Who Wins Ethereum Block Building Auctions and Why?

• URL: http://arxiv.org/abs/2407.13931v1
• Date: Thu, 18 Jul 2024 22:49:37 GMT
• Title: Who Wins Ethereum Block Building Auctions and Why?
• Authors: Burak Öz, Danning Sui, Thomas Thiery, Florian Matthes,
• Abstract summary: The MEV-Boost block auction contributes approximately 90% of all blocks. Between October 2023 and March 2024, only three builders produced 80% of them. We identify features that play a significant role in builders' ability to win blocks and earn profits.
• Score: 2.762397703396294
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The MEV-Boost block auction contributes approximately 90% of all Ethereum blocks. Between October 2023 and March 2024, only three builders produced 80% of them, highlighting the concentration of power within the block builder market. To foster competition and preserve Ethereum's decentralized ethos and censorship-resistance properties, understanding the dominant players' competitive edges is essential. In this paper, we identify features that play a significant role in builders' ability to win blocks and earn profits by conducting a comprehensive empirical analysis of MEV-Boost auctions over a six-month period. We reveal that block market share positively correlates with order flow diversity, while profitability correlates with access to order flow from Exclusive Providers, such as integrated searchers and external providers with exclusivity deals. Additionally, we show a positive correlation between market share and profit margin among the top ten builders, with features such as exclusive signal, non-atomic arbitrages, and Telegram bot flow strongly correlating with both metrics. This highlights a "chicken-and-egg" problem where builders need differentiated order flow to profit, but only receive such flow if they have a significant market share. Overall, this work provides an in-depth analysis of the key features driving the builder market towards centralization and offers valuable insights for designing further iterations of Ethereum block auctions, preserving Ethereum's censorship resistance properties.

Related papers

• MEV Ecosystem Evolution From Ethereum 1.0 [6.151915040556504]
  In traditional finance, there are possibilities to create values, e.g., arbitrage offers to create value from market inefficiencies or front-running offers to extract value for the participants having privileged roles. Such opportunities are readily available in DeFi ecosystems, where diverse participants engage in financial activities. In this survey, first, we show how lucrative such opportunities can be. Then, we discuss how protocolfollowing participants trying to capture such opportunities threaten to sabotage blockchain's performance. Finally, we review the current state of research trying to restore trustlessness and decentralization to provide all DeFi participants with a fair marketplace
  arXiv  Detail & Related papers  (2024-06-19T14:22:26Z)
• Remeasuring the Arbitrage and Sandwich Attacks of Maximal Extractable Value in Ethereum [7.381773144616746]
  Maximal Extractable Value (MEV) drives the prosperity of the blockchain ecosystem. We propose a profitability identification algorithm to identify MEV activities on our collected largest-ever dataset. We have characterized the overall landscape of the MEV ecosystem, the impact the private transaction architectures bring in, and the adoption of back-running mechanisms.
  arXiv  Detail & Related papers  (2024-05-28T08:17:15Z)
• The Writing is on the Wall: Analyzing the Boom of Inscriptions and its Impact on EVM-compatible Blockchains [8.744676168760394]
  We present a data-driven analysis of the transaction surge in late 2023 and early 2024, attributed to inscriptions. We show that, on certain days, inscriptions accounted nearly 90% on Arbitrum and ZKsync Era. We also show that ZKsync and Arbitrum saw lower median gas fees during these surges.
  arXiv  Detail & Related papers  (2024-05-24T07:21:53Z)
• Flashback: Enhancing Proposer-Builder Design with Future-Block Auctions in Proof-of-Stake Ethereum [27.386337024680245]
  Auction mechanisms used between searchers, builders and proposers are crucial to the overall health of the blockchain. In this paper, we consider PBS design in as a game between searchers, builders and proposers. A key novelty in our design is the inclusion of future block proposers, as all proposers of an epoch are decided ahead of time in proof-of-stake (PoS) Our analysis shows the existence of alternative auction mechanisms that result in a better equilibrium to players compared to state-of-the-art.
  arXiv  Detail & Related papers  (2024-05-15T15:58:21Z)
• Enhancing Trust and Privacy in Distributed Networks: A Comprehensive Survey on Blockchain-based Federated Learning [51.13534069758711]
  Decentralized approaches like blockchain offer a compelling solution by implementing a consensus mechanism among multiple entities. Federated Learning (FL) enables participants to collaboratively train models while safeguarding data privacy. This paper investigates the synergy between blockchain's security features and FL's privacy-preserving model training capabilities.
  arXiv  Detail & Related papers  (2024-03-28T07:08:26Z)
• Graph Attention Network-based Block Propagation with Optimal AoI and Reputation in Web 3.0 [59.94605620983965]
  We design a Graph Attention Network (GAT)-based reliable block propagation optimization framework for blockchain-enabled Web 3.0. To achieve the reliability of block propagation, we introduce a reputation mechanism based on the subjective logic model. Considering that the GAT possesses the excellent ability to process graph-structured data, we utilize the GAT with reinforcement learning to obtain the optimal block propagation trajectory.
  arXiv  Detail & Related papers  (2024-03-20T01:58:38Z)
• Strategic Bidding Wars in On-chain Auctions [14.64404722196177]
  We introduce a game-theoretic model for MEV-Boost auctions and use simulations to study different builders' bidding strategies observed in practice. Our results demonstrate the importance of latency on the effectiveness of builders' strategies and the overall auction outcome from the proposer's perspective.
  arXiv  Detail & Related papers  (2023-12-22T08:18:25Z)
• Identifying key players in dark web marketplaces [58.720142291102135]
  This paper aims to identify the key players in Bitcoin transaction networks linked to dark markets. We show that a large fraction of the traded volume is concentrated in a small group of elite market participants. Our findings suggest that understanding the behavior of key players in dark web marketplaces is critical to effectively disrupting illegal activities.
  arXiv  Detail & Related papers  (2023-06-15T20:30:43Z)
• Blockchain Large Language Models [65.7726590159576]
  This paper presents a dynamic, real-time approach to detecting anomalous blockchain transactions. The proposed tool, BlockGPT, generates tracing representations of blockchain activity and trains from scratch a large language model to act as a real-time Intrusion Detection System.
  arXiv  Detail & Related papers  (2023-04-25T11:56:18Z)
• Token Spammers, Rug Pulls, and SniperBots: An Analysis of the Ecosystem of Tokens in Ethereum and in the Binance Smart Chain (BNB) [50.888293380932616]
  We study the ecosystem of the tokens and liquidity pools. We find that about 60% of tokens are active for less than one day. We estimate that 1-day rug pulls generated $240 million in profits.
  arXiv  Detail & Related papers  (2022-06-16T14:20:19Z)
• ProportionNet: Balancing Fairness and Revenue for Auction Design with Deep Learning [55.76903822619047]
  We study the design of revenue-maximizing auctions with strong incentive guarantees. We extend techniques for approximating auctions using deep learning to address concerns of fairness while maintaining high revenue and strong incentive guarantees.
  arXiv  Detail & Related papers  (2020-10-13T13:54:21Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.