Importance sampling for a mixed Poisson model of portfolio credit risk

Author

Glasserman, Paul ; Li, Jingyi

Author_Institution

Columbia Bus. Sch., Columbia Univ., New York, NY, USA

Volume

1

fYear

2003

fDate

7-10 Dec. 2003

Firstpage

267

Abstract

Simulation is widely used to estimate losses due to default and other credit events in financial portfolios. The challenge in doing this efficiently results from (i) rare-event aspects of large losses and (ii) complex dependence between defaults of multiple obligors. We discuss importance sampling techniques to address this problem in two portfolio credit risk models developed in the financial industry, with particular emphasis on a mixed Poisson model. We give conditions for asymptotic optimality of the estimators as the portfolio size grows.

Keywords

digital simulation; financial data processing; importance sampling; risk analysis; stochastic processes; asymptotic optimality; complex dependence; credit events; financial industry; financial portfolios; importance sampling; loss estimation; mixed Poisson model; multiple obligors; portfolio credit risk models; portfolio size; rare-event aspects; simulation; Business; Computational modeling; Discrete event simulation; Heart; Law; Legal factors; Loss measurement; Monte Carlo methods; Portfolios; Risk management;

fLanguage

English

Publisher

ieee

Conference_Titel

Simulation Conference, 2003. Proceedings of the 2003 Winter

Print_ISBN

0-7803-8131-9

Type

conf

DOI

10.1109/WSC.2003.1261433

Filename

1261433