A regression-based Monte Carlo method to solve backward stochastic differential equations

被引：238
|
作者：
Gobet, E [1 ]
Lemor, JP
Warin, X
机构：
[1] Ecole Polytech, Ctr Math Appl, F-91128 Palaiseau, France
[2] EDF R&D, F-92141 Clamart, France
来源：
ANNALS OF APPLIED PROBABILITY | 2005年 / 15卷 / 03期
关键词：
backward stochastic differential equations; regression on function bases; Monte Carlo methods;
D O I：
10.1214/105051605000000412
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
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
收藏
页码：2172 / 2202
页数：31
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