Unpacking Maximum Extractable Value on Polygon: A Study on Atomic Arbitrage

2025-08-29

AI Summary

This study systematically investigates the generation mechanisms and evolutionary patterns of atomic arbitrage (AA)-driven maximum extractable value (MEV) on the Polygon blockchain. Leveraging 22 months of real-world on-chain data spanning 23 million blocks, we propose a verifiable AA transaction identification framework. Integrating sequential pattern mining with statistical modeling, we quantitatively assess how searcher behavior, bidding strategies—specifically “Spam” versus “Auction”—and token liquidity jointly influence MEV magnitude. Our analysis reveals that although Auction-style post-auction bidding accounts for less than 1% of AA transactions, it yields significantly higher per-transaction profits than Spam-based approaches. Furthermore, we identify structural effects of network architecture and transaction ordering rules on MEV distribution. These findings provide empirical grounding and novel theoretical insights for diagnosing root causes of MEV ecosystem imbalance and for designing fair, MEV-resilient transaction ordering mechanisms.

Technology Category

• Multiagent Systems: Mechanism Design
• Game Theory and Economic Paradigms: Auctions and Market-Based Systems
• Search and Optimization: Evaluation and Analysis

Application Category

• Economics, Online Markets and Human Computation: Uses of LLMs and GenAI for marketplace design, bidding, and strategic interactions
• Web Mining and Content Analysis: Models for Web evolution
• Security and Privacy: Blockchains and distributed ledgers

Abstract

The evolution of blockchain technology, from its origins as a decentralized ledger for cryptocurrencies to its broader applications in areas like decentralized finance (DeFi), has significantly transformed financial ecosystems while introducing new challenges such as Maximum Extractable Value (MEV). This paper explores MEV on the Polygon blockchain, with a particular focus on Atomic Arbitrage (AA) transactions. We establish criteria for identifying AA transactions and analyze key factors such as searcher behavior, bidding dynamics, and token usage. Utilizing a dataset spanning 22 months and covering 23 million blocks, we examine MEV dynamics with a focus on Spam-based and Auction-based backrunning strategies. Our findings reveal that while Spam-based transactions are more prevalent, Auction-based transactions demonstrate greater profitability. Through detailed examples and analysis, we investigate the interactions between network architecture, transaction sequencing, and MEV extraction, offering comprehensive insights into the evolution and challenges of MEV in decentralized ecosystems. These results emphasize the need for robust transaction ordering mechanisms and highlight the implications of emerging MEV strategies for blockchain networks.

Problem

• Analyzing atomic arbitrage MEV on Polygon blockchain
• Examining searcher behavior and bidding dynamics
• Comparing spam-based versus auction-based backrunning strategies

Innovation

• Identified atomic arbitrage transaction criteria
• Analyzed spam-based and auction-based backrunning strategies
• Examined network architecture and transaction sequencing interactions