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Improving DeFi Accessibility through Efficient Liquidity Provisioning with Deep Reinforcement Learning

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  • Haonan Xu
  • Alessio Brini

Abstract

This paper applies deep reinforcement learning (DRL) to optimize liquidity provisioning in Uniswap v3, a decentralized finance (DeFi) protocol implementing an automated market maker (AMM) model with concentrated liquidity. We model the liquidity provision task as a Markov Decision Process (MDP) and train an active liquidity provider (LP) agent using the Proximal Policy Optimization (PPO) algorithm. The agent dynamically adjusts liquidity positions by using information about price dynamics to balance fee maximization and impermanent loss mitigation. We use a rolling window approach for training and testing, reflecting realistic market conditions and regime shifts. This study compares the data-driven performance of the DRL-based strategy against common heuristics adopted by small retail LP actors that do not systematically modify their liquidity positions. By promoting more efficient liquidity management, this work aims to make DeFi markets more accessible and inclusive for a broader range of participants. Through a data-driven approach to liquidity management, this work seeks to contribute to the ongoing development of more efficient and user-friendly DeFi markets.

Suggested Citation

  • Haonan Xu & Alessio Brini, 2025. "Improving DeFi Accessibility through Efficient Liquidity Provisioning with Deep Reinforcement Learning," Papers 2501.07508, arXiv.org.
    • Handle: RePEc:arx:papers:2501.07508
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    References listed on IDEAS

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    1. Jiahua Xu & Krzysztof Paruch & Simon Cousaert & Yebo Feng, 2021. "SoK: Decentralized Exchanges (DEX) with Automated Market Maker (AMM) Protocols," Papers 2103.12732, arXiv.org, revised Mar 2023.
    2. 'Alvaro Cartea & Fayc{c}al Drissi & Marcello Monga, 2023. "Decentralised Finance and Automated Market Making: Predictable Loss and Optimal Liquidity Provision," Papers 2309.08431, arXiv.org, revised Jun 2024.
    3. Stefan Loesch & Nate Hindman & Mark B Richardson & Nicholas Welch, 2021. "Impermanent Loss in Uniswap v3," Papers 2111.09192, arXiv.org.
    4. Ye Wang & Yan Chen & Haotian Wu & Liyi Zhou & Shuiguang Deng & Roger Wattenhofer, 2021. "Cyclic Arbitrage in Decentralized Exchanges," Papers 2105.02784, arXiv.org, revised Jan 2022.
    5. Andreas A. Aigner & Gurvinder Dhaliwal, 2021. "UNISWAP: Impermanent Loss and Risk Profile of a Liquidity Provider," Papers 2106.14404, arXiv.org.
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