Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5130046 | Stochastic Processes and their Applications | 2017 | 18 Pages |
Abstract
In this paper, we consider a numerical approximation of the stochastic differential equation (SDE) Xt=x0+â«0tb(s,Xs)ds+Lt,x0âRd,tâ[0,T], where the drift coefficient b:[0,T]ÃRdâRd is Hölder continuous in both time and space variables and the noise L=(Lt)0â¤tâ¤T is a d-dimensional Lévy process. We provide the rate of convergence for the Euler-Maruyama approximation when L is a Wiener process or a truncated symmetric α-stable process with αâ(1,2). Our technique is based on the regularity of the solution to the associated Kolmogorov equation.
Related Topics
Physical Sciences and Engineering
Mathematics
Mathematics (General)
Authors
Olivier Menoukeu Pamen, Dai Taguchi,