decentralized exchange developers

Abstract: Many decentralized exchanges use automated market makers (AMMs) to trade assets against liquidity pools. Modern AMMs allow third-party contracts, called Hooks, to customize this process. However, Hooks can impose additional deductions that fee breakdowns based on standard pool parameters do not itemize. We present, to the best of our knowledge, the first large-scale empirical study of the production Hook ecosystem, focusing on these undisclosed settlement charges. Our study covers 7,873 Hook deployments, 50,011 pools, and 296M pool events on Uniswap v4 and PancakeSwap Infinity across Ethereum and BNB Smart Chain (BSC) through August 1, 2026. We develop a bytecode analysis that reconstructs how Hooks change traders' payments and receipts, separating charges from exchanged assets and standard fees. We then reconstruct historical settlements to measure charging frequency and economic burden. We find that direct settlement adjustment is the dominant Hook capability, supported by 71.37% of registered Hooks. Charging capability is widespread and often exercised: 24.30% of Hooks can impose undisclosed deductions, and these deductions occur in 59.23% of accounted swaps involving such Hooks. These charges generate millions of dollars in revenue, with $3.97M recorded across Hooks with available token prices. These findings reveal a gap between standard fee displays and actual trading costs, motivating explicit disclosure of Hook deductions alongside standard fees.

Abstract: Automated market makers (AMMs) are central to decentralized exchanges, but their reserve curves make mechanism design different from classical double auctions. We study a batch double auction with buyers, sellers, and a liquidity-nondecreasing AMM: post-trade reserves must have weakly larger product than the initial reserves. Each user has two-dimensional private information: a unit value and a demand or supply quantity. User trades clear at one uniform price subject to AMM feasibility. The objective is user-side trading volume, benchmarked against the optimal feasible individually rational (IR) uniform-price allocation. We give a randomized uniform-price mechanism based on binary quantity buckets. It randomly chooses one of three clearing modes: peer-to-peer matching, AMM sales to buyers, and seller sales to the AMM. Every deterministic realization of the mechanism is ex-post feasible and satisfies IR and weak quantity incentive compatibility: conditional on any quantity report, truthful unit-value reporting is dominant whenever it gives a non-negative utility, no unit-value deviation gives a positive utility if the truthful one doesn't, and users cannot benefit by under-reporting the quantity together with their truthful unit value. Let $V^\ast$ be the optimal feasible IR uniform-price volume without incentive constraints, and let $γ=\bar q/\underline q$, where $\bar q$ and $\underline q$ are the quantity-domain bounds. For $γ\ge1$, the mechanism achieves an expected trading volume of $ Ω(1/(1+\logγ)^2)V^\ast - O(\bar q). $ We also show that full incentive compatibility over the two-dimensional type space forces a worst-case approximation ratio of $O(1/γ)$ at every prescribed initial reserve ratio, even when both AMM reserves are scaled by an arbitrarily large common factor and the optimal volume $V^\ast$ is arbitrarily large relative to $\bar q$.