On the pathwise approximation of stochastic differential equations

Tony Shardlow, Phillip Taylor

Research output: Contribution to journalArticlepeer-review

8 Citations (SciVal)
188 Downloads (Pure)


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 anerror-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.
Original languageEnglish
Pages (from-to)1101-1129
JournalBIT Numerical Mathematics
Issue number3
Early online date18 Dec 2015
Publication statusPublished - Sept 2016


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