Numerical approximation of SDEs driven by fractional Brownian motion for all $H\in(0,1)$ using WIS integration
It provides the first practical numerical scheme for WIS SDEs across the full range of H, enabling efficient simulation for small H values where other interpretations fail.
This paper develops a numerical method for approximating SDEs driven by fractional Brownian motion for all Hurst parameters H in (0,1) using Wick-Itô-Skorohod integration, proving strong convergence rates of O(Δt^H) (autonomous) and O(Δt^{min(H,ζ)}) (non-autonomous), with numerical experiments suggesting a higher rate of min(H+1/2,1).
We examine the numerical approximation of a quasilinear stochastic differential equation (SDE) with multiplicative fractional Brownian motion. The stochastic integral is interpreted in the Wick-Itô-Skorohod (WIS) sense that is well defined and centered for all $H\in(0,1)$. We give an introduction to the theory of WIS integration before we examine existence and uniqueness of a solution to the SDE. We then introduce our numerical method which is based on previous theoretical results for $H\geq \frac{1}{2}$. We construct explicitly a translation operator required for the practical implementation of the method and are not aware of any other implementation of a numerical method for the WIS SDE. We then prove a strong convergence result that gives, in the autonomous case, an error of $O(Δt^H)$ and in the non-autonomous case $O(Δt^{\min(H,ζ)})$, where $ζ$ is a time-Hölder continuity parameter. We present some numerical experiments and conjecture that the theoretical results may not be optimal since we observe numerically a rate of $\min(H+\frac{1}{2},1)$ in the autonomous case. This work opens up the possibility to efficiently simulate SDEs for all $H$ values, including small values of $H$ when the stochastic integral is interpreted in the WIS sense.