The truncated milstein method for stochastic differential equations
arXiv:1704.0413560 citations
AI Analysis
Provides a new numerical method with improved convergence for stochastic differential equations, but the improvement is incremental over existing truncation techniques.
The paper proposes a truncated Milstein method for highly non-linear stochastic differential equations, proving a strong convergence rate close to 1.
Inspired by the truncated Euler-Maruyama method developed in Mao (J. Comput. Appl. Math. 2015), we propose the truncated Milstein method in this paper. The strong convergence rate is proved to be close to 1 for a class of highly non-linear stochastic differential equations. Numerical examples are given to illustrate the theoretical results.