Impermanent Loss in Uniswap v3

Loesch, Stefan; Hindman, Nate; Richardson, Mark B.; Welch, Nicholas

doi:10.48550/arxiv.2111.09192

Cited by 7 publications

(9 citation statements)

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“…Running on blockchain gives advantages over centralised exchanges: transparency, pseudonymity, censorship resistance and security, see references in e.g. [16]. However blockchain-based CFMs suffer from a number of problems: namely questionable returns for LPs as has been already mentioned as well as traders (liquidity takers) being front-run by miners (known as miner-extractable-value) [8], [10].…”

Section: Literature Reviewmentioning

confidence: 99%

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: Literature Reviewmentioning

confidence: 99%

Inefficiency of CFMs: hedging perspective and agent-based simulations

Cohen¹,

Vidales²,

Šiška³

et al. 2023

Preprint

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“…A recent report presented by Loesch et al [23] makes a first attempt at analyzing the returns of real Uniswap V3 liquidity positions and concludes that around 50% of liquidity positions are losing money. However, their report has several shortcomings.…”

Section: Related Workmentioning

confidence: 99%

Risks and Returns of Uniswap V3 Liquidity Providers

Heimbach,

Schertenleib,

Wattenhofer

2022

Preprint

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Trade execution on Decentralized Exchanges (DEXes) is automatic and does not require individual buy and sell orders to be matched. Instead, liquidity aggregated in pools from individual liquidity providers enables trading between cryptocurrencies. The largest DEX measured by trading volume, Uniswap V3, promises a DEX design optimized for capital efficiency. However, Uniswap V3 requires far more decisions from liquidity providers than previous DEX designs.In this work, we develop a theoretical model to illustrate the choices faced by Uniswap V3 liquidity providers and their implications. Our model suggests that providing liquidity on Uniswap V3 is highly complex and requires many considerations from a user. Our supporting data analysis of the risks and returns of real Uniswap V3 liquidity providers underlines that liquidity providing in Uniswap V3 is incredibly complicated, and performances can vary wildly. While there are simple and profitable strategies for liquidity providers in liquidity pools characterized by negligible price volatilities, these strategies only yield modest returns. Instead, significant returns can only be obtained by accepting increased financial risks and at the cost of active management. Thus, providing liquidity has become a game reserved for sophisticated players with the introduction of Uniswap V3, where retail traders do not stand a chance. KEYWORDSblockchain, decentralized exchange, constant product market maker, liquidity provider 1 We focus on the financial risks stemming from price fluctuations and analyze them using historical data. Other risk, e.g., risks related to the protocol, are not considered.

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“…Since the Summer of 2020, the Uniswap protocol has awarded over $1.1 billion USD in transaction fees to liquidity providers [18]. However, historically, liquidity providers have lost more in Impermanent Loss than they have received in fees [12], where Impermanent Loss is defined as the difference between the value of the Liquidity Position and the value of holding initially equal amounts of each asset. The net value of a liquidity position is directly dependent on the price of the underlying cryptocurrencies in the pool.…”

Section: Motivationmentioning

confidence: 99%

“…If the final price of 𝑎 in terms of 𝑏 is less than the lower price of the liquidity position range, then only 𝑎 tokens will remain as all 𝑏 tokens would be swapped for 𝑎 tokens (as the price crosses the lower tick). An AMM sells the outperforming asset in exchange for the underperforming asset [12]. Let 𝑛 0 be the portfolio notional.…”

Section: Lemma B: Final Token Amounts In Terms Of Pricementioning

confidence: 99%

Delta Hedging Liquidity Positions on Automated Market Makers

Khakhar¹,

Chen²

2022

Preprint

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Liquidity Providers on Automated Market Makers generate millions of USD in transaction fees daily. However, the net value of a Liquidity Position is vulnerable to price changes in the underlying assets in the pool. The dominant measure of loss in a Liquidity Position is Impermanent Loss. Impermanent Loss for Constant Function Market Makers has been widely studied. We propose a new metric to measure Liquidity Position PNL based on price movement from the underlying assets. We show how this new metric more appropriately measures the change in the net value of a Liquidity Position as a function of price movement in the underlying assets. Our second contribution is an algorithm to delta hedge arbitrary Liquidity Positions on both uniform liquidity Automated Market Makers (such as Uniswap v2) and concentrated liquidity Automated Market Makers (such as Uniswap v3) via a combination of derivatives.

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Impermanent Loss in Uniswap v3

Cited by 7 publications

References 0 publications

Inefficiency of CFMs: hedging perspective and agent-based simulations

Inefficiency of CFMs: hedging perspective and agent-based simulations

Risks and Returns of Uniswap V3 Liquidity Providers

Delta Hedging Liquidity Positions on Automated Market Makers

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