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.).
Язык оригиналаанглийский
Страницы (с-по)155-161
Число страниц7
ЖурналMonte Carlo Methods and Applications
Том25
Номер выпуска2
DOI
СостояниеОпубликовано - 1 июн 2019

    Области исследований

  • Monte Carlo methods, Markov chain Monte Carlo, stochastic differential equations

    Предметные области Scopus

  • Математика (все)
  • Прикладная математика
  • Теория вероятности и статистика

ID: 42905698