The quickhull algorithm for convex hulls
ACM Transactions on Mathematical Software (TOMS)
Monte carlo computation of conditional expectation quantiles
Monte carlo computation of conditional expectation quantiles
Design and Analysis of Simulation Experiments
Design and Analysis of Simulation Experiments
Stochastic Kriging for Simulation Metamodeling
Operations Research
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We present an efficient two-level simulation procedure which uses stochastic kriging, a metamodeling technique, to estimate expected shortfall, a portfolio risk measure. The outer level simulates financial scenarios and the inner level of simulation estimates the portfolio value given a scenario. Spatial metamodeling enables inference about portfolio values in a scenario based on inner-level simulation of nearby scenarios, reducing the required computational effort. Because expected shortfall involves the scenarios that entail the largest losses, our procedure adaptively allocates more computational effort to inner-level simulation of those scenarios, which also improves computational efficiency.