Deviations from Tradition: Stylized Facts in the Era of DeFi

ArXiv ID: 2510.22834 “View on arXiv”

Authors: Daniele Maria Di Nosse, Federico Gatta, Fabrizio Lillo, Sebastian Jaimungal

Abstract

Decentralized Exchanges (DEXs) are now a significant component of the financial world where billions of dollars are traded daily. Differently from traditional markets, which are typically based on Limit Order Books, DEXs typically work as Automated Market Makers, and, since the implementation of Uniswap v3, feature concentrated liquidity. By investigating the twenty-four most active pools in Uniswap v3 during 2023 and 2024, we empirically study how this structural change in the organization of the markets modifies the well-studied stylized facts of prices, liquidity, and order flow observed in traditional markets. We find a series of new statistical regularities in the distributions and cross-autocorrelation functions of these variables that we are able to associate either with the market structure (e.g., the execution of orders in blocks) or with the intense activity of Maximal Extractable Value searchers, such as Just-in-Time liquidity providers and sandwich attackers.

Keywords:

Complexity vs Empirical Score

• Math Complexity: 4.5/10
• Empirical Rigor: 8.0/10
• Quadrant: Street Traders
• Why: The paper relies heavily on statistical analysis of real DeFi trading data (24 pools over 2 years) and focuses on market microstructure deviations, but the math is primarily standard econometrics and descriptive statistics rather than dense theoretical derivations.

  flowchart TD
    A["Research Goal: Study impact of AMM & concentrated liquidity on market stylized facts"] --> B["Data Collection: 24 most active pools in Uniswap v3 during 2023-2024"]
    B --> C["Empirical Analysis: Compare price, liquidity, and order flow dynamics"]
    C --> D["Computational Processes: Analyze distributions & cross-autocorrelation functions"]
    D --> E{"Key Outcomes"}
    E --> F["New Stylized Facts: Statistical regularities in distributions & correlations"]
    E --> G["Market Structure Causes: Block execution of orders"]
    E --> H["MEV Activity Causes: Just-in-Time liquidity provision & sandwich attacks"]