On solving stochastic differential equations

Author:

Ermakov Sergej M.,Pogosian Anna A.

Abstract

Abstract This paper proposes a new approach to solving Ito stochastic differential equations. It is based on the well-known Monte Carlo methods for solving integral equations (Neumann–Ulam scheme, Markov chain Monte Carlo). The estimates of the solution for a wide class of equations do not have a bias, which distinguishes them from estimates based on difference approximations (Euler, Milstein methods, etc.).

Funder

Russian Science Foundation

Publisher

Walter de Gruyter GmbH

Subject

Applied Mathematics,Statistics and Probability

Reference14 articles.

1. Expansion of random boundary excitations for some elliptic PDEs;Monte Carlo Methods Appl.,2007

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