This article is extracted from the Q1 2024 Quarterly Insights. To read the full report, please visit https://chorus.one/reports-research/quarterly-network-insights-q1-2024
Ethena is a project that has recently captured significant attention, driven not only by their fundraising announcement in February but also by the early April launch of their governance token, $ENA. However, it is their product called USDe, that lies at the heart of ongoing debates and discussions. Described by the Ethena team as a 'synthetic dollar', a concept originally proposed by Bitmex, USDe has emerged as a focal point of discussion within the crypto community. While USDe may indeed be perceived as an innovative product, it's essential to acknowledge that all innovation carries inherent risks that must be carefully evaluated. This piece aims to explain how Ethena operates, including the mechanisms behind USDe and sUSDe, while also examining market dynamics and potential vulnerabilities in the case of black swan scenarios. The goal is to provide readers with comprehensive insights to better understand Ethena’s mechanisms.
When reviewing the official documentation, one will find the following passages:
Ethena is a synthetic dollar protocol built on Ethereum that provides a crypto-native solution for money not reliant on traditional banking system infrastructure, alongside a globally accessible dollar denominated instrument - the 'Internet Bond'.
and
Ethena's synthetic dollar, USDe, provides the crypto-native, scalable solution for money achieved by delta-hedging Ethereum and Bitcoin collateral. USDe is fully-backed (subject to the discussion in the Risks section regarding events potentially resulting in loss of backing) and free to compose throughout DeFi.
Understanding USDe isn't necessarily straightforward for everyone, as it necessitates some basic understanding of trading strategies and derivative products. What Ethena is doing with USDe is a cash and carry trade, which is a concept very well known in TradFi.
In this specific scenario, Ethena's objective in executing a cash and carry trade is to use spot assets as collateral to open a short position with a perpetual futures contract linked to the same underlying assets. That way, the position is delta-hedged and Ethena capitalizes on positive funding rates, ultimately distributing profits between USDe stakers (those who hold sUSDe tokens) and an insurance fund.
For those not familiar with the concept of perpetual futures contracts and delta hedging/delta neutral strategies, let’s define the concepts.
Perpetual futures contracts were popularized by BitMEX and are crypto derivatives that allow users to trade long or short positions with leverage if they want to. The concept is similar to traditional Futures Contracts but without an expiration date or settlement. Traders can maintain their positions indefinitely, with a funding mechanism ensuring that the contract's price stays closely tied to the spot price of the underlying asset.
A Delta Neutral strategy is a strategy that aims to minimize directional risk by keeping a position's delta at zero. To achieve delta neutrality, traders typically offset the delta of one position with the delta of another position in such a way that any gains or losses from price movements are balanced out.
This strategy is popular among professional traders and market makers to hedge against market direction. Ethena uses this strategy to keep USDe stable around $1 without being affected by market movements.
Let’s take a look at a concrete example:
Let’s take the example of stETH. We assume stETH is trading at par(1 stETH = 1 ETH) with the price of ETH at $3000. If the price of ETH increases by 10% from $3000 to $3300, here's what will happen:
Note: If the stETH/ETH pair experiences a depeg, it could potentially result in a liquidation event, which may cause USDe to no longer be backed by $1 worth of collateral.
Therefore, the total P&L of the position would be:
Total P&L = $300 + staking yield - 300 + funding rate
The generalized formula would be:
Total P&L = (Δa+Σ pk) + (Гb+ f)
Δ = rate of change of position a
a = collateral
p = additional parameters related to asset a (example: staking yield)
Г = rate of change of position
bf = funding rate
To conclude this part, we can argue that USDe is not a stablecoin. Ethena’s USDe represents a tokenized, delta-hedged strategy. It’s a pioneering concept that offers decentralized access to a hedge fund’s strategy.
A. The USDe total supply
There are exclusively two ways to acquire USDe, depending on whether one is a whitelisted participant (a market maker for example) or not. The methods vary as follows:
1) Minting: A whitelisted entity decides to mint USDe by selecting a backing asset (like stETH) and entering the amount to use for minting. Then, the backing asset is swapped against the agreed amount of USDe that is newly minted.
Note: This method is exclusively available for whitelisted entities.
2) Buying though a liquidity pool: A user decides to buy USDe via the Ethena dApp and can exchange different sorts of stablecoins for USDe, which are available in liquidity pools from protocols such as Curve. This transaction done via the Ethena UI, is routed using MEV protection through CowSwap.
At the time of writing, the total supply of USDe is 2,317,686,500 USDe in circulation. The evolution of the cumulative supply can be seen on the dashboard below:
As we can see, USDe has experienced steady growth from February until early April, and then has stagnated for most of the months of April and May.
The largest daily inflow occurred on April 2nd, with 232,176,843 USDe minted. This corresponds to the launch of the $ENA governance token and its associated airdrop.
On the contrary, the largest outflow occurred on April 13th, with 19,514,466 USDe removed from circulation. This happened during a sell-off triggered by the Bitcoin halving and the fact that funding turned negative during that short period of time.
To redeem USDe, only addresses whitelisted by the Ethena Protocol are eligible. These whitelisted addresses typically belong to entities such as market makers or arbitrageurs. For non-whitelisted addresses, the only way to exit is by selling USDe in liquidity pools, which can lead to a depegging event, similar to what occurred mid-April 2024 and May 2024.
In these specific scenarios, whitelisted addresses capitalize on this arbitrage opportunity by buying USDe on-chain and redeeming the collateral to realize profits.
B. Ethena’s collateral
Whitelisted addresses have the ability to generate USDe by providing a range of collateral options, including BTC, ETH, ETH LSTs, or USDT. Below is the current allocation of collateral held by Ethena:
This allocation is split between CEXs for executing a cash and carry trade, with some portion remaining unallocated.
The purpose of USDT is to purchase collateral and establish a delta-hedged position. However, there is currently a lack of publicly available information regarding the frequency of swaps, the trading process, and allocation specifics. Similar to a traditional hedge fund, this aspect appears to be at the discretion of the team, which makes this process opaque.
C. USDe, sUSDe and Insurance Fund
USDe could be seen as a claim over Ethena’s collateral. Users provide collateral (BTC, ETH, etc.) and receive USDe in exchange, while Ethena delta hedges the collateral to ensure that 1 USDe should be worth $1 of Ethena collateral (factoring the execution costs). Therefore, USDe could be seen as a notice debt, in which if you decide to reclaim the collateral, users should be able to redeem it. USDe could be seen as a claim over Ethena’s collateral, users provide a collateral (BTC, ETH etc), and receive in exchange USDe which delta collateral the collateral to ensure that 1 USDe should be worth $1 of Ethena collateral (magnus execution cost). Therefore, USDe could be seen as a debt or a 'repayment commitment' from Ethena Labs, wherein USDe holders can redeem Ethena’s collateral.
However, even if considered a debt, holding USDe does not offer any yield. To earn yield on USDe, users can either:
In the second case, USDe has to be staked in order to receive the yield which comes from two sources:
Yield is not paid directly to sUSDe holders; rather, it accumulates within the staking contract, resulting in the "value" of sUSDe rising over time. The relationship between sUSDe and USDe is as follows:
sUSDe:USDe ratio = Total sUSDe supply / Total USDe staked + total protocol yield deposited
At the time of writing, 1 sUSDE = 1.058 USDe
What is surprising is when we look at the data, it seems like only a few portion of USDe holders are staking their USDe to earn a yield.
The portion of 370,127,486 sUSDe represents 391,594,880 USDe with a ratio of 1.058.
Out of the 2,317,686,500 USDe in circulation, only 391,594,880 are staked and generating yield. This represents only 16.8% of the supply that is staked and generates yield.Why wouldn't the remaining 83.2% stake to get the yield? This is because of the Sats Campaign.
Ethena is currently running a SATS campaign that incentivizes USDe holders not to stake by giving them SATS, which would result in additional incentives in ENA by locking USDe, holding it, or providing USDe liquidity into diverse protocols.
Therefore, Ethena is using the ENA tokens as incentives to prevent USDe holders from staking it. Why is that? Because of the Insurance Fund.
The Insurance Fund is a safety measure created by the Ethena team to have a reserve for use in case of events such as negative funding rates (which we will discuss later in this article). The Insurance Fund can be track in the following address.
Which represents a total of more than $39 million. Part of Ethena’s strategy is to use ENA to incentivize USDe holders not to stake in order to fill in the insurance fund and prepare in case of a bad scenario. This sets the stage for the next part, in which we will discuss some of the intrinsic risks related to the protocol.
Note: Since the publication of this article, the number of sUSDe in circulation has significantly increased. This is due to the fact that the insurance fund now has a fairly large treasury, as well as the increase in the caps for sUSDe on Pendle.
A. Negative funding rates
One of the most well-known risks of Ethena’s architecture is probably the risk of funding rates turning negative. As explained in the first part, Ethena is taking a short perpetual position to delta-hedge the spot collateral. If the funding rates turn negative (indicating more people are on the short side than the long side), there is a risk that the protocol starts losing money.
There are two mechanisms in place to mitigate losses coming from negative funding rates:
The Insurance Fund steps in when the negative funding rate > the collateral yield.
Based on Ethena’s analysis, there has only been one quarter in the last 3 years where the average sum yield was negative, and this data was polluted by the ETH PoW arbitrage period, which was a one-off event that dragged funding deeply negative.
However, it’s important to mention that past data is not necessarily a representation of the future. As of May 13, 2024, Ethena represents 14% of the total Open Interest on ETH, and approximately 5% of the total open interest on BTC.
If Ethena continues to grow, there is a chance that it will start representing too significant a portion of the total open interest to be known to be on the short side, leading to a natural decrease in funding rates and potentially experiencing negative funding rates more often due to the protocol becoming too large for the market.
If this scenario happens, Ethena will be forced at some point to cap USDe supply in order to adapt to the total open interest. Otherwise, Ethena would shoot itself in the foot.
B. The Liquidity Crunch
This is somewhat related to the negative funding rates mentioned earlier. When negative funding rates occur, there is a sell-off, as shown here:
We can notice that funding rates started to be more frequent on some specific exchanges between mid-April and mid-May. This has been translated into some periods of USDe depegs, with an inflow of USDe probably explained by whitelisted entities taking advantage of that depeg, and a USDe total supply not really growing.
The only way for non-whitelisted people to exit from USDe is to sell on the market, which will create a depeg. This will be captured by the whitelisted entities. If a depeg happens, whitelisted entities will buy USDe at a discount to redeem collateral by giving back USDe, therefore reducing the USDe circulating supply and capturing the profits.
This is an easy way for whitelisted entities to capture profits.
Example:
With negative funding rates, some people decide to exit USDe and sell on a DEX. USDe is now trading at $0.8. Whitelisted actors will buy USDe at $0.8 and redeem USDe against BTC or ETH for $1 worth of assets, then sell the collateral to capture $0.2 of profits (factoring the execution cost).
Things become more complex when they have to deal with ETH LSTs; this is where the liquidity crunch can happen. Ethena currently has 14% of its total collateral in ETH LSTs, which at the time of writing, represents around $324 million. It is not detailed which assets are held within the LSTs category, therefore we will assume it’s mostly stETH.
Let’s now imagine a scenario where all native assets such as ETH and BTC have been redeemed by whitelisted actors, and Ethena now only has ETH LSTs as collateral.
Funding rates turn negative again, there is a sell-off of USDe, and whitelisted actors start redeeming USDe against ETH LSTs. Different scenarios can happen, we will present three main scenarios below:
Scenario 1: Whitelisted entities are directly selling the ETH LSTs on the market, capturing some profits but also reducing the arbitrage opportunity if more and more actors do so, as the ETH/ETH LSTs pair will start depegging.
This scenario can happen initially, and some traders will take advantage of the ETH/stETH depeg to buy stETH at a discount and unstake to get ETH. This will start impacting the exit/unstaking queue, leading to negative consequences in other scenarios.
Scenario 2: Whitelisted entities decide to unstake the ETH LSTs to get ETH and simultaneously open a short perp position on ETH to delta hedge and mitigate the risk associated with the token price.
They then wait for the exit queue to end, get the native ETH, close the short perp position, and profit.
If the funding rates are negative, the whitelisted actor might not engage in this arbitrage and redeem the collateral because it depends on how negative the funding rates are and how long the exit queue is.
If the exit queue is too long and funding rates are too negative to make that trade profitable, then actors who don’t want exposure to the asset price won’t take that trade. This would leave USDe depegged and trigger a bank run, with more and more people selling their USDe on the market.
If USDe starts depegging and remains that way, Ethena’s insurance fund will also take a significant hit, mostly due to the negative funding rates and the fact that a portion of the insurance fund is in USDe.
Of course, all these scenarios would only occur in a situation of a very extreme event. However, if such a scenario were to happen, non-whitelisted USDe holders would suffer the most, as their only way of exit would be to sell USDe. At least, changing this model by offering the redemption feature to everyone could improve the situation. In any case, if Ethena were to become big enough, this could lead to significant unstaking events, thereby impacting Ethereum's economic security.
If an attacker sees that most of Ethena's collateral is in ETH LSTs, they can choose to borrow USDe, sell it heavily on liquidity pools to break the peg, allow the first whitelisted actors to arbitrage and begin increasing the unstaking queue, and then keep selling massively USDe to start a bank run.
That's why it's important for Ethena not to grow too large and to ensure that the collateral in ETH LSTs is also capped.
C. The Execution risk
Holding USDe also involves trusting the Ethena team to execute the cash and carry trade effectively. Unfortunately, there isn't much information available about how this trade is executed. After reviewing the official documentation, there is no information provided about the trading team or how frequently this trade occurs. For example, there is currently $109.5 million of unallocated collateral in USDT, which will be used for the cash and carry trade, but no information on when those trades will be executed.
This is a review of the hidden risks associated with Ethena that users should be aware of. Of course, there are many more traditional risks related to the protocol, such as smart contract risks, custodial risks, or exchange risks. The Ethena team has done a great job of mentioning these traditional risks here.
In conclusion, the goal of this article was to explain what Ethena is, show the various mechanisms behind the protocol and its innovations, while also outlining the associated risks. Users of a protocol should be aware of their exposures and act accordingly, there is no free lunch in the market, and Ethena presents multiple risks that should be taken into account before engaging with the protocol.
About Chorus One
Chorus One is one of the biggest institutional staking providers globally, operating infrastructure for 50+ 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. We are a team of over 50 passionate individuals spread throughout the globe who believe in the transformative power of blockchain technology.
The following article is a summary of a recent ETHResearch contribution by Chorus One Research, which describes a bug we've encountered in mev-boost, the standard software validators used to solicit blocks from sophisticated, specialized entitites called builders on Ethereum. This bug is not specific to Chorus One; it can affect all Ethereum validators running mev-boost.
To read the full paper, please visit: https://chorus.one/reports-research/mev-boost-withdrawal-bug
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Chorus One runs a proprietary version of mev-boost, dubbed Adagio, which optimizes for mev capture by optimizing latency. Our commitment to Adagio obligates us to have an in-depth understanding of mev-boost and Ethereum's PBS setup in general. As such, we decided to dive deeper, and to make our findings available to the Ethereum community.
In practice, mev-boost facilitates an auction, where the winning builder commits to paying a certain amount of ETH for the right to provide the block that the validator proposing the next slot ("proposer") will include. This amount then accrues to an address provided by the validator, referred to as the "fee recipient".
Proposers and builders do not communicate directly, but exchange standardized messages via a third party called a "relay". The relay can determine the amount paid for a block by comparing the balance of the fee recipient at certain fixed times in the auction.
We have observed that in instances where the block in question coincidentally includes reward withdrawals due to the fee recipient, the relay has been unable to separate these withdrawals from the amount paid by the builder. This leads to an inflated value for the auction payment. This inaccuracy can negatively reflect on the Ethereum network under its current economic model (EIP-1559). Specifically, it may decrease the amount of transactions processed and decrease the amount of ETH burned, thus manifesting a small but measurable negative net outcome for the network overall.
For a deep dive, please visit: https://chorus.one/reports-research/mev-boost-withdrawal-bug
About Chorus One
Chorus One is one of the biggest institutional staking providers globally operating infrastructure for 50+ 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.
Throughout 2023, Chorus One maintained its standing as one of the select few node operators to consistently deliver in-depth research reports, wherein our dedicated in-house research team delves into the latest developments in the crypto and staking world.
Edition #4 of our 2023 Reflections series recaps Chorus One’s significant research efforts in 2023. Dive in!
This year, Chorus One introduced a major research effort, fueled by a grant from dYdX, that examines the implications of Maximum Extractable Value (MEV) within the context of dYdX v4 from a validator's perspective.
This comprehensive analysis presents the first-ever exploration of mitigating negative MEV externalities in a fully decentralized, validator-driven order book.
Additionally, it delves into the uncharted territory of cross-domain arbitrage involving a fully decentralized in-validator order book and other venues.
Dive in: https://chorus.one/reports-research/mev-on-the-dydx-v4-chain#
We present a comprehensive analysis of the implications of artificial latency in the Proposer-Builder-Separation framework on the Ethereum network. Focusing on the MEV-Boost auction system, we analyze how strategic latency manipulation affects Maximum Extractable Value yields and network integrity. Our findings reveal both increased profitability for node operators and significant systemic challenges, including heightened network inefficiencies and centralization risks. We empirically validate these insights with a pilot that Chorus One has been operating on Ethereum mainnet.
Dive in: https://chorus.one/reports-research/the-cost-of-artificial-latency-in-the-pbs-context
TL;DR: https://chorus.one/articles/timing-games-and-implications-on-mev-extraction
We published a whitepaper comparing key characteristics of Ethereum and Solana, which explores the block-building marketplace model, akin to the "flashbots-like model," and examines the challenges of adapting it to Solana.
Additionally, recognizing Solana's unique features, we also proposed an alternative to the block-building marketplace: the solana-mev client. This model enables decentralized extraction by validators through a modified Solana validator client, capable of handling MEV opportunities directly in the banking stage of the validator. Complementing the whitepaper, we also shared an open-source prototype implementation of this approach.
Dive in: https://chorus.one/reports-research/breaking-bots-an-alternative-way-to-capture-mev-on-solana
Every quarter, we publish an exclusive report on the events and trends that dominated the Proof-of-Stake world. Check out our Quarterly reports below, with a glimpse into the topics covered in each edition.
Titles covered:
Read it here: https://chorus.one/reports-research/quarterly-network-insights-q1-2023
Titles covered:
Read it here: https://chorus.one/reports-research/quarterly-network-insights-q2-2023
Titles covered:
Read it here: https://chorus.one/reports-research/quarterly-network-insights-q3-2023-2024
If you have any questions, would like to learn more, or get in touch with our research team, please reach out to us at research@chorus.one
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.
Today, our research team published a study on ethresear.ch, delving into the impact of latency (time) on MEV extraction. More specifically, we demonstrate the costs associated with introducing artificial latency within a PBS (Proposer-Builder Separation) framework. Additionally, we present findings from Adagio, an empirical study that explores the implications of latency optimization aimed at maximizing MEV capture.
In late August 2023, we launched Adagio, a latency-optimized setup on the Ethereum mainnet. The primary objective was to collect actionable data ethically, with minimal disruptions to the network. Until this point, Adagio has not been a client-facing product, but an internal research initiative running on approximately 100 self-funded validators. We initially shared ongoing results of the Adagio pilot in our Q3 Quarterly Insights report in October.
In alignment with our commitment to operational honesty and rational competition, this study discloses the full results of Adagio, alongside an extensive discussion of node operator incentives and potential adverse knock-on effects on the Ethereum network. As pioneers in MEV research, our primary objective is to address and mitigate existing competitive dynamics by offering a detailed analysis backed by proprietary data from our study, which will be explored further in the subsequent sections of this article.
This article offers a top-level summary of our study, contextualizing it within the ongoing Ethereum community dialogue on ethically optimizing MEV performance. We dive into the key findings of the study, highlighting significant observations and results. Central to our discussion is the exploration of the outcomes tied to the implementation of the Adagio setup, which demonstrates an overarching boost in MEV capture.
Ultimately, we recognise that node operators are compelled and incentivised to employ latency optimization as a matter of strategic necessity. As more operators take advantage of this inefficiency, they set a higher standard for returns, making it easier for investors to choose setups that use latency optimization.
This creates a cycle where the use of latency optimization becomes a standard practice, putting pressure on operators who are hesitant to join in. In the end, the competitive advantage of a node operator is determined by their willingness to exploit this systematic inefficiency in the system.
Additionally, we demonstrate that the parameters set by our Adagio setup corresponds to an Annual Percentage Rate (APR) that is 1.58% higher than the vanilla (standard) case, with a range from 1.30% to 3.09%. Insights into these parameters are provided below, with additional clarity available in the original post.
Let’s preface this section with the phrase - Right Place at the Right Time.
Delightfully analogous to the quote above, we’re adding further insights to the overarching discourse on the implication of latency optimization (i.e, a strategy where block proposers intentionally delay the publication of their block for as long as possible to maximize MEV capture) when it has become a burning topic within the Ethereum community, drawing increased attention from various stakeholders concerned about its network implications.
Yet, despite its growing significance, there has been a noticeable lack of empirical research on this subject. As pioneers in MEV research, we've been investigating this concept for over a year, incorporating latency optimization as one of our MEV strategies from the outset. Now, we're proud to contribute to the ongoing discussions and scrutinize the most significant claims with robust, evidence-based research.
In a previous article about Chorus One’s approach to MEV, we emphasized the importance of exploring the dynamics between builders, relays, and validators with the dimension of time.
Our focus on how latency optimization can profoundly influence MEV performance remains unchanged. However, we've identified a crucial gap in empirical data supporting this concept. Compounding this issue, various actors have advocated for methods to increase MEV extraction without rigorous analysis, resulting in inflated values based on biased assumptions. Recognizing the serious consequences this scenario poses in terms of centralization pressure, we now find it imperative to conduct a deep dive into this complex scenario.
Our strategy involves implementing a setup tailored to collect actionable data through self-funded validators in an ethical manner, ensuring minimal disruptions to the network. This initiative is geared toward addressing the existing gap in empirical research and offering a more nuanced understanding of the implications of latency optimization in the MEV domain.
The key objectives of this research is three-fold, including:
In the following section, we will present a comprehensive overview of the three most pivotal and relevant observations from the study, and as promised earlier, we will also delve into the results of Adagio.
Context: First, we delve into PBS inefficiencies and MEV returns.
Here, we explore the inefficiencies in the Proposer-Builder Separation (PBS) framework, showing how timing in auctions can be strategically exploited to generate consistent, excess MEV returns.
Additionally, we demonstrate how all client-facing node operators are incentivized to compete for latency-optimized MEV capture, irrespective of their voting power.
Key Finding: Latency optimization is beneficial for all client-facing node operators, irrespective of their size or voting power.
Using an empirical framework to estimate the potential yearly excess returns for validators who optimize for latency considering factors like the frequency of MEV opportunities, network conditions, and different latency strategies, our results indicate that node operators with different voting powers have varying levels of predictability in their MEV increases.
The above figure demonstrates that higher voting power tends to result in more predictable returns, while lower voting power introduces more variance. The median weekly MEV reward increase is around 5.47% for a node operator with 13% voting power and 5.11% for a node operator with 1% voting power.
The implication here is that big and small node operators cater to different utilities of their clients (delegators) because they operate at different levels of risk and reward. As a result, optimizing for latency is beneficial for both small and large node operators. In simpler terms, regardless of their size, node operators could consider optimizing latency to better serve their clients and enhance their overall performance.
As we look at a longer timeframe, the variability in rewards for any voting power profile is expected to decrease due to statistical principles. This means that rewards are likely to cluster around the 5% mark, regardless of the size of the node operator.
In practical terms, if execution layer rewards make up 30% of the total rewards, adopting a latency-aware strategy can boost the Annual Percentage Rate (APR) from 4.2% to 4.27%. This represents a noteworthy 1.67% increase in overall APR. Therefore, this presents a significant opportunity, encouraging node operators to adopt strategies that consider and optimize for latency.
Context: Second, we discuss the costs of introducing artificial delays, explaining how it increases MEV rewards but at the expense of subsequent proposers.
Key Finding: MEV tends to benefit node operators with higher voting power, giving them more stable returns. When these operators engage in strategic latency tactics, it can increase centralization risks and potentially raise gas cost and faster burnt ETH for the next proposer..
While sophisticated validators benefit from optimized MEV capture with artificial latency, the broader impact results in increased gas costs and a faster burning of ETH for the next proposers. The Ethereum network aims to maximize decentralization by encouraging hobbyists to run validators, but the outlined risks disproportionately affect solo validators. Below, we demonstrate that these downside risks are significant in scale, and disproportionately impact solo validators.
Figure 2 illustrates that introducing artificial latency increases the percentage of ETH burned, potentially reducing final rewards. Even a small increase in burnt ETH can significantly decrease rewards, especially for smaller node operators who are chosen less frequently to propose blocks. The negative impact is most significant for solo validators, making them less competitive on overall APR and subject to greater income variability. Large node operators playing timing games benefit from comparatively higher APR at lower variance to the detriment of other operators.
MEV tends to benefit node operators with higher voting power, giving them more stable returns. When these operators engage in strategic latency tactics, it can increase centralization risks and potentially raise gas fees for the entire Ethereum network. Moreover, larger node operators, due to their size, have access to more data, giving them an edge in testing strategies and optimizing latency.
In this scenario, node operators find it necessary to optimize for latency to stay competitive. As more operators adopt these strategies, it becomes a standard practice, creating a cycle where those hesitant to participate face increasing pressure. This results in an environment where a node operator's success is tied to its willingness to exploit systematic inefficiencies in the process.
Context: In late August 2023, Chorus One launched a latency-optimized setup — internally dubbed Adagio — on Ethereum mainnet.
Its goal was to gather actionable data in a sane manner, minimizing any potential disruptions to the network. Until this point, Adagio has not been a client-facing product, but an internal research initiative running on approximately 100 self-funded validators. We are committed to both operational honesty and rational competition, and therefore disclose our findings via this study.
In simple terms, this section analyzes the outcomes of our Adagio pilot, focusing on how different relay configurations affect the timing of bid selection and eligibility in the MEV-Boost auction.
Our pilot comprises four distinct setups, each representing a variable (i.e. a relay) in our experiment:The Benchmark Setup, The Aggressive Setup, The Normal Setup, and the Moderate Setup.
Key Findings: The results of this pilot indicate that the timing strategies opted by node operators used within relay operations have a significant impact on how competitive they are.
The aggressive setup, in particular, allows non-optimistic relays to perform similarly to optimistic ones. This means that certain relays can only effectively compete if they introduce an artificial delay.
In extreme cases, a relay might not be competitive on its own, but because it captures exclusive order flow, node operators might intentionally introduce an artificial delay when querying it or might choose not to use it at all. Essentially, these timing strategies play a crucial role in determining how relays can effectively participate and compete in the overall system.
These results offer valuable insights into how strategically introducing latency within the relay infrastructure can impact the overall effectiveness and competition in the MEV-Boost auction. The goal is to level the playing field among different relays by customizing their latency parameters.
The above graph displays the eligibility time of winning bids in the Adagio pilot compared to the broader network distribution. As expected, Adagio selects bids that become eligible later with respect to the network distribution. Notably, our setup always selects bids eligible before 1s, reducing the risks of missed slots and increased number of forks for the network.
Finally, it’s worth mentioning that our results indicate that certain setups are more favorable to winning bids. This opens up the possibility for relays adopting latency optimization to impact their submission rate.
Bringing together the data on latency optimization payoff and the results of our Adagio pilot allows us to quantify the expected annual increase of validator-side MEV returns.
The simulation results presented in Fig. 4 show that, on average, there is a 4.75% increase in MEV extracted per block, with a range from 3.92% to 9.27%. This corresponds to an Annual Percentage Rate (APR) that is 1.58% higher than the vanilla (standard) case, with a range from 1.30% to 3.09%.
The increased variability in the range is mainly due to the limited voting power in the pilot, but some of it is also caused by fluctuations in bid eligibility times. The observed median value is 5% lower than the theoretically projected value. To address this difference, the approach will be updated to minimize variance in bid selections and keep eligibility times below the 950ms threshold.
Let’s take a moment to consolidate the key takeaways derived from our study and the Adagio setup.
Since inception, Chorus One has recognised the importance of MEV and spearheaded the exploration of the concept within the industry. From establishing robust MEV policies and strategies, receiving a grant from dYdX for investigating MEV in the context of the dYdX Chain to conducting empirical studies that investigate the practical implications of factors influencing MEV returns, we've consistently taken a pioneering role. Our dedication revolves around enhancing the general understanding of MEV through rational, honest, and practical methods.
For comprehensive details about our MEV policies, work, and achievements, please visit our MEV page.
If you’d like to learn more, have questions, or would like to get in touch with our research team, please reach out to us at research@chorus.one.
If you want to learn more about our staking services, or would like to get started, please reach out at staking@chorus.one
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.
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