对 AMM 上的事务进行 CLVR 排序

Robert McLaughlin, Nir Chemaya, Dingyue Liu, Dahlia Malkhi
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引用次数: 0

摘要

通过自动做市商(AMM)机制在去中心化交易所进行的交易已被大量采用,日交易量达到 10 亿美元。这种交易方法也受到了研究人员、中央银行和金融公司的密切关注,他们有可能将其应用到传统金融市场,如国外交易所和股票市场。以 AMM 为动力的交易面临的一个关键挑战是交易订单具有很高的金融价值,因此以 "良好"(最优)的方式安排交易订单的政策或方法至关重要。我们提供了价格稳定性(低波动性)和不平等性的经济衡量标准,为 "社会规划者 "如何选择最优排序提供了参考。我们表明,在实现价格稳定和减少不平等之间存在权衡,决策者必须选择哪个优先。此外,选择最优排序往往代价高昂,尤其是在对交易排序(排列)进行穷举搜索时。作为一种替代方法,我们提供了一种简单的算法--聪明的前瞻波动率降低算法(Clever Look-ahead VolatilityReduction,CLVR)。该算法能以较小的计算成本构建一个近似最小化价格波动的排序。我们还提供了交易者采用这种排序算法时可能发生的策略变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CLVR Ordering of Transactions on AMMs
Trading on decentralized exchanges via an Automated Market Maker (AMM) mechanism has been massively adopted, with a daily trading volume reaching $1B. This trading method has also received close attention from researchers, central banks, and financial firms, who have the potential to adopt it to traditional financial markets such as foreign exchanges and stock markets. A critical challenge of AMM-powered trading is that transaction order has high financial value, so a policy or method to order transactions in a "good" (optimal) manner is vital. We offer economic measures of both price stability (low volatility) and inequality that inform how a "social planner" should pick an optimal ordering. We show that there is a trade-off between achieving price stability and reducing inequality, and that policymakers must choose which to prioritize. In addition, picking the optimal order can often be costly, especially when performing an exhaustive search over trade orderings (permutations). As an alternative we provide a simple algorithm, Clever Look-ahead Volatility Reduction (CLVR). This algorithm constructs an ordering which approximately minimizes price volatility with a small computation cost. We also provide insight into the strategy changes that may occur if traders are subject to this sequencing algorithm.
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