UNBIASED MONTE CARLO ESTIMATE OF STOCHASTIC DIFFERENTIAL EQUATIONS EXPECTATIONS

被引：8
|
作者：
Doumbia, Mahamadou [1 ,2 ]
Oudjane, Nadia [1 ,2 ]
Warin, Xavier [1 ,2 ]
机构：
[1] EDF R&D, 7 Blvd Gaspard Monge, F-91120 Palaiseau, France
[2] FiME, Lab Finance Marches Energie, 7 Blvd Gaspard Monge, F-91120 Palaiseau, France
来源：
ESAIM-PROBABILITY AND STATISTICS | 2017年 / 21卷
关键词：
Unbiased estimate; linear parabolic PDEs; interacting particle systems; EXACT SIMULATION;
D O I：
10.1051/ps/2017001
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 propose an unbiased Monte Carlo method to compute E(g(X-T)) where g is a Lipschitz function and X an Ito process. This approach extends the method proposed in [16] to the case where X is solution of a multidimensional stochastic differential equation with varying drift and diffusion coefficients. A variance reduction method relying on interacting particle systems is also developed.
引用
收藏
页码：56 / 87
页数：32
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