Playing the MEV Game on a First-Come-First-Served Blockchain

First-Come-First-Served (FCFS) transaction ordering has been discussed as a fairness approach against harmful Maximal Extractable Value (MEV) strategies. However, such an ordering mechanism promotes latency optimizations, similar to High-Frequency Trading in Traditional Finance. This paper examines the dynamics of the MEV extraction game in an FCFS network, specifically Algorand. We introduce an arbitrage opportunity detection algorithm tailored to Algorand’s time constraints and assess its effectiveness. Our analysis reveals that while the states of exchange pools are updated approximately only every six blocks, pursuing MEV at the block state level is not viable, as arbitrage opportunities are typically closed within the block they appear. Additionally, we experiment on a private Algorand network to uncover latency optimization factors and show the importance of reducing latency in connections with relays well-connected to high-staked proposers.