Price manipulation schemes of new crypto-tokens in decentralized exchanges

Paper: arXiv 2502.10512

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.

Complexity vs Empirical Score

• Math Complexity: 4.5/10
• Empirical Rigor: 6.0/10 (capped from 8.5: no out-of-sample test; see penalty flags)
• Quadrant: Street Traders — practical and empirical, lighter on theory

Why this score: 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.

Research Flowchart

  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

Cited References (45)

1. Router02 (Uniswap V2) — Technical Reference
2. Ethereum Gas Tracker
3. The fragility of decentralised trustless socio-technical systems (2019) — link
4. DApps ecosystems: mapping the network structure of smart contract interactions (2024) — link
5. Mitigating MEV attacks with a two-tiered architecture utilizing verifiable decryption (2024) — link
6. Transaction-based classification and detection approach for Ethereum smart contract (2021) — link
7. TokenAware: Accurate and Efficient Bookkeeping Recognition for Token Smart Contracts (2023) — link
8. Detecting DeFi securities violations from token smart contract code (2024) — link

1 of 45 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.