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

• 成果类型: Article
• 署名作者: Gobet, E; Lemor, JP; Warin, X
• 署名单位: Institut Polytechnique de Paris; ENSTA Paris; Ecole Polytechnique; Electricite de France (EDF)
• 刊物名称: ANNALS OF APPLIED PROBABILITY
• ISSN/ISSBN: 1050-5164
• DOI: 10.1214/105051605000000412
• 发表日期: 2005
• 页码: 2172-2202
• 关键词: simulation; options

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.