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.).
Original languageEnglish
Pages (from-to)155-161
Number of pages7
JournalMonte Carlo Methods and Applications
Volume25
Issue number2
DOIs
StatePublished - 1 Jun 2019

    Research areas

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

    Scopus subject areas

  • Mathematics(all)
  • Applied Mathematics
  • Statistics and Probability

ID: 42905698