AMM流动性提供者的均衡激励与奖励
文章 arXiv papers · 作者: Alif Aqsha et al.
总结
本文分析自动做市商如何为策略性流动性提供者设置奖励，以吸引订单流。模型将交易场所设定为选择合约的领导者，将代表性提供者设定为作出响应的跟随者，并将双方互动描述为随机博弈。
作者推导近似闭式均衡解，并考察由此形成的合约如何影响流动性决策。当资金池平均流动性增加与吸引更多噪声交易相关时，提供者会受到激励贡献流动性。奖励安排取决于外部市场价格、资金池参考价格和储备。摘要提出一个理论框架及其对 AMM设计的启示，但没有提供实证验证或详细假设，因此应将结论视为基于模型的推论，而非已由市场结果证实的发现。
核心观点
- 交易场所选择奖励合约，代表性流动性提供者则作出策略性响应。
- 双方互动被建模为领导者—跟随者随机博弈。
- 研究使用近似闭式解刻画均衡合约。
- 当平均流动性加深与噪声交易增加相关时，提供者会贡献流动性。
- 合约取决于外部价格、资金池参考价格和储备。
标签
全文
# Equilibrium Reward for Liquidity Providers in Automated Market Makers # Equilibrium Reward for Liquidity Providers in Automated Market Makers We find the equilibrium contract that an automated market maker (AMM) offers to their strategic liquidity providers (LPs) in order to maximize the order flow that gets processed by the venue. Our model is formulated as a leader-follower stochastic game, where the venue is the leader and a representative LP is the follower. We derive approximate closed-form equilibrium solutions to the stochastic game and analyze the reward structure. Our findings suggest that under the equilibrium contract, LPs have incentives to add liquidity to the pool only when higher liquidity on average attracts more noise trading. The equilibrium contract depends on the external price, the pool reference price, and the pool reserves. Our framework offers insights into AMM design for maximizing order flow while ensuring LP profitability.
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此摘要由 Stratmill 研究智能体根据原文撰写，并非原文副本。