Introduction
For much of crypto’s existence, trading on permissionless blockchains won on access and lost on execution. Markets were composable, transparent, and easy to build on. They were, however, not the best execution venues and, as a direct consequence, were also not where the best prices lived for traders. That was the necessary tradeoff of decentralization, or at least it was widely assumed to be. If you wanted tighter spreads, faster repricing, and more sophisticated market making, the belief was that you had to move back toward more closed or permissioned systems.
If the first era of onchain markets was defined by that assumed tradeoff, the current will be defined by breaking it. We believe permissionless blockchains have reached the point where the market structures built atop them can not only provide comparable execution to centralized exchanges but outcompete them entirely. Today PropAMMs on Solana are the first evidence of that new beginning.
The (Onchain) Evolution So Far
The first generation of passive AMMs solved a real market-structure problem; they made liquidity permissionless. Anyone could deposit assets, anyone could trade against the pool, and anyone could build on top of that liquidity.
The liquidity pool exposed a simple pricing formula like x × y = k, users traded against it, and price discovery emerged from arbitrage and natural flow. This is elegant, and today it still solves a problem that active market makers cannot solve cleanly, how to provide transparent and always available liquidity for new assets with no reference prices and sparse demand. For these long-tail assets, this model remains dominant.
PropAMMs are designed for the markets where execution quality matters most, the short and medium tail of highly traded assets such as BTC, ETH, and SOL, and, as we argue later in this piece, can extend well to all onchain markets including prediction markets, perpetual futures, and tokenized securities. They do this by opening up a much wider design space for active trading, where book construction, inventory management, and defensive logic can be customized and programmatically embedded directly in the onchain program leading to superior execution quality.
What PropAMMs Actually Are
A PropAMM is best understood as a two-part system: an offchain pricing engine and an onchain execution program. The offchain engine forms a view of the market by continuously estimating fair value and deciding when that view should be pushed onchain. The onchain program then turns that market view into executable liquidity through book construction, fee logic, inventory management, and other customizable defensive control logic written directly in the contract. The closest analogy we can think of here is co-location. In traditional markets, co-location places a trader’s systems physically next to the matching engine. For a PropAMM, deploying the program onchain effectively places part of that market making logic directly on the exchange’s execution environment itself.
No two PropAMMs are exactly alike. Each reflects its operator’s own proprietary logic (which is where the name comes from) even if the execution itself is fully onchain and verifiable. In the sections that follow, we focus on the core functions and design patterns shared across many of the PropAMMs competing today, including our own, BisonFi.
How It Works: The Mechanics
The Oracle Update
The oracle update is the link between the offchain pricing engine and the onchain execution program. The offchain system watches centralized exchange order books and other venues relevant to the pricing model, continuously recomputes fair value, and pushes those updates to the program as signed transactions. PropAMMs typically submit oracle updates on a fixed cadence, for example every 100 milliseconds, and will push more frequently when fair value moves far enough away from the current onchain reference price.
Each update carries a nonce for replay protection and message ordering. The program rejects updates whose nonce is older than the current onchain counter and, on success, advances that counter to one above the accepted value. Conceptually, this serves the same purpose as sequence numbering in FIX, including MsgSeqNum tag 34: stale or replayed messages are rejected deterministically. In practice, this lets operators A/B different infrastructure paths, test transaction fee strategies, or race submission modes to see which ones produce the best landing outcomes.
For competitive markets like SOL/USDC, operators need fast inclusion signals confirming that an update has made it into the current block. On Solana, the leader builds the block over roughly a 400ms window as transactions arrive and streams portions of that block as shreds through Turbine. As a result, the round-trip time from submission to a probabilistic inclusion acknowledgement can be as low as a few milliseconds to a few tens of milliseconds, depending on the leader’s block-packing logic.
Round-trip time from oracle submission to shredstream observation.
It is also important to note that Solana, like every blockchain, has finite compute capacity per block, and every transaction competes for that blockspace. That is why, in many PropAMMs, the oracle update is reduced to a compact binary payload containing an instruction identifier, a nonce for ordered delivery, a fair value estimate, and whatever metadata the onchain strategy requires. In some designs, including BisonFi, the update does not, by default, transmit a full book snapshot. As we discuss below, the liquidity profile is produced by the onchain program from current pool reserves and stored configuration.
The Onchain Book and Strategy
Once the oracle update lands, the program turns that market view into executable liquidity. In BisonFi’s case, it does this through a discrete tick book built around the oracle mid-price from the pool’s current reserves and a predefined target inventory configuration. The book has ten levels, five bids and five asks, plus a mid-price reference level. Each tick represents a configurable share of pool inventory at a given offset from the oracle. The result is a depth profile rebuilt directly from onchain state.
This means the oracle update does not need to carry a full book snapshot on every refresh. The program already knows the pool’s current balances, target allocations, and tick structure. The oracle update tells the program where the market is; the onchain program decides how much liquidity to show around it.
Simulated BisonFi Tick Book
Ask T4 +8.0 bps 74.5%
Ask T3 +4.0 bps 19.9%
Ask T2 +0.5 bps 3.0%
Ask T1 +0.5 bps 1.0%
Ask T0 +0.0 bps 1.0%
Mid
Bid T0 -0.0 bps 1.0%
Bid T1 -0.5 bps 1.0%
Bid T2 -0.5 bps 3.1%
Bid T3 -4.0 bps 20.1%
Bid T4 -8.0 bps 75.1%
0%25%50%75%
Share of pool reserves posted at that level
Long USD / short SOLBalancedLong SOL / short USD
Deviation from target balance
A second consequence is that the book can adjust programmatically to its environment. As trades consume liquidity at particular ticks, the live book can become depleted at those levels. Tick liquidity for smaller trades may be replenished atomically while larger trades that reach deeper into the book may leave those levels depleted as a defensive measure. Each new oracle update can then restore affected ticks toward their baseline allocation, effectively replenishing the quote stack once per update cycle. On a centralized exchange, that re-layering loop lives outside the venue requiring a series of submissions to cancel, recalculate, repost. Here, it sits inside the execution environment and updates atomically with each trade or oracle update.
The onchain program also controls how aggressively the pool trades. It does not expose the same liquidity on the same terms under all conditions. Instead, it can skew spreads and available depth according to inventory position, oracle freshness, and the character of incoming flow.
For example, when the pool drifts away from its target balance, the program will typically encourage rebalancing flow by showing more liquidity on the side where inventory is short and less on the side where it is long. It will also penalize trades that push inventory further out of line by widening the relevant price offset.
Another example is using slot progression as a proxy for quote staleness. A swap that arrives in the same slot as the last update may see the full standard book, while a quote that has gone stale across multiple slots can trigger wider fees, less accessible depth, or more conservative quoting to reduce the risk of being picked off. Because the program can observe slot progression directly, these controls are enforced programmatically as confidence in the last market view weakens.
Simulated BisonFi Tick Book
Ask T4 +8.0 bps 26.0%
Ask T3 +4.0 bps 7.5%
Ask T2 +1.0 bps 1.3%
Ask T1 +0.5 bps 0.5%
Ask T0 +0.2 bps 0.3%
Mid
Bid T0 -0.8 bps 2.5%
Bid T1 -1.4 bps 4.0%
Bid T2 -2.0 bps 9.5%
Bid T3 -5.0 bps 28.0%
Bid T4 -9.0 bps 82.0%
0%25%50%75%
Share of pool reserves posted at that level
Last oracle update
Same slot1 slot ago2 slots ago
Inventory
Long SOL / short USD
Tick access
5 ticks live
Replenishment
Refresh active
Long USD / short SOLBalancedLong SOL / short USD
Deviation from target balance
Comparative Trading Outcomes
Across the top PropAMM cohort on Solana, the median SOL/USDC fill executed 0.67 bps from Binance mid. A Binance taker, by contrast, pays the spread plus an exchange fee on every fill. Even at VIP 9, the most favorable tier available and one that requires over $1 billion per month in volume to qualify, the all-in cost is 2.57 bps. Against that line, nearly 94.6% of top PropAMM fills and 90.2% of notional cleared cheaper. For a retail trader at VIP 0, the all-in cost rises to 10.57 bps, and 99.15% of those top PropAMM fills beat it.
March 2026 execution-cost comparison between top Solana PropAMMs and Binance VIP taker tiers, with lower cost meaning a fill landed closer to Binance mid.
Beat rate across the Binance fee ladder
These results hold regardless of where a trader falls on Binance's fee schedule. The chart below shows the fraction of PropAMM fills that cleared cheaper than each Binance VIP tier (spread cost plus the tier's taker fee). Even at VIP 9, PropAMMs still undercut on more than 94% of fills and 90% of notional.
PropAMM fill cost vs every Binance VIP taker fee tier, March 2026. Left panel shows beat rate by fill count, right panel by notional volume.
Volume: PropAMMs are now the dominant SOL dollar venue
This wasn't some niche segment of the SOL spot market. Onchain volume for March across the top PropAMM cohort on Solana totaled $18.19 billion in SOL/USDC and $1.68 billion in SOL/USDT, for a combined $19.87 billion across the two pairs.
March 2026 SOL dollar-market volume, comparing PropAMM volume against Binance and Coinbase across the main dollar pairs.
For that same period, Binance recorded $1.79 billion in SOL/USDC and $8.77 billion in SOL/USDT. Coinbase recorded $3.63 billion in SOL/USD. PropAMM volume in SOL/USDC was nearly 10x Binance's SOL/USDC volume and 5.0x Coinbase's SOL/USD volume. Aggregating the relevant dollar-denominated SOL pairs across Binance and Coinbase, PropAMM volume remained ~2x higher than the combined CEX March notional.
Why this happens
What makes these results compelling is that PropAMMs were better on both dimensions inside the same month, in other words, they quoted tighter effective spreads and they facilitated materially more dollar volume. This is exactly what you would expect in a highly competitive execution environment. Multiple PropAMM operators are competing for the same user flow, and weak quoting gets punished immediately. If one operator widens too far or refreshes too slowly, routers can see it and the flow migrates elsewhere. Competition compresses spreads, aggregation concentrates flow toward the best live quotes, and the resulting market looks less like a passive pool complex and more like a contested electronic execution venue.
Tokenized Securities
The previous sections demonstrate that PropAMMs can deliver superior execution quality for spot crypto pairs on a permissionless blockchain. We believe this model is not limited to spot crypto pairs and that it will be particularly well suited to tokenized securities.
The core function of a PropAMM, taking an offchain view of fair value and turning it into executable onchain liquidity with embedded defensive logic, is structurally asset-agnostic. The offchain pricing engine references whatever venues are relevant: centralized crypto exchanges for SOL/USDC, and equity exchanges, dark pools, and consolidated quote feeds for tokenized stocks. The onchain program constructs a book, manages inventory, and controls trading logic. The asset in the pool changes. The architecture does not.
What does change is the regulatory environment, and that environment is both the obstacle and the opportunity. To understand why, it is necessary to understand the market structure framework that currently governs US equity trading and why that framework is under active reconsideration.
NMS
Regulation National Market System, adopted by the SEC in 2005, was the most significant structural reform to US equity markets in a generation. Its core objectives were straightforward: ensure that investors receive the best available price when they trade, promote fair competition among trading venues, and modernize the infrastructure through which quotes and trades are disseminated.
The central component of Reg NMS is the Order Protection Rule (Rule 611), which established the concept of "protected quotes." Under this rule, a trading venue cannot execute an order at a price that is worse than the best displayed price on another venue that is part of the national market system. This best displayed price, aggregated across all participating venues, is the National Best Bid and Offer (NBBO). In practice, the rule means that if NYSE is showing a bid of $100.01 and Nasdaq is showing a bid of $100.02, a sell order arriving at NYSE cannot be executed at $100.01 without first attempting to route to or match the $100.02 bid on Nasdaq. The NBBO is disseminated through the Securities Information Processors (SIPs), consolidated data feeds that aggregate quotes from all protected venues.
The intent was to ensure that fragmentation across venues did not harm investors by allowing trades to execute at inferior prices when better prices were available elsewhere. The mechanism was to create a consolidated, continuously updated reference price that all venues were obligated to respect.
The results have been mixed, and the criticisms are now well-documented. Reg NMS did not reduce fragmentation, it accelerated it. By guaranteeing that any venue displaying a protected quote would receive order flow routed to it under Rule 611, the rule lowered the barrier to launching new trading venues. The number of exchanges with protected quotes has more than tripled since enactment. Each new venue adds complexity to routing, introduces new fee structures and rebate tiers, and creates additional infrastructure dependencies.
SEC Chair Paul Atkins has acknowledged these structural concerns directly, noting the increasing complexity of a system that was designed for a much simpler venue landscape. The Principal Traders Group (PTG), representing many of the largest electronic market makers (including Jump), has argued in its white paper for a shift from prescriptive rules like Rule 611 to a principles-based best execution standard. Their argument is that the current rule-based approach has become a source of complexity and cost that does not reliably produce better outcomes for investors, and that a principles-based framework would allow execution quality to be measured by outcomes rather than by compliance with a routing topology that has grown unwieldy. The SEC has signaled openness to modernizing Reg NMS, though the form that modernization will take remains uncertain.
What PropAMMs Could Offer Tokenized Equity Markets
We believe PropAMMs are well-suited to providing liquidity for tokenized securities for reasons that go beyond simply replicating existing markets on blockchain settlement rails. The structural properties of PropAMMs on permissionless blockchains address several of the specific problems that Reg NMS was designed to solve and that its critics argue it has failed to solve adequately.
Execution quality and price improvement. As the data in this piece demonstrates, PropAMMs on Solana are already delivering effective spreads and total cost of execution that are competitive with, and in many cases superior to, the largest centralized venues. This is for a crypto pair (SOL/USDC) where PropAMMs have been operating for a relatively short period of time. For highly liquid equities, the offchain pricing engine has even richer inputs to work with. PropAMMs for tokenized equities would have access to the same reference pricing that informs existing market makers on existing equities venues.
A PropAMM that is consuming the NBBO as an input to its offchain pricing engine can construct onchain quotes that are at or within the NBBO, offering price improvement to retail traders. This could even be enforced programmatically by onchain aggregators. This is functionally what wholesale market makers do today when they internalize retail order flow from brokers under Rule 606 arrangements: they reference the NBBO and offer a small improvement to win the order. The difference is that in the current system, this price improvement happens inside the wholesaler's private matching engine, with execution quality reported in aggregate on a quarterly basis through Rule 605 disclosures.
On a PropAMM, the same economic function, referencing a consolidated price and offering improvement, would occur on a public ledger with PropAMMs competing and where every individual execution is independently verifiable.
Transparency that exceeds current reporting requirements. The transparency argument for PropAMMs in equity markets is not abstract. Today, Rule 605 requires market centers to publish execution quality statistics aggregated by order type and size category. Rule 606 requires brokers to disclose their routing practices and payment-for-order-flow arrangements on a quarterly basis. These disclosures are aggregated and delayed to where meaningful comparison across venues requires significant analytical effort. A retail investor cannot easily determine, after the fact, whether their specific order received the best available execution or whether their broker's routing decisions were optimal.
On a permissionless blockchain, every trade executed by a PropAMM is recorded immutably with the execution price, the size, the block timestamp, and the oracle reference price at the time of execution. This data is available in real time to anyone. A regulator does not need to request it through a compliance department. A retail investor does not need to wait for a quarterly report. An independent analyst can compute price execution quality (improvement or disimprovement) for every individual trade against the NBBO.
One of the core criticisms of Reg NMS is that the protected-quote mechanism has incentivized venue proliferation without corresponding improvements in execution quality. Each new exchange exists in part because Rule 611 guarantees that its displayed quotes will receive routed order flow, creating an economic incentive to launch venues that capture routing fees and rebates rather than venues that provide meaningfully better execution.
PropAMMs compete differently. There is no rule requiring order flow to be routed to a PropAMM simply because it is displaying a quote. Flow goes to PropAMMs because they offer the best price after fees at the moment of execution. Aggregators and front-ends route to whichever PropAMM (or combination of PropAMMs and other liquidity sources) provides the best executable price for a given order. If a PropAMM's quotes are stale, too wide, or non-competitive, it simply does not and should not receive flow. Aggregators could choose to not process trades that would execute outside the NBBO. There is no protected-quote subsidy. The competitive discipline is continuous and unmediated.
This produces a dynamic that looks more like what Reg NMS intended than what Reg NMS achieved: genuine price competition among liquidity providers, with flow gravitating toward best execution, but without the venue-proliferation incentive that Reg NMS and its related rules inadvertently created.
Moving Forward
Every prior transition in market structure shared a common feature: the new system did not merely replicate the old one faster. It changed what was structurally possible through new technology. PropAMMs follow this pattern precisely. They do not merely recreate a central limit order book inside a smart contract. They merge the expressiveness of proprietary market making (oracle-informed pricing, inventory-awareness, spread management) with the structural guarantees that only a permissionless blockchain can provide: self-custody of assets, atomic settlement, immutable and publicly auditable execution records, and composability with the broader onchain financial system.
The result is a liquidity mechanism that is already, on certain pairs, delivering tighter effective spreads and better total cost of execution than centralized venues while simultaneously offering a degree of transparency that no existing regulatory reporting regime requires or achieves.
The significance of this moment is not lost on us. The SEC and CFTC are reconsidering market structure frameworks that were drafted in an era where the choice was between competing centralized venues, not between centralized and decentralized paradigms entirely. Simultaneously, onchain market microstructure has matured to the point where it can credibly compete on the metrics that matter most to regulators and market participants alike: price improvement, fill quality, transparency, and systemic resilience. These two developments are not coincidental. The technology is forcing the question, and the question is overdue. As the SEC approaches re-evaluating decades-old market structure rules, innovation exemptions allowing for new models like the PropAMM will allow for careful re-evaluation of how best execution should be addressed.
We want to be explicit about the importance of permissionless blockchains in this thesis, because it is the point on which we feel most strongly and which invites the most skepticism from traditional market participants. The argument for permissioned or private chains in capital markets rests on the notion that regulated activity requires controlled environments, known participants, and gatekept access.
Compliance does not require a permissioned chain. It requires permissioned access to specific applications and instruments running on the chain. A tokenized security can enforce transfer restrictions, KYC/AML gating, and jurisdictional controls at the token contract and application layer without requiring the underlying settlement infrastructure to be closed. The base layer and trading remain open, verifiable, and composable, which provides the transparency and resilience properties that make it superior to private infrastructure. A permissioned blockchain is just a database with extra steps. It inherits none of the properties of public verifiability, permissionless composability, and perfect competition that make blockchains useful as market infrastructure in the first place.
The practical implications are significant. On a permissionless chain, a regulator does not need to request execution data through a broker-dealer's compliance department and wait for a quarterly 605 report. Every trade and price update is recorded in real time on a ledger that anyone, regulator, institution, or retail participant alike can independently verify.
PropAMMs today operate in spot crypto markets on Solana. They are competing against passive AMMs, centralized exchange order books, and each other. They are winning that competition on execution quality and doing so in a way that is measurable and public . The natural extension of PropAMMs to other asset classes including tokenized securities, perpetual futures, and prediction markets is not a speculative leap. It requires adapting a microstructure model that works and thoughtful engagement with regulators.
We believe that time is now. PropAMMs on Solana are not a proof of concept. They are production systems delivering superior execution to real participants trading real capital. The question for traditional markets is the same one it has always been at these inflection points: not whether the transition will happen, but whether you will be early enough to embrace and shape it.
