Arbitrageurs' profits, LVR, and sandwich attacks: batch trading as an AMM design response

TL;DR

This paper introduces the FM-AMM, a novel batch trading AMM design that eliminates arbitrage profits and sandwich attacks, showing promising liquidity provision returns based on Binance data.

Contribution

The paper proposes the FM-AMM, a new AMM design that uses batch trading to prevent arbitrage and sandwich attacks, addressing key issues in decentralized finance.

Findings

FM-AMM eliminates arbitrage profits and sandwich attacks.

Simulated liquidity returns are slightly higher than Uniswap v3.

Lower bound returns suggest competitive performance for FM-AMM.

Abstract

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).