Efficient estimation of large portfolio loss probabilities in t-copula models

European Journal of Operational Research

Volumn 205, Issue 2, 2010, Pages 361-367

  Chan, Joshua C C ^a   Kroese, Dirk P ^a  

^a UNIVERSITY OF QUEENSLAND   (Australia)

Author keywords

Conditional Monte Carlo; Copula models; Credit risk; Cross entropy method; Rare event simulation

Indexed keywords

CONDITIONAL MONTE CARLO; CREDIT RISKS; CROSS-ENTROPY METHOD; MONTE CARLO; RARE EVENT SIMULATION;

ESTIMATION; MONTE CARLO METHODS; PROBABILITY; RISK ASSESSMENT;

RISK PERCEPTION;

EID: 76949106058     PISSN: 03772217     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ejor.2010.01.003     Document Type: Article

References (26)

1. Asmussen S., and Glynn P.W. Stochastic Simulation: Algorithms and Analysis (2007), Springer, New York
2. Asmussen S., and Kroese D.P. Improved algorithms for rare event simulation with heavy tails. Advances in Applied Probability 38 (2006) 545-558
3. Azzalini A. A class of distributions which includes the normal ones. Scandinavian Journal of Statistics 12 (1985) 171-178
4. Azzalini A., and Dalla Valle A. The multivariate skew-normal distribution. Biometrika 83 (1996) 715-726
5. Bassamboo A., Juneja S., and Zeevi A. Portfolio credit risk with extremal dependence: Asymptotic analysis and efficient simulation. Operations Research 56 3 (2008) 593-606
6. Bluhm C., Overbeck L., and Wagner C. An Introduction to Credit Risk Modeling (2002), Chapman & Hall/CRC
7. Chan, J.C.C., Kroese, D.P., in press. Rare-event probability estimation with Monte Carlo. Annals of Operations Research. doi:10.1007/s10479-009-0539-y.
8. Egloff, D., Leippold, M., Jöhri, S., Dalbert, C., 2005. Optimal importance sampling for credit portfolios with stochastic approximation SSRN working paper.
9. Fernandez C., and Steel M.F.J. On Bayesian modeling of fat tails and skewness. Journal of the American Statistical Association 93 441 (1998) 359-371
10. Franses P.H., and van Dijk D. Non-linear Time Series Models in Empirical Finance (2000), Cambridge University Press, Cambridge
11. Geweke, J., 1991. Efficient simulation from the multivariate normal and student-t distributions subject to linear constraints and the evaluation of constraint probabilities. In: Keramidas, E., Kaufman, S. (Eds.), Computing Science and Statistics: Proceedings of the 23rd Symposium on the Interface, pp. 571-578.
12. Geweke J. Bayesian treatment of the independent student-t linear model. Journal of Applied Econometrics 8 (1993) S19-S40
13. Glasserman P., and Li J. Importance sampling for portfolio credit risk. Management Science 51 11 (2005) 1643-1656
14. Glasserman P., Kang W., and Shahabuddin P. Large deviations of multifactor portfolio credit risk. Mathematical Finance 17 (2007) 345-379
15. Glasserman P., Kang W., and Shahabuddin P. Fast simulation of multifactor portfolio credit risk. Operations Research 56 5 (2008) 1200-1217
16. Grundke P. Importance sampling for integrated market and credit portfolio models. European Journal of Operational Research 194 1 (2009) 206-226
17. Gupton, G., Finger, C., Bhatia, M., 1997. Creditmetrics technical document. Technical report, J.P. Morgan & Co., New York.
18. Joshi, M.S., 2004. Applying importance sampling to pricing single tranches of CDOs in a one-factor Li model. Technical report, QUARC, Group Risk Management, Royal Bank of Scotland.
19. Juneja S., and Shahabuddin P. Simulating heavy tailed processes using delayed hazard rate twisting. ACM Transactions on Modeling and Computer Simulation 12 2 (2002) 94-118
20. Kalkbrener M., Lotter H., and Overbeck L. Sensible and efficient capital allocation for credit portfolios. Risk 17 1 (2004) S19-S24
21. Li D. On default correlations: A copula function approach. Journal of Fixed Income 9 (2000) 43-54
22. McNeil A., Frey R., and Embrechts P. Quantitative Risk Management: Concepts, Techniques and Tools (2005), Princeton University Press, Princeton, New Jersey
23. Robert C.P. Simulation of truncated normal variables. Statistics and Computing 5 (1995) 121-125
24. Rubinstein R.Y., and Kroese D.P. The Cross-Entropy Method: A Unified Approach to Combinatorial Optimization Monte-Carlo Simulation, and Machine Learning (2004), Springer-Verlag, New York
25. Rubinstein R.Y., and Kroese D.P. Simulation and the Monte Carlo Method. second ed. (2007), John Wiley & Sons, New York
26. van der Vert A.W. Asymptotic Statistics (1998), Cambridge University Press