SIMULATION OF DIFFUSIONS BY MEANS OF IMPORTANCE SAMPLING PARADIGM

• 成果类型: Article
• 署名作者: Deaconu, Madalina; Lejay, Antoine
• 署名单位: Inria; Centre National de la Recherche Scientifique (CNRS); CNRS - National Institute for Mathematical Sciences (INSMI); Universite de Lorraine
• 刊物名称: ANNALS OF APPLIED PROBABILITY
• ISSN/ISSBN: 1050-5164
• DOI: 10.1214/09-AAP659
• 发表日期: 2010
• 页码: 1389-1424
• 关键词: STOCHASTIC DIFFERENTIAL-EQUATIONS; variance reduction; random-walk; approximations; densities

摘要

The aim of this paper is to introduce a new Monte Carlo method based on importance sampling techniques for the simulation of stochastic differential equations. The main idea is to combine random walk on squares or rectangles methods with importance sampling techniques. The first interest of this approach is that the weights can be easily computed from the density of the one-dimensional Brownian motion. Compared to the Euler scheme this method allows one to obtain a more accurate approximation of diffusions when one has to consider complex boundary conditions. The method provides also an interesting alternative to performing variance reduction techniques and simulating rare events.