An Improved Algorithm to Identify More Arbitrage Opportunities on Decentralized Exchanges
Yu Zhang, Tao Yan, Jianhong Lin, Benjamin Kraner, Claudio Tessone

TL;DR
This paper introduces a novel algorithm combining line graph and a modified Moore-Bellman-Ford method to detect more arbitrage opportunities, including non-loop paths, on decentralized exchanges like Uniswap, revealing larger potential profits.
Contribution
The paper presents a new method that overcomes limitations of existing algorithms by detecting more arbitrage loops and non-loop paths starting from any token, increasing detection scope.
Findings
Detected more arbitrage loops and non-loop paths on Uniswap V2.
Found arbitrage profits up to one million dollars.
Showed how arbitrage opportunities evolve over time.
Abstract
In decentralized exchanges (DEXs), the arbitrage paths exist abundantly in the form of both arbitrage loops (e.g. the arbitrage path starts from token A and back to token A again in the end, A, B,..., A) and non-loops (e.g. the arbitrage path starts from token A and stops at a different token N, A, B,..., N). The Moore-Bellman-Ford algorithm, often coupled with the ``walk to the root" technique, is commonly employed for detecting arbitrage loops in the token graph of decentralized exchanges (DEXs) such as Uniswap. However, a limitation of this algorithm is its ability to recognize only a limited number of arbitrage loops in each run. Additionally, it cannot specify the starting token of the detected arbitrage loops, further constraining its effectiveness in certain scenarios. Another limitation of this algorithm is its incapacity to detect non-loop arbitrage paths between any specified…
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Taxonomy
TopicsEconomic theories and models · Stochastic processes and financial applications · Complex Systems and Time Series Analysis
