Price manipulation schemes of new crypto-tokens in decentralized exchanges

ArXiv ID: 2502.10512 “View on arXiv”

Authors: Unknown

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, which offer 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.

Keywords: Decentralized Exchanges (DEXs), Uniswap V2, liquidity manipulation, sandwich attacks, Cryptocurrencies

Complexity vs Empirical Score

• Math Complexity: 4.5/10
• Empirical Rigor: 8.5/10
• Quadrant: Street Traders
• Why: The paper relies heavily on real blockchain data (17k+ tokens) and empirical techniques like clustering and dynamic simulation for classification, showing high empirical rigor. However, the mathematical models are relatively accessible, focusing on descriptive analytics, optimal sandwich sizing, and time-series comparisons rather than dense theoretical derivations.

  flowchart TD
    A["Research Goal:<br>Analyze financial impact & risks<br>of new tokens on Uniswap V2"] --> B["Data Collection & Processing"]
    B --> C["Methodology: Buy-and-Hold Strategy<br>& Liquidity Analysis"]
    C --> D["Computational Processes:<br>Sandwich Attack Simulation & Clustering"]
    D --> E["Key Findings"]
    
    subgraph B ["Data/Inputs"]
        B1["Uniswap V2 Event Logs"]
        B2["On-chain Transaction Data"]
    end

    subgraph D ["Computational Details"]
        D1["Extract Optimal Sandwich Amount"]
        D2["Cluster Price Evolution:<br>Swap Time vs. Physical Time"]
    end

    subgraph E ["Outcomes"]
        E1["Honeypots trap significant liquidity"]
        E2["Prevalence of Rug Pulls & Sandwich Attacks"]
        E3["Identification of Honeypot vs.<br>Sellable Token Patterns"]
    end

    B2 --> C
    B1 --> D1
    B2 --> D2