# Signature Methods for Optimal Market Making

arXiv: https://arxiv.org/abs/2606.19772 · HTML: https://mlsanity.com/paper/2606.19772/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Jun 2026.

## Built on by (most cited first, 1 of 1)

- [Continuous-Time Reinforcement Learning for Controlled Hawkes Jump-Diffusions](https://mlsanity.com/paper/2608.19151/) (2026)

## Abstract (arXiv)

We propose a signature-based method to solve the optimal market-making problem under a mean-variance criterion. By exploiting signature linearization techniques, we reduce the market-making problem to a pseudo-linear optimization over the expected signature of an augmented market path, and we develop a signature algorithm named Sig-REINFORCE to learn the optimal bid and ask quotes. We test our method in two scenarios, in which market-order arrivals follow either a Poisson or a self-exciting Hawkes process, and we benchmark it against a Proximal Policy Optimization (PPO) baseline.