Profitability of Liquidity Provision on Automated Market Makers: An Empirical Analysis of Arbitrage Losses and Trading Fees

Alapfogalmak

Liquidity provision on major Uniswap AMM pools often fails to generate sufficient trading fee revenue to compensate for losses incurred to arbitrageurs, with Uniswap v2 pools performing better than their v3 counterparts. Faster blockchain block times can significantly reduce these arbitrage losses.

Kivonat

The paper presents a comprehensive empirical study on the profitability of liquidity provision on automated market makers (AMMs), focusing on the largest Uniswap v2 and v3 pools.
Key findings:

In most of the largest Uniswap liquidity pools, the historical earnings from trading fees are smaller than the losses incurred to arbitrageurs, questioning the sustainability of the high liquidity currently provided.
However, some less-traded token pools on Uniswap v3 are found to be profitable, with fees exceeding arbitrage losses.
Remarkably, Uniswap v2 pools perform significantly better than their v3 counterparts when comparing fees to arbitrage losses, even for pools with the same trading fee.
The relationship between arbitrage losses and blockchain block times varies across trading pairs. Reducing block times from Ethereum's current 12 seconds to 100ms can decrease arbitrage losses by 20-70%, depending on the pair.
The paper builds on the concept of "loss-versus-rebalancing" (LVR) to quantify the profitability of liquidity provision, comparing historical trading fee earnings to simulated arbitrage losses. The results provide insights into the sustainability of AMM liquidity and the potential benefits of design choices like faster block times to mitigate arbitrage losses.

Statisztikák

The paper analyzes historical trading data from Uniswap v2 and v3 pools, as well as price data from the Binance exchange.
Some key data points:

The most-traded Uniswap v3 WETH-USDC 5bp pool sees fees covering only around 80% of arbitrage losses on average.
In contrast, the less-traded MATIC-ETH and LINK-ETH Uniswap v3 pools have fees exceeding arbitrage losses by up to 50%.
Uniswap v2 pools, even with the same 0.3% trading fee as some v3 pools, have fees around 3 times higher than arbitrage losses.
Reducing block times from Ethereum's 12 seconds to 100ms can decrease arbitrage losses by 20-70%, depending on the trading pair.

Idézetek

"Remarkably, we identify a higher profitability among less capital-efficient Uniswap v2 pools compared to their Uniswap v3 counterparts."
"We observe notable variations in the manner of decline of arbitrage losses across different trading pairs. For instance, when comparing 100ms block times to Ethereum's current 12-second block times, the decrease in losses to arbitrageurs ranges between 20% to 70%, depending on the specific trading pair."

Főbb Kivonatok

Measuring Arbitrage Losses and Profitability of AMM Liquidity

by Robin Fritsc... : arxiv.org 04-10-2024

https://arxiv.org/pdf/2404.05803.pdf

Mélyebb kérdések

What factors beyond trading fees and arbitrage losses, such as market risk or capital efficiency, might influence liquidity providers' decisions to allocate capital to AMM pools

Liquidity providers' decisions to allocate capital to AMM pools are influenced by various factors beyond trading fees and arbitrage losses. One crucial factor is market risk, which refers to the uncertainty of financial loss due to adverse market movements. Liquidity providers assess the market risk associated with providing liquidity in AMM pools, considering factors such as price volatility, slippage, and impermanent loss. Higher market risk can deter liquidity providers from allocating capital to pools with significant price fluctuations, as it increases the likelihood of incurring losses.
Another factor that influences liquidity providers' decisions is capital efficiency. Liquidity providers seek to maximize their returns while minimizing their capital exposure. AMM pools that are more capital-efficient allow providers to achieve higher returns on their capital, as they can generate more trading fees with less capital locked in the pool. Providers may prefer pools that offer higher capital efficiency to optimize their profitability and overall return on investment.
Additionally, considerations such as the token pair being traded, the volume of trading activity, and the overall liquidity depth of the pool can also impact liquidity providers' decisions. Pools with high trading volumes and deep liquidity are more attractive to providers as they offer more opportunities to earn fees and mitigate risks associated with low liquidity. The popularity and demand for specific token pairs can also influence providers' choices, as they may prefer pools that align with market trends and investor preferences.

How might the design of AMM mechanisms, beyond just block times, be improved to better align the incentives of liquidity providers and arbitrageurs

Improving the design of AMM mechanisms beyond block times is essential to better align the incentives of liquidity providers and arbitrageurs. One approach is to implement dynamic fee structures that adjust based on market conditions and liquidity levels. By dynamically setting fees, AMMs can incentivize liquidity provision during periods of high volatility or low liquidity, ensuring that providers are adequately compensated for the risks they undertake.
Furthermore, introducing mechanisms that incentivize long-term liquidity provision, such as yield farming programs or liquidity mining incentives, can encourage providers to commit their capital for extended periods. By offering additional rewards or governance tokens for sustained liquidity provision, AMMs can attract more providers and enhance the overall liquidity depth of the pools.
Moreover, enhancing transparency and providing tools for risk management can empower liquidity providers to make informed decisions. AMMs can offer detailed analytics on market trends, risk exposure, and historical performance to help providers assess the potential risks and rewards of participating in liquidity provision. By equipping providers with the necessary information and risk management tools, AMMs can foster a more sustainable and mutually beneficial ecosystem for both providers and arbitrageurs.

Given the varying relationships between arbitrage losses and block times across trading pairs, what insights could be gained by studying the underlying market dynamics and microstructure that drive these differences

Studying the underlying market dynamics and microstructure that drive the varying relationships between arbitrage losses and block times across trading pairs can provide valuable insights into the efficiency and effectiveness of AMM mechanisms. By analyzing factors such as liquidity depth, trading volume, price movements, and arbitrage opportunities, researchers can gain a deeper understanding of how different market conditions impact the profitability of liquidity provision.
For instance, examining the impact of market volatility on arbitrage losses and block times can reveal how providers can adjust their strategies to mitigate risks during turbulent market conditions. Understanding how liquidity providers respond to changing market dynamics and adjust their positions in response to arbitrage opportunities can shed light on the resilience and adaptability of AMM mechanisms.
Furthermore, studying the correlation between block times and arbitrage losses across various trading pairs can help identify optimal block time intervals that minimize losses and maximize efficiency. By analyzing the relationship between block times and arbitrage profitability for different pairs, researchers can develop insights into the optimal design parameters for AMMs that enhance liquidity provider returns and overall system performance.