Abstract
AbstractConditional Monte Carlo replaces a naive estimateZof a numberzby its conditional expectation given a suitable piece of information. It always reduces variance and its traditional applications are in that vein. We survey here other potential uses such as density estimation and calculations for Value-at-Risk and/or expected shortfall, going in part into the implementation in various copula structures. Also the interplay between these different aspects comes into play.
Publisher
Cambridge University Press (CUP)
Subject
Statistics, Probability and Uncertainty,Economics and Econometrics,Statistics and Probability
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