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Impermanent Loss in Uniswap v3

Author

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  • Stefan Loesch
  • Nate Hindman
  • Mark B Richardson
  • Nicholas Welch

Abstract

AMMs are autonomous smart contracts deployed on a blockchain that make markets between different assets that live on that chain. In this paper we are examining a specific class of AMMs called Constant Function Market Makers whose trading profile, ignoring fees, is determined by their bonding curve. This class of AMM suffers from what is commonly referred to as Impermanent Loss, which we have previously identified as the Gamma component of the associated self-financing trading strategy and which is the risk that LP providers wager against potential fee earnings. The recent Uniswap v3 release has popularized the concept of leveraged liquidity provision - wherein the trading range in which liquidity is provided is reduced and achieves a higher degree of capital efficiency through elimination of unused collateral. This leverage increases the fees earned, but it also increases the risk taken, ie the IL. Fee levels on Uniswap v3 are well publicized so, in this paper, we focus on calculating the IL. We found that for the 17 pools we analyzed, covering 43% of TVL and chosen by size, composite tokens and data availability, total fees earned since inception until the cut-off date was $199.3m. We also found that the total IL suffered by LPs during this period was USD 260.1m, meaning that in aggregate those LPs would have been better off by USD 60.8m had they simply HODLd.

Suggested Citation

  • Stefan Loesch & Nate Hindman & Mark B Richardson & Nicholas Welch, 2021. "Impermanent Loss in Uniswap v3," Papers 2111.09192, arXiv.org.
    • Handle: RePEc:arx:papers:2111.09192
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    File URL: http://arxiv.org/pdf/2111.09192
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    Cited by:

    1. Matthew Willetts & Christian Harrington, 2024. "Rebalancing-versus-Rebalancing: Improving the fidelity of Loss-versus-Rebalancing," Papers 2410.23404, arXiv.org.
    2. Maxim Bichuch & Zachary Feinstein, 2024. "DeFi Arbitrage in Hedged Liquidity Tokens," Papers 2409.11339, arXiv.org, revised Dec 2024.
    3. Agostino Capponi & Ruizhe Jia & Brian Zhu, 2023. "The Paradox Of Just-in-Time Liquidity in Decentralized Exchanges: More Providers Can Sometimes Mean Less Liquidity," Papers 2311.18164, arXiv.org, revised Feb 2024.
    4. Lioba Heimbach & Eric Schertenleib & Roger Wattenhofer, 2022. "Exploring Price Accuracy on Uniswap V3 in Times of Distress," Papers 2208.09642, arXiv.org, revised Nov 2022.
    5. Viraj Nadkarni & Sanjeev Kulkarni & Pramod Viswanath, 2024. "Adaptive Curves for Optimally Efficient Market Making," Papers 2406.13794, arXiv.org.
    6. Philippe Bergault & Louis Bertucci & David Bouba & Olivier Gu'eant, 2022. "Automated Market Makers: Mean-Variance Analysis of LPs Payoffs and Design of Pricing Functions," Papers 2212.00336, arXiv.org, revised Nov 2023.
    7. Samuel Cohen & Marc Sabat'e Vidales & David v{S}iv{s}ka & {L}ukasz Szpruch, 2023. "Inefficiency of CFMs: hedging perspective and agent-based simulations," Papers 2302.04345, arXiv.org.
    8. Srisht Fateh Singh & Panagiotis Michalopoulos & Andreas Veneris, 2024. "Deeper: A shared liquidity decentralized exchange design for low trading volume tokens to enhance average liquidity," International Journal of Network Management, John Wiley & Sons, vol. 34(4), July.

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