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Automated Market Making and Loss-Versus-Rebalancing

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Is a
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Academic paper
0

Academic Paper attributes

arXiv ID
2208.060460
arXiv Classification
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Quantitative finance
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Publication URL
arxiv.org/pdf/2208.0...46.pdf0
Publisher
ArXiv
ArXiv
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DOI
doi.org/10.48550/ar...08.060460
Paid/Free
Free0
Academic Discipline
Mathematics
Mathematics
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Mathematical finance
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Portfolio Management
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Quantitative finance
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Submission Date
August 11, 2022
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September 22, 2022
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June 23, 2023
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November 27, 2023
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Author Names
Anthony Lee Zhang0
Tim Roughgarden0
Jason Milionis0
Ciamac C. Moallemi0
Paper abstract

Automated market making (AMM) protocols such as Uniswap have recently emerged as an alternative to the most common market structure for electronic trading, the limit order book. Relative to limit order books, AMMs are both more computationally efficient and do not require the participation of active market making intermediaries. As such, AMMs have emerged as the dominant market mechanism for trust-less decentralized exchanges (DEXs). We develop a model the underlying economics of AMMs from the perspective of their passive liquidity providers (LPs). Our central contribution is a Black-Scholes formula for AMMs. Like the Black-Scholes formula, we consider the return to LPs once market risk has been hedged. We identify the main adverse selection cost incurred by LPs, which we call loss-versus-rebalancing (LVR, pronounced lever). LVR captures costs incurred by AMM LPs due to stale prices that are picked off by better informed arbitrageurs. In a continuous time Black-Scholes setting, we are able to derive closed-form expressions for this adverse selection cost, for all automated market makers, including constant function market makers and those featuring concentrated liquidity (e.g., Uniswap v3). Qualitatively, we highlight the main forces that drive AMM LP returns, including asset characteristics (volatility) and AMM characteristics (curvature/marginal liquidity). Quantitatively, we illustrate how our models expressions for LP returns match actual LP returns for the Uniswap v2 WETH-USDC trading pair. Our model provides tradable insight into both the ex ante and ex post assessment of AMM LP investment decisions. LVR can also inform the design of the next generation of DEX market mechanisms – in fact, in the short time since our work has been released, LVR mitigation has already emerged as the dominant challenge among practitioners in the AMM protocol designer community.

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