Efficient VaR and CVaR Measurement via Stochastic Kriging
Published Online:17 Aug 2016https://doi.org/10.1287/ijoc.2016.0705
References
- (2010) Stochastic kriging for simulation metamodeling. Oper. Res. 58(2):371–382.Link, Google Scholar
- (2007) Stochastic Simulation (Springer, New York).Google Scholar
- (2014) Steady-state quantile parameter estimation: An empirical comparison of stochastic kriging and quantile regression. Tolk A, Diallo SY, Ryzhov IO, Yilmaz L, Buckley S, Miller JA, eds. Proc. 2014 Winter Simulation Conf. (Institute of Electrical and Electronics Engineers, Inc., Washington, DC), 3880–3891.Crossref, Google Scholar
- (2012) Combating risk with predictive intelligence. Technical report, IBM Global Services, Somers, NY.Google Scholar
- (2009) Metamodels for estimating quantiles of systems with one controllable parameter. Simulation 85(5):307–317.Crossref, Google Scholar
- (2013) Building metamodels for quantile-based measures using sectioning. Pasupathy R, Kim SH, Tolk A, Hill R, Kuhl ME, eds. Proc. 2013 Winter Simulation Conf. (Institute of Electrical and Electronics Engineers, Inc., Washington, DC), 521–532.Crossref, Google Scholar
- (2014) Stochastic kriging with biased sample estimates. ACM Trans. Modeling Comput. Simulation 24:8/1–8/23.Crossref, Google Scholar
- (2012) The effects of common random numbers on stochastic kriging metamodels. ACM Trans. Modeling Comput. Simulation 22:7/1–7/20.Crossref, Google Scholar
- (2013) Enhancing stochastic kriging metamodels with gradient estimators. Oper. Res. 61(2):512–528.Link, Google Scholar
- (2015) Optimal jackknife for unit root models. Statist. Probab. Lett. 99:135–142.Crossref, Google Scholar
- (2012) Confidence intervals for quantiles when applying variance-reduction techniques. ACM Trans. Modeling Comput. Simulation 22:10/1–10/25.Crossref, Google Scholar
- (2010) Robust quantile estimation and prediction for spatial processes. Statist. Probab. Lett. 80(17–18):1447–1458.Crossref, Google Scholar
- (2003) Order Statistics, 3rd ed. (Wiley, Hoboken, NJ).Crossref, Google Scholar
- (2012) Robust optimization in simulation: Taguchi and Krige combined. INFORMS J. Comput. 24(3):471–484.Link, Google Scholar
- (1982) The Jackknife, the Bootstrap and Other Resampling Plans (SIAM, Philadelphia).Crossref, Google Scholar
- (1981) The jackknife estimate of variance. Ann. Statist. 9(3):586–596.Crossref, Google Scholar
- (1993) An Introduction to the Bootstrap (Chapman & Hall/CRC, New York).Crossref, Google Scholar
- (2006) Graduent estimation. Henderson SG, Nelson BL, eds. Simulation, Handbooks in Operations Research and Management Science, Vol. 13 (Elsevier, Amsterdam), 575–616.Crossref, Google Scholar
- (2010) Nested simulation in portfolio risk measurement. Management Sci. 56(10):1833–1848.Link, Google Scholar
- (2007) Adaptive distributed metamodeling. Kuhl ME, Steiger NM, Armstrong FB, Joines JA, eds. Proc. 7th Internat. Conf. High Performance Comput. Computational Sci. (VECPAR 2006) (Springer-Verlag, Berlin), 579–588.Crossref, Google Scholar
- (2013) Error estimation properties of Gaussian process models in stochastic simulations. Eur. J. Oper. Res. 228(1):131–140.Crossref, Google Scholar
- (2009) Estimating quantile sensitivities. Oper. Res. 57(1):118–130.Link, Google Scholar
- (2009) Simulating sensitivities of conditional value at risk. Management Sci. 55(2):281–293.Link, Google Scholar
- (1990) Control variates for quantile estimation. Management Sci. 36(7):835–851.Link, Google Scholar
- (1967) On Bahadur’s representation of sample quantiles. Ann. Math. Statist. 38(5):1323–1342.Crossref, Google Scholar
- (2005) Supply chain simulation tools and techniques: A survey. Internat. J. Simulation Process Model. 1(1–2):82–89.Crossref, Google Scholar
- (2015) Design and Analysis of Simulation Experiments, 2nd ed. (Springer, New York), 579–588.Crossref, Google Scholar
- (2009) A note on nonparametric estimation of the CTE. Astin Bull. 39(2):717–734.Crossref, Google Scholar
- (2005) Quantile Regression (Cambridge University Press, New York).Crossref, Google Scholar
- (1990) A unified view of the IPA, SF, and LR gradient estimation techniques. Management Sci. 36(11):1364–1383.Link, Google Scholar
- (2012) A new approach to risk comparison via uncertain measure. Indust. Engrg. Management Systems 11(2):176–182.Crossref, Google Scholar
- (2015) Classic Kriging versus Kriging with bootstrapping or conditional simulation: Classic Kriging’s robust confidence intervals and optimization. J. Oper. Res. Soc. 66(11):1804–1814.Crossref, Google Scholar
- (2014) Confidence intervals for quantiles using sectioning when applying variance-reduction techniques. ACM Trans. Modeling Comput. Simulation 24:19/1–19/21.Crossref, Google Scholar
- (2002) Perspectives on the evolution of simulation. Oper. Res. 50(1):161–172.Link, Google Scholar
- (2005) Jackknifing bond option prices. Rev. Financial Stud. 18(2):707–742.Crossref, Google Scholar
- (2013) Quantile-based optimization of noisy computer experiments with tunable precision (with comments and rejoinder). Technometrics 55(1):2–36.Crossref, Google Scholar
- (1990) Variance reduction for quantile estimates in simulations via nonlinear controls. Comm. Statist.—Simulation Comput. 19(3):1045–1077.Crossref, Google Scholar
- (2013) Mathematical Risk Analysis (Springer-Verlag, Berlin).Crossref, Google Scholar
- (1989) Design and analysis of computer experiments. Statist. Sci. 4(4):409–423.Crossref, Google Scholar
- (2003) The Design and Analysis of Computer Experiments (Springer, New York).Crossref, Google Scholar
- (2012) A quantitative analysis of disruption risk in a multi-echelon supply chain. Internat. J. Production Econom. 139(1):22–32.Crossref, Google Scholar
- (1982) A batching approach to quantile estimation in regenerative simulations. Management Sci. 28(5):573–581.Link, Google Scholar
- (1980) Approximation Theorems of Mathematical Statistics (Wiley, New York).Crossref, Google Scholar
- (1993) Differentiability of statistical functionals and consistency of the jackknife. Ann. Statist. 21(1):61–75.Crossref, Google Scholar
- (1995) The Jackknife and Bootstrap (Springer, New York).Crossref, Google Scholar
- (1989) A general theory for jackknife variance estimation. Ann. Statist. 17(3):1176–1197.Crossref, Google Scholar
- (2015) A comparison study of parametric and semiparametric bootstrapping in deterministic simulation. Internat. J. Appl. Math. Statist. 53(5):172–181.Google Scholar
- (1998) Quantitative Models for Supply Chain Management (Springer, New York).Google Scholar
- (2007) Financial prediction with constrianed tail risk. J. Banking Finance 31(11):3524–3538.Crossref, Google Scholar
- (2008) Estimating cycle time percentile curves for manufacturing systems via simulation. INFORMS J. Comput. 20(4):628–643.Link, Google Scholar
- (2009) A study on the effects of parameter estimation on kriging model’s prediction error in stochastic simulations. Rossetti MD, Hill RR, Johansson B, Dunkin A, Ingalls RG, eds. Proc. 2009 Winter Simulation Conf. (IEEE, Austin, TX), 674–685.Crossref, Google Scholar

