mlsanityData to 7 Oct 2026

Market Making via Reinforcement Learning

arXiv 1804.04216 ↗First posted 11 Apr 2018cs.AI q-fin.TRcited by 45

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Abstract (arXiv)

Market making is a fundamental trading problem in which an agent provides liquidity by continually offering to buy and sell a security. The problem is challenging due to inventory risk, the risk of accumulating an unfavourable position and ultimately losing money. In this paper, we develop a high-fidelity simulation of limit order book markets, and use it to design a market making agent using temporal-difference reinforcement learning. We use a linear combination of tile codings as a value function approximator, and design a custom reward function that controls inventory risk. We demonstrate the effectiveness of our approach by showing that our agent outperforms both simple benchmark strategies and a recent online learning approach from the literature.

Key facts. Cited by 45 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Apr 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 10; 2022: 8; 2023: 9; 2024: 6; 2025: 7; 2026: 5.

45 papers.

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  1. 2021Recent Advances in Reinforcement Learning in Financecited by 102
  2. 2021Towards Realistic Market Simulations: a Generative Adversarial Networks Approachcited by 29
  3. 2021Machine learning and deep learningcited by 26
  4. 2021Reinforcement Learning for Quantitative Tradingcited by 24
  5. 2021Bayesian Bellman Operatorscited by 16
  6. 2023Conditional Generators for Limit Order Book Environments: Explainability, Challenges, and Robustnesscited by 14
  7. 2023JAX-LOB: A GPU-Accelerated limit order book simulator to unlock large scale reinforcement learning for tradingcited by 12
  8. 2024The Evolution of Reinforcement Learning in Quantitative Finance: A Surveycited by 11
  9. 2022Towards Multi-Agent Reinforcement Learning driven Over-The-Counter Market Simulationscited by 10
  10. 2021Quantum Machine Learning for Financecited by 7
  11. 2023Reinforcement Learning with Maskable Stock Representation for Portfolio Management in Customizable Stock Poolscited by 7
  12. 2023IMM: An Imitative Reinforcement Learning Approach with Predictive Representation Learning for Automatic Market Makingcited by 6
33 more
  1. 2022Market Making with Scaled Beta Policiescited by 5
  2. 2023PRUDEX-Compass: Towards Systematic Evaluation of Reinforcement Learning in Financial Marketscited by 5
  3. 2023Uniswap Liquidity Provision: An Online Learning Approachcited by 5
  4. 2021Optimal Market Making by Reinforcement Learningcited by 4
  5. 2024FORM: Learning Expressive and Transferable First-Order Logic Reward Machinescited by 4
  6. 2025LOB-Bench: Benchmarking Generative AI for Finance -- an Application to Limit Order Book Datacited by 4
  7. 2021Computational Performance of Deep Reinforcement Learning to find Nash Equilibriacited by 3
  8. 2021Robust Risk-Sensitive Reinforcement Learning Agents for Trading Marketscited by 3
  9. 2022Model-based gym environments for limit order book tradingcited by 3
  10. 2022Limited or Biased: Modeling Sub-Rational Human Investors in Financial Marketscited by 2
  11. 2022Neural Augmented Kalman Filtering with Bollinger Bands for Pairs Tradingcited by 2
  12. 2022Reinforcement Learning Applied to Trading Systems: A Surveycited by 2
  13. 2025Robust Market Making: To Quote, or not To Quotecited by 2
  14. 2025ARL-Based Multi-Action Market Making with Hawkes Processes and Variable Volatilitycited by 2
  15. 2022Deep Reinforcement Learning for Market Making Under a Hawkes Process-Based Limit Order Book Modelcited by 1
  16. 2022Predictive Crypto-Asset Automated Market Making Architecture for Decentralized Finance using Deep Reinforcement Learningcited by 1
  17. 2023Market Making with Deep Reinforcement Learning from Limit Order Bookscited by 1
  18. 2023Integrating Tick-level Data and Periodical Signal for High-frequency Market Makingcited by 1
  19. 2023Combining Deep Learning on Order Books with Reinforcement Learning for Profitable Tradingcited by 1
  20. 2025Dynamic Reinsurance Treaty Bidding via Multi-Agent Reinforcement Learningcited by 1
  21. 2021Deep Q-Learning Market Makers in a Multi-Agent Simulated Stock Marketcited by 0
  22. 2024Modelling crypto markets by multi-agent reinforcement learningcited by 0
  23. 2024Fitted Q-Iteration via Max-Plus-Linear Approximationcited by 0
  24. 2024Solving The Dynamic Volatility Fitting Problem: A Deep Reinforcement Learning Approachcited by 0
  25. 2024Trading Devil RL: Backdoor attack via Stock market, Bayesian Optimization and Reinforcement Learningcited by 0
  26. 2025Resolving Latency and Inventory Risk in Market Making with Reinforcement Learningcited by 0
  27. 2025The Invisible Handshake: Persistent Overpricing by Adaptive Market Agentscited by 0
  28. 2025Two Heads are Better than One: Distilling Large Language Model Features Into Small Models with Feature Decomposition and Mixturecited by 0
  29. 2026RAmmStein: Regime Adaptation in Mean-reverting Markets with Stein Thresholds -- Optimal Impulse Control in Concentrated AMMscited by 0
  30. 2026When Quotes Crumble: Detecting Transient Mechanical Liquidity Erosion in Limit Order Bookscited by 0
  31. 2026Eliciting ESG Preferences for Reinforcement Learning-Based Portfolio Optimizationcited by 0
  32. 2026SAiFE-gym: Model-based Environments for Automated Market Making with Concentrated Liquiditycited by 0
  33. 2026Robust Market Making with Hawkes Order Flow and Price Impact via Adversarial Reinforcement Learningcited by 0