Title :
A new approach to unbiased estimation for SDE´s
Author :
Chang-han Rhee ; Glynn, Peter W.
Author_Institution :
Stanford Univ., Stanford, CA, USA
Abstract :
In this paper, we introduce a new approach to constructing unbiased estimators when computing expectations of path functionals associated with stochastic differential equations (SDEs). Our randomization idea is closely related to multi-level Monte Carlo and provides a simple mechanism for constructing a finite variance unbiased estimator with “square root convergence rate” whenever one has available a scheme that produces strong error of order greater than 1/2 for the path functional under consideration.
Keywords :
Monte Carlo methods; convergence of numerical methods; differential equations; estimation theory; stochastic processes; SDE; expectation computation; multilevel Monte Carlo methods; path functionals; randomization idea; square root convergence rate; stochastic differential equations; unbiased estimation; variance unbiased estimator; Approximation algorithms; Approximation methods; Convergence; Differential equations; Estimation; Monte Carlo methods; Standards;
Conference_Titel :
Simulation Conference (WSC), Proceedings of the 2012 Winter
Conference_Location :
Berlin
Print_ISBN :
978-1-4673-4779-2
Electronic_ISBN :
0891-7736
DOI :
10.1109/WSC.2012.6465150
