arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2402.09357cs.GTcs.CG
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自动化做市商的机制设计

Mechanism Design for Automated Market Makers

T-H. Hubert Chan, Ke Wu, Elaine Shi

AI总结:

本文提出一种批量处理区块内所有交易的AMM新机制,在传统区块链中实现套利弹性与公平对待,在去中心化排序公平的区块链中实现激励相容,从而消除MEV机会。

摘要:

区块链普及了自动化做市商(AMM)。AMM交易所是运行在区块链上的应用程序,它维护一个加密资产池,并根据某些基于资产相对需求/供给为其定价的定价函数,自动与用户进行资产交易。AMM创造了一个通常被称为矿工可提取价值(MEV)的重要挑战。具体而言,控制区块内交易内容和排序的矿工可以通过抢先交易和尾随交易用户的交易来提取价值,从而产生套利机会,保证他们获得无风险回报。在本文中,我们考虑如何设计消除MEV机会的AMM机制。具体而言,我们提出了一种新的AMM机制,该机制以批处理方式处理包含在一个区块内的所有交易。我们表明,我们的新机制满足两个层级的保证。首先,对于每个区块由单个(可能轮换的)矿工提议的传统区块链,我们证明我们的机制满足套利弹性,即矿工无法获得无风险利润。此外,我们还保证同一区块内所有交易之间的公平对待,使得矿工无法将区块内的有利位置出售给用户或套利者。其次,对于区块提议过程去中心化并提供排序公平性的区块链,我们证明了一个称为激励相容性的更强概念——粗略地说,我们保证任何个体用户的最佳响应都是遵循诚实策略。

英文摘要:

Blockchains have popularized automated market makers (AMMs). An AMM exchange is an application running on a blockchain which maintains a pool of crypto-assets and automatically trades assets with users governed by some pricing function that prices the assets based on their relative demand/supply. AMMs have created an important challenge commonly known as the Miner Extractable Value (MEV). In particular, the miners who control the contents and ordering of transactions in a block can extract value by front-running and back-running users' transactions, leading to arbitrage opportunities that guarantee them risk-free returns. In this paper, we consider how to design AMM mechanisms that eliminate MEV opportunities. Specifically, we propose a new AMM mechanism that processes all transactions contained within a block in a batch. We show that our new mechanism satisfies two tiers of guarantees. First, for legacy blockchains where each block is proposed by a single (possibly rotating) miner, we prove that our mechanism satisfies arbitrage resilience, i.e., a miner cannot gain risk-free profit. Moreover, we also guarantee fair treatment among all transactions within the same block, such that the miner is unable to sell off favorable positions in the block to users or arbitragers. Second, for blockchains where the block proposal process is decentralized and offers sequencing-fairness, we prove a stronger notion called incentive compatibility -- roughly speaking, we guarantee that any individual user's best response is to follow the honest strategy.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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