Calibrating credit portfolio loss distributions

• Published in: Proceedings of the 36th conference on Winter simulation pp. 1661 - 1667
• Main Authors: Cao, Menghui, Morokoff, William J.
• Format: Conference Proceeding
• Language: English
• Published: Piscataway NJ Winter Simulation Conference 05.12.2004; IEEE
• Series: ACM Conferences
• Subjects: Applied computing; Applied computing > Enterprise computing; Applied sciences; Computer science; control theory; systems; Exact sciences and technology; Mathematics of computing; Mathematics of computing > Probability and statistics; Mathematics of computing > Probability and statistics > Probabilistic reasoning algorithms; Mathematics of computing > Probability and statistics > Probabilistic reasoning algorithms > Markov-chain Monte Carlo methods; Simulation; Software; Correlation; Credit; Gaussian process; Simulation; Banking; Markets; Continuous time; Risk analysis; Risk management; Portfolio management; Modeling
• ISBN: 9780780387867; 0780387864
• DOI: 10.5555/1161734.1162043

Determination of credit portfolio loss distributions is essential for the valuation and risk management of multi-name credit derivatives such as CDOs. The default time model has recently become a market standard approach for capturing the default correlation, which is one of the main drivers for the portfolio loss. However, the default time model yields very different default dependency compared with a continuous-time credit migration model. To build a connection between them, we calibrate the correlation parameter of a single-factor Gaussian copula model to portfolio loss distribution determined from a multi-step credit migration simulation. The deal correlation is produced as a measure of the portfolio average correlation effect that links the two models. Procedures for obtaining the portfolio loss distributions in both models are described in the paper and numerical results are presented.