Year: 2014
Type: preprint
Abstract: We consider one-step methods for integrating stochastic differential equations and prove pathwise convergence using ideas from rough path theory. In contrast to alternative theories of pathwise convergence, no knowledge is required of convergence in pth mean and the analysis starts from a pathwise bound on the sum of the truncation errors. We show how the theory is applied to the Euler-Maruyama method with fixed and adaptive time-stepping strategies. The assumption on the truncation errors suggests an error-control strategy and we implement this as an adaptive time-stepping Euler-Maruyama method using bounded diffusions. We prove the adaptive method converges and show some computational experiments.
Source: arXiv (Cornell University)
Authors: Shardlow, Tony, Taylor, Phillip
Institutions: University of Bath, University of Manchester
Language: English
Subfield: Numerical Analysis
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2952845197