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Don't Let MEV Slip: The Costs of Swapping on the Uniswap Protocol

Austin Adams, Benjamin Y Chan, Sarit Markovich, Xin Wan

TL;DR

The paper tackles the problem of quantifying the true costs of trading on a DEX by decomposing slippage into adversarial and benign components and introducing reordering slippage as a robust, data-driven metric. Using a large on-chain dataset from Uniswap v3 across two pools (USDC-ETH and PEPE-ETH), it shows that small trades are gas-dominated while large trades are driven by price impact and slippage, with memecoin trades experiencing substantially higher adversarial slippage. The authors provide a formal framework and empirical evidence, including regression analyses and an examination of MEV infrastructure (private RPCs and builder trust), demonstrating that private ordering can nearly eliminate adversarial slippage and that MEV ecosystems influence execution costs. Overall, the work establishes a baseline for DEX efficiency, highlights where improvements are most needed (liquidity depth and MEV resilience), and offers tools for auditing MEV participants and protocol designs aimed at reducing slippage. The findings suggest DEXs can be a competitive, trust-less alternative to centralized exchanges, while also underscoring the importance of robust MEV-mitigation and transparency mechanisms for broader adoption.

Abstract

We present the first in-depth empirical characterization of the costs of trading on a decentralized exchange (DEX). Using quoted prices from the Uniswap Labs interface for two pools -- USDC-ETH (5bps) and PEPE-ETH (30bps) -- we evaluate the efficiency of trading on DEXs. Our main tool is slippage -- the difference between the realized execution price of a trade, and its quoted price -- which we breakdown into its benign and adversarial components. We also present an alternative way to quantify and identify slippage due to adversarial reordering of transactions, which we call reordering slippage, that does not require quoted prices or mempool data to calculate. We find that the composition of transaction costs varies tremendously with the trade's characteristics. Specifically, while for small swaps, gas costs dominate costs, for large swaps price-impact and slippage account for the majority of it. Moreover, when trading PEPE, a popular 'memecoin', the probability of adversarial slippage is about 80% higher than when trading a mature asset like USDC. Overall, our results provide preliminary evidence that DEXs offer a compelling trust-less alternative to centralized exchanges for trading digital assets.

Don't Let MEV Slip: The Costs of Swapping on the Uniswap Protocol

TL;DR

The paper tackles the problem of quantifying the true costs of trading on a DEX by decomposing slippage into adversarial and benign components and introducing reordering slippage as a robust, data-driven metric. Using a large on-chain dataset from Uniswap v3 across two pools (USDC-ETH and PEPE-ETH), it shows that small trades are gas-dominated while large trades are driven by price impact and slippage, with memecoin trades experiencing substantially higher adversarial slippage. The authors provide a formal framework and empirical evidence, including regression analyses and an examination of MEV infrastructure (private RPCs and builder trust), demonstrating that private ordering can nearly eliminate adversarial slippage and that MEV ecosystems influence execution costs. Overall, the work establishes a baseline for DEX efficiency, highlights where improvements are most needed (liquidity depth and MEV resilience), and offers tools for auditing MEV participants and protocol designs aimed at reducing slippage. The findings suggest DEXs can be a competitive, trust-less alternative to centralized exchanges, while also underscoring the importance of robust MEV-mitigation and transparency mechanisms for broader adoption.

Abstract

We present the first in-depth empirical characterization of the costs of trading on a decentralized exchange (DEX). Using quoted prices from the Uniswap Labs interface for two pools -- USDC-ETH (5bps) and PEPE-ETH (30bps) -- we evaluate the efficiency of trading on DEXs. Our main tool is slippage -- the difference between the realized execution price of a trade, and its quoted price -- which we breakdown into its benign and adversarial components. We also present an alternative way to quantify and identify slippage due to adversarial reordering of transactions, which we call reordering slippage, that does not require quoted prices or mempool data to calculate. We find that the composition of transaction costs varies tremendously with the trade's characteristics. Specifically, while for small swaps, gas costs dominate costs, for large swaps price-impact and slippage account for the majority of it. Moreover, when trading PEPE, a popular 'memecoin', the probability of adversarial slippage is about 80% higher than when trading a mature asset like USDC. Overall, our results provide preliminary evidence that DEXs offer a compelling trust-less alternative to centralized exchanges for trading digital assets.
Paper Structure (32 sections, 7 equations, 1 figure, 7 tables)

This paper contains 32 sections, 7 equations, 1 figure, 7 tables.

Table of Contents

  1. Introduction
  2. Summary of our contributions.
  3. Background
  4. Decentralized Exchanges
  5. Anatomy of a Swap
  6. The MEV Ecosystem
  7. Our Framework
  8. Other desiderata.
  9. Reordering Slippage
  10. Defining reordering slippage.
  11. Backruns and arbitrages.
  12. Achieving zero reordering slippage.
  13. Concurrent work.
  14. Empirical Findings
  15. Data
  16. ...and 17 more sections

Figures (1)

  • Figure 1: Transaction Cost Composition For Different Transaction Types

Theorems & Definitions (1)

  • Definition 3.2: Reordering Slippage