MEV Capture Through Time-Advantaged Arbitrage
Robin Fritsch, Maria Inês Silva, Akaki Mamageishvili, Benjamin Livshits, Edward W. Felten
TL;DR
This work analyzes Maximal Extractable Value (MEV) capture via a time-advantaged transaction sequencing mechanism (Timeboost) for arbitrage between AMMs and external venues on rollups. It introduces a formal model with a single time-advantaged arbitrageur, derives the optimal strategy through dynamic programming, and characterizes profits for Constant Product pools under different pricing and fee settings. Through simulations with geometric Brownian motion and empirical price-distribution data, the authors show that waiting until the end of the time-advantage window is often optimal, though mean-reversion can alter this outcome for certain pairs. They compare Timeboost to FCFS and PGA, and propose an AMM adaptation that shares MEV with liquidity providers (e.g., 25% to the pool and 50% to the time-advantaged arb in equilibrium), highlighting practical implications for rollup design and liquidity provision.
Abstract
As blockchains begin processing significant economic activity, the ability to include and order transactions inevitably becomes highly valuable, a concept known as Maximal Extractable Value (MEV). This makes effective mechanisms for transaction inclusion and ordering, and thereby the extraction of MEV, a key aspect of blockchain design. Beyond traditional approaches such as ordering in a first-come-first-serve manner or using priority fees, a recent proposal suggests auctioning off a time advantage for transaction inclusion. In this paper, we investigate this time advantage mechanism, focusing specifically on arbitrage opportunities on Automated Market Makers (AMMs), one of the largest sources of MEV today. We analyze the optimal strategy for a time-advantaged arbitrageur and compare the profits generated by various MEV extraction methods. Finally, we explore how AMMs can be adapted in the time advantage setting to capture a portion of the MEV.