Fragmentation and optimal liquidity supply on decentralized exchanges

ArXiv ID: 2307.13772 “View on arXiv”

Authors: Unknown

Abstract

We investigate how liquidity providers (LPs) choose between high- and low-fee trading venues, in the face of a fixed common gas cost. Analyzing Uniswap data, we find that high-fee pools attract 58% of liquidity supply yet execute only 21% of volume. Large LPs dominate low-fee pools, frequently adjusting out-of-range positions in response to informed order flow. In contrast, small LPs converge to high-fee pools, accepting lower execution probabilities to mitigate adverse selection and liquidity management costs. Fragmented liquidity dominates a single-fee market, as it encourages more liquidity providers to enter the market, while fostering LP competition on the low-fee pool.

Keywords: Liquidity Provision, Uniswap, Adverse Selection, Decentralized Finance, Gas Costs, Cryptocurrency

Complexity vs Empirical Score

• Math Complexity: 7.5/10
• Empirical Rigor: 8.0/10
• Quadrant: Holy Grail
• Why: The paper employs a formal theoretical model with heterogeneous agents, game theory, and analytical derivations to establish equilibrium conditions, which requires advanced mathematics. Additionally, it is backed by empirical analysis of real Uniswap v3 data, analyzing high-frequency liquidity dynamics, volume statistics, and LP behavior across different fee tiers.

  flowchart TD
    A["Research Goal<br>How do LPs choose between high-<br>and low-fee DEX pools?<br>Is fragmented liquidity optimal?"] --> B["Methodology<br>Analyze Uniswap V2 & V3 Data<br>Track LP positions & tx history"]

    B --> C{"Data Inputs"}
    C --> C1["Pool Parameters<br>High fee 1%<br>Low fee 0.05%"]
    C --> C2["Liquidity Supply<br>58% in High Fee<br>42% in Low Fee"]
    C --> C3["Trading Volume<br>21% executed in High Fee<br>79% in Low Fee"]

    C --> D["Computational Analysis<br>1. Correlate LP size vs. pool choice<br>2. Track position rebalancing frequency<br>3. Measure adverse selection costs<br>4. Model gas cost impact"]

    D --> E{"Key Findings"}
    E --> E1["Large LPs dominate Low Fee<br>Frequent adjustments for informed flow"]
    E --> E2["Small LPs prefer High Fee<br>Accept lower execution to mitigate<br>adverse selection & gas costs"]
    E --> E3["Fragmented Liquidity > Single Fee<br>Encourages LP entry & competition"]