Reinforcement learning approaches to optimal market making

B Gašperov, S Begušić, P Posedel Šimović… - Mathematics, 2021 - mdpi.com
Market making is the process whereby a market participant, called a market maker,
simultaneously and repeatedly posts limit orders on both sides of the limit order book of a …

Reinforcement learning for market making in a multi-agent dealer market

S Ganesh, N Vadori, M Xu, H Zheng, P Reddy… - arXiv preprint arXiv …, 2019 - arxiv.org
Market makers play an important role in providing liquidity to markets by continuously
quoting prices at which they are willing to buy and sell, and managing inventory risk. In this …

Decentralized Finance and Automated Market Making: Predictable Loss and Optimal Liquidity Provision

Á Cartea, F Drissi, M Monga - SIAM Journal on Financial Mathematics, 2024 - SIAM
Constant product markets with concentrated liquidity (CL) are the most popular type of
automated market makers. In this paper, we characterize the continuous-time wealth …

Deep reinforcement learning for market making in corporate bonds: beating the curse of dimensionality

O Guéant, I Manziuk - Applied Mathematical Finance, 2019 - Taylor & Francis
In corporate bond markets, which are mainly OTC markets, market makers play a central role
by providing bid and ask prices for bonds to asset managers. Determining the optimal bid …

Robust market making via adversarial reinforcement learning

T Spooner, R Savani - arXiv preprint arXiv:2003.01820, 2020 - arxiv.org
We show that adversarial reinforcement learning (ARL) can be used to produce market
marking agents that are robust to adversarial and adaptively-chosen market conditions. To …

Fundamentals of market making via stochastic optimal control

E Savku - Operations Research, 2022 - taylorfrancis.com
A Market Maker (MM) is an individual or an agent, who actively provides bids and offers asks
in a financial market. Her main goal is to maximize her profit and loss functional by getting …

Automated market makers: Mean-variance analysis of lps payoffs and design of pricing functions

P Bergault, L Bertucci, D Bouba, O Guéant - Digital Finance, 2024 - Springer
With the emergence of decentralized finance, new trading mechanisms called automated
market makers have appeared. The most popular Automated Market Makers are Constant …

Double-execution strategies using path signatures

Á Cartea, IP Arribas, L Sánchez-Betancourt - SIAM Journal on Financial …, 2022 - SIAM
We employ the expected signature of equity and foreign exchange markets to derive an
optimal double-execution trading strategy. The signature of a path of a stochastic process is …

Optimizing market making using multi-agent reinforcement learning

Y Patel - arXiv preprint arXiv:1812.10252, 2018 - arxiv.org
In this paper, reinforcement learning is applied to the problem of optimizing market making.
A multi-agent reinforcement learning framework is used to optimally place limit orders that …

Algorithmic market making in dealer markets with hedging and market impact

A Barzykin, P Bergault, O Guéant - Mathematical Finance, 2023 - Wiley Online Library
In dealer markets, dealers provide prices at which they agree to buy and sell the assets and
securities they have in their scope. With ever increasing trading volume, this quoting task …