@inproceedings{51d2ca01e9f04e1794857f16315b28e0,
title = "Finite variance unbiased estimation of stochastic differential equations",
abstract = "We develop a new unbiased estimation method for Lipschitz continuous functions of multi-dimensional stochastic differential equations with Lipschitz continuous coefficients. This method provides a finite variance estimator based on a probabilistic representation which is similar to the recent representations obtained through the parametrix method and recursive application of the automatic differentiation formula. Our approach relies on appropriate change of variables to carefully handle the singular integrands appearing in the iterated integrals of the probabilistic representation. It results in a scheme with randomized intermediate times where the number of intermediate times has a Pareto distribution.",
author = "Ankush Agarwal and Emmanuel Gobet",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 Winter Simulation Conference, WSC 2017 ; Conference date: 03-12-2017 Through 06-12-2017",
year = "2017",
month = jun,
day = "28",
doi = "10.1109/WSC.2017.8247930",
language = "English",
series = "Proceedings - Winter Simulation Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1950--1961",
editor = "Victor Chan",
booktitle = "2017 Winter Simulation Conference, WSC 2017",
}