# Signature approach for pricing and hedging path-dependent options with frictions

arXiv: https://arxiv.org/abs/2511.23295 · HTML: https://mlsanity.com/paper/2511.23295/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Nov 2025.

## Built on by (most cited first, 3 of 3)

- [Deep Hilbert--Galerkin Methods for Infinite-Dimensional PDEs and Optimal Control](https://mlsanity.com/paper/2603.19463/) (2026)
- [Tradable Ito Signatures: A Model-Free, Interpretable Framework for Dynamic Hedging](https://mlsanity.com/paper/2608.18120/) (2026)
- [Deep kernel hedging](https://mlsanity.com/paper/2609.34474/) (2026)

## Abstract (arXiv)

We introduce a novel signature approach for pricing and hedging path-dependent options with instantaneous and permanent market impact under a mean-quadratic variation criterion. Leveraging the expressive power of signatures, we recast an inherently nonlinear and non-Markovian stochastic control problem into a tractable form, yielding hedging strategies in (possibly infinite) linear feedback form in the time-augmented signature of the control variables, with coefficients characterized by non-standard infinite-dimensional Riccati equations on the extended tensor algebra. Numerical experiments demonstrate the effectiveness of these signature-based strategies for pricing and hedging general path-dependent payoffs in the presence of frictions. In particular, market impact naturally smooths optimal trading strategies, making low-truncated signature approximations highly accurate and robust in frictional markets, contrary to the frictionless case.