Global universal approximation with Brownian signatures
Probability
2025-12-19 v1 Machine Learning
Mathematical Finance
Abstract
We establish -type universal approximation theorems for general and non-anticipative functionals on suitable rough path spaces, showing that linear functionals acting on signatures of time-extended rough paths are dense with respect to an -distance. To that end, we derive global universal approximation theorems for weighted rough path spaces. We demonstrate that these -type universal approximation theorems apply in particular to Brownian motion. As a consequence, linear functionals on the signature of the time-extended Brownian motion can approximate any -integrable stochastic process adapted to the Brownian filtration, including solutions to stochastic differential equations.
Cite
@article{arxiv.2512.16396,
title = {Global universal approximation with Brownian signatures},
author = {Mihriban Ceylan and David J. Prömel},
journal= {arXiv preprint arXiv:2512.16396},
year = {2025}
}