The main aim of this study is to construct a new approximation method for solving stif Itˆo stochastic ordinary diferential equations based on explicit Milstein scheme. Under the suicient conditions such as Lipschitz condition and linear growth bound, we prove that split-step (α, β)-Milstein method strongly convergence to exact solution with order one. The means-quare stability of the our method for linear stochastic diferential equation with one-dimensional Wiener process is studied. Stability analysis shows that the mean-square stability our proposed method contains the mean-square stability region of linear scalar test equation. Finally, numerical examples illustrates the efectiveness of the theoretical results. پرونده مقاله

In this paper, we improved the split step $ vartheta $ method to solve the stochastic differential equations. The strong convergence of this approximation for stochastic differential equations, whose drift and diffusion coefficients are globally Lipschitz continuous, are investigated. Furthermore, we analyze the stability in the mean square sense of our scheme by scalar stochastic differential equation with multi dimensional Wiener processes. The study of stability shows the mean square stability of the method for $ vartheta in [1/2, 1] $. Finally, we present some numerical examples to describe the methodology and implementation of the split step $ vartheta $ method to solve linear and nonlinear one dimensional stochastic differential equations and the Lotka-Volterra stochastic system. پرونده مقاله