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Non-Atomic Arbitrage in Decentralized Finance

Published 3 Jan 2024 in cs.CE and q-fin.GN | (2401.01622v3)

Abstract: The prevalence of maximal extractable value (MEV) in the Ethereum ecosystem has led to a characterization of the latter as a dark forest. Studies of MEV have thus far largely been restricted to purely on-chain MEV, i.e., sandwich attacks, cyclic arbitrage, and liquidations. In this work, we shed light on the prevalence of non-atomic arbitrage on decentralized exchanges (DEXes) on the Ethereum blockchain. Importantly, non-atomic arbitrage exploits price differences between DEXes on the Ethereum blockchain as well as exchanges outside the Ethereum blockchain (i.e., centralized exchanges or DEXes on other blockchains). Thus, non-atomic arbitrage is a type of MEV that involves actions on and off the Ethereum blockchain. In our study of non-atomic arbitrage, we uncover that more than a fourth of the volume on Ethereum's biggest five DEXes from the merge until 31 October 2023 can likely be attributed to this type of MEV. We further highlight that only eleven searchers are responsible for more than 80% of the identified non-atomic arbitrage volume sitting at a staggering $132 billion and draw a connection between the centralization of the block construction market and non-atomic arbitrage. Finally, we discuss the security implications of these high-value transactions that account for more than 10% of Ethereum's total block value and outline possible mitigations.

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References (60)
  1. Y. Wang, Y. Chen, H. Wu, L. Zhou, S. Deng, and R. Wattenhofer, “Cyclic Arbitrage in Decentralized Exchanges,” in Companion Proceedings of the Web Conference 2022.   ACM, 4 2022, pp. 12–19.
  2. “Total Value Locked,” https://defillama.com/chains.
  3. “MEV-Boost Dashboard,” https://mevboost.pics/.
  4. T. Gupta, M. M. Pai, and M. Resnick, “The centralizing effects of private order flow on proposer-builder separation,” in 5th Conference on Advances in Financial Technologies, 10 2023.
  5. “Proposer-Builder Separation,” https://ethereum.org/roadmap/pbs/.
  6. P. Daian, S. Goldfeder, T. Kell, Y. Li, X. Zhao, I. Bentov, L. Breidenbach, and A. Juels, “Flash boys 2.0: Frontrunning in decentralized exchanges, miner extractable value, and consensus instability,” in 2020 IEEE Symposium on Security and Privacy (SP), 5 2020, pp. 910–927.
  7. K. Qin, L. Zhou, P. Gamito, P. Jovanovic, and A. Gervais, “An empirical study of defi liquidations: incentives, risks, and instabilities,” in Proceedings of the 21st ACM Internet Measurement Conference.   ACM, 11 2021, pp. 336–350.
  8. “DefiLlama,” https://defillama.com/protocols/dexes/Ethereum.
  9. “Zeromev,” https://zeromev.org/.
  10. Mempool Guru, “Mempool Guru,” https://mempool.guru/, 2023.
  11. S. Yang, F. Zhang, K. Huang, X. Chen, Y. Yang, and F. Zhu, “SoK: MEV Countermeasures: Theory and Practice,” arXiv preprint arXiv:2212.05111, 2023.
  12. Binance, “Historical Market Data,” https://www.binance.com/en/landing/data, 2023.
  13. “Today’s cryptocurrency prices by market cap,” 2023. [Online]. Available: https://coinmarketcap.com/
  14. H. Adams, N. Zinsmeister, and D. Robinson, “Uniswap v2 core,” 2020.
  15. H. Adams, N. Zinsmeister, M. Salem, R. Keefer, and D. Robinson, “Uniswap v3 core,” 2021.
  16. Sushiswap, “Be a Crypto Chef with Sushi,” https://docs.sushi.com/pdf/whitepaper.pdf, 2023.
  17. K. Qin, L. Zhou, and A. Gervais, “Quantifying blockchain extractable value: How dark is the forest?” in 2022 IEEE Symposium on Security and Privacy (SP).   IEEE, 5 2022, pp. 198–214.
  18. L. Zhou, K. Qin, C. F. Torres, D. V. Le, and A. Gervais, “High-Frequency Trading on Decentralized On-Chain Exchanges,” in 2021 IEEE Symposium on Security and Privacy (SP).   IEEE, 5 2021, pp. 428–445.
  19. C. F. Torres, R. Camino, and R. State, “Frontrunner Jones and the Raiders of the Dark Forest: An Empirical Study of Frontrunning on the Ethereum Blockchain,” in 30th USENIX Security Symposium, 8 2021, pp. 1343–1359.
  20. L. Heimbach, L. Kiffer, C. Ferreira Torres, and R. Wattenhofer, “Ethereum’s Proposer-Builder Separation: Promises and Realities,” in 2023 ACM Internet Measurement Conference (IMC), Montreal, QC, Canada, Oct. 2023.
  21. “DefiLlama API,” https://defillama.com/docs/api.
  22. “Jump Etherscan,” https://etherscan.io/address/0x9507c04b10486547584c37bcbd931b2a4fee9a41, 2023.
  23. Investopedia, “The Collapse of FTX: What Went Wrong With the Crypto Exchange?” https://www.investopedia.com/what-went-wrong-with-ftx-6828447, 2023.
  24. Cointelegraph, “TUSDC depegs as Circle confirms $3.3B stuck with Silicon Valley Bank,” https://cointelegraph.com/news/usdc-depegs-as-circle-confirms-3-3b-stuck-with-silicon-valley-bank, 2023.
  25. Blockworks, “The Investor’s Guide to Crypto Correlation,” https://blockworks.co/news/the-investors-guide-to-crypto-correlation, 2023.
  26. K. Q. Nguyen, “The correlation between the stock market and bitcoin during covid-19 and other uncertainty periods,” Finance Research Letters, vol. 46, p. 102284, 2022. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S1544612321003238
  27. “Meeting calendars, statements, and minutes (2018-2024),” https://www.federalreserve.gov/monetarypolicy/fomccalendars.html, 2023.
  28. “How the fed impacts stocks, crypto and other investments,” https://www.bankrate.com/investing/federal-reserve-impact-on-stocks-crypto-other-investments/#crypto, 2023.
  29. G. Konstantopoulos and V. Buterin, “Ethereum Reorgs After The Merge,” https://www.paradigm.xyz/2021/07/ethereum-reorgs-after-the-merge, 2021.
  30. D. Grandjean, L. Heimbach, and R. Wattenhofer, “Ethereum Proof-of-Stake Consensus Layer: Participation and Decentralization,” arXiv preprint arXiv:2306.10777, 2023.
  31. J. Milionis, C. C. Moallemi, T. Roughgarden, and A. L. Zhang, “Automated Market Making and Loss-Versus-Rebalancing,” arXiv preprint arXiv:2208.06046, 2022.
  32. J. Milionis, C. C. Moallemi, and T. Roughgarden, “Automated Market Making and Arbitrage Profits in the Presence of Fees,” arXiv preprint arXiv:2305.14604, 2023.
  33. S. Eskandari, S. Moosavi, and J. Clark, “SoK: Transparent Dishonesty: Front-Running Attacks on Blockchain,” in Financial Cryptography and Data Security, vol. 11599.   Springer International Publishing, 2020, pp. 170–189.
  34. I. Bentov, Y. Ji, F. Zhang, L. Breidenbach, P. Daian, and A. Juels, “Tesseract: Real-time cryptocurrency exchange using trusted hardware,” in Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security, ser. CCS ’19, 2019, p. 1521–1538.
  35. C. Stathakopoulou, S. Rüsch, M. Brandenburger, and M. Vukolić, “Adding Fairness to Order: Preventing Front-Running Attacks in BFT Protocols using TEEs,” in 2021 40th International Symposium on Reliable Distributed Systems (SRDS).   IEEE, 2021, pp. 34–45.
  36. M. Kelkar, F. Zhang, S. Goldfeder, and A. Juels, “Order-Fairness for Byzantine Consensus,” in Annual International Cryptology Conference.   Springer, 2020, pp. 451–480.
  37. L. Baird, “The Swirlds Hashgraph Consensus Algorithm: Fair, Fast, Byzantine Fault Tolerance,” Swirlds Tech Reports SWIRLDS-TR-2016-01, Tech. Rep, 2016.
  38. K. Kursawe, “Wendy, the Good Little Fairness Widget: Achieving Order Fairness for Blockchains,” in Proceedings of the 2nd ACM Conference on Advances in Financial Technologies, 2020, pp. 25–36.
  39. Y. Zhang, S. Setty, Q. Chen, L. Zhou, and L. Alvisi, “Byzantine Ordered Consensus Without Byzantine Oligarchy,” in 14th {normal-{\{{USENIX}normal-}\}} Symposium on Operating Systems Design and Implementation ({normal-{\{{OSDI}normal-}\}} 20), 2020, pp. 633–649.
  40. M. Kelkar, S. Deb, and S. Kannan, “Order-Fair Consensus in the Permissionless Setting,” IACR Cryptol. ePrint Arch., vol. 2021, p. 139, 2021.
  41. M. Kelkar, S. Deb, S. Long, A. Juels, and S. Kannan, “Themis: Fast, Strong Order-Fairness in Byzantine Consensus,” Cryptology ePrint Archive, Report 2021/1465, 2021.
  42. C. Cachin, J. Mićić, and N. Steinhauer, “Quick Order Fairness,” in Financial Cryptography and Data Security (FC), Grenada, 2022.
  43. M. K. Reiter and K. P. Birman, “How to Securely Replicate Services,” ACM Transactions on Programming Languages and Systems (TOPLAS), vol. 16, no. 3, pp. 986–1009, 1994.
  44. A. Miller, Y. Xia, K. Croman, E. Shi, and D. Song, “The Honey Badger of BFT Protocols,” ser. CCS ’16, 2016, p. 31–42.
  45. A. Asayag, G. Cohen, I. Grayevsky, M. Leshkowitz, O. Rottenstreich, R. Tamari, and D. Yakira, “A Fair Consensus Protocol for Transaction Ordering,” in 2018 IEEE 26th International Conference on Network Protocols (ICNP), 2018.
  46. A. Orda and O. Rottenstreich, “Enforcing Fairness in Blockchain Transaction Ordering,” Peer-to-peer Networking and Applications, vol. 14, no. 6, pp. 3660–3673, 2021.
  47. H. Zhang, L.-H. Merino, V. Estrada-Galinanes, and B. Ford, “Flash freezing flash boys: Countering blockchain front-running,” in 2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops (ICDCSW).   IEEE, 2022, pp. 90–95.
  48. A. Constantinescu, D. Ghinea, L. Heimbach, Z. Wang, and R. Wattenhofer, “A Fair and Resilient Decentralized Clock Network for Transaction Ordering,” in 27th International Conference on Principles of Distributed Systems (OPODIS), Tokyo, Japan, Dec. 2023.
  49. P. Momeni, S. Gorbunov, and B. Zhang, “Fairblock: Preventing Blockchain Front-Running with Minimal Overheads,” in Security and Privacy in Communication Networks: 18th EAI International Conference, SecureComm 2022, Virtual Event, October 2022, Proceedings.   Springer, 2023, pp. 250–271.
  50. A. Tatabitovska, O. Ersoy, and Z. Erkin, “Mitigation of Transaction Manipulation Attacks in UniSwap,” 2021.
  51. L. Breidenbach, P. Daian, F. Tramèr, and A. Juels, “Enter the Hydra: Towards Principled Bug Bounties and Exploit-Resistant Smart Contracts,” in 27th USENIX Security Symposium, 2018, pp. 1335–1352.
  52. Y. Doweck and I. Eyal, “Multi-Party Timed Commitments,” arXiv preprint arXiv:2005.04883, 2020.
  53. L. Heimbach and R. Wattenhofer, “Eliminating Sandwich Attacks with the Help of Game Theory,” in ACM Asia Conference on Computer and Communications Security (ASIA CCS), Nagasaki, Japan, Jun. 2022.
  54. L. Zhou, K. Qin, and A. Gervais, “A2MM: Mitigating Frontrunning, Transaction Reordering and Consensus Instability in Decentralized Exchanges,” 2021.
  55. L. Heimbach and R. Wattenhofer, “SoK: Preventing Transaction Reordering Manipulations in Decentralized Finance,” in 4th ACM Conference on Advances in Financial Technologies (AFT), Cambridge, MA, USA, Sep. 2022.
  56. L. Heimbach, Y. Wang, and R. Wattenhofer, “Behavior of Liquidity Providers in Decentralized Exchanges,” in 2021 Crypto Valley Conference on Blockchain Technology (CVCBT), Rotkreuz, Switzerland, Oct. 2021.
  57. L. Heimbach, E. Schertenleib, and R. Wattenhofer, “Risks and Returns of Uniswap V3 Liquidity Providers,” in 4th ACM Conference on Advances in Financial Technologies (AFT), Cambridge, MA, USA, Sep. 2022.
  58. A. Wahrstätter, J. Ernstberger, A. Yaish, L. Zhou, K. Qin, T. Tsuchiya, S. Steinhorst, D. Svetinovic, N. Christin, M. Barczentewicz, and A. Gervais, “Blockchain Censorship,” arXiv preprint arXiv:2305.18545, 2023.
  59. A. Wahrstätter, L. Zhou, K. Qin, D. Svetinovic, and A. Gervais, “Time to Bribe: Measuring Block Construction Market,” arXiv preprint arXiv:2305.16468, 2023.
  60. C. Schwarz-Schilling, F. Saleh, T. Thiery, J. Pan, N. Shah, and B. Monnot, “Time is Money: Strategic Timing Games in Proof-of-Stake Protocols,” arXiv preprint arXiv:2305.09032, 2023.
Citations (13)

Summary

  • The paper introduces non-atomic arbitrage as a form of MEV by capturing on-chain and off-chain price discrepancies between DEXes and CEXes.
  • It presents a profit model using CFMMs and analyzes a case study from block 18,360,789 where 26 arbitrage transactions were identified.
  • The study highlights the integration of searchers and builders, discussing centralization risks and suggesting mitigations to secure blockchain operations.

Non-Atomic Arbitrage in Decentralized Finance

Introduction

The concept of maximal extractable value (MEV) has been a focal point in the Ethereum ecosystem, particularly with the introduction of non-atomic arbitrage. This paper investigates non-atomic arbitrage, a form of MEV that capitalizes on price discrepancies between decentralized exchanges (DEXes) on Ethereum and centralized exchanges (CEXes), or other blockchain platforms. Such arbitrage involves both on-chain and off-chain mechanisms, presenting unique challenges and opportunities for traders in the decentralized finance (DeFi) sector. Figure 1

Figure 1

Figure 1: The process of non-atomic arbitrage illustrating the interaction between DEXes and off-chain markets.

Non-Atomic Arbitrage Model

The paper proposes a model for quantifying profits from non-atomic arbitrage trades between two cryptocurrencies. In DEXes, prices result from previous transactions and can differ significantly from CEX prices, creating arbitrage opportunities. Utilizing constant function market makers (CFMM) like Uniswap, traders can exploit these price discrepancies. The model calculates arbitrageur profits based on liquidity pools and price differences, showcasing significant profits for substantial price changes. Figure 2

Figure 2: Arbitrageur profit as a function of price difference, highlighting profitability in significant price variations.

Case Study and Data Collection

An in-depth analysis of block 18,360,789 provides insight into real-world non-atomic arbitrage execution, demonstrating substantial price changes in ETH and BTC preceding the block proposal. Builders submit bids reflecting these changes, resulting in high-value transactions driven primarily by integrated searchers. The study reveals that 26 non-atomic arbitrage transactions were identified in this block, underscoring the volume and value extracted during times of volatility. Figure 3

Figure 3: Bids submitted by builders during volatile market conditions, showcasing strategic responses to price changes.

Searcher and Builder Integration

A notable aspect of non-atomic arbitrage is the potential integration between searchers — entities identifying and executing arbitrage opportunities — and builders, who construct blocks in Ethereum's PBS scheme. The paper speculates on the relationship between builders like beaverbuild and rsyncbuilder and their corresponding searchers, suggesting that integrated searchers are pivotal in capturing arbitrage opportunities, thereby influencing block construction and increasing centralization in the block building market. Figure 4

Figure 4: Cumulative volume of non-atomic arbitrage illustrating dominance by integrated searchers.

Effects of Market Volatility

Arbitrage opportunities correlate strongly with cryptocurrency price volatility. The paper establishes that non-atomic arbitrage volume spikes during periods of high volatility, such as the FTX collapse and USDC depeg events. Builders with integrated searchers are more likely to win blocks during these periods, reflecting a centralized approach to block construction that favors volatility. This behavior underscores concerns about centralization and security implications within the Ethereum ecosystem. Figure 5

Figure 5: Daily volume of non-atomic arbitrage trades and their correlation with the volatility of ETH and BTC prices.

Mitigations and Implications

Several mitigations are proposed to address the centralizing effects of non-atomic arbitrage, such as separating top-of-block extractions and reducing block time. These strategies aim to lessen arbitrage profitability and mitigate security risks associated with high-value trades, offering a path forward for maintaining decentralized balance in Ethereum blockchain operations.

Conclusion

The prevalence and impact of non-atomic arbitrage in Ethereum's DeFi landscape are profound, accounting for significant DEX volume and influencing the centralization of the block construction market. The insights provided by this paper are vital for understanding the dynamics of MEV in decentralized systems and devising strategies to promote equilibrium and security in blockchain ecosystems. Figure 6

Figure 6: Daily share of non-atomic arbitrage volume in HFT builder blocks, demonstrating the centralization trend.

Overall, this paper informs future research directions about MEV and decentralization challenges in Ethereum and similar blockchain systems, setting the stage for subsequent advancements in transaction security and efficiency.

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