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Distribution of MEV Surplus

The Impact of MEV Surplus Distribution - Galaxy Ventures

Who captures MEV? Who should capture MEV?

Before Ethereum’s transition to proof-of-stake (PoS), Miner Extractable Value (MEV) was primarily captured by searchers and miners. Today, on Ethereum, network stakeholders known as builders and validators compete alongside searchers for MEV revenue. In the future, there will be even more participants fighting over MEV. This begs a few questions: How is MEV currently distributed between participants? What is the total size of the MEV pie today? What will the total MEV market and its distribution look like going forward? 

Stylized view of where values go in a transaction - diagram

MEV is Endemic

MEV is the surplus value extracted from blockchain systems. As long as there is value transacting through a permissionless system, there is MEV. For example, if a trader sets too high of a slippage setting, a searcher can sandwich their transaction. In this case, the searcher captures MEV at the trader's expense. To explore the factors that shape MEV, it is essential to have a taxonomy that understands the growth and declines of distinct MEV segments. 

High level taxonomy of MEV.
High level taxonomy of MEV.

Although MEV often has negative connotations, MEV can feed into the ecosystem's health. MEV can create incentive alignment for the system’s actors. For instance, without searcher liquidations and arbitrage running between venues, protocols would accrue bad debt, and users would face larger spreads, receiving worse execution onchain.

Observable MEV is The Tip of The Iceberg

While calculating MEV’s Total Addressable Market (TAM) is challenging, we estimate the lower bound of annual MEV extracted from Ethereum is between $300M - $900M, based on estimates from various data providers [1].

This MEV TAM is the summation of value lost by MEV. For example, if a transaction is worth 100 units of value and the user only ends up with 90 units of value, 10 units of value is leaked to MEV. In practice this is calculated by identifying MEV transactions (e.g., arbitrages, sandwiches, or liquidations) then determining searcher revenue. This number can be further split into searcher profit, builder profit, and net new money to validators.

Mental model of MEV’s TAM, not to scale - diagram

However, we would estimate that the true MEV TAM is larger than the $300M - $900M spread, and that the 2022 MEV TAM could exceed a billion dollars. Calculating MEV’s true TAM is difficult since MEV analytics are best at identifying MEV that follow predictable or deterministic patterns, such as arbitrages, sandwiches, and liquidations. This does not capture the long tail of MEV with NFTs and other DeFi applications, hence the real TAM is actually larger than the estimates. Today, market participants are increasingly sophisticated as they compete with each other. For example, off-chain hedging cannot be tracked, Multiblock MEV is challenging to identify, and probabilistic MEV is almost impossible to detect.

2022 to early 2023 MEV TAM per observable strategy of arbitrages, liquidations, and sandwiches from EigenPhi - chart

Validators Capture the Majority of MEV

The status quo is that validators (also known as proposers or block producers) capture the majority of Observed MEV. Over time, we have seen profitability shift from searchers to validators and recently back to searchers. Revenue compression is especially apparent for sandwiches and liquidations, as these types of MEV opportunities are highly competitive. Searchers must bid most of their expected value to block producers to ensure transaction inclusion.

Daily Distribution of MEV Surplus - chart

However, validators may be taking a smaller slice in practice as the Total MEV is much greater than the Observed MEV. Additionally, the universe of Unobserved MEV tends to be less competitive. Therefore, searchers will not have to bid as much for transaction inclusion.

Who Will Capture MEV in the Future?

Who Will Capture MEV in the Future? - table

The standard today is that three parties capture MEV – block producers, searchers, and builders. However, there is a prevailing narrative that MEV originators, often the transaction originators, should get rebated for the MEV they generate. MEV-Share is a recent instantiation of this philosophy, where searchers can bid on order flow from users, wallets, and/or dApps. Ultimately, there are market dynamics that drive how much senders get rebated for the MEV they generate and how MEV surplus value is distributed between different market participants. But there is a philosophical question that asks what is the optimal split between MEV originator vs. searchers vs. other parties.

MEV-Aware Apps Will Reduce MEV TAM

However, this debate over fairness and value distribution is likely moot. As multiple parties fight to access the MEV surplus, we expect MEV’s TAM to decrease. From an application or dApp perspective, why should they leak value to searchers when they can keep the value for themselves or their users? These “MEV-Aware” apps will implement features that reduce the MEV they generate.

This is already happening. For example, MakerDAO and Euler both use auctions for liquidations as opposed to lenders Compound and Aave, which set liquidations at a fixed discount. In Maker’s and Euler’s case, because keepers compete on price to liquidate a loan, the liquidated user suffers a reduced loss. In other words, it recaptures value that they would have lost. For Aave and Compound, there is a fixed liquidation discount. This means that the liquidated user suffers a fixed loss, instead of a variable one that is likely less than the fixed amount. As apps compete for users and liquidity, we can expect dApps to implement features that reduce value leakage to encourage usage over competitors.

How will dApps think about allocating value? Instead of having a liquidation auction reduce the loss to LPs, the protocol can implement an auction fee that shifts some value back to token holders.

We expect applications to use a better combination of mechanism design (primarily auctions) and smarter parameter defaults to plug MEV leakage that their users experience. Some examples include UI warnings to prevent fat fingering, volatility, and pool-aware slippage limits for AMMs. The famous 2.08m USDC to 0.05 USDT swap can easily be prevented.

Relevant meme - diagram

Looking back at our MEV taxonomy, we expect some categories to be easier to minimize than others. For example, front running and sandwiching will be minimized through more intelligent slippage settings. However, some forms of MEV might be inevitable—arbitrage between DEXs, for example, cannot be easily reduced without changes to the base protocol [2].

Trading, keepers, and situation - table

Who Decides the Future?

The MEV market landscape will continue to evolve going forward and impact various market participants. Many interesting questions remain: How will protocols balance the needs of different user groups and how will value flow between these groups? Will the market decide on what amount of MEV should be returned, or instead will there be intervention by protocol designers? Will users gravitate towards protocols that protect them more from MEV, or will users ultimately not care?

We expect application-specific MEV will approach zero in the medium term. Over the long run, inter-application MEV will slowly shift more value back to the originators of the order flow through protocol design. Ultimately, protocols and dApps who protect their users the most will win.

Many thanks to Sina, Hasu, Dev Ojha, Walter Smith, and Christine Kim for their conversations and feedback.


[1] MEV TAM estimates from various data providers.

MEV TAM estimates from various data providers - table

[1] Chorus One’s data annualized is roughly $921m a year (their data starts from August 2020 and ends at the Merge)
[2] Chorus One further separates the number into good and bad MEV, $713.95M good (arbitrage and liquidations) + $1206.11M bad (sandwiches)
[3] EigenPhi only has data for 2022 and onwards
[4] Flashbot’s does have sandwich data in Dune, unfortunately the data is not particularly clean. However, digging around has yielded numbers that are similar to Chorus One’s topline.

[2] Arbitrage between venues is difficult to minimize without changing the underlying L1/L2 protocol. Some designs include auctioning off access to the first transaction in a block, but that would require a change to the base layer. Though there may be some constructions where if a sufficient percentage of ETH validators restake then there can be an extra protocol auction.

[3] Dev from Osmosis notes how this can be mitigated by enshrining the oracles into the consensus for appchains (forcing ⅓ of the validator set to collude is difficult). Perhaps restaking can be used to mitigate this. Or auction for the right to “submit” the oracle update, and thereby the right to front run / back run it (h/t Sina)