Abstract
We consider the impact of trading fees on the profits of arbitrageurs trading against an automated marker marker (AMM) or, equivalently, on the adverse selection incurred by liquidity providers due to arbitrage. We extend the model of Milionis et al. [1] for a general class of two asset AMMs to both introduce fees and discrete Poisson block generation times. In our setting, we are able to compute the expected instantaneous rate of arbitrage profit in closed form. When the fees are low, in the fast block asymptotic regime, the impact of fees takes a particularly simple form: fees simply scale down arbitrage profits by the fraction of time that an arriving arbitrageur finds a profitable trade.
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Reference
Milionis, J., Moallemi, C.C., Roughgarden, T., Zhang, A.L.: Quantifying loss in automated market makers. In: Proceedings of the 2022 ACM CCS Workshop on Decentralized Finance and Security, pp. 71–74. Association for Computing Machinery, New York, USA (2022). https://doi.org/10.1145/3560832.3563441
Acknowledgment
The first author is supported in part by NSF awards CNS-2212745, CCF-2212233, DMS-2134059, and CCF-1763970. The second author is supported by the Briger Family Digital Finance Lab at Columbia Business School. The third author’s research at Columbia University is supported in part by NSF awards CNS-2212745, and CCF-2006737.
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© 2024 International Financial Cryptography Association
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Milionis, J., Moallemi, C.C., Roughgarden, T. (2024). Extended Abstract: The Effect of Trading Fees on Arbitrage Profits in Automated Market Makers. In: Essex, A., et al. Financial Cryptography and Data Security. FC 2023 International Workshops. FC 2023. Lecture Notes in Computer Science, vol 13953. Springer, Cham. https://doi.org/10.1007/978-3-031-48806-1_17
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DOI: https://doi.org/10.1007/978-3-031-48806-1_17
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