PropAMMs lower Solana trade costs, and public pool returns crash

A trader can get a better Solana (SOL) swap price while a passive pool depositor remains exposed to traders picking off stale quotes, and a Sept. 29 preprint measures that divide.

For quiet-market SOL/USDC fills, propAMMs, pools controlled by professional operators, had a reference-relative execution cost proxy of 0.26 basis points versus 2.59 for public automated market makers (AMMs).

The study covers Sept. 1, 2025, through Aug. 31, 2026, with shorter Base and Monad samples. It weights fills by notional against Bybit’s size-weighted top-of-book USDT microprice, converted with its USDC/USDT midpoint. Its authors list ETH Zurich and Category Labs affiliations.

A swapper wants more tokens for the same input, while a depositor supplies the inventory others trade against and needs compensation for the risks that inventory carries. Low execution cost can attract the first participant without being a sufficient investment case for the second.

Swap prices and depositor returns on Solana

Across its Solana sample, the paper reports two-second gross maker markouts of +0.37 basis points for propAMMs and −0.22 for public AMMs. A markout compares a fill with a later reference price, and a positive number favors the maker.

Quiet-flow execution asks how much a trader gives up against a relatively stable reference. The proxy requires less than 1 basis point of reference movement from five seconds before to one second after a fill.

Maker markouts ask what happens to a trade’s value after the pool accepts it. Mixing the measures would turn evidence about pricing and adverse selection into a profitability claim the numbers cannot support.

Lower swap costs do not guarantee reliable quotes or positive LP returns.

When an outside market moves first, a pool still offering an old price can sell too cheaply or buy too dearly. An arbitrageur brings the prices back into line, but the correction comes through a trade against the liquidity already sitting in the pool.

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Loss-versus-rebalancing research treats that arbitrage cost as one component of LP economics. Returns also reflect asset exposure and fees earned, so an investment assessment needs a position, a holding period, and the income and costs attributable to it.

Trading fees need to be allocated correctly, while inventory changes, hedging, operating expenses and transaction costs also matter when applicable. The short horizon leaves that accounting unresolved, and venue averages cannot establish that professional pools caused aggregate passive-LP losses.

Depositors need a return assessment that includes this wider balance sheet, and swappers can benefit from liquidity whose operator actively manages pricing risk.

Jump Crypto’s April account describes propAMMs, including its own BisonFi, adapting prices and available liquidity to inventory, quote freshness, and the quality of incoming flow. Jump is an interested operator, and implementations differ.

A maker holding too much of an asset can discourage trades that add more of it, while a stale price can justify withdrawing depth or widening a fee. A routing path associated with adverse selection can receive different terms from flow the maker considers less risky.