Weak error analysis for strong approximation schemes of SDEs with super-linear coefficients
Abstract
We present an error analysis of weak convergence of one-step numerical schemes for stochastic differential equations (SDEs) with super-linearly growing coefficients. Following Milstein’s weak error analysis on the one-step approximation of SDEs, we prove a general result on weak convergence of the one-step discretization of the SDEs mentioned above. As applications, we show the weak convergence rates for several numerical schemes of half-order strong convergence, such as tamed and balanced schemes. Numerical examples are presented to verify our theoretical analysis.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Nov 08, 2023
- Source ID
- 10.1093/imanum/drad083
Entities
People
- Xiaojie Wang
- Yuying Zhao
- Zhongqiang Zhang
Organizations
- Air Force Office of Scientific Research
- Central South University
- Natural Science Foundation of Ningbo
- Natural Science Foundation of Hunan Province
- Worcester Polytechnic Institute