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Multidimensional Blockchain Fees Are (Essentially) Optimal

Authors Guillermo Angeris , Theo Diamandis , Ciamac Moallemi

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ACM Subject Classification
  • Theory of computation → Online algorithms
  • Theory of computation → Convex optimization
  • Information systems → Digital cash
  • Theory of computation → Algorithmic mechanism design
Keywords
  • Blockchains
  • transaction fees
  • online optimization
  • convex optimization

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Abstract

In this paper we show that, using only mild assumptions, dynamic multidimensional blockchain fee markets have strong performance guarantees, even against worst-case adversaries. In particular, we show that the average welfare gap between the following two scenarios is at most O(1/√T), where T is the length of the time horizon considered. In the first scenario, the designer knows all future actions by users and is allowed to fix the optimal prices of resources ahead of time, based on the designer’s oracular knowledge of those actions. In the second, the prices are updated by a very simple algorithm that does not have this oracular knowledge, special cases of which are EIP-4844 and EIP-1559, both fee mechanisms used by the Ethereum blockchain. Roughly speaking, this means that, on average, over a reasonable timescale, there is no difference in welfare between "correctly" fixing the prices, with oracular knowledge of the future, when compared to the proposed algorithm. We show a matching lower bound of Ω(1/√T) for any implementable algorithm and also separately consider the case where the adversary is known to be stochastic.

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Guillermo Angeris, Theo Diamandis, and Ciamac Moallemi. Multidimensional Blockchain Fees Are (Essentially) Optimal. In 7th Conference on Advances in Financial Technologies (AFT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 354, pp. 24:1-24:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.AFT.2025.24

Author Details

Guillermo Angeris
  • Bain Capital Crypto, Boston, MA, USA
Theo Diamandis
  • Bain Capital Crypto, Boston, MA, USA
Ciamac Moallemi
  • Graduate School of Business, Columbia University, New York, NY, USA

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