MEV Makes Everyone Happy under Greedy Sequencing Rule
Yuhao Li, Mengqian Zhang, Jichen Li, Elynn Chen, Xi Chen, Xiaotie Deng · 2023
Trading through decentralized exchanges (DEXs) has become crucial in today's blockchain ecosystem, enabling users to swap tokens efficiently and automatically. However, the capacity of miners to strategically order transactions has led to exploitative practices (e.g., front-running attacks, sandwich attacks) and gain substantial Maximal Extractable Value (MEV) for their own advantage. To mitigate such manipulation, Ferreira and Parkes recently proposed a greedy sequencing rule where transactions within a block are executed in a back-and-forth manner around the starting price. Utilizing this sequencing rule restricts the feasibility of miners conducting sandwich attacks, consequently mitigating the MEV problem. However, no sequencing rule can prevent miners from obtaining risk-free profits. This paper systemically studies the computation of a miner's optimal strategy for maximizing MEV under the greedy sequencing rule, where the utility of miners is measured by the overall value of their token holdings. Our results unveil a dichotomy between the no trading fee scenario, where an optimal strategy can be computed in polynomial time, and the scenario with a constant fraction of trading fee, where finding an optimal strategy is NP-hard. The latter represents a significant challenge for miners seeking optimal MEV. Following the computation results, we further show a remarkable phenomenon: Miner's optimal MEV also benefits users. Precisely, in the scenarios without trading fees, when miners adopt the optimal strategy given by our algorithm, all users' transactions will be executed, and each user will receive as good profits as expected. This outcome provides further support for the study and design of sequencing rules in decentralized exchanges.