A regression-based Monte Carlo method to solve backward stochastic differential equations
概率论
2007-05-23 v1
摘要
We are concerned with the numerical resolution of backward stochastic differential equations. We propose a new numerical scheme based on iterative regressions on function bases, which coefficients are evaluated using Monte Carlo simulations. A full convergence analysis is derived. Numerical experiments about finance are included, in particular, concerning option pricing with differential interest rates.
引用
@article{arxiv.math/0508491,
title = {A regression-based Monte Carlo method to solve backward stochastic differential equations},
author = {Emmanuel Gobet and Jean-Philippe Lemor and Xavier Warin},
journal= {arXiv preprint arXiv:math/0508491},
year = {2007}
}
备注
Published at http://dx.doi.org/10.1214/105051605000000412 in the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org)