We study a novel automated market maker design: the function maximizing AMM (FM-AMM). Our central assumption is that trades are batched before execution. Because of competition between arbitrageurs, the FM-AMM eliminates arbitrage profits (or LVR) and sandwich attacks, currently the two main problems in decentralized finance and blockchain design more broadly. We then consider 11 token pairs and use Binance price data to simulate the lower bound to the return of providing liquidity to an FM-AMM. Such a lower bound is, for the most part, slightly higher than the empirical returns of providing liquidity on Uniswap v3 (currently the dominant AMM).

翻译：本研究探讨一种新型自动做市商设计：函数最大化AMM（FM-AMM）。核心假设为交易在执行前进行批量处理。由于套利者之间的竞争，FM-AMM消除了套利利润（或LVR）和三明治攻击——这两个问题目前是去中心化金融及区块链设计中更广泛领域的主要难题。随后，我们选取11个代币对，利用币安价格数据模拟向FM-AMM提供流动性收益的下限。该下限在大多数情况下略高于当前主流AMM——Uniswap v3上提供流动性的经验收益水平。