The Origins of MEV: Systematic Attribution of Arbitrage Opportunity Creation at Scale

2026-04-30

AI Summary

This study addresses the lack of systematic attribution methods for identifying the origins of on-chain arbitrage opportunities, commonly known as Maximal Extractable Value (MEV). We propose the first scalable MEV attribution framework that formally defines the causal relationship between MEV opportunities and their originating transactions, conducting a retrospective analysis across over one million blocks on the Polygon network. Four attribution methodologies—based on bot logs, transaction simulation, linear coefficients, and Shapley values—are designed and compared, all applicable to any EVM-compatible chain. Empirical results reveal that the vast majority of atomic arbitrage opportunities are triggered by single transactions, and MEV generation is highly concentrated within a small number of protocols. Our work quantifies protocol-level MEV leakage distributions, offering critical insights for protocol design, block construction, and ecosystem health evaluation.

Abstract

Maximal Extractable Value (MEV) represents billions of dollars in extracted value that fundamentally shapes blockchain network dynamics and participant incentives. While research has focused on MEV extraction and mitigation, we lack systematic methods to attribute MEV opportunities to their on-chain origins. This paper formalizes the MEV opportunity attribution problem and introduces a systems framework for identifying which transactions create arbitrage opportunities and quantifying their contributions. We design and evaluate four attribution methods for atomic arbitrage on EVM-compatible networks: bot-data-driven, simulation-based, coefficient-based, and Shapley-based approaches. Through large-scale retrospective analysis spanning over one million blocks on Polygon, we demonstrate that the majority of atomic arbitrage opportunities can be traced to single source transactions, validating our central hypothesis about competitive MEV markets. We quantify a highly concentrated distribution of MEV creation, where a small subset of protocols generates most opportunities, and provide comparative analysis of method trade-offs in accuracy, cost, and scalability. Our findings offer insights for protocol designers reducing MEV leakage, validators optimizing transaction ordering, and analysts measuring ecosystem health through opportunity creation.

Problem

• MEV
• arbitrage
• attribution
• blockchain
• transaction

Innovation

• MEV attribution
• arbitrage opportunity
• Shapley-based attribution
• EVM-compatible networks
• systematic framework