The Origins of MEV: Systematic Attribution of Arbitrage Opportunity Creation at Scale
Fuente:
arXiv
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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866914521360105472 |
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| author | Seoev, Andrei Belousov, Dmitry Smirnova, Anastasiia Kurinova, Ksenia Smirnov, Aleksei Fedyanin, Denis Yanovich, Yury |
| author_facet | Seoev, Andrei Belousov, Dmitry Smirnova, Anastasiia Kurinova, Ksenia Smirnov, Aleksei Fedyanin, Denis Yanovich, Yury |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_27979 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | The Origins of MEV: Systematic Attribution of Arbitrage Opportunity Creation at Scale Seoev, Andrei Belousov, Dmitry Smirnova, Anastasiia Kurinova, Ksenia Smirnov, Aleksei Fedyanin, Denis Yanovich, Yury Distributed, Parallel, and Cluster Computing 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. |
| title | The Origins of MEV: Systematic Attribution of Arbitrage Opportunity Creation at Scale |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2604.27979 |