Quantifying Loss in Automated Market Makers

Milionis, Jason; Moallemi, Ciamac C.; Roughgarden, Tim; Zhang, Anthony Lee

doi:10.1145/3560832.3563441

Cited by 15 publications

(17 citation statements)

References 6 publications

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“…Assumption 1 holds in the case when the fee (1 − γ) = 0 and arbitrageurs continuously close the gap between S t and the price of the CFM, as demonstrated in [17]. Hence we expect the the arbitrage-free fee derived below to be a good proxy for CFMs that charge small fee (e.g Uniswap).…”

Section: Model and Assumptionsmentioning

confidence: 88%

“…We will proceed to derive an arbitrage-free fee bound in a similar way to the construction of the predictable loss in [17], and to classical arguments for no-arbitrage pricing in financial markets.…”

Section: Model and Assumptionsmentioning

confidence: 99%

“…This is our Theorem 1. This is complementary perspective to that of loss versus rebalancing (LVR) introduced in [17].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Inefficiency of CFMs: hedging perspective and agent-based simulations

Cohen¹,

Vidales²,

Šiška³

et al. 2023

Preprint

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We investigate whether the fee income from trades on the CFM is sufficient for the liquidity providers to hedge away the exposure to market risk. We first analyse this problem through the lens of continuous-time financial mathematics and derive an upper bound for not-arbitrage fee income that would make CFM efficient and liquidity provision fair. We then evaluate our findings by performing multi-agent simulations by varying CFM fees, market volatility, and rate of arrival of liquidity takers. We observe that, on average, fee income generated from liquidity provision is insufficient to compensate for market risk.

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Section: Model and Assumptionsmentioning

confidence: 88%

Section: Model and Assumptionsmentioning

confidence: 99%

See 1 more Smart Citation

Inefficiency of CFMs: hedging perspective and agent-based simulations

Cohen¹,

Vidales²,

Šiška³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Whenever an arbitrageur interacts with an AMM pool, say at time t with reserves (R x,t , R y,t ), we assume as in [10] that the arbitrageur always moves the pool reserves to a point which maximizes arbitrageur profits, exploiting the difference between P (R x,t , R y,t ) and the external market price at time t, denoted t . In this paper, we consider only the subset of CFMMs in which, given the LVR extracted in block B t+1 corresponds to reserves (R x,t+1 , R y,t+1 ), P (R x,t+1 , R y,t+1 ) = t+1 .…”

Section: Constant Function Market Makersmentioning

confidence: 99%

An AMM minimizing user-level extractable value and loss-versus-rebalancing

McMenamin¹,

Daza²

2023

Preprint

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We present V0LVER, an AMM protocol which solves an incentivization trilemma between users, passive liquidity providers, and block producers. V0LVER enables users and passive liquidity providers to interact without paying MEV or incurring uncontrolled loss-versusrebalancing to the block producer. V0LVER is an AMM protocol built on an encrypted transaction mempool, where transactions are decrypted after being allocated liquidity by the AMM. V0LVER ensures this liquidity, given some external market price, is provided at that price in expectancy. This is done by providing just enough loss-versus-rebalancing profits to the block producer, incentivizing the block producer to move the pool price to the external market price. With this, users transact in expectancy at the external market price in exchange for a fee, with AMMs providing liquidity in expectancy at the external market price. Under block producer and liquidity provider competition, all of the fees in V0LVER approach zero. Without block producer arbitrage, V0LVER guarantees fall back to those of an AMM capable of processing encrypted transactions, free from loss-versus-rebalancing or user-level MEV.

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“…[26] analyze the risk profile of LPs and discuss differences in the presence of concentrated liquidity. [27] propose a decomposition of the LP returns into an instantaneous market risk component and a predictable component, which they term as "loss-versusrebalancing". [28] analyze the returns of LPs of Uniswap V2 pools and study the movement of liquidity between pools.…”

Section: Related Workmentioning

confidence: 99%

Decentralized Exchanges: The Profitability Frontier of Constant Product Market Makers

Bitterli¹,

Schär²

2023

Preprint

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In this paper we analyze constant product market makers (CPMMs). We formalize the liquidity providers' profitability conditions and introduce a concept we call the profitability frontier in the xyk-space. We study the effect of mint and burn fees on the profitability frontier, consider various pool types, and compile a large data set from all Uniswap V2 transactions. We use this data to further study our theoretical framework and the profitability conditions. We show how the profitability of liquidity provision is severely affected by the costs of mint and burn events relative to the portfolio size and the characteristics of the trading pair.

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Quantifying Loss in Automated Market Makers

Cited by 15 publications

References 6 publications

Inefficiency of CFMs: hedging perspective and agent-based simulations

Inefficiency of CFMs: hedging perspective and agent-based simulations

An AMM minimizing user-level extractable value and loss-versus-rebalancing

Decentralized Exchanges: The Profitability Frontier of Constant Product Market Makers

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