Multilevel Monte Carlo path simulation
成果类型：
Article
署名作者：
Giles, Michael B.
署名单位：
University of Oxford; University of Oxford
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.1070.0496
发表日期：
2008
页码：
607-617
关键词：
摘要：
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(epsilon) is reduced from O(epsilon(-3)) to O(epsilon(-2)(log epsilon)(2)). The analysis is supported by numerical results showing significant computational savings.