An efficient simulation procedure for point estimation of expected shortfall

Proceedings - Winter Simulation Conference

Volumn , Issue , 2010, Pages 2821-2831

  Liu, Ming ^a   Nelson, Barry L ^a   Staum, Jeremy ^a  

^a Northwestern University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL BUDGET; COMPUTATIONAL RESOURCES; COMPUTATIONALLY EFFICIENT; EFFICIENT SIMULATION; EXPECTED SHORTFALL; INTERVAL ESTIMATION; MEAN SQUARED ERROR; POINT ESTIMATION; RANKING AND SELECTION; SIMULATION PROCEDURES;

ESTIMATION;

EID: 79951645943     PISSN: 08917736     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WSC.2010.5678977     Document Type: Conference Paper

References (18)

1. Boesel, J., B. L. Nelson, and S. Kim. 2003. Using ranking and selection to 'clean up' after simulation optimization. Operations Research 51:814-825.
2. Broadie, M., Y. Du, and C. C. Moallemi. 2010. Efficient risk estimation via nested sequential simulation. Working paper, Columbia University.
3. Frye, J. 1998. Monte Carlo by day. Risk 11:66-71.
4. Gordy, M. B., and S. Juneja. 2006. Efficient simulation for risk measurement in portfolio of CDOs. In Proceeedings of the 2006 Winter Simulation Conference, ed. L. F. Perrone, B. Lawson, J. Liu, and F. P. Wieland, 749-756: IEEE Press.
5. Gordy, M. B., and S. Juneja. 2008. Nested simulation in portfolio risk measurement. Finance and Economics Discussion Series 2008-21, Federal Reserve Board.
6. Henderson, S. G. 2006. Mathematics for simulation. In Simulation, ed. S. G. Henderson and B. L. Nelson, Volume 13 of Handbooks in Operations Research and Management Science, Chapter 2. Amsterdam: Elsevier.
7. Kim, S.-H., and B. L. Nelson. 2006. Selecting the best system. In Simulation, ed. S. G. Henderson and B. L. Nelson, Volume 13 of Handbooks in Operations Research and Management Science, Chapter 17. Amsterdam: Elsevier.
8. Lan, H. 2010. Two-level simulation of expected shortfall: Confidence intervals, efficient simulation procedures, and high-performance computing. Ph. D. thesis, Northwestern University.
9. Lan, H., B. L. Nelson, and J. Staum. 2007. A confidence interval for tail conditional expectation via two-level simulation. In Proceedings of the 2007 Winter Simulation Conference, ed. S. G. Henderson, B. Biller, M.-H. Hsieh, J. Shortle,
10. J. D. Tew, and R. R. Barton, 949-957: IEEE Press.
11. Lan, H., B. L. Nelson, and J. Staum. 2010. Confidence interval procedures for expected shortfall via two-level simulation. Operations Research. In press.
12. Law, A. M., and W. D. Kelton. 2000. Simulation modeling and analysis. 3rd ed. New York: McGraw-Hill.
13. Lee, S.-H. 1998. Monte Carlo computation of conditional expectation quantiles. Ph. D. thesis, Stanford University.
14. Lesnevski, V., B. L. Nelson, and J. Staum. 2007. Simulation of coherent risk measures based on generalized scenarios. Management Science 53:1756-1769. (Pubitemid 351159573)
15. Lesnevski, V., B. L. Nelson, and J. Staum. 2008. An adaptive procedure for simulating coherent risk measures based on generalized scenarios. Journal of Computational Finance 11:1-31.
16. Liu, M. 2010. Efficient simulation in financial risk management. Ph. D. thesis, Northwestern University.
17. Liu, M., B. L. Nelson, and J. Staum. 2008. An efficient simulation procedure for point estimation of expected shortfall. Working paper 08-03, Dept. of IEMS, Northwestern University.
18. Shaw, J. 1998. Beyond VAR and stress testing. In Monte Carlo: Methodologies and Applications for Pricing and Risk Management, ed. B. Dupire, 231-244. London: Risk Books.