Bayesian methodsBayesian / computational

Multilevel Monte Carlo Simulation

Multilevel Monte Carlo (MLMC) is a variance-reduction technique that estimates expectations by combining simulations run at multiple levels of numerical resolution. Coarse, cheap simulations capture most of the signal; fine, expensive simulations correct only the remaining small difference — dramatically reducing total computational cost compared with standard Monte Carlo at the finest level alone.

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Sources

  1. Giles, M. B. (2008). Multilevel Monte Carlo path simulation. Operations Research, 56(3), 607–617. DOI: 10.1287/opre.1070.0496
  2. Giles, M. B. (2015). Multilevel Monte Carlo methods. Acta Numerica, 24, 259–328. DOI: 10.1017/S096249291500009X

Related methods

ScholarGateMultilevel Monte Carlo Simulation (Multilevel Monte Carlo Simulation). Retrieved 2026-06-04 from https://scholargate.app/en/bayesian/multilevel-monte-carlo-simulation