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Universal approximation with signatures of non-geometric rough paths

Author

Listed:
  • Mihriban Ceylan
  • Anna P. Kwossek
  • David J. Promel

Abstract

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 It\^o, Stratonovich, and backward It\^o 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 It\^o 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.

Suggested Citation

  • Mihriban Ceylan & Anna P. Kwossek & David J. Promel, 2026. "Universal approximation with signatures of non-geometric rough paths," Papers 2602.05898, arXiv.org.
  • Handle: RePEc:arx:papers:2602.05898
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    References listed on IDEAS

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    1. Kei Kobayashi, 2011. "Stochastic Calculus for a Time-Changed Semimartingale and the Associated Stochastic Differential Equations," Journal of Theoretical Probability, Springer, vol. 24(3), pages 789-820, September.
    2. Federico M. Bandi & Roberto Ren`o & Sara Svaluto-Ferro, 2025. "Local signature-based expansions," Papers 2504.06351, arXiv.org.
    3. Ilya Chevyrev & Andrey Kormilitzin, 2026. "A Primer on the Signature Method in Machine Learning," Springer Finance, in: Christian Bayer & Goncalo dos Reis & Blanka Horvath & Harald Oberhauser (ed.), Signature Methods in Finance, pages 3-64, Springer.
    4. Christian Bayer & Luca Pelizzari & John Schoenmakers, 2025. "Primal and dual optimal stopping with signatures," Finance and Stochastics, Springer, vol. 29(4), pages 981-1014, October.
    5. Christian Bayer & Luca Pelizzari & John Schoenmakers, 2023. "Primal and dual optimal stopping with signatures," Papers 2312.03444, arXiv.org, revised Feb 2025.
    6. Munawar Ali & Qi Feng, 2025. "Branched Signature Model," Papers 2511.00018, arXiv.org.
    7. Erdinc Akyildirim & Matteo Gambara & Josef Teichmann & Syang Zhou, 2022. "Applications of Signature Methods to Market Anomaly Detection," Papers 2201.02441, arXiv.org, revised Feb 2022.
    8. Nicolas Perkowski & David J. Promel, 2013. "Pathwise stochastic integrals for model free finance," Papers 1311.6187, arXiv.org, revised Jun 2016.
    9. Terry Lyons & Sina Nejad & Imanol Perez Arribas, 2019. "Numerical Method for Model-free Pricing of Exotic Derivatives in Discrete Time Using Rough Path Signatures," Applied Mathematical Finance, Taylor & Francis Journals, vol. 26(6), pages 583-597, November.
    10. Christa Cuchiero & Guido Gazzani & Janka Möller & Sara Svaluto‐Ferro, 2025. "Joint calibration to SPX and VIX options with signature‐based models," Mathematical Finance, Wiley Blackwell, vol. 35(1), pages 161-213, January.
    11. Andrew L. Allan & Christa Cuchiero & Chong Liu & David J. Prömel, 2023. "Model‐free portfolio theory: A rough path approach," Mathematical Finance, Wiley Blackwell, vol. 33(3), pages 709-765, July.
    12. Christa Cuchiero & Francesca Primavera & Sara Svaluto-Ferro, 2025. "Universal approximation theorems for continuous functions of càdlàg paths and Lévy-type signature models," Finance and Stochastics, Springer, vol. 29(2), pages 289-342, April.
    13. Andrew L. Allan & Chong Liu & David J. Prömel, 2024. "A càdlàg rough path foundation for robust finance," Finance and Stochastics, Springer, vol. 28(1), pages 215-257, January.
    14. Xin Guo & Binnan Wang & Ruixun Zhang & Chaoyi Zhao, 2025. "On Consistency of Signature Using Lasso," Operations Research, INFORMS, vol. 73(5), pages 2530-2549, September.
    15. Eduardo Abi Jaber & Nathan De Carvalho, 2023. "Reconciling rough volatility with jumps," Papers 2303.07222, arXiv.org, revised Sep 2024.
    16. Andrew L. Allan & Anna P. Kwossek & Chong Liu & David J. Promel, 2025. "Pathwise analysis of log-optimal portfolios," Papers 2507.18232, arXiv.org.
    17. Eduardo Abi Jaber & Nathan de Carvalho, 2024. "Reconciling rough volatility with jumps," Post-Print hal-04295416, HAL.
    18. Owen Futter & Blanka Horvath & Magnus Wiese, 2023. "Signature Trading: A Path-Dependent Extension of the Mean-Variance Framework with Exogenous Signals," Papers 2308.15135, arXiv.org, revised Aug 2023.
    19. Imanol Perez Arribas, 2018. "Derivatives pricing using signature payoffs," Papers 1809.09466, arXiv.org.
    20. Heston, Steven L, 1993. "A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 327-343.
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