Multilevel Monte Carlo path simulation

We show that multigrid ideas can be used to reduce the computational complexity of estimating an expected value arising from a stochastic differential equation using Monte Carlo path simulations. In the simplest case of a Lipschitz payoff and a Euler discretisation, the computational cost to achieve...

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Main Author: Giles, M
Format: Journal article
Language:English
Published: 2008
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author Giles, M
author_facet Giles, M
author_sort Giles, M
collection OXFORD
description We show that multigrid ideas can be used to reduce the computational complexity of estimating an expected value arising from a stochastic differential equation using Monte Carlo path simulations. In the simplest case of a Lipschitz payoff and a Euler discretisation, the computational cost to achieve an accuracy of O(ε) is reduced from O(ε-3) to O(ε-2(logε)2). The analysis is supported, by numerical results showing significant computational savings. © 2008 INFORMS.
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spelling oxford-uuid:0aa80ab7-9406-4778-8f1a-cdafc9c1ed9b2022-03-26T09:25:00ZMultilevel Monte Carlo path simulationJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:0aa80ab7-9406-4778-8f1a-cdafc9c1ed9bEnglishSymplectic Elements at Oxford2008Giles, MWe show that multigrid ideas can be used to reduce the computational complexity of estimating an expected value arising from a stochastic differential equation using Monte Carlo path simulations. In the simplest case of a Lipschitz payoff and a Euler discretisation, the computational cost to achieve an accuracy of O(ε) is reduced from O(ε-3) to O(ε-2(logε)2). The analysis is supported, by numerical results showing significant computational savings. © 2008 INFORMS.
spellingShingle Giles, M
Multilevel Monte Carlo path simulation
title Multilevel Monte Carlo path simulation
title_full Multilevel Monte Carlo path simulation
title_fullStr Multilevel Monte Carlo path simulation
title_full_unstemmed Multilevel Monte Carlo path simulation
title_short Multilevel Monte Carlo path simulation
title_sort multilevel monte carlo path simulation
work_keys_str_mv AT gilesm multilevelmontecarlopathsimulation