Robert McLaughlin, Nir Chemaya, Dingyue Liu, Dahlia Malkhi
{"title":"对 AMM 上的事务进行 CLVR 排序","authors":"Robert McLaughlin, Nir Chemaya, Dingyue Liu, Dahlia Malkhi","doi":"arxiv-2408.02634","DOIUrl":null,"url":null,"abstract":"Trading on decentralized exchanges via an Automated Market Maker (AMM)\nmechanism has been massively adopted, with a daily trading volume reaching $1B.\nThis trading method has also received close attention from researchers, central\nbanks, and financial firms, who have the potential to adopt it to traditional\nfinancial markets such as foreign exchanges and stock markets. A critical\nchallenge of AMM-powered trading is that transaction order has high financial\nvalue, so a policy or method to order transactions in a \"good\" (optimal) manner\nis vital. We offer economic measures of both price stability (low volatility)\nand inequality that inform how a \"social planner\" should pick an optimal\nordering. We show that there is a trade-off between achieving price stability\nand reducing inequality, and that policymakers must choose which to prioritize.\nIn addition, picking the optimal order can often be costly, especially when\nperforming an exhaustive search over trade orderings (permutations). As an\nalternative we provide a simple algorithm, Clever Look-ahead Volatility\nReduction (CLVR). This algorithm constructs an ordering which approximately\nminimizes price volatility with a small computation cost. We also provide\ninsight into the strategy changes that may occur if traders are subject to this\nsequencing algorithm.","PeriodicalId":501478,"journal":{"name":"arXiv - QuantFin - Trading and Market Microstructure","volume":"64 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"CLVR Ordering of Transactions on AMMs\",\"authors\":\"Robert McLaughlin, Nir Chemaya, Dingyue Liu, Dahlia Malkhi\",\"doi\":\"arxiv-2408.02634\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Trading on decentralized exchanges via an Automated Market Maker (AMM)\\nmechanism has been massively adopted, with a daily trading volume reaching $1B.\\nThis trading method has also received close attention from researchers, central\\nbanks, and financial firms, who have the potential to adopt it to traditional\\nfinancial markets such as foreign exchanges and stock markets. A critical\\nchallenge of AMM-powered trading is that transaction order has high financial\\nvalue, so a policy or method to order transactions in a \\\"good\\\" (optimal) manner\\nis vital. We offer economic measures of both price stability (low volatility)\\nand inequality that inform how a \\\"social planner\\\" should pick an optimal\\nordering. We show that there is a trade-off between achieving price stability\\nand reducing inequality, and that policymakers must choose which to prioritize.\\nIn addition, picking the optimal order can often be costly, especially when\\nperforming an exhaustive search over trade orderings (permutations). As an\\nalternative we provide a simple algorithm, Clever Look-ahead Volatility\\nReduction (CLVR). This algorithm constructs an ordering which approximately\\nminimizes price volatility with a small computation cost. We also provide\\ninsight into the strategy changes that may occur if traders are subject to this\\nsequencing algorithm.\",\"PeriodicalId\":501478,\"journal\":{\"name\":\"arXiv - QuantFin - Trading and Market Microstructure\",\"volume\":\"64 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - QuantFin - Trading and Market Microstructure\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2408.02634\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - Trading and Market Microstructure","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2408.02634","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.