PANews published a long-form analysis by danny arguing that Binance’s real target in weekend equities is not just longer trading hours. The bigger ambition, according to the piece, is to compete for price-setting power after traditional stock markets close.
The framework in the article is straightforward: use perpetual contracts to seize the price high ground, and use bStocks to absorb inventory and provide a correction layer.
Why the article starts with CBOT
The piece opens with an analogy from the early history of the Chicago Board of Trade, or CBOT. When CBOT was established in 1848, Chicago was becoming a major grain hub in the American Midwest. Railroads and canals were bringing wheat and corn into the city, but one shipment of wheat was not the same as another. Grain differed by farm, by harvest year and by quality. Without knowing what exactly was being bought, buyers had little basis for a unified market price.
According to the article, one of CBOT’s first major functions was not financial engineering in the modern sense, but standardization. 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 had also been formalized.
That may sound closer to warehouse administration than to a breakthrough in finance, but the article argues that the warehouse changed the market’s structure. Once grain entered large elevators and became part of a graded inventory system, participants no longer had to ask which farm a given bag of wheat came from. Trade could happen against a standardized grade. The piece cites the U.S. Federal Reserve’s historical review of the period, saying grading and standardized storage reduced transaction costs and created the conditions for a liquid market.
Only after that did futures become central. Farmers could sell future harvests in advance, merchants could buy future supply, and speculators could bet on price changes without moving thousands of bushels themselves. The article says CBOT evolved from early forward and “to-arrive” trading into standardized futures, and by the second half of the 19th century Chicago grain futures were already serving as a venue for price discovery, risk management and public quotations.
The point the author wants to emphasize is that while futures eventually became the larger and faster market, what kept the market tied to reality was the warehouse system behind it.
A weekend sample that frames the debate
The article then shifts to Binance. During one weekend in August 2026, stock perpetuals tied to NVDA, TSLA, SNDK and SKHY recorded about $461 million in combined trading volume on Binance. By Sunday, all four perpetuals were trading above the previous cash-market close. When the U.S. cash market reopened on Monday, all four opened lower.
SNDK is presented as the clearest example from that weekend. Its perpetual contract traded about $338 million. The Friday cash close was $1,212.21, the Sunday price reached $1,223.98, but the Monday cash open came in at $1,203.41.
The article contrasts that with a different SNDK result from the U.S. Independence Day long weekend a month earlier. Cash trading had stopped at $1,745, but Binance traded the name at $1,841.88 on Sunday, and the Monday cash open was $1,828.68. The U.S. market then reopened with an opening gap of about 4.8%. Binance’s weekend market had already priced in most of the move, though it overshot the final opening level.
That contrast is the article’s setup. The same product could, in one case, pre-trade most of Monday’s gap correctly and, in another, get the direction wrong after hundreds of millions of dollars of turnover. For the author, that moves the debate beyond “longer hours” and into market structure. Volume, the piece argues, is not the same thing as pricing power.
The target is the first price after the cash market closes
The article says there is a temporal gap in stock markets. After 4 p.m. in New York on Friday, companies can still release news, macro policy can still shift, supply chains can still move, and geopolitical events do not wait for Nasdaq to reopen. Capital continues to revalue those risks. The issue is not a lack of information, but where that information can be expressed with actual positions while cash equity books are closed.
If one market can absorb stock risk while NYSE, Nasdaq, KRX and Hong Kong are closed, it has a shot at forming the first version of the next price before the underlying cash market reopens.
The article breaks Binance’s relevant products into three roles:
- Direct Stock handles real securities, corporate actions and the interface with traditional markets.
- bStocks turns a stock into an asset that can be held, converted, bridged and pledged.
- TradFi Perps handle long-short positioning, leverage and continuous trading.
In that structure, the author says the best candidate to move first is not bStocks but Perps, because price formation starts by letting market views enter the book, and derivatives generally let participants express a view at lower cost than spot.
Why Perps move first more easily
The article uses NVDA as a concrete example. In a sample covering July 17 to July 22, NVDAB spot posted about $4.21 million in notional volume, while NVDAUSDT Perp recorded about $418 million. That is roughly a 99x difference. Looking only at the weekend, the Perp was about 37 times larger than bStocks on July 18 and 68 times larger on July 19.
The author notes that this is an internal comparison between two Binance products, not a claim that Binance’s NVDA Perp is larger than NVDA cash trading on Nasdaq. U.S. cash equity volume is still bigger. The reason for the comparison is to ask where new directional orders are more likely to go when the cash market is shut.
Spot can be bought and held for months. A Perp position, by contrast, can be opened, closed, reversed, levered up, used in basis trading and tied to funding flows, while market makers can keep re-hedging around it. The same amount of capital can generate multiple rounds of gross turnover in the derivatives venue. The distinction is even sharper on the short side. If bad news hits NVDA on a Saturday, anyone without NVDAB inventory would need to solve the borrow question first in spot. In Perps, selling is enough to express the view.
The article summarizes that first-stage path as Information → Perp → Candidate Price. Perps generate the candidate price, but they do not certify its correctness. That is where bStocks comes in.
The 25-sample framework
To examine how this process works, the article collects and organizes trading data for NVDAUSDT, TSLAUSDT, SNDKUSDT, SPCXUSDT and SKHYUSDT. There are 25 samples where the U.S. market close can be matched cleanly to the next cash open: six each for NVDA, TSLA, SNDK and SPCX, and one for SKHY.
Each sample starts at the previous cash close and runs through pure weekend trading, a Sunday price observation, Monday premarket, the opening auction and the next cash open. Sunday 19:59 ET is used as a point before regular U.S. equity premarket has started. After 04:00 on Monday, premarket trading is back. After 09:25, opening-auction information enters. The official cash open is then used as the validation point.
The article says the dataset is meant to answer four separate questions:
- How far weekend quotations are from the next cash open.
- How much real order size screen liquidity can absorb.
- How much notional value actually traded.
- Whether the turnover looks more like independent investor conviction or like market making, high-frequency trading and other systematic flows.
The author argues that a market can have a quoted price without having an executable one, it can have volume without independent judgment behind it, and it can have liquidity without necessarily possessing genuine price discovery.
Sunday direction was 13 out of 25
The error measure in the piece is the absolute distance between the Binance Perp price at a given point and the next cash open, converted into basis points. In the 25-sample set, Sunday direction matched the next cash open 13 times, or 52%, and missed 12 times.
The article says that result is not meaningfully different from a 50% random directional call. On that basis, it argues the data cannot prove stable weekend price discovery by Binance.
The author also points to a later-stage convergence figure. By 09:29:59, the error had narrowed to 11.3 bp. But the article says that should not be read as Binance “predicting” the Monday open. By then, the U.S. premarket has already been trading for hours and opening-auction information is in play. If the Perp were still materially away from the stock’s premarket price at that point, an arbitrage opportunity would exist by definition.
So the move from 181.9 bp to 11.3 bp shows that Binance Perps converge toward the next cash open as traditional markets come back online. It does not prove that Binance leads the cash market.
To answer the leadership question, the article says Binance Perps, bStocks and the same-second U.S. premarket last, bid and ask would all have to be compared in a proper lead-lag framework. If premarket moves from 100 to 105 first and the Perp follows, that is follow behavior. If the Perp goes to 105 first and premarket moves toward it, that is where price discovery and price leadership begin to matter.
Convergence before the open is not linear
The article walks through three names over the 2026 Independence Day long weekend and says the path into the open is not a straight line.
NVDA looks like a correction case. Sunday traded at $198.35, while the final cash open was $194.42, a gap of about 202 bp. By 09:25, the price was back to $194.97, and by 09:29:59 it was $194.55, narrowing the error to 6.7 bp.
TSLA got the direction right from Sunday. The cash close was $393.45, the Sunday level was $399.40 and the cash open was $397.50. The market traded the up move in advance, but the Sunday level overshot the eventual opening gap.
SNDK shows why path matters. At 09:25, the Perp was at $1,828.97 and the final cash open was $1,828.68, less than 2 bp away. By 09:29:59, however, the Perp had slipped to $1,825, pushing the error back out to about 20 bp.
The author’s point is that prices before the opening cross do not move smoothly and monotonically toward the final open. Premarket trading, NOII, market-maker inventory and last-minute order flow can all change the path. Looking only at Sunday and Monday 09:29:59 misses the full lead-lag sequence.
Perps are not always closer than bStocks
The article also uses a lower-frequency sample that compares UTC end-of-day prices for NVDAB, TSLAB, MUB and COINB with the next U.S. cash open, adding the matching Perp where data is available.
In that set, the median handoff error for eight bStocks observations is about 117.2 bp. For six comparable Perp observations, it is about 118.9 bp.
The author uses a July 23 to 24 NVDA handoff as an example. NVDAB was $207.97, the Perp was $207.99 and the next cash open was $207.45. Both were high by roughly 25 to 26 bp. The conclusion is that the value of bStocks is not necessarily to print a price closer than the Perp to the underlying equity open. Its value is to preserve a stock price formed while the market is closed as a holdable, transferable, convertible and financeable spot inventory.
The article sums that up in a simple line: Perps move the price, bStocks turn the price into an asset.
Different names show different weekend behavior
Looking at the names separately, the article says NVDA had an average absolute Sunday-to-next-open deviation of about 113 bp with direction correct in 3 of 6 cases. TSLA came in at about 81 bp with direction correct in 4 of 6. SPCX was about 149 bp with direction at 3 of 6. SNDK was the largest at about 351 bp with direction also at 3 of 6.
By 09:29:59, those descriptive average deviations had narrowed to about 11.8 bp for NVDA, 8.6 bp for TSLA, 9.4 bp for SPCX and 16.0 bp for SNDK.
The author frames NVDA as the best correction example. In the Independence Day case, Sunday was $198.35 and the cash open was $194.42, with the price then moving back toward the mid-$194 area.
TSLA is framed as the overshoot case. The market got direction right, but the Sunday move ran past the final opening gap.
SNDK is used to show both states in one name. During the Independence Day long weekend, it pre-traded most of a roughly 4.8% opening gap. In another August weekend, the Friday close was $1,212.21, the Sunday level was $1,223.98 and the Monday cash open was $1,203.41, meaning direction was wrong.
SPCX, meanwhile, is described as a different kind of experiment. According to the article, it moved from a pre-IPO Perp into a public stock, a TradFi Perp and SPCXB, all within Binance’s product stack. That makes it useful for watching how a 24/7 pricing system connects to a cash market that arrives later.
SPCX as a pricing experiment
The article gives SPCX its own section because its structure differs from the other names. It says Binance Futures launched SPCXUSDT in May 2026 as the first Pre-IPO Perpetual, designed to trade SpaceX’s future public-market valuation. After SpaceX listed, SPCXUSDT became a standard TradFi Perp, and Binance added SPCX Direct Stock and SPCXB.
That created an uncommon market sequence: Pre-IPO Perp → Public Stock → TradFi Perp → bStocks. For NVDA and TSLA, Binance added a 24/7 risk layer around an already mature market. For SPCX, the article says the continuously traded derivative got a stable Monday cash open only after the stock itself appeared, making repeated validation possible.
Across six full weekends, SPCXUSDT had Sunday direction correct 3 times out of 6. The average absolute deviation to the next cash open was about 148.8 bp, with a median of about 134.4 bp. By Monday 04:00, that average deviation had fallen to 114.1 bp. At 08:00 it was 102.0 bp, at 09:00 it was 53.8 bp, at 09:25 it was 29.3 bp and by 09:29:59 it had dropped to 9.4 bp.
The article says all six cases were directionally aligned with the final opening gap after 08:00, but because premarket had already resumed by then, that curve shows price handoff and convergence, not independent discovery by Binance alone.
SPCX also concentrated the overshoot pattern. In the three weekends when Sunday direction was right and the 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 Aug. 10.
The Aug. 10 path is singled out in detail. The Friday close was $133.11, Sunday had already reached $135.57 and the Monday cash open was $134.95. That Sunday price was only about 46 bp above the final open. But by 08:00 Monday, SPCXUSDT briefly surged to $138.80, widening the gap to about 285 bp, before falling back to $134.86 by 09:29:59, just 6.7 bp away from the final cash open.
The article also looks at turnover. Across six weekends, SPCXUSDT traded about $1.546 billion, roughly 10 times the comparable NVDA figure, with about 3.58 million underlying fills, averaging 3.45 fills per second. The author says that is not a quiet spot-style market. It looks more like a continuously running programmed risk engine. For bStocks, the implication is that once Perp turnover speeds up and customers produce net order flow, market makers need an inventory leg such as SPCXB or SPCX to absorb delta.
Weekend volume does not map cleanly to natural investor demand
The article compiles six-weekend turnover figures as follows: NVDAUSDT at about $154 million, TSLAUSDT at about $107 million, SPCXUSDT at about $1.546 billion and SNDKUSDT at about $2.922 billion.
That creates a clear ranking: SNDK first, SPCX second, NVDA third and TSLA fourth. SPCX is about 10 times NVDA and about 14 times TSLA, yet only around half of SNDK. The author points out that this ranking does not scale neatly with market capitalization or traditional brand recognition, which is why gross volume should not be translated directly into natural investment demand.
There is another figure the article highlights. In the last five minutes before the open, average turnover across the six observations was still about $26.64 million for SNDK, $18.88 million for SPCX, $2.49 million for NVDA and $2.01 million for TSLA. The point is that the Perp market is not sitting still waiting for the opening cross. It is still actively repricing.
Frequency matters more than ticket size
When the article breaks down SNDK’s $2.922 billion and SPCX’s $1.546 billion into fills, the market shape changes. SNDK generated about 7.57 million fills across six weekends, or about 7.3 fills per second. SPCX generated about 3.58 million fills, or about 3.45 fills per second. NVDA had about 640,000 fills, or about 0.62 per second.
The biggest difference, the article argues, is not in average fill size but in trading frequency. SNDK’s average raw fill was about $386, SPCX’s about $432 and NVDA’s about $241. SPCX’s median ticket was about $171, close to SNDK’s $173. In other words, the large turnover in SNDK and SPCX was not built by a few giant prints. It came from denser trading activity.
The piece says it cannot identify accounts or determine how many independent participants, institutions or market makers were behind those fills. Even so, from size and frequency alone, the author leans toward the view that tens of billions in turnover should not be treated as an equal amount of independent investor opinion. In the article’s framing, SNDK and SPCX have both become high-speed stock-derivatives markets, with SNDK simply running faster.
SPCX’s intraday weekend distribution adds another layer. From midnight to 6 a.m. Eastern, it still contributed about 20.8% of weekend gross notional and about 20.9% of raw fills, averaging about 2.9 fills per second. Across six weekends, taker buy/sell notional imbalance was about -1.16%, close to two-way balance. The article says that profile looks more like a round-the-clock market produced jointly by market making, systematic trading and cross-market arbitrage.
Perps and bStocks may be serving different order types
The article then compares those Perp figures with a Binance Research report on bStocks. On the Perp side, SNDK’s average raw fill was about $386, SPCX’s about $432 and NVDA’s about $241. The median aggTrade size for SPCX and SNDK was about $171 and $173, respectively.
Binance Research, the article says, found that about 93% of bStocks trades were fractional trades, with a median trade size of just $18.81, and that about 80% of tokenized-stock activity came from users in emerging markets.
The author notes that the methodologies differ, so the figures cannot be used to infer that Perp users take positions 20 times larger on average. Still, put side by side, they suggest a division of labor. bStocks are better suited to small-ticket spot exposure, long-term inventory, cross-time-zone retail users and on-chain users. Perps are better suited to leverage, basis trading, market making, high-frequency strategies and high turnover capital.
One market forms holdable stock inventory. The other lets the same risk change hands at high speed. The article says a functioning price network appears only when market makers and arbitrageurs connect the two.
Why bigger Perp volume increases the need for bStocks
If Perp volume can run tens of times larger than bStocks, why does Binance still need bStocks? The answer, the article says, sits on a market maker’s balance sheet.
Customer and market-maker Perp positions mirror each other. If customers are net long, the market maker is short the Perp and needs to buy positive delta via bStocks or the underlying stock. If customers are net short, the market maker is long the Perp and needs to sell bStocks inventory or borrow bStocks and sell them.
Perps solve for speed. bStocks solve for where risk sits on the balance sheet. If net customer flow keeps leaning one way, a market maker’s delta builds up. That risk cannot stay inside the derivative forever. At some point it needs an inventory leg.
For that reason, the article says heavy Perp turnover is not evidence that bStocks are unnecessary. It is part of the argument for why they matter. The faster derivatives turn over, the more important inventory, financing and stock borrow become.
1:1 backing as a terminal constraint
The article warns against treating bStocks as a simple spot anchor in the same way USDT is anchored to the dollar. At least in weekend equities, it says the analogy does not hold. Converting NVDAB into NVDA stock on a Saturday does not mean a same-second cash arbitrage can be completed on Nasdaq. What the holder has is inventory that can ultimately reconnect to the real stock, not an instantly executable cash-market leg.
That is why the article calls 1:1 backing a terminal constraint. Market participants know bStocks can ultimately connect back to the real stock, and they know the cash market will reopen. That means weekend prices can deviate, but once the deviation exceeds funding cost, inventory cost, event risk and execution friction, traders have an incentive to wait for the traditional market to reopen and then compress the gap.
In that framing, bStocks do not tell Perps the “correct” price in real time. They attach to the candidate price an inventory that can be held, hedged and arbitraged. That is why the author says “inventory layer” and “correction layer” are more accurate descriptions than “anchor.”
Once bStocks are on-chain, circulation matters
The article then turns to on-chain distribution. If NVDAB stays only inside a Binance Spot account, it is just an internal CEX inventory layer. Once bStocks move on-chain, they can enter DEXs, lending systems, collateral frameworks and margin structures, changing market structure in the process.
The article lists several examples:
- PancakeSwap has listed pools for bStocks including TSLAB, NVDAB, MUB and SNDKB.
- Lista supports some bStocks as collateral for borrowing stablecoins.
- Aster allows eligible bStocks to enter Multi-Assets Mode.
- Youcanshortit.com lets users lend out bStocks with leverage.
- Pundi X Basket lets users build customized portfolios and index-style baskets that others can follow.
These are not solving the same problem, the author says, but they all push in the same direction: making NVDAB, SNDKB and SPCXB tradable, pledgeable, financeable, market-makable and hedgeable rather than static wallet assets.
The article distinguishes between added utility and added liquidity. Locking NVDAB into a lending protocol as collateral increases utility, but it does not necessarily create a new buy or sell order in the market. Inventory begins to increase effective liquidity only when it can be borrowed by market makers, arbitrageurs or short sellers and then routed into CEXs, DEXs or Perp hedges.
The ideal loop, in the article’s telling, is not simply Binance → Wallet → DEX. It is bStocks → DEX / Lending / Credit Pool → Market Maker → Perp Hedge → CEX → Stock Conversion. Inventory starts to matter when the same unit can be used multiple times across different accounts.
That is why TVL is not the key metric in the author’s framework. The more important question is how many times a unit of stock inventory can be used. The article gives a simple example: if $1 million of NVDAB just sits locked in a protocol, it remains static. If part of it can be borrowed by a market maker for quoting, hedged via a Perp and then recycled back into the inventory pool after trades, it starts functioning as infrastructure.
The article also cites Binance’s own research saying 2,806 users engaged in approximate arbitrage-style trading across bStocks, Perps and Equity, involving about $216 million, and that about 58.5% of bStocks users also used Perps and/or Equity.
It outlines two possible paths. One is to pledge NVDAB, borrow stablecoins and then use those stablecoins on a CEX to trade NVDAUSDT Perps. Another is to place NVDAB into a DEX LP and hedge the LP’s stock delta using NVDAUSDT Perps. In that sense, bStocks link CEX Perps, CEX Spot, real stock, DEXs, lending and stablecoins into a single risk network.
The missing piece is borrow
One of the article’s strongest arguments is that the system needs borrow more than it needs more tickers. It distinguishes between borrowing against NVDAB as collateral to obtain USDT, which is financing, and borrowing NVDAB itself and then selling it, which is stock borrow. Both involve lending, but they do different things for price formation.
If Perps are expensive and bStocks are cheap, arbitrageurs can buy bStocks and short the Perp. That trade is relatively easy. Buy the cheap spot leg and sell the rich derivative leg, and the premium narrows.
If bStocks are expensive and Perps are cheap, the trade should run in reverse: short bStocks and buy the Perp. The problem is that without borrowable inventory, the trade cannot be executed. When an asset is cheap, cash is enough to buy it. When it is rich, not everyone already has stock to sell.
That is why the article says bStocks maturity should not be judged by listing count alone. Borrow depth, borrow rate, available inventory and borrow stability during event weekends determine whether the market can correct in both directions. Without borrow, bStocks remain an asset layer. With borrow, they start to look more like a securities inventory market.
The article sketches a feedback loop: market-making demand drives borrow, borrow demand lifts rates, higher rates attract more deposits, and larger inventory pools support more bStocks trading and demand.
For CEX depth, borrow still sits at the center
Back on Binance’s centralized exchange, the same logic becomes more visible. If customers heavily sell NVDAB, market makers can buy NVDAB and short NVDAUSDT to hedge. That mainly consumes cash on the bid side. If customers heavily buy NVDAB, market makers must keep selling stock to them. Once inventory runs out, and without borrow, they can only cut ask size, widen the quote or step away.
The result is a natural inventory constraint in the bStocks spot book. Without borrow, market makers quote around whatever stock they physically hold. With borrow, inventory stops being a hard cap and becomes a priced resource. A market maker can borrow NVDAB, sell it to customers and hedge with long Perp exposure or with the underlying stock. Rising borrow demand increases the borrow rate, which can attract more holders to place bStocks into inventory pools.
Borrow also solves the reverse-basis problem discussed earlier. When the Perp is rich and bStocks are cheap, long bStocks plus short Perp is broadly available. When bStocks are rich and Perps are cheap, short bStocks plus long Perp is the needed correction trade, and without borrowable inventory that trade path breaks.
The article also says borrow is not enough on its own. To deepen CEX liquidity, Binance would also need stock-to-bStocks conversion to replenish inventory, portfolio margin to reduce capital use in bStocks-Perp hedges, and market-maker programs to turn inventory into firm bids and offers. Maker rebates can encourage market makers and protocols such as Pundi X Basket to run bots, but borrow determines whether those bots actually have inventory to work with.
The section’s core formula is simple: Perps generate orders, bStocks provide stock inventory and borrow makes that inventory mobile.
The end state is coordinated markets, not Perps versus bStocks
The article says the real endgame is not bStocks competing against Perps. It is four markets connecting to each other once borrow, conversion and on-chain depth are more mature. At that point, the same NVIDIA risk could exist at four prices at once.
In that world, a cross-venue trader is not first asking about next year’s EPS. The first question is where the asset is expensive and where it is cheap. If NVDAB is 201 on a DEX and the Perp is 199.60, the expensive leg can be sold and the cheap leg bought. If there is no bStocks inventory, it can be borrowed. If there is no cash, existing assets can be posted as collateral. If the trader does not want outright NVDA exposure, delta can be locked on the other leg. When the cash market reopens, inventory can be adjusted according to the basis across stock, bStocks and Perps.
In that setup, bStocks stop being just another standalone trading product. They become the asset format through which risk moves across Stock, CEX Spot, DEX, Perp and Credit. Price is then not something a single exchange simply declares. It is something arbitrageurs compress into existence across venues and balance sheets.
What the article says to watch next
Using only AUM, 24-hour volume and ticker count to judge bStocks would miss their role in market structure, the article says. Volume and liquidity matter, but gross volume is also affected by high-frequency rotation and systematic turnover.
If Binance wants bStocks to function as the inventory layer for a weekend stock market, the author says borrow depth, executable spot depth, conversion capacity and Perp-bStocks basis stability may matter more than listing hundreds of extra tickers or posting a larger top-of-book in any single name.
The article’s closing argument is that Perps solve the problem of keeping prices moving when the market is closed. But whether that first price becomes a credible market price depends on who can hold it, finance it, move it, hedge it and prove it wrong. That is where bStocks, stock conversion and borrow enter.
Its final formula is blunt: Perps produce the first version of the price, and bStocks determine whether that price can become an asset that is held, financed, transported and falsified by the market.
The article ends with a scenario. If major news hits NVIDIA on a Saturday, NVDAUSDT might move first. NVDAB could then reprice, the Perp-bStocks basis could widen, borrow rates could shift, DEX LP positions could be rebalanced, market makers could adjust inventory and arbitrageurs could compress the spread. Once the U.S. premarket comes online and then the 09:30 opening cross arrives, the more important question would no longer be whether Binance guessed right over the weekend. It would be whose price the market is moving toward.
In the article’s final judgment, if Binance keeps chasing traditional markets once premarket starts, it is just a 24/7 stock exchange. If the cash market begins moving toward prices that were traded for hours across Perps, bStocks, DEXs, lending venues and inventory markets, and if external OTC desks, risk systems and market-data systems begin referencing those prices, then Binance would be gaining more than extra trading hours. It would be gaining pricing power.