mlsanityData to 14 Oct 2026

ABIDES: Towards High-Fidelity Market Simulation for AI Research

arXiv 1904.12066 ↗First posted 26 Apr 2019cs.MAcited by 32

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Abstract (arXiv)

We introduce ABIDES, an Agent-Based Interactive Discrete Event Simulation environment. ABIDES is designed from the ground up to support AI agent research in market applications. While simulations are certainly available within trading firms for their own internal use, there are no broadly available high-fidelity market simulation environments. We hope that the availability of such a platform will facilitate AI research in this important area. ABIDES currently enables the simulation of tens of thousands of trading agents interacting with an exchange agent to facilitate transactions. It supports configurable pairwise network latencies between each individual agent as well as the exchange. Our simulator's message-based design is modeled after NASDAQ's published equity trading protocols ITCH and OUCH. We introduce the design of the simulator and illustrate its use and configuration with sample code, validating the environment with example trading scenarios. The utility of ABIDES is illustrated through experiments to develop a market impact model. We close with discussion of future experimental problems it can be used to explore, such as the development of ML-based trading algorithms.

Key facts. Cited by 32 papers in the map (data through 14 Oct 2026). First posted on arXiv 26 Apr 2019.

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Citing papers per year: 2021: 7; 2022: 5; 2023: 4; 2024: 3; 2025: 5; 2026: 8.

32 papers.

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  1. 2021ABIDES-Gym: Gym Environments for Multi-Agent Discrete Event Simulation and Application to Financial Marketscited by 36
  2. 2021Reinforcement Learning for Quantitative Tradingcited by 24
  3. 2021Deep Reinforcement Learning for Active High Frequency Tradingcited by 21
  4. 2021Deep Learning for Market by Order Datacited by 8
  5. 2022DSLOB: A Synthetic Limit Order Book Dataset for Benchmarking Forecasting Algorithms under Distributional Shiftcited by 6
  6. 2023K-SHAP: Policy Clustering Algorithm for Anonymous Multi-Agent State-Action Pairscited by 6
  7. 2024A Financial Time Series Denoiser Based on Diffusion Modelcited by 6
  8. 2022Phantom -- A RL-driven multi-agent framework to model complex systemscited by 5
  9. 2023Towards Generalizable Reinforcement Learning for Trade Executioncited by 5
  10. 2025Fox in the Henhouse: Supply-Chain Backdoor Attacks Against Reinforcement Learningcited by 5
  11. 2023Deep Calibration of Market Simulations using Neural Density Estimators and Embedding Networkscited by 4
  12. 2021Robust Risk-Sensitive Reinforcement Learning Agents for Trading Marketscited by 3
20 more
  1. 2023Asynchronous Deep Double Duelling Q-Learning for Trading-Signal Execution in Limit Order Book Marketscited by 3
  2. 2022Limited or Biased: Modeling Sub-Rational Human Investors in Financial Marketscited by 2
  3. 2025Safe and Compliant Cross-Market Trade Execution via Constrained RL and Zero-Knowledge Auditscited by 2
  4. 2026PredictionMarketBench: A SWE-bench-Style Framework for Backtesting Trading Agents on Prediction Marketscited by 2
  5. 2021Deep Q-Learning Market Makers in a Multi-Agent Simulated Stock Marketcited by 1
  6. 2024Empirical Equilibria in Agent-based Economic systems with Learning agentscited by 1
  7. 2024Limit Order Book Simulation and Trade Evaluation with K-Nearest-Neighbor Resamplingcited by 1
  8. 2025DiffVolume: Diffusion Models for Volume Generation in Limit Order Bookscited by 1
  9. 2021Similarity metrics for Different Market Scenarios in Abidescited by 0
  10. 2022CTMSTOU driven markets: simulated environment for regime-awareness in trading policiescited by 0
  11. 2022Intelligent Systematic Investment Agent: an ensemble of deep learning and evolutionary strategiescited by 0
  12. 2025Dropout-Robust Mechanisms for Differentially Private and Fully Decentralized Mean Estimationcited by 0
  13. 2025Tail-Safe Hedging: Explainable Risk-Sensitive Reinforcement Learning with a White-Box CBF--QP Safety Layer in Arbitrage-Free Marketscited by 0
  14. 2026When Quotes Crumble: Detecting Transient Mechanical Liquidity Erosion in Limit Order Bookscited by 0
  15. 2026TT-DAC-PS: Twin-Target Deterministic Actor-Critic with Policy Smoothing for Optimal Trade Executioncited by 0
  16. 2026CARD: Controlled Agentic Reddit Discussions for Credit Card Simulationcited by 0
  17. 2026M3: A State-Event Generative Foundation Model for Market Microstructure Dynamicscited by 0
  18. 2026WolfSociety: Understanding Collective Risk from Harmful-Agent Scaling in Financial Agent Societiescited by 0
  19. 2026PAWS: Policy-driven Agentic World Simulationcited by 0
  20. 2026Multi-Agent Debate for Explainable Trading: Reasoning, Consensus, and Performance in Simulated Marketscited by 0