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.
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.
To estimate the PNL, we built a Dune Analytics dashboard, where we consider the USDC/ETH pool with 0.05% fees.
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.
Chorus One is proud to introduce our new 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.
This paper, marking a significant milestone in exploring MEV dynamics, identifies factors that influence undesirable MEV extraction, and proposes concrete strategies to level the playing field in derivative trading by counteracting such behavior.
dYdX v4 signifies a transformative phase in the evolution of the dYdX protocol. It embraces a fully decentralized derivatives exchange built on a central limit order book (CLOB). Unlike previous iterations, which combined smart contracts with centralized services, v4 employs a decentralized off-chain order book and a high-performance matching engine. This architecture, powered by the CometBFT consensus and Cosmos SDK, strives to achieve scalability alongside decentralization while allowing community-driven protocol development.
This transition signifies a substantial shift, as v4 introduces the industry's first truly decentralized perpetual futures exchange. Validators will manage the order books, with meticulous steps taken to ensure fair and trustless trading through effective negative MEV mitigation.
Set against the backdrop of this pivotal upgrade, our paper serves a crucial purpose by shedding light on the complexities of mitigating bad MEV on dYdX v4, thus equipping the community with the resources needed to navigate the upcoming transition. By providing comprehensive insights, our analysis aids in anticipating the impact of MEV on the new chain and trading experience, as well as the wider Cosmos ecosystem, ultimately fostering informed decision-making.
Our analysis uncovers pivotal insights that reverberate across the ecosystem:
Finally, our research extends beyond insights to practical solutions for mitigating validator-driven MEV risks. We propose that such MEV might manifest through partnerships between trading firms and market makers, favoring those with established advantages. We underscore the risks associated with harmful MEV, including asymmetric risk for delegators. Even in optimistic scenarios, potential revenue from partnerships may not fully offset these risks. To address this, we suggest a combination of measures including potential penalties and flexible unbonding periods for re-delegation to ethical actors, aiming to effectively manage validator-driven MEV risks.
At Chorus One, we leverage a sophisticated and ethical set of MEV strategies to optimize our validators' performance and continuously monitor progress. Backed by in-house experts and extensive research, we deploy various infrastructural solutions such as relay optimization, latency games, and investing in robust machines to improve our MEV performance. Learn more about Chorus One's winning MEV strategies by reading our recent blog.
For a comprehensive exploration of our research on MEV implications within dYdX v4, we invite you to read the full research paper here.
About Chorus One
Chorus One is one of the biggest institutional staking providers globally operating infrastructure for 40+ 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.
The staking economy is a thriving industry, offering over $12 billion in rewards, with $600 million attributed to Maximal Extractable Value (MEV). At Chorus One, we deeply recognize the significance of MEV for both validators and investors, which has fueled our commitment to continuously optimize our infrastructure to ideally integrate with the Ethereum MEV pipeline.
MEV serves as a gateway for validators to maximize the value extracted from transactions within a block. As early as 2019, the research paper "Flash Boys 2.0," authored by Ari Juels and Lorenz Breidenbach, shed light on its real-world impact, particularly in decentralized exchanges and user experiences. The cumulative value of MEV extracted on Ethereum alone surpassed $78 million in early 2021 and has skyrocketed to an astonishing $600 million in 2023.
MEV has become a cornerstone of Chorus One's research efforts. As one of the earliest and most influential contributors to MEV research, we conduct in-house studies and experiments to optimize MEV yield. Notably, we were commissioned by dYdX to produce an in-depth report on MEV within dYdX v4, and released the first public tracker of (pre-protorev) MEV on Osmosis (@chorusonemev). Furthermore, we have developed a customized version of the Solana client to capture MEV opportunities on the Solana network.
To achieve the highest possible MEV yield, employing effective infrastructure strategies is paramount. At Chorus One, we conduct a series of experiments to identify the most efficient combination of strategies, aiming to optimize our MEV performance. Below, we delve into the fundamentals of MEV extraction, exploring the solutions we implement to improve our performance.
In general, MEV empowers block producers to rearrange, include, or exclude transactions, providing advantages that can impact users. However, there is a subtle distinction in how MEV operates on Ethereum compared to other blockchain networks.
On Ethereum, the process involves a 'block builder' constructing the block, which is then passed on to a 'relay' before being proposed by a validator. This Proposer-Builder Separation (PBS) introduces a separation between the block producer and the proposer. As an Ethereum validator, Chorus One focuses on optimizing MEV rewards by fine-tuning our interaction with relays.
Conversely, on most other chains, validators themselves build the block and have the freedom to prioritize transaction sorting to maximize MEV rewards.
We continuously optimize our infrastructure to capture the highest possible MEV rewards.
The following graph illustrates our performance over a 60-day period. Over this time period, Chorus One nodes have captured close to 14% more MEV rewards per validator (ETH) when compared to the weighted industry average, observed on Lido.
*Please note that this is a snapshot, and that MEV rewards fluctuate as a function of variance and market conditions. Please visit Rated Network to view the latest figures.
This process of continuous infrastructure optimization highlights the significance of employing a combination of well-established best practices to achieve higher MEV rewards. By utilizing specific methods in tandem, validators can effectively maximize their MEV yield. More on this below.
Before diving into Chorus One's approach, we briefly explore the process of extracting MEV. It involves key players with distinct roles:
Block Producers: They create blocks of transactions on the blockchain, deciding which transactions to include and their order.
Relays: A relayer is an entity responsible for checking blocks before passing them to the block producers. The relay confirms the builder blocks for validity and estimate the MEV-related value of each block. By tweaking how block producers/validators interface with relays, they can add value by optimizing MEV rewards.
Searchers: These individuals or automated bots constantly monitor the blockchain, searching for profitable opportunities to manipulate transaction order and earn additional profits through MEV.
DApps and Protocol Developers: Decentralized applications (DApps) and the developers who create rules for block producers support MEV extraction. DApps create opportunities for MEV extraction through their design, while protocol developers establish rules that enable block producers to capture MEV.
In simpler terms, block producers create blocks,relays check the blocks, searchers seek ways to profit by manipulating transaction order, and DApps and protocol developers provide the framework and incentives for MEV extraction.
Validators often employ similar solutions to increase rewards and actively seek optimization opportunities. For instance, MEV-Boost, an implementation of proposer-builder separation (PBS) developed by Flashbots for Ethereum, enables validators to maximize staking rewards by selling block space to builders in an open market.
MEV-Boost is free, open-source, and neutral software designed to democratize MEV while minimizing associated negative implications, such as consensus-layer security risks, centralization, or the risk of searchers going rogue. For more information on MEV-Boost software, visit https://boost.flashbots.net.
MEV plays a significant role in yield generation on networks like Ethereum, and as a result, our nodes are MEV-boost enabled by default.
With a team of in-house experts, we continuously adjust our infrastructure to optimally integrate with the Ethereum MEV pipeline.
1. Relay Selection
Relays are crucial intermediaries in the MEV extraction process, acting as trusted connectors between block builders and validators. Their primary role is to facilitate seamless data exchange and ensure the selection of the most lucrative bids for validators. We continuously conduct experiments to identify the optimal combination of relays (as shown in the relay market dashboard below) , aiming to establish efficient communication and achieve the highest valid bid submission to validators.
Our approach: By carefully selecting the best relays, we enable our validators to receive winning bids from all connected relays.
2. Latency Games
Exploring the dynamics between builders, relays, and validators is even more interesting with a new dimension: time.
Latency, the delay in data transmission, has gained significant importance for relays and the entire MEV supply chain, leading to notable consequences. It acts as a centralizing force within the MEV supply chain, with relays having shorter latency likely to be more successful in auctions. This preference encourages builders to prioritize sending their blocks to those relays.
Our approach: We optimize our connection to relays when requesting blocks by prioritizing payoff and minimizing the probability of a missed slot.
3. Infrastructure Optimization
On the infrastructure and hardware front, we prioritize optimizing the performance of our validators. Through the strategic selection of hardware, geographical distribution, and client implementation, we ensure that our infrastructure operates at its peak efficiency. This optimization enhances the rewards generated for our customers.
Our approach: We are actively investing in and expanding our infrastructure to further elevate performance and rewards.
TL;DR: More rewards, more revenue.
Through our unique solutions and ongoing research, we continuously push the boundaries to enhance the rewards obtained through MEV. Today, our MEV-boost enabled nodes capture significantly higher APR on staked ETH, surpassing the yield of the average validator.
To learn more about our approach to MEV, visit: https://chorus.one/mev-maximum-extractable-value
To stake with Chorus One, reach out to staking@chorus.one and we'll get back to you.
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.
