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

  • Søren Asmussen (a1)

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.

Corresponding author
*Correspondence to: Søren Asmussen, Department of Mathematics, Aarhus University, Ny Munkegade, 8000 Aarhus C, Denmark. Tel: +45-8715 5756; E-mail:
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Annals of Actuarial Science
  • ISSN: 1748-4995
  • EISSN: 1748-5002
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