Efficient risk estimation via nested sequential simulation

Management Science

Volumn 57, Issue 6, 2011, Pages 1172-1194

  Broadie, Mark ^a   Du, Yiping ^b   Moallemi, Ciamac C ^a  

^a Och Spine at New York Presbyterian Hospitals   (United States)

^b NONE   (United States)

Author keywords

Decision analysis; Risk; Risk management; Sequential analysis; Simulation

Indexed keywords

COMPUTATIONAL EFFORT; COMPUTATIONAL PROBLEM; FASTER CONVERGENCE; FINANCIAL RISKS; NESTED SIMULATION; NUMERICAL RESULTS; PORTFOLIO VALUE; RISK ESTIMATION; RISK ESTIMATORS; RISK MEASURES; SEQUENTIAL ANALYSIS; SEQUENTIAL SIMULATION; SIMULATION; SIMULATION-BASED; THEORETICAL RESULT;

ALGORITHMS; ESTIMATION; RISK ANALYSIS; RISK ASSESSMENT; RISK MANAGEMENT;

RISK PERCEPTION;

EID: 79959249121     PISSN: 00251909     EISSN: 15265501     Source Type: Journal    
DOI: 10.1287/mnsc.1110.1330     Document Type: Article

References (28)

1. Artzner, P., F. Delbaen, J.-M. Eber, D. Heath. 2000. Coherent measures of risk. Math. Finance 9(3) 203-228.
2. Chan, T. F., G. H. Golub, R. J. LeVeque. 1983. Algorithms for computing the sample variance: Analysis and recommendations. Amer. Statist. 37(3) 242-247.
3. Chen, C.-H., L. Lee. 2010. Stochastic Simulation Optimization: An Optimal Computing Budget Allocation. World Scientific, Singapore.
4. Cormen, T. H., C. E. Leiserson, R. L. Rivest, C. Stein. 2002. Introduction to Algorithms, 2nd ed. MIT Press, Cambridge, MA.
5. Crouhy, M., D. Galai, R. Mark. 2000. Risk Management. McGraw- Hill, New York.
6. Föllmer, H., A. Schied. 2002. Robust preferences and convex measures of risk. K. Sandmann, P. J. Schönbucher, eds. Advances in Finance and Stochastics. Springer-Verlag, Berlin, 39-56.
7. Frazier, P. I., W. B. Powell, S. Dayanik. 2008. A knowledge-gradient policy for sequential information collection. SIAM J. Control Optim. 47(5) 2410-2439.
8. Glasserman, P., P. Heidelberger, P. Shahabuddin. 2000. Variance reduction techniques for estimating value-at-risk. Management Sci. 46(10) 1349-1364. (Pubitemid 32021940)
9. Glasserman, P., P. Heidelberger, P. Shahabuddin. 2002. Portfolio value-at-risk with heavy-tailed risk factors. Math. Finance 12(3) 239-270.
10. Gordy, M. B., S. Juneja. 2008. Nested simulation in portfolio risk measurement. FEDS 2008-21, Federal Reserve Board, Washington, DC.
11. Gordy, M. B., S. Juneja. 2010. Nested simulation in portfolio risk management. Management Sci. 56(10) 1833-1848.
12. Gut, A. 1974. On the moments and limit distributions of some first passage times. Ann. Probab. 2(2) 277-308.
13. Hong, L. J., S. Juneja. 2009. Estimating the mean of a non-linear function of conditional expectation. M. D. Rossetti, R. R. Hill, B. Johansson, A. Dunkin, R. G. Ingalls, eds. Proc. 2009 Winter Simulation Conf., IEEE Press, Piscataway, NJ, 1223-1236.
14. Jorion, P. 2006. Value at Risk. McGraw-Hill, New York.
15. Kim, S.-H., B. L. Nelson. 2005. Selecting the best system. S. G. Henderson, B. L. Nelson, eds. Handbooks in Operations Research and Management Science: Simulation. Elsevier, Oxford, UK, 501-534.
16. Lan, H., B. L. Nelson, J. Staum. 2007. Two-level simulations for risk management. Proc. 2007 INFORMS Simulation Soc. Res. Workshop, Fontainebleau, France, 102-107.
17. Lan, H., B. L. Nelson, J. Staum. 2010. A confidence interval procedure for expected shortfall risk measurement via two-level simulation. Oper. Res. 58(5) 1481-1490.
18. Lee, S.-H. 1998. Monte Carlo Computation of Conditional Expectation Quantiles. Ph.D. thesis, Stanford University, Stanford, CA.
19. Lee, S.-H., P. W. Glynn. 2003. Computing the distribution function of a conditional expectation via Monte Carlo: Discrete conditioning spaces. ACM Trans. Modeling Comput. Simulation 13(3) 238-258.
20. Lesnevski, V., B. L. Nelson, J. Staum. 2004. Simulation of coherent risk measures. Proc. 2004 Winter Simulation Conf., IEEE Press, Piscataway, NJ, 1579-1585.
21. Lesnevski, V., B. L. Nelson, J. Staum. 2007. Simulation of coherent risk measures based on generalized scenarios. Management Sci. 53(11) 1756-1769. (Pubitemid 351159573)
22. Liu, M., J. Staum. 2010. Stochastic kriging for efficient nested simulation of expected shortfall. J. Risk 12(3) 3-27.
23. Liu, M., B. L. Nelson, J. Staum. 2010. An efficient simulation procedure for point estimation of expected shortfall. Proc. 2010 Winter Simulation Conf., IEEE Press, Piscataway, NJ, 2821-2831.
24. Lorden, G. 1970. On excess over the boundary. Ann. Math. Statist. 41(2) 520-527.
25. McNeil, A., R. Frey, P. Embrechts. 2006. Quantitative Risk Management: Concepts, Techniques, and Tools. Princeton University Press, Princeton, NJ. Pruitt,W. E. 1981. The growth of random walks and Levy processes. Ann. Probab. 9(6) 948-956.
26. Rockafellar, R. T., S. Uryasev. 2002. Conditional value-at-risk for general loss distributions. J. Banking Finance 26(7) 1443-1471.
27. Siegmund, D. 1985. Sequential Analysis: Tests and Confidence Intervals. Springer, New York.
28. Sun, Y., D. W. Apley, J. Staum. 2011. Efficient nested simulation for estimating the variance of a conditional expectation. Oper. Res. Forthcoming.