Conditional Monte Carlo for sums, with applications to insurance and finance

Søren Asmussen

Annals of Actuarial Science, 2018, vol. 12, issue 2, 455-478

Abstract: Conditional Monte Carlo replaces a naive estimate Z of a number z by 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.

Date: 2018
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