A WuBlockchain repost argues that Binance’s stock-linked product stack is not trying to beat Nasdaq on its own turf. The article’s claim is that if Binance wants a say in stock pricing after traditional exchanges close, it should lean into what it already does better: Perps, 24/7 trading, leverage, on-chain inventory, and a mix of formal and informal market makers across crypto rails.
The article’s framing is simple. Perps take the high ground on price formation first, then bStocks absorb inventory and help correct mistakes. Only then does the discussion move from extended trading hours to pricing power.
Why the article starts with Chicago grain trading
The piece opens with the Chicago Board of Trade, founded in 1848. At the time, Chicago was becoming a grain hub for the U.S. Midwest, but wheat was not a uniform financial product. Grain from different farms and harvest years did not carry identical quality. Buyers often did not know exactly what they were purchasing, which made a unified market price hard to establish.
One of CBOT’s early jobs was to turn that disorder into a tradable standard. After receiving authorization from Illinois in 1859, CBOT could define grain grades and rely on designated inspectors to determine quality. By 1865, margin and delivery rules were being formalized as well. The article says this may sound more like warehouse administration than financial innovation, yet it changed the shape of the market. Once grain went into large elevators, traders no longer needed to ask which farm a sack came from. Trading shifted toward standardized grades instead. The Federal Reserve, in its historical review cited by the article, noted that grading and standardized storage lowered transaction costs and created the conditions for liquid markets.
Only after that foundation was built did futures take off. Farmers could sell future harvests in advance, merchants could buy future supply, and speculators could bet on future prices without hauling grain home. CBOT moved from early forward and to-arrive deals toward standardized futures, and by the late 19th century Chicago grain futures were handling price discovery, risk management and public quotation.
The article’s point is that the fastest, deepest market ended up being futures, but futures did not stay tethered to reality on their own. The warehouse sat behind them. That structure is the analogy the author applies to Perps and bStocks today.
Weekend stock Perps: big turnover, mixed answers
The article then jumps to a weekend in August 2026. On Binance, perpetual contracts tied to NVDA, TSLA, SNDK and SKHY posted roughly $461 million in combined trading volume. By Sunday, all four Perps were trading above the prior cash-market close. When the U.S. cash session reopened on Monday, all four stocks opened lower instead.
SNDK is used as the clearest example. Over that weekend, the SNDK Perp traded about $338 million. Friday cash close was $1,212.21. Sunday trading reached $1,223.98. Monday cash open came in at $1,203.41.
The same product had delivered a different result one month earlier during the U.S. Independence Day long weekend. Cash trading had stopped at $1,745, Binance printed $1,841.88 on Sunday, and Monday cash open was $1,828.68. The stock market reopened with a gap of about 4.8%, and Binance’s weekend price had already captured most of that move, though it overshot.
One product, two weekends, two very different outcomes. In one case, the market traded much of Monday’s gap in advance. In the other, it got the direction wrong after hundreds of millions in turnover. The article treats that as evidence that the real issue with 24/7 stock trading is not merely time extension. Market structure matters, and trading volume does not automatically buy pricing authority.
Three product roles inside Binance’s stock stack
The article says that if Binance only wanted to let users trade stocks on a Saturday, longer hours would be enough. But when Direct Stock, TradFi Perps and bStocks are viewed together, they form a different architecture.
- Direct Stock handles real securities, corporate actions and the traditional-market interface.
- bStocks turn equities into assets that can be held, converted, bridged and posted as collateral.
- TradFi Perps handle long-short exposure, leverage and continuous trading.
Once the traditional stock market closes, Perps take the first wave of directional, leveraged and high-frequency flow. bStocks supply stock inventory that can be held, moved, financed, hedged and delivered into other strategies. On-chain protocols then pull in capital from outside centralized exchanges. When the regular stock market reopens, the question becomes whether the price formed in this 24/7 system is accepted by the cash market.
The article says the real debate is not whether bStocks qualify as yet another tokenized stock format. It is why Perps should be the engine if Binance wants the first draft of the post-close price, and why bStocks belong in the inventory and correction layers behind that engine.
Why Perps are better suited to the first stage of price expression
The author uses NVDA as a case study. In a sample from July 17 to July 22, NVDAB spot recorded about $4.21 million in notional turnover, while NVDAUSDT Perps traded about $418 million, a gap of roughly 99 times. Looking only at the weekend, Perp turnover was around 37 times that of bStocks on July 18 and about 68 times on July 19.
The article is careful about scope. This is a comparison between two Binance products, not a claim that Binance stock Perps are larger than Nasdaq cash trading in NVDA. U.S. cash equity turnover is still larger. The purpose of the comparison is narrower: when the stock market is shut, where do fresh directional orders go first?
Spot can be bought and held for months. Perps, by contrast, see repeated opening, closing, flipping, leverage adjustments, basis trades and funding collection, while market makers keep hedging around them. The same dollar of capital can generate gross turnover multiple times in a Perp venue. Short selling creates an even sharper distinction. If negative news hits NVDA on a Saturday, a trader without NVDAB inventory would need borrow before shorting on the spot side. In a Perp, a sell order expresses the view immediately.
That is why the article writes the first path of post-close pricing as Information → Perp → Candidate Price. Perps produce a candidate price. They do not guarantee a correct one. That gap, the author says, is where bStocks become useful.
The 25-sample close-to-reopen study
To examine how the price gets formed, the article compiles data for NVDAUSDT, TSLAUSDT, SNDKUSDT, SPCXUSDT and SKHYUSDT. It identifies 25 U.S. market closure-to-reopen samples that can be matched cleanly to the next cash open. NVDA, TSLA, SNDK and SPCX each contribute six samples, while SKHY contributes one.
Each sample starts at the prior cash close and moves through Pure Weekend, Sunday Price, Monday Premarket, Opening Auction and the next Cash Open. Sunday 19:59 ET is used as an observation point before regular U.S. equity premarket has started. From Monday 04:00 onward, premarket returns. After 09:25, opening-auction information enters the picture. The official cash open is then used as the validation point.
The article says the dataset is meant to answer four questions: how far weekend prices sit from the next cash open; how much real order size the quoted market can absorb; how much money actually changed hands; and whether the trading cadence looks more like independent investor views or like a high-turnover machine driven by market making, HFT and systematic activity.
A quoted price does not mean it is executable. A market with trades does not mean those trades come from independent conviction. And liquidity on its own does not prove a market can discover price, the article argues.
Error narrows from 181.9 bp to 11.3 bp, but that does not settle who leads
The article defines error as the absolute distance between the Binance Perp price at a given point and the next cash open, expressed in basis points.
At the Sunday observation point, the result was 13 out of 25, or 52%. Thirteen samples matched the eventual opening direction, 12 did not. In the author’s reading, that is not distinguishable from a 50% coin flip, so the dataset does not prove stable weekend discovery by Binance.
The same caution applies to the 11.3 bp reading at 09:29:59. By then, U.S. premarket has already traded for hours and opening-auction information is circulating. If a Perp is still materially away from the stock’s premarket price at that stage, an arbitrage opportunity would appear on its own. So the move from 181.9 bp to 11.3 bp shows convergence as traditional markets come back online. It does not show that Binance led the cash market there.
The article says that question would need a proper lead-lag study using Binance Perps, bStocks and U.S. premarket last, bid and ask at the same timestamps. If premarket moves from 100 to 105 first and the Perp follows later, that is follow-through. If the Perp reaches 105 first and premarket then gravitates toward it, that would carry stronger implications for price leadership.
SNDK shows that pre-open convergence is not a straight line
The article uses the 2026 Independence Day long weekend, July 3 to July 5, to compare price paths in NVDA, TSLA and SNDK from Sunday through the opening cross.
NVDA looks like a correction path. Sunday printed $198.35 and the final cash open was $194.42, a gap of about 202 bp. By 09:25, the Perp had returned to $194.97. At 09:29:59, it was $194.55, leaving only about 6.7 bp of error.
TSLA started in the right direction from Sunday. Cash close was $393.45, Sunday price was $399.40 and cash open was $397.50. The market traded the rise in advance, but Sunday’s move was larger than the eventual opening gap.
SNDK is the sharper example. At 09:25, the Perp was $1,828.97 and the final cash open was $1,828.68, a difference of less than 2 bp. Five minutes later, at 09:29:59, the Perp had dropped to $1,825, widening the error to about 20 bp.
The article says this matters because prices before the opening auction do not travel in a smooth line toward the final opening print. Premarket trading, NOII, market-maker inventory and last-minute order flow can all push the price around. Any attempt to identify who has pricing power has to study the full lead-lag path, not just Sunday and one timestamp before 09:30.
bStocks are not automatically closer to the next open than Perps
Another lower-frequency dataset compares end-of-day UTC prices for NVDAB, TSLAB, MUB and COINB against the next U.S. cash open, then adds Perps where the data exists.
The median handoff error for eight bStocks observations was about 117.2 bp. For six comparable Perp observations, it was about 118.9 bp.
The article uses NVDA on July 23 to 24 as an example. NVDAB was 207.97, the Perp was 207.99 and the next cash open was 207.45. Both markets were high by roughly 25 to 26 bp. The point, according to the author, is that bStocks do not need to beat Perps at predicting the next cash print. Their value lies in preserving a price formed during market closure in the form of spot-like inventory that can be held, moved, converted and financed.
Perps move the price. bStocks turn that price into an asset.
What the single-name breakdown shows
Breaking the sample apart, the article assigns a different role to each ticker. For NVDA, the average absolute deviation between Sunday and the next cash open was about 113 bp, with direction correct in 3 of 6 samples. TSLA came in at about 81 bp with 4 of 6 directional hits. SPCX posted about 149 bp with 3 of 6. SNDK was far wider at about 351 bp, also 3 of 6. By 09:29:59, the descriptive average deviations had fallen to roughly 11.8 bp for NVDA, 8.6 bp for TSLA, 9.4 bp for SPCX and 16.0 bp for SNDK.
NVDA is presented as the better case for studying how wrong prices get corrected. TSLA is used to study overshoot. SNDK shows both states in one name: one long weekend where it captured most of an eventual opening gap, and another where large turnover still pointed the wrong way. SPCX is treated differently because of its product history inside Binance.
The article suggests that post-close prices should not be sorted only into right and wrong. It proposes a finer classification: Direction Discovery, Magnitude Discovery and Correction Dependency.
SPCX as a product migration and pricing experiment
SPCX is structurally different from NVDA, TSLA and SNDK. According to the article, when Binance Futures launched its Pre-IPO Perpetual product in May 2026, the first contract was SPCXUSDT, designed to trade SpaceX’s future public-market valuation. After SpaceX listed, SPCXUSDT became a standard TradFi Perp. Binance then added SPCX Direct Stock and SPCXB.
In other words, this name had a derivatives price before it had a public cash market for repeated validation, and only later gained a holdable, on-chain bStocks format. The article says that creates a rare environment for observation. For NVDA and TSLA, Binance is layering a 24/7 risk venue on top of a mature market. For SPCX, the migration runs Pre-IPO Perp → Public Stock → TradFi Perp → bStocks.
Across six full weekends, SPCXUSDT’s Sunday direction was correct 3 times out of 6. The average absolute deviation from the next cash open was about 148.8 bp, with a median near 134.4 bp. By Monday 04:00, the average deviation had dropped to 114.1 bp; by 08:00 it was 102.0 bp; by 09:00 it was 53.8 bp; by 09:25 it was 29.3 bp; by 09:29:59 it had narrowed to 9.4 bp. Direction matched the final opening gap in all six samples after 08:00, but by that point U.S. premarket had already returned. The author treats this as evidence of handoff and convergence, not of Binance discovering the price in isolation.
SPCX also concentrates the overshoot problem. In the three weekends where Sunday got the direction right and the eventual opening gap exceeded 50 bp, the Sunday move was about 2.79 times the final gap on July 20, about 1.60 times on July 27 and about 1.34 times on August 10.
The August 10 path is singled out. Friday close was $133.11, Sunday had already reached $135.57 and Monday cash open was $134.95. Sunday’s print was only about 46 bp above the final open, but by Monday 08:00 SPCXUSDT briefly surged to $138.80, widening the distance to the final cash open to about 285 bp. By 09:29:59, it had fallen back to $134.86, only about 6.7 bp away.
SPCX’s trading structure is also described as anything but quiet spot activity. Across six weekends, SPCXUSDT traded about $1.546 billion, around 10 times NVDA on the same basis, with roughly 3.58 million underlying fills, or 3.45 fills per second on average. The article says that for bStocks, the implication is direct: the faster the Perp turns over, the more market makers need an inventory leg such as SPCXB or SPCX to absorb delta when customer net flow persists.
Volume and fill rates: a fast machine, not necessarily pure investor conviction
Across six weekends, NVDAUSDT posted about $154 million in cumulative turnover, TSLAUSDT about $107 million, SPCXUSDT about $1.546 billion and SNDKUSDT about $2.922 billion.
The article notes that this ranking does not map neatly to company size or public familiarity, which means gross volume cannot simply be translated into natural investor demand. In the final five minutes before the open, SNDK still averaged roughly $26.64 million in trading across six events, SPCX about $18.88 million, NVDA about $2.49 million and TSLA about $2.01 million. Perps were still repricing actively rather than waiting passively for the opening cross.
Looking at trade frequency changes the picture again. Over six weekends, SNDK generated roughly 7.57 million fills, or about 7.3 per second. SPCX recorded about 3.58 million fills, or 3.45 per second. NVDA came in near 640,000 fills, or about 0.62 per second. The main difference lies in frequency more than ticket size.
Average raw fill size was about $386 for SNDK, about $432 for SPCX and about $241 for NVDA. SPCX’s median amount, at about $171, was close to SNDK’s $173. The article argues that SNDK and SPCX were not producing huge turnover through a handful of outsized orders. They were doing it through denser, repeated trading.
Because the dataset does not reveal account identities, the number of unique participants, or how much came from institutions versus market makers, the author stops short of a stronger claim. Still, the article leans toward the view that tens of billions in turnover over time do not represent an equivalent scale of independent investment views. SNDK and SPCX, in this framing, look more like high-speed stock-derivatives markets, with SNDK running at a faster clip.
For SPCX, the article goes one step deeper into the 24-hour pattern. From midnight to 06:00 Eastern Time, the contract still accounted for about 20.8% of weekend gross notional and about 20.9% of raw fills, averaging around 2.9 fills per second during that deep-night window. Across six weekends, taker buy/sell notional imbalance was about -1.16%, close to two-way balance overall. The author says that shape looks more like a round-the-clock venue formed by market making, systematic activity and cross-market arbitrage than by one-sided directional betting.
Perps and bStocks may be serving different order types
The article places Perp ticket-size data next to a Binance Research report on bStocks. As noted, average raw fills were about $386 for SNDK Perps, about $432 for SPCX and about $241 for NVDA, while median aggTrade amounts for SPCX and SNDK were about $171 and $173.
Binance Research, by contrast, said roughly 93% of bStocks trading was fractional, with a median trade size of only $18.81, and that about 80% of tokenized-stock trading came from users in emerging markets.
The author stresses that the datasets are not directly comparable, so one cannot divide 386 by 18.81 and declare that Perp users are 20 times larger than bStocks users. But the side-by-side view does suggest a division of labor. bStocks appear better suited to small spot positions, long-term inventory, cross-time-zone retail flow and on-chain users. Perps appear better suited to leverage, basis trades, market making, HFT and high-turnover capital.
The article says one market is better at creating holdable stock inventory, while the other is better at making the same risk turn over rapidly. A real pricing network only emerges when market makers and arbitrageurs connect the two. The author argues that this linkage is still incomplete and remains an area where the system could be strengthened.
Why bigger Perp volume makes bStocks more important, not less
If Perp trading can run at dozens of times the volume of bStocks, why does Binance still need bStocks at all? The article answers from the market maker’s balance sheet.
Customer positions and market-maker positions in Perps mirror each other. If customers are net long, the market maker is short the Perp and needs positive-delta exposure through bStocks or stock. If customers are net short, the market maker is long the Perp and needs to sell bStocks inventory, or borrow bStocks first and then sell them.
Perps solve the speed problem. bStocks solve the question of where risk sits on the balance sheet. If customer net order flow keeps leaning in one direction, delta accumulates. It cannot stay inside the Perp venue forever. At some point, an inventory leg has to carry that risk.
That is why high Perp volume is not evidence that bStocks failed, the article says. It is one reason they are needed. The faster derivatives turn over, the greater the demand for inventory, financing and stock borrow. Retail traders may not feel this directly. Market makers do.
1:1 backing as a terminal constraint, not an instant peg
The article warns against treating bStocks as if they were the stock-market equivalent of USDT against the dollar. In the weekend stock context, that analogy breaks down.
Converting NVDAB into NVDA stock on a Saturday does not mean a Nasdaq cash leg exists at that exact second to finish a full cash arbitrage. What the holder has is inventory that can ultimately reconnect to the real stock, not a same-second cash-market settlement path.
So the author describes 1:1 backing as a terminal constraint. The market knows that bStocks can ultimately reconnect to real equities, and it knows the cash market will reopen. Prices can drift while the market is shut, but once the divergence exceeds funding cost, inventory cost, event risk and execution frictions, the incentive to wait for the traditional market to reopen and then compress the spread starts to appear.
In that sense, bStocks are not there to tell Perps the correct price. They are there to give the candidate price created by Perps an inventory base that can be held, hedged and arbitraged. That is why the article says “inventory layer” and “correction layer” are better descriptions.
Once bStocks are on-chain, the key is circulation of inventory
The article then argues that if NVDAB only sits inside a Binance spot account, it remains an internal CEX stock inventory layer. Once bStocks move on-chain, they can enter DEX, lending, collateral and margin systems, changing the market structure around them.
Examples listed in the piece include PancakeSwap pools for bStocks such as TSLAB, NVDAB, MUB and SNDKB; Lista supporting some bStocks as collateral to borrow stablecoins; Aster allowing eligible bStocks into Multi-Assets Mode; Youcanshortit.com allowing users to lend out bStocks with leverage; and Pundi X Basket letting users customize portfolios and index ETF-style baskets that others can follow.
These platforms are not solving the same problem. The common direction is to make NVDAB, SNDKB and SPCXB do more than sit idle in wallets. The assets can become tradable, financeable, collateralizable, hedgeable and useful in market-making loops.
The article draws a distinction between adding utility and adding liquidity. If NVDAB is locked in a lending protocol as collateral, utility rises, but that does not automatically create fresh two-way order flow. Inventory only starts to increase market liquidity when market makers, arbitrageurs or short sellers can borrow it and feed it back into CEX, DEX or Perp hedging.
That leads to the article’s preferred circulation loop: not Binance → Wallet → DEX, but bStocks → DEX / Lending / Credit Pool → Market Maker → Perp Hedge → CEX → Stock Conversion. Inventory starts to matter when the same stock units can be reused by different accounts and across different venues.
In that framing, TVL is not the key metric. A better one is how many times a unit of stock inventory can be used. If $1 million of NVDAB simply sits locked in a protocol, it remains a static $1 million asset. If part of it can be borrowed by a market maker, quoted into the market, hedged with Perps and then returned to the pool after trading, it begins to function as infrastructure.
The article also cites Binance research saying that 2,806 users took part in approximate arbitrage-style trades across bStocks, Perps and Equity, involving about $216 million, and that about 58.5% of bStocks users also used Perps and/or Equity. The author takes that as evidence that “wild” quant-style participation already exists and could be developed into a seed user base for bStocks.
Two pathways are highlighted. One is to post NVDAB as collateral, borrow stablecoins and bring those stablecoins back to the CEX to trade NVDAUSDT Perps. Another is to place NVDAB into a DEX liquidity pool and hedge the stock delta of the LP position using NVDAUSDT Perps. In this setup, bStocks tie together CEX Perps, CEX spot, real stock, DEX, lending and stablecoins in one risk network.
The missing piece is not more tickers. It is borrow.
The article distinguishes financing from stock borrow. Using NVDAB as collateral to borrow USDT is financing. Borrowing NVDAB itself and then selling it is stock borrow. Both involve “borrowing,” but they matter differently for price formation.
If Perps are rich and bStocks are cheap, an arbitrageur can buy bStocks and short the Perp. That trade is relatively straightforward and should compress the Perp premium. If bStocks are rich and Perps are cheap, the reverse trade is required: short bStocks and go long the Perp. Without borrowable inventory, that trade cannot happen. Anyone with cash can buy into a discount. Not everyone has stock to sell into a premium.
That is why the article says bStocks should not be judged mainly by listing count. Borrow depth, borrow rate, available lendable inventory, and the stability of borrow through event-heavy weekends determine whether the market has two-way correction capacity. Without borrow, bStocks remain an asset layer. With borrow, they begin to resemble a true securities-inventory market.
The article sketches a flywheel as well: market-making demand increases borrow demand, borrow demand pushes rates higher, higher rates attract more deposits, and deeper deposits feed bStocks trading and usage in return.
For CEX bStocks, deeper markets still come back to borrow
Inside Binance’s CEX, the same constraint appears more clearly, according to the article. If customers are heavily selling NVDAB, market makers can buy NVDAB and short NVDAUSDT to hedge, with the bid side mostly consuming cash. If customers are heavily buying NVDAB, market makers have to keep delivering stock to them. Once inventory is exhausted, a venue without borrow leaves the market maker with only a few options: reduce ask size, raise offers, or step back.
That means bStocks spot order books carry an inherent inventory problem. Without borrow, a market maker can only quote around the stock already on hand. With borrow, inventory becomes a resource with a price rather than a hard cap. The market maker can borrow NVDAB, sell it to customers, and hedge with a long Perp or stock. Rising borrow demand lifts the borrow rate, which can then attract more holders to contribute bStocks into inventory pools.
Borrow also fixes the reverse-basis problem described earlier. When Perps are expensive and bStocks are cheap, long bStocks plus short Perp is available to nearly anyone. When bStocks are expensive and Perps are cheap, the market needs short bStocks plus long Perp. Without borrowable stock, that arbitrage chain breaks.
The article adds that borrow does not work alone. Deep CEX liquidity also needs stock-to-bStocks conversion to replenish inventory, portfolio margin to reduce the capital burden of hedging bStocks against Perps, and market-maker programs to convert inventory into bids and offers. Maker rebates may persuade market makers and protocols such as Pundi X Basket to run automated quoting strategies, but borrow determines whether those bots actually have stock to sell.
The author summarizes the structure this way: Perps generate orders, bStocks provide stock inventory, and borrow makes that inventory move. If borrow develops, bStocks can move from “tradable stock tokens” toward “securities inventory that can be market-made, financed and arbitraged in both directions.”
The endgame is four linked markets, not bStocks versus Perps
The article ultimately frames the goal as interaction among four markets rather than a contest between two products. If borrow, conversion and on-chain depth become mature, one NVIDIA risk line could carry four prices at once. In that environment, a cross-venue trader first asks which market is rich and which is cheap, not what next year’s EPS might be.
If DEX NVDAB trades at 201 while the Perp sits at 199.60, the expensive leg can be sold and the cheap leg bought. If the trader lacks bStocks inventory, the solution is borrow. If the trader lacks cash, the solution is collateral. If the trader does not want outright NVDA exposure, delta can be neutralized on the other side. Once the cash market reopens, stock, bStocks and Perp basis relationships can be used to rebalance inventory again.
In that picture, bStocks stop looking like a standalone trading product. They become an asset format that allows risk to move between stock, CEX spot, DEX, Perps and credit. Price, in turn, is not something one venue simply declares. It is formed after arbitrageurs across venues keep pressing spreads tighter with their own balance sheets.
The article’s closing argument
The article closes by saying that once price, turnover, trade frequency, order-book structure and stock inventory are considered together, bStocks sit far beyond the narrow label of “tokenized stock.”
If Binance wants influence over post-close stock pricing, Perps are the part that moves first. The article restates that in one NVDA sample, Perp turnover reached 99 times that of bStocks; over six pure weekends SNDK traded $2.922 billion; SPCX traded $1.546 billion; and SKHYNIX exceeded $2.4 billion over six UTC weekend windows. To the author, those figures show that some equity-risk trading is already shifting into 24/7 derivatives markets after traditional stock venues close.
But the same data also show that volume and price discovery are not interchangeable. SNDK could still get the direction wrong after hundreds of millions in weekend volume. Four names together could still misread the next open despite $461 million in trading. Once SPCX is included, the Sunday direction score across 25 U.S. close-to-reopen samples is still only 13 out of 25, or 52%. SNDK’s $2.922 billion breaks down into about 7.3 fills per second, while SPCX’s $1.546 billion works out to about 3.45 fills per second. The article argues that these high-turnover numbers cannot simply be interpreted as equally large pools of independent investor opinion.
Perps solve the problem of keeping the market quotable while cash equities are closed. But for a quoted price to gain credibility, the market also needs a mechanism for correcting it when it is wrong. The article says bStocks are that mechanism. They can serve as the inventory leg for market makers hedging Perps, the spot leg for basis traders, the core holding for longer-term investors, collateral in lending systems, stock exposure inside DEX LPs, and a cross-time-zone inventory tool through stock conversion. If borrow matures, bStocks can also become the securities inventory that short sellers need, allowing overpriced conditions to be arbitraged as well.
The relationship, in the article’s final formulation, is this: Perps produce the first version of the price, and bStocks turn that first version into an asset that can be held, financed, moved and falsified.
The original post cited by the repost is available at https://x.com/agintender/status/2088240935276876180?s=20. WuBlockchain’s repost notice says the material is shared for information purposes only, does not constitute investment advice and does not represent WuBlockchain’s own view or position.