A Midsummer Meme's Dream: Investigating Market Manipulations in the Meme Coin Ecosystem
Alberto Maria Mongardini, Alessandro Mei
摘要
From viral jokes to a billion-dollar phenomenon, meme coins have become one of the most popular segments in cryptocurrency markets. Unlike utility-focused crypto assets like Bitcoin, meme coins derive value primarily from community sentiment, making them vulnerable to manipulation. This study presents an unprecedented cross-chain analysis of the meme coin ecosystem, examining 34,988 tokens across Ethereum, BNB Smart Chain, Solana, and Base. We characterize their tokenomics and track their growth in a three-month longitudinal analysis. We discover that among high-return tokens (>100%), an alarming 82.8% show evidence of artificial growth strategies designed to create a misleading appearance of market interest. These include wash trading and a new form of manipulation we define as Liquidity Pool-Based Price Inflation (LPI), where small strategic purchases trigger dramatic price increases. We find that profit extraction schemes, such as pump and dumps and rug pulls, typically follow initial manipulations like wash trading or LPI, indicating how early manipulations create the foundation for later exploitation. We quantify the economic impact of these schemes, identifying over 17,000 victimized addresses with realized losses exceeding $9.3 million. These findings reveal that combined manipulations are widespread among high-performing meme coins, suggesting that their dramatic gains are often driven by coordinated efforts rather than natural market dynamics.
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- The Anatomy of a Cryptocurrency Pump-and-Dump SchemeJiahua Xu, Benjamin LivshitsUSENIX Security 2019 · 被引用 146 次
- Detecting and Quantifying Wash Trading on Decentralized Cryptocurrency ExchangesFriedhelm Victor, Andrea Marie WeintraudWWW 2021 · 被引用 111 次
- Token Spammers, Rug Pulls, and Sniper Bots: An Analysis of the Ecosystem of Tokens in Ethereum and in the Binance Smart Chain (BNB)Federico Cernera, Massimo La Morgia, Alessandro Mei, Francesco SassiUSENIX Security 2023
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