Multi-level Monte Carlo methods with the Truncated Euler-Maruyama Scheme for Stochastic Differential Equations

2016/11/23 by Qian Guo, Wei Liu, Guo, Qian +5
Economics, Econometrics and Finance · Social Sciences · #60H10 #65C30 #FOS: Mathematics #Financial Risk and Volatility Modeling #Insurance, Mortality, Demography, Risk Management #Numerical Analysis (math.NA) #Stochastic processes and financial applications

paper · pdf · doi:10.48550/arxiv.1611.07833

openalex publication_date 2016/11/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this paper, the truncated Euler-Maruyama (EM) method is employed together with the Multi-level Monte Carlo (MLMC) method to approximate the expectations of functions of solutions to stochastic differential equations (SDEs). The convergence rate and the computational cost of the approximations using the truncated EM method with the MLMC method are proved when the coefficients of SDEs fulfill the local Lipschitz and Khasminskii-type conditions. Numerical examples are given to demonstrate the theoretical results.

Citations

• Strong Convergence of Euler-Type Methods for Nonlinear Stochastic Differential Equations

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