mlsanityData to 14 Oct 2026

Reinforcement Learning for Market Making in a Multi-agent Dealer Market

arXiv 1911.05892 ↗First posted 14 Nov 2019q-fin.TR cs.LG cs.MAcited by 39

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Abstract (arXiv)

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 paper, we build a multi-agent simulation of a dealer market and demonstrate that it can be used to understand the behavior of a reinforcement learning (RL) based market maker agent. We use the simulator to train an RL-based market maker agent with different competitive scenarios, reward formulations and market price trends (drifts). We show that the reinforcement learning agent is able to learn about its competitor's pricing policy; it also learns to manage inventory by smartly selecting asymmetric prices on the buy and sell sides (skewing), and maintaining a positive (or negative) inventory depending on whether the market price drift is positive (or negative). Finally, we propose and test reward formulations for creating risk averse RL-based market maker agents.

Key facts. Cited by 39 papers in the map (data through 14 Oct 2026). First posted on arXiv 14 Nov 2019.

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Citing papers per year: 2021: 7; 2022: 7; 2023: 4; 2024: 11; 2025: 6; 2026: 4.

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  3. 2023TorchRL: A data-driven decision-making library for PyTorchcited by 60
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  5. 2022Transfer RL across Observation Feature Spaces via Model-Based Regularizationcited by 18
  6. 2023JAX-LOB: A GPU-Accelerated limit order book simulator to unlock large scale reinforcement learning for tradingcited by 14
  7. 2024A Review of Reinforcement Learning in Financial Applicationscited by 13
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  9. 2021Towards a fully RL-based Market Simulatorcited by 10
  10. 2022Towards Multi-Agent Reinforcement Learning driven Over-The-Counter Market Simulationscited by 10
  11. 2022Market Making with Scaled Beta Policiescited by 5
  12. 2022Phantom -- A RL-driven multi-agent framework to model complex systemscited by 5
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  4. 2021Architecture of Automated Crypto-Finance Agentcited by 3
  5. 2022Model-based gym environments for limit order book tradingcited by 3
  6. 2022Influence-Augmented Local Simulators: A Scalable Solution for Fast Deep RL in Large Networked Systemscited by 2
  7. 2022Deep Reinforcement Learning for Market Making Under a Hawkes Process-Based Limit Order Book Modelcited by 2
  8. 2024Modelling Opaque Bilateral Market Dynamics in Financial Trading: Insights from a Multi-Agent Simulation Studycited by 2
  9. 2024Decoding OTC Government Bond Market Liquidity: An ABM Model for Market Dynamicscited by 2
  10. 2025Multi-Agent Reinforcement Learning for Market Making: Competition without Collusioncited by 2
  11. 2026Training Generalizable Collaborative Agents via Strategic Risk Aversioncited by 2
  12. 2021Deep Q-Learning Market Makers in a Multi-Agent Simulated Stock Marketcited by 1
  13. 2024Hedging and Pricing Structured Products Featuring Multiple Underlying Assetscited by 1
  14. 2024Think Smart, Act SMARL! Analyzing Probabilistic Logic Shields for Multi-Agent Reinforcement Learningcited by 1
  15. 2025EvoRL: A GPU-accelerated Framework for Evolutionary Reinforcement Learningcited by 1
  16. 2025Reinforcement Learning-Based Market Making as a Stochastic Control on Non-Stationary Limit Order Book Dynamicscited by 1
  17. 2025Adaptive Agents in Spatial Double-Auction Markets: Modeling the Emergence of Industrial Symbiosiscited by 1
  18. 2026Learning Market Making with Closing Auctionscited by 1
  19. 2021Similarity metrics for Different Market Scenarios in Abidescited by 0
  20. 2024Modelling crypto markets by multi-agent reinforcement learningcited by 0
  21. 2024Reinforcement Learning in High-frequency Market Makingcited by 0
  22. 2024Solving The Dynamic Volatility Fitting Problem: A Deep Reinforcement Learning Approachcited by 0
  23. 2024Trading Devil RL: Backdoor attack via Stock market, Bayesian Optimization and Reinforcement Learningcited by 0
  24. 2025Resolving Latency and Inventory Risk in Market Making with Reinforcement Learningcited by 0
  25. 2025The Invisible Handshake: Persistent Overpricing by Adaptive Market Agentscited by 0
  26. 2026Reinforcement Learning with Hawkes-Structured Networks for Market Makingcited by 0
  27. 2026When and How Order-Flow Interventions Work After Dealers Adaptcited by 0