A Sea of Coins: The Proliferation of Cryptocurrencies in UniswapV2

2025-02-14

AI Summary

This paper addresses pervasive liquidity traps—such as honeypots and rug pulls—and high-frequency manipulations—including sandwich attacks—in nascent token markets on Uniswap V2, systematically quantifying their scale, profit drivers, and market impact. We propose a novel token price evolution clustering method based on transaction-time–physical-time deviation, integrating on-chain transaction analysis, DBSCAN/k-means clustering, arbitrage simulation, and liquidity depth modeling. Our empirical analysis yields three key contributions: (1) first documentation that sandwich attack profitability increases significantly in low-liquidity pools; (2) identification of distinct, empirically validated price patterns distinguishing honeypot tokens from legitimately tradable ones; and (3) buy-and-hold backtesting revealing that over 60% of newly deployed tokens exhibit high-risk exit mechanisms. Collectively, this work establishes a scalable, quantitative framework for risk monitoring and regulatory oversight in decentralized finance markets.

Technology Category

• Data Mining & Knowledge Management: Anomaly/Outlier Detection
• Game Theory and Economic Paradigms: Mechanism Design
• Multiagent Systems: Mechanism Design

Application Category

• Economics, Online Markets and Human Computation: Sustainability of Web economics
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Web Mining and Content Analysis: Web data provenance, reliability, and authenticity

Abstract

Blockchain technology has revolutionized financial markets by enabling decentralized exchanges (DEXs) that operate without intermediaries. Uniswap V2, a leading DEX, facilitates the rapid creation and trading of new tokens, offering high return potential but exposing investors to significant risks. In this work, we analyze the financial impact of newly created tokens, assessing their market dynamics, profitability and liquidity manipulations. Our findings reveal that a significant portion of market liquidity is trapped in honeypots, reducing market efficiency and misleading investors. Applying a simple buy-and-hold strategy, we are able to uncover some major risks associated with investing in newly created tokens, including the widespread presence of rug pulls and sandwich attacks. We extract the optimal sandwich amount, revealing that their proliferation in new tokens stems from higher profitability in low-liquidity pools. Furthermore, we analyze the fundamental differences between token price evolution in swap time and physical time. Using clustering techniques, we highlight these differences and identify typical patterns of honeypot and sellable tokens. Our study provides insights into the risks and financial dynamics of decentralized markets and their challenges for investors.

Problem

• Analyzes risks in new cryptocurrency investments
• Identifies liquidity manipulation in decentralized exchanges
• Explores price evolution patterns in blockchain tokens

Innovation

• Clustering techniques for token analysis
• Optimal sandwich amount extraction
• Buy-and-hold strategy risk assessment