Hybrid Adaptive Multilevel Monte Carlo Algorithm for Non-Smooth Observables of Itô Stochastic Differential Equations

Hybrid Adaptive Multilevel Monte Carlo Algorithm for Non-Smooth Observables of Itô Stochastic Differential Equations

The Monte Carlo forward Euler method with uniform time stepping is the standard technique to compute an approximation of the expected payoff of a solution of an Itô SDE. For a given accuracy requirement TOL, the complexity of this technique for well behaved problems, that is the amount of computatio...

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Bibliographic Details
Main Author: Rached, Nadhir B.
Other Authors: Tempone, Raul
Language:en
Published: 2013
Subjects:
Multilevel Monte Carlo
non-smooth observables
Ito^ SDE
Hybrid Adaptivity
Online Access:Rached, N. B. (2013). Hybrid Adaptive Multilevel Monte Carlo Algorithm for Non-Smooth Observables of Itô Stochastic Differential Equations. KAUST Research Repository. https://doi.org/10.25781/KAUST-QJRW1
http://hdl.handle.net/10754/306490

Internet

Rached, N. B. (2013). Hybrid Adaptive Multilevel Monte Carlo Algorithm for Non-Smooth Observables of Itô Stochastic Differential Equations. KAUST Research Repository. https://doi.org/10.25781/KAUST-QJRW1
http://hdl.handle.net/10754/306490

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