mlsanityData to 7 Oct 2026

Universal approximation with signatures of non-geometric rough paths

arXiv 2602.05898 ↗First posted 5 Feb 2026math.PR cs.LG q-fin.MFcited by 4

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Abstract (arXiv)

We establish a universal approximation theorem for signatures of rough paths that are not necessarily weakly geometric. By extending the path with time and its rough path bracket terms, we prove that linear functionals of the signature of the resulting rough paths approximate continuous functionals on rough path spaces uniformly on compact sets. Moreover, we construct the signature of a path extended by its pathwise quadratic variation terms based on general pathwise stochastic integration `a la F"ollmer, in particular, allowing for pathwise Ito, Stratonovich, and backward Ito integration. In a probabilistic setting, we obtain a universal approximation result for linear functionals of the signature of continuous semimartingales extended by the quadratic variation terms, defined via stochastic Ito integration. Numerical examples illustrate the use of signatures when the path is extended by time and quadratic variation in the context of model calibration and option pricing in mathematical finance.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 5 of its 48 references that are in the map. First posted on arXiv 5 Feb 2026.

Builds on

5 of 48 references.

References · 5

  1. 2022Signature Methods in Machine Learningcited by 33
  2. 2023Signature Methods in Stochastic Portfolio Theorycited by 11
  3. 2022Applications of Signature Methods to Market Anomaly Detectioncited by 9
  4. 2023On Consistency of Signature Using Lassocited by 5
  5. 2023Signature Trading: A Path-Dependent Extension of the Mean-Variance Framework with Exogenous Signalscited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 4.

4 papers.