data, and these internal data sets are usually completed using external credit bureau’s data and finally used for estimating PD in banks. There is also a continuous interest for bank to use rule based classifiers to b...
متن کاملParticle Methods for the Estimation of Credit Portfolios Loss Distribution
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 s...
متن کاملModelling Credit Risk in portfolios of consumer loans: Transition Matrix Model for Consumer Credit Ratings
The corporate credit risk literature has many studies modelling the change in the credit risk of corporate bonds over time. There is far less analysis of the credit risk for portfolios of consumer loans. However behavioural scores, which are commonly calculated on a monthly basis by most consumer lenders are the analogues of ratings in corporate credit risk. Motivated by studies in corporate cr...
متن کامل