去中心化金融与自动做市：执行与投机
Decentralised Finance and Automated Market Making: Execution and Speculation
AI总结：
本文研究恒定乘积市场（CPMs）中的最优交易与统计套利问题，明确凸性成本的影响规律，针对不同汇率形成场景建模，推导了考虑随机凸性成本的高效策略并验证其样本外表现。
摘要：
自动做市商（AMMs）是去中心化交易所的一种新型范式，正在彻底改变市场交互方式。大多数AMMs属于恒定乘积市场（CPMs），其汇率由交易函数设定。本文研究CPMs中的最优交易与统计套利问题，其中平衡汇率风险与执行成本是核心关键。实证证据表明，执行成本可通过交易函数的凸性准确估算。这些凸性成本与交易规模呈线性关系，与流动性深度及汇率呈非线性关系。我们针对汇率在竞争性中心化交易所、CPM或两类场所中形成的不同场景分别构建了模型。最后，我们推导了考虑随机凸性成本的计算高效策略，并展示了其样本外表现。
英文摘要：
Automated market makers (AMMs) are a new prototype of decentralised exchanges which are revolutionising market interactions. The majority of AMMs are constant product markets (CPMs) where exchange rates are set by a trading function. This work studies optimal trading and statistical arbitrage in CPMs where balancing exchange rate risk and execution costs is key. Empirical evidence shows that execution costs are accurately estimated by the convexity of the trading function. These convexity costs are linear in the trade size and are nonlinear in the depth of liquidity and in the exchange rate. We develop models for when exchange rates form in a competing centralised exchange, in a CPM, or in both venues. Finally, we derive computationally efficient strategies that account for stochastic convexity costs and we showcase their out-of-sample performance.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
