Written by Jake Koch-Gallup and Sam Schubert
Compiled by AididiaoJP, Foresight News
This article examines how the market structure differs between Backpack and xStocks for tokenized U.S. stocks on Solana, and how these differences directly impact execution costs.
Market performance has diverged. The Solana ecosystem index rose another 8.0%, but nearly all of the gains came from just two tokens, META and PUMP, rather than broad-based growth across the entire ecosystem.
Yesterday, the Solana ecosystem index continued to lead, rising 8.0%, more than double the gain of the second-place sector. Launchpad (+3.2%), the Bittensor ecosystem (+2.7%), AI (+2.2%), and perpetual contracts (+2.0%) followed. Traditional U.S. stocks outperformed most crypto assets: the Nasdaq 100 rose 3.0%, the S&P 500 gained 1.9%, while Bitcoin increased just 0.9%. Crypto mining stocks performed worst, declining 3.1%; the Ethereum ecosystem and lending sectors both fell 2.0%.
From a weekly perspective, sector rotation has been extremely rapid. Even though crypto mining stocks experienced a sharp decline yesterday, they still rank second for the week, up 15.1%. DEX, which was second on Monday, has now fully retraced its gains and is currently down 1.1%. The lending sector performed the worst this week, falling 10.0%, followed closely by the Ethereum ecosystem, down 9.8%. The public blockchain sector is down 2.0% for the week; SOL is currently trading at approximately $73, with a monthly decline of about 10%.
The rise in the Solana Index was actually quite narrow. Since its listing on Upbit, META has gained 46.6% for the week, and PUMP has gained 22.9%, together accounting for about one-third of the index’s weight—these two tokens contributed nearly all of the index’s 17.8% weekly gain. Seven of the 11 components declined: BP fell 13.7%, BONK fell 7.7%, and the median component dropped 5.4%. Solana’s rise was driven by just two tokens, not by broad capital inflows into the entire ecosystem.
This week, both Solana and Ethereum proposed measures to reduce issuance. Solana’s “Double Deflation Proposal” aims to double the annual deflation rate from 15% to 30%, move the 1.5% terminal inflation floor from 2032 to 2029, and reduce SOL issuance by approximately 18.9 million tokens over the next six years. Ethereum’s EIP-8361 plans to gradually burn more validator rewards, eliminate incentives for staking beyond 50% of total supply, bring net consensus issuance to zero at that threshold, and roughly halve the current yield to around 1.1%. Both are draft proposals, and neither cryptocurrency’s price has yet reflected these proposals.
Solana Tokenized U.S. Stocks: Backpack vs xStocks
Backpack Securities and xStocks have both launched overlapping tokenized U.S. stocks on Solana, but their market structures differ significantly. Backpack primarily relies on proprietary market makers (Prop AMM) quoting from dealer inventories to execute trades, while xStocks' trading volume is highly concentrated in public liquidity pools on Raydium and Orca.
On the surface, trading volumes appear similar: from June 12 to July 30, xStocks traded $2.43 billion, while Backpack traded $2.10 billion. However, SPYx alone contributed $1.70 billion, accounting for 70% of xStocks’ total volume, with a significant portion consisting of intra-pool circular trades. Excluding SPYx, the comparable xStocks volume drops to just $726 million—far below Backpack’s $2.10 billion.
Since SPCX launched, 66%–74% of Backpack’s weekly trading volume has been executed through Prop AMM, averaging approximately 71% over the past four full weeks. In contrast, xStocks has seen only about 33% of its trading volume executed through Prop AMM, a figure inflated by a single week of $284 million in trading from AlphaQ; excluding that week, the percentage has consistently been below 10%.
Only redeemable and hedgeable underlying assets make professional quoting reasonable. This was evident from day one: within hours of SPCX's launch on June 12, market makers began posting two-way quotes of $10,000, rather than waiting weeks to enter the market.
The intraday data also adds two key points. Prop AMM provides continuous quoting: on weekdays, the median share of trades routed through Prop AMM over 30-minute intervals is 69% (with the middle 80% of intervals ranging between 62% and 84%); on weekends, the median remains at 64%. Market makers widen spreads and skew quotes during U.S. market hours but do not cancel their orders. The remaining pool and order book traffic accounts for roughly one-fifth to one-third of volume during most periods, with pool volume clearly spiking around U.S. market open and close—consistent with arbitrage and hedging of underlying assets. Thus, gross pool volume likely overstates the amount of capital actively choosing the pool.
The volume itself is largely composed of transit capital. In Solana tokenized stock trading, approximately 68% are round-trip transactions: 31% enter and exit within minutes (including atomic trades completed within a single transaction), 34.5% enter and exit on the same day, while truly directional positions held for longer periods account for only 7.1%, and about a quarter remain unclassified. Meanwhile, the number of holders continues to rise—from 129,000 in early May to 211,000 by the end of July—with $164 million in buying volume still unmatched by selling activity for at least a week as of the end of July.
In terms of order size matching, Backpack’s SPCX execution cost is consistently lower than xStocks’. We compared executions between June 12 and July 20 in the $100–$500 range, against the NBBO during regular trading hours and overnight Blue Ocean quotes. The analysis used actual executions by different traders within the same time window, not the same order routed twice. During regular hours, xStocks was approximately 2.4–2.5 basis points more expensive; overnight, it was 2.8–2.9 basis points more expensive. Out of 25 eligible regular trading days, Backpack was cheaper on 22 days; it was cheaper on all 17 overnight periods. This aligns with the logic of Prop AMM competing for flow around real-time reference prices.
