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

页码：56 / 87

页数：32

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