Decentralized Finance (DeFi) is a profound paradigm shift, redefining how the world engages with financial services. At its center, open liquidity provisioning allows for seamless decentralized trading,lending, and more complex financial strategies. In contrast to traditional finance, centralized intermediaries are not required as liquidity providers, instead, users are empowered to bootstrap liquidity.
Automated Market Makers (AMMs) - see e.g. Uniswap - allow anyone to contribute assets to pools and thus facilitate trading. Users are compensated with a share of trading fees, and potentially,idiosyncratic incentives added by parties benefiting from liquidity (e.g. a project issuing a token). AMMs are simple - users may provide liquidity over the entire price range, or for a specific pricing interval.
DeFi composability and the absence of asset custody by intermediaries push market participants to opt for AMMs over centralized exchanges (CEXs). AMMs have the potential to outperform centralized exchanges in terms of liquidity provision (G. Liao and D. Robinson).
Conversely, Decentralized Exchanges (DEXs) driven by a Central Limit Order Book (CLOB) - see e.g. dYdX v4 - demand a substantial pool of assets and ample order book depth for smooth operation. A CLOB is adept at consolidating liquidity around the market price and has the flexibility to adjust quotes as needed.
However, the process of actively matching buy and sell orders to connect traders is complex and rewards sophistication. Market makers in CLOB-based DEXs must consistently update their positions to prevent their orders from becoming stagnant. This dynamic nature of CLOBs, while offering powerful tools for price discovery, also renders liquidity provision a more intricate endeavor. This complexity is particularly pronounced for those traders who may not have access to real-time market data, as remaining profitable in such an environment requires a deep understanding of market dynamics and order flow.
AMMs and decentralized CLOBs are the dynamic engines driving the DeFi ecosystem. For Liquidity Providers (LPs) navigating the DeFi landscape, a central challenge looms – adverse selection, as extensively explored in J. Milionis et al for AMMs and U. Natale et al for CLOBs. This article delves deep into these mechanisms, highlighting challenges and opportunities facing LPs. We’ll zoom in on Uniswap v3, the most widely used AMM, to explore the complexities and potential solutions in this dynamic landscape. In the final section, we argue that staking, specifically with a validator optimizing for MEV, is a way of recouping potential losses.
Uniswap is the leading DEX by volume with $1.5 trillion in lifetime volume since its 2018 debut (cfr. DefiLlama), and over $1 trillion alone processed by Uniswap v3 (H. Adams et al). Central to its operation is the concept of concentrated liquidity (CL), empowering LPs to offer assets within specific price ranges. LPs facilitate the smooth flow of assets and liquidity, making the success of these AMMs critically dependent on LPs participation, who provide liquidity in exchange for trading fees.
For LPs participating in AMMs, the primary challenge is adverse selection, cfr. J. Milionis et al. This issue arises because parties with access to real-time market prices can exploit price discrepancies between AMMs and other platforms. These transactions often involve arbitrage between CEXs and DEXs. To succeed in capitalizing on price disparities, individuals need not only priority access to the first few on-chain transactions in a block (T. Gupta et al) but also the ability to execute high-quality trades on CEX. This transaction flow between different venues forms the backbone of efficient AMM trading, however, it can have adverse effects on LPs via adverse selection.
In U. Natale et al, we evaluate how pricing on dYdX v4 could be impacted by the presence of another CLOB with higher liquidity, for a given asset - e.g. on a CEX. However, it's important to note that this platform is not live at the moment. This means that making an exact comparison of the profitability of professional Market Makers in a decentralized order book like dYdX v4 is currently unfeasible. Consequently, for the remainder of our analysis, our primary focus will be on Uniswap v3, where Concentrated Liquidity presents opportunities and challenges worth exploring.
Estimating the effective profit & loss (PNL) for a LP has been a subject of extensive study in literature. One widely debated estimator, frequently discussed in the context of the profitability of ETH/USDC LPs on Uniswap v3, revolves around markouts, as outlined in a series of medium articles by Ambient finance, formerly known as CrocSwap. However, it's crucial to highlight that markouts, as an estimator, may not present a holistic view of LP profitability on Uniswap v3.
This is because markouts typically overlook the genuine liquidity and the precise price range within the pool. Consequently, they may overlook changes in the value of the numéraire within the pool, focusing solely on the risky asset's fluctuations. The omission of these critical factors can significantly impact the accuracy of LP profitability assessments.
In order to avoid possible biases in the analysis, we decided to use an estimator that is dependent on the actual variation in pool value, see here for the description of the mathematical framework.
The picture above shows the final Pool’s PNL since the beginning of the year, which corresponds to a general gain of around $35M. Let’s observe that, to achieve this figure, we need to consider the total TVL as capital deployed for the strategy. At current TVL of $206.59M, this corresponds to a 16.9% gain, instead, by considering the maximum historical TVL (~$320M) the total gain since the beginning of the year is around 10% of the capital deployed.
If we focus on the PNL from pool value variation, i.e. no fees, we can see how the overall gain is primarily driven by accrued fees. Indeed, the adversarial selection produced - at time of writing - a loss of $400k, with a maximum loss of ~$1M in May.
If we compare with the ETH price movement during the same time period, we can see that this effect is primarily driven by the movement in ETH price.
More precisely, this is an effect related to price volatility, as shown in Milionis et al. Indeed, when price volatility sharply increases, the price discrepancy between Uniswap v3 and other venues also increases, amplifying the MEV size. The two plots below show the pool value variation due to Toxic Flow and the correlation between pool value from toxic flow and spikes in volatility (24h Moving Average). Here by Toxic Flow we indicate all the transactions coming from informed traders that generate a negative PNL for the LPs. Given the nature of DEXs, informed traders aim to include their transactions in the top part of the block (we used the first 10 txs in the block) to avoid price movements due to market activity.
Before concluding this section, it's worth mentioning that, despite the PNL of $35M due to the accrued fees, being competitive and effectively implementing a strategy that generates a positive PNL is a complex undertaking. This is because there are sophisticated LPs, and the accrued fees need to be divided among all participants. Barriers to entry include access to highly performant price feeds and pricing models, as well as optimized execution. Furthermore, the previous estimator considers the PNL from the pool value, inherently assuming that the entity deploying the strategy has infinite capital that can be allocated each time the price moves. If we utilize the estimator defined in Eq. (8) of this document, we can illustrate how an LP with a fixed initial amount deployed in the liquidity provision strategy experiences a PNL of -30% (without accounting for the fees), as demonstrated below.
Additionally, by updating the positions every minute, the LP accumulates a total gas cost of $2M since the beginning of the year. It's important to note that this cost can be hedged with solutions like Alkymia, in which Chorus One has invested.
We have seen how LPs, who diligently provide liquidity, may face losses as arbitrageurs exploit price differences between centralized and decentralized platforms. Staking represents a strategic approach for LPs to recapture a portion of the extracted MEV. This is particularly advantageous when LPs choose validators that are actively working to optimize MEV yields, like Chorus One (see previous chapter). By aligning their staked assets with validators who specialize in maximizing MEV yields, LPs can amplify their returns while bolstering their resilience against the challenges of adverse selection.
This endeavor is not about exploiting MEV at the expense of the ecosystem but rather about recapturing it for the benefit of those who contribute to the DeFi landscape. Maximizing MEV yields is a way to ensure that the value generated from the MEV ultimately flows back to the stakers, aligning incentives and fostering a fairer and more rewarding DeFi ecosystem. Moreover, the staked amount can be thoughtfully hedged against price fluctuations using external sources, creating a comprehensive strategy to safeguard LPs' investments and enhance their gains.
In summary, LPs, who play a pivotal role in DeFi liquidity provision, can employ a multifaceted strategy combining liquidity provision, staking, and hedging to mitigate the impacts of adverse selection and recapture a portion of the extracted MEV. By making strategic choices in validator selection and actively managing their positions, LPs can navigate the complexities of the DeFi landscape and emerge as resilient and profitable participants.
About Chorus One
Chorus One is one of the biggest institutional staking providers globally operating infrastructure for 45+ Proof-of-Stake networks including Ethereum, Cosmos, Solana, Avalanche, and Near amongst others. Since 2018, we have been at the forefront of the PoS industry and now offer easy enterprise-grade staking solutions, industry-leading research, and also invest in some of the most cutting-edge protocols through Chorus Ventures.