mlsanityData to 14 Oct 2026

Automated Market Making and Loss-Versus-Rebalancing

arXiv 2208.06046 ↗First posted 11 Aug 2022q-fin.MF math.OC q-fin.PMcited by 10

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Abstract (arXiv)

Automated Market Makers (AMMs) are both liquidity sources and investment vehicles for market participants. This paper analyzes the risks and returns of liquidity provision (LP) investments in AMMs. In a continuous-time model, we show that LP returns decompose into a beta-like component reflecting market risk exposure, and an alpha-like component reflecting microstructural forces: accrued fees minus losses to arbitrageurs. Applying our decomposition to the Uniswap v2 ETH-USDC pool, we find that over 99.991% of LP return variance is driven by beta exposure to market risk

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 Aug 2022.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 2; 2024: 1; 2025: 1; 2026: 6.

10 papers.

  1. 2023Adaptive Liquidity Provision in Uniswap V3 with Deep Reinforcement Learningcited by 6
  2. 2025Improving DeFi Accessibility through Efficient Liquidity Provisioning with Deep Reinforcement Learningcited by 2
  3. 2024Optimal Automated Market Makers: Differentiable Economics and Strong Dualitycited by 1
  4. 2026Werracle: Sub-Cent Intra-Block AI Reflex Oracles and Flash-Loan Circuit Breakers for EVM Smart Contractscited by 1
  5. 2023ZeroSwap: Data-driven Optimal Market Making in DeFicited by 0
  6. 2026RAmmStein: Regime Adaptation in Mean-reverting Markets with Stein Thresholds -- Optimal Impulse Control in Concentrated AMMscited by 0
  7. 2026Optimal Adaptive Market Making: A Theoretical Framework for High-Yield Liquidity Provision in Perpetual Futures Marketscited by 0
  8. 2026Concentrated Liquidity Provision: a Reinforcement Learning Perspectivecited by 0
  9. 2026Artificial Intelligence in Equity and Crypto Markets: Progress, Profitability Evidence, and the Limits of Automated Investingcited by 0
  10. 2026Zero-Storage Procedural Neural Synthesis via Boundary Dynamics: Formal Verification in Lean 4 and Bare-Metal Gauntlet Validationcited by 0