Analyzing MEV Instances on Solana — Part 3
Maximum Extractable Value (MEV) represents a fundamental concept in cryptoeconomics, highly affecting permissionless blockchains. MEV is the consequence of the design of protocols and brings with it bad and good externalities. Indeed, not all MEV can be considered benign as some represent an invisible tax on the user, e.g. check out one of our previous articles — Solana MEV Outlook. In general, MEV can also be an incentive for consensus instability, see e.g. the time bandit attack. However, considering all types of MEV as bad externalities is wrong. There exist benign forms of MEV that ensure protocol efficiency, and one prominent example is arbitrage. Let’s imagine that some user swaps a huge amount of token A on a specific AMM (huge with respect to the total amount in the pool) and that this transaction creates a $5,000 arbitrage opportunity. All users that swap tokens in the same pool and same direction will see their output lowered with respect to the actual value. Thus, whoever exploits this MEV opportunity will also bring the market back to parity with the true price. This will make the AMM more efficient without harming its users in the process.
On Solana, MEV still represents a dark forest since no one has pointed a flashlight at it. This is because Solana is a much younger blockchain compared to Ethereum, which can be seen in the lack of products like Flashbots. One project that is moving in this direction is Jito Labs, which recently delivered the first MEV Dashboard for Solana representing an explorer aimed at illuminating MEV — see here for an introduction. However, it is not the only one trying to fulfill this duty. Pointing lights on some Solana Decentralized Exchanges (DEXs) in order to illuminate the dark forest is one of the key objectives at Chorus One. MEV is a consequence that will be a crucial factor for the future of PoS networks and we are continually looking for the best way to ride it. You can explore our Solana MEV dashboard here.
It is important to understand that a simple copy of Flashbots may not be good for Solana, since it represents a drastically different network from Ethereum — and Jito seems to be something intrinsically different. In this article, we are going to assess what are the MEV challenges Solana faces. We’ll also review the status of our internal research regarding MEV.
In Section 2, we’ll analyze the current and future status of MEV on Solana, with a detailed analysis of what we found on-chain in Section 2.1.
In Section 3, we’ll discuss some implications of the current MEV strategies and how these can affect the functionality of a PoS network.
Section 2: Current and Future Status of MEV on Solana
MEV has a specific supply chain, which “describes the chain of activity which helps users transform intentions into finalized state transitions in the presence of MEV ”. However, despite this “universal” definition, MEV on Proof of Stake (PoS) networks is drastically different from what it represents on Proof of Work (PoW) networks. This is for several reasons. For sure, the most important difference relies on the possibility of knowing for sure that a validator will propose a block at some point. Further, validators have delegators and can offer to them a portion of the MEV revenue (e.g. lowering the commission) attracting users to delegate with them. This makes MEV on PoS networks a growing business model, which constitutes one of the building blocks for cryptoeconomic incentives. From one side, we have validators who can use MEV revenue to reduce commission rate — even go to negative values — by returning all incomes to the delegators. On the other side, we have incentives for Layer-1 (L1) blockchains to improve network performance. This is because, if the “scaling problem” is solved by the introduction of L2s, the MEV and transaction (txs) fees are also moved away from the main chain, weakening the L1 business model.
This is exactly what blockchains like Ethereum are facing right now, representing one of the great risks over the next few years. See this Twitter thread for a better understanding of the topic.
But, what is the current status of MEV on Solana? Let’s start from the beginning. Solana does not have a public mempool, meaning that some bad externalities of MEV are very difficult to achieve. However, Solana is not free from them since MEV extraction may produce a bad performance of the network, e.g. spam txs, dropped txs, etc. Indeed, some MEV opportunities only exist if searchers run their own validator, inspect txs that come to them, and run an MEV-extraction code on top of it. Having a high stake and getting access to more MEV opportunities is not an easy task. This dramatically reduces the likelihood of being highly profitable, as the distribution of MEV revenues averages around zero, with a tail towards higher values — see Fig. 2.2.
Note that this is obtained in a specific time window, so it is only representative of the shape of the actual distribution.
Since txs fees on Solana are low and MEV opportunities can bring validators more profit, validators are incentivized to auction off their block space to searchers, or at least some rumors are pointing towards this possibility.
Further, on Solana, fees are currently fixed and cheap, meaning that if there is high competition in a specific market, users face the risk of not getting transactions executed. Since a gas-fee auction is still missing, currently MEV searchers spam transactions to the leader (and following validators in the leader schedule) in the hopes of “winning the battle”.
Lastly, on Solana, MEV competition may incentivize validators to perform denial of service (DoS) attacks on other validators in order to leave the spotted MEV opportunities just there, sitting on the table where they are until the attacker can extract them.
The current status of MEV indicates how bad the problem of blockspace-waste is, which resulted in degraded performance for normal users. At the time of writing, according to what can be found on Jito’s MEV dashboard, we have 12,072,328 successful arbitrages against the 350,179,786 unsuccessful ones in 6 months (i.e. a 3.3% of success rate). If we also include liquidations, the success rate goes down to roughly 3%. The total extracted “good” MEV is around $33M. Of course, this is only a lower-bound since MEV can be created any time a user interacts with a blockchain, and smart contracts enable a functionally infinite number of potential interactions. Thus, it is computationally infeasible to calculate a blockchain’s total potential MEV by brute force. Further, we have some previous analyses that show how a huge amount was extracted during periods of stressful market conditions, e.g. $13M MEV during Wormhole Incident and $43M Total MEV from Luna/ UST Collapse on Solana.
Future Solana improvements aim to introduce several features, forcing current MEV strategies to change. Introducing these new features represents a two-sided coin for MEV searchers. Indeed, some spamming bots would be forced to shut down since the local fee market will make it unprofitable to massively spam txs. However, improving the network means more and more users are attracted to use it. This has the immediate consequence of also increasing the total amount of MEV, allowing the chain of implications to continue by incentivizing competition around MEV and “inviting” new searchers to step in.
Section 2.1: Pool congestion assessment
One of the main problems that can worsen an AMM’s functionality is pool congestion. This is because if there are too many txs happening on a specific pool, users may experience a worse trade due to pool unbalancing. This is why arbitraging is a sort of service that normalizes DEXs functionality. But, despite the fact that we know MEV is happening on Solana, where are the greatest opportunities? In other words, what are the DEXs with the highest pool congestion, and who is “solving” it? To answer these questions, we built an MEV dashboard on Dune Analytics. This is because, by looking at the exchanged volume, — using Solscan — you can definitely have an idea of where the congestion is, but nothing is clear when the question is if searchers are solving for it.
Our preliminary research shows that in 10 days (from July 16th to July 26th), the paths with the highest extracted MEV on Solana were live on Orca and Raydium with a lower bound of 20,775 USD extracted, see Fig. 2.5. There were 68 MEV extractors on these cross DEXs during the analyzed period, thus not a great number in terms of competition. Fig. 2.6 shows how the extracted revenues are concentrated among a few searchers. Precisely, 5 different accounts extracted 80.1% of the total MEV.
It is worth mentioning that none of the studied DEX combinations show a uniform distribution in terms of MEV opportunities, according to what we show in Fig. 2.2.
If we extend the analysis by looking at the USDC Token Accounts belonging to the most profitable MEV searchers, we have that 7 accounts were able to extract 95.6% of total extracted MEV, see Fig. 2.7. Two of them, GjT…m2P and G9D…y2m, interact with the same smart contract, which may indicate that these two accounts belong to the same user. Since these accounts are in the top 7 accounts, this means that it is likely that only 6 users were able to extract 95.6% of the total extracted MEV.
By deep diving, we also found two accounts interacting with a smart contract with clear reference to Jito, Jito…HoMA, with a total extracted MEV in 10 days of 3,342.30 USDC (at time of writing), over a total of 158,132 USDC extracted — i.e. 2.1% of the total amount.
Section 3: Challenges for securing MEV
We already stated that, on PoS networks, MEV can be seen as a business model since validators can share a portion of the extracted amount with their delegators. However, as shown in Sec. 2.1, this sometimes can constitute a deal that does not truly mean high returns. MEV revenues are strongly correlated with market conditions and DEXs’ usage, meaning that we’re unable to estimate a fixed income to share with delegators. Further, if competition does not grow fast, the promise of sharing revenue with delegators may bring a centralization problem.
To assess this statement, let’s try to formulate a “gedanken-experiment”. Imagine that the volume exchanged by DEXs on Solana grows by a factor 30, and assume that there is only one validator extracting MEV and redistributing the revenues to delegators. The implication of the increased volume is that MEV also increases. Indeed, a factor of 30 means that in 30 days the DEX’s volume on Solana is greater than $30B, and assuming that the 0.04% of it is MEV — as it happens on Ethereum — this means more than $144M yearly. The implication of having only one validator playing this game is that the extracted amount also increases, making the delegation to them an appealing deal. We can just think that a validator with ~2% of the total stake can extract an MEV of ~ $2.9M yearly. Once the delegation starts to concentrate around a single validator — the sole player — again we have a boost in MEV revenues, since the leader schedule is “stake-dependent” on Solana. This is because the revenue per block is not uniformly distributed, so a higher stake means an increased likelihood of capturing a rare juicy opportunity, pushing up the median of the extracted MEV. If there is no competition, this gedanken-experiment has a single outcome: concentration of stake — i.e. centralization.
Risks become higher if one considers that at the moment Solana is one of the fastest blockchains and that future development aims to improve this even further. The high number of processed txs per second could pave the way for prop firms to enter the market, meaning that more SOL can be delegated to a single validator — the winner of the MEV war.
This, without any doubt, points toward the necessity of building competitive validators for what regards MEV extraction. Once Jito delivers its third-party client for Solana that’s been optimized for efficient MEV extraction (plus its bundle), the risk of centralization can be mitigated. However, even with decentralized block building, as Flashbots aims to achieve with MEV-boost, we remain still far from a definitive solution. Indeed, such an environment makes it easier for builders to buy the blockspace of all validators and thereby isolate the centralization to the builder layer, see e.g. here. At the moment a decentralized MEV from top to bottom is a chimera. The first step toward this direction would require open-sourcing the MEV-extracting validator, starting collaboration between many validators, in the true spirit of open source. Indeed, it is worth noting that adopting validator products developed — and belonging — to a single entity reduces the problem of stake concentration, but can decrease the network’s censorship resistance. If block production is centralized to a single entity, that may represent an enormous censorship risk, regardless of how many validators participate.
For example, let’s assume that this entity gets adopted by 50% of the stake. Suppose now that this entity is regulated by a specific government, which demands that all transactions are blocked. Then, at best, users would need to get their transactions into the other blocks, but in the worst case, this entity can refuse to include vote transactions that vote on blocks that contain sanctioned transactions. This is a simple example that shows how some MEV strategy outcomes could pave the way for censorship risks.
Before concluding, it is worth mentioning that other possibilities do exist. One of them is to frame MEV-extraction as a service, where it is the protocol itself that takes the MEV and shares the corresponding revenue with protocol-token stakers, see e.g. recent rumors on Osmosis development. Despite this “method” seeming to be less prone to a centralization risk, it remains unclear if the time needed to extract MEV is enough to guarantee the AMM functionality — remember that poor competition means some opportunities may remain there for a “long” time. The outcome is the difficulty of assessing all the details of how this will affect the future of the chain.
This article aims to collect some thoughts on how framing MEV may affect the future of PoS ecosystems, focussing on some of its “bad” consequences. Despite the fast development around this huge and complex topic, we at Chorus One are continuously researching this topic with an eye to the future: the healthiness of all networks is always our first priority.
If you’re interested in framing the topic and require research/advisory services on MEV, you can contact our Research Team at email@example.com