Track market-moving stories before they get noisy

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A Hyperliquid perpetual linked to Anthropic’s implied value traded after the company’s investor briefing this week, with a reported $1.95 trillion mark and almost $21 million of turnover in the previous 24 hours. The contract is a wager settled between traders. It grants no Anthropic stock, no claim on company earnings and no ability to redeem for a share. Its most important unresolved question is how a market sets a reference price for a company whose shares do not trade publicly.

Summary

MarketWatch reported an Anthropic linked Hyperliquid contract near $1.95 trillion on October 15.
Its reported 24 hour trading turnover was almost $21 million at that snapshot.
The io:ANTH market is a builder deployed perpetual operated by Entropy, not an Anthropic share.
HIP 3 puts oracle selection and market parameters in the hands of the deployer.
A $1 move in io:ANTH’s quoted price represents $1 billion of implied company value.

MarketWatch’s October 15 observation said the indicative contract fell 4%. The name of a private company on a trading screen can make the instrument look like a share. In Entropy’s io:ANTH market it is a cash settled derivative built under Hyperliquid’s HIP 3 framework. Anthropic neither issued it nor received proceeds when one trader bought from another.

Prior coverage of Hyperliquid’s pre IPO markets explained the rise of synthetic company exposure. Today’s hook is sharper because Anthropic has been discussing its financials with prospective investors while the derivative generates a price minute by minute. The way that price is produced deserves more attention than whether its last tick was green or red.

A market cap quote is not a share price
The io:ANTH instrument is quoted in units of implied billions of dollars of Anthropic value, according to FalconX’s examination of its contract design. A displayed price around 1,950 corresponds to an indicative $1.95 trillion company valuation. A move from 1,950 to 1,900 is a 50 point fall, or $50 billion in the convention used by this market. It does not mean $50 billion left Anthropic or that investors sold $50 billion of its shares.

MarketWatch’s nearly $21 million is gross notional trading turnover in a day, not the amount of equity exchanged. Dividing $1.95 trillion by $21 million gives roughly 92,900. The ratio is a deliberately simple scale comparison, not a liquidity metric: the valuation mark is roughly 93,000 times the reported daily derivative turnover. It shows why a small market can display a very large implied company value without buying anything close to that value in underlying shares.

The market does not know an authoritative public share count and a continuously traded share price from which to calculate an ordinary equity market capitalization. Its quotation convention bypasses that problem by expressing the view as a valuation number directly. Another venue could quote an expected share price using its own assumed capitalization and share count. The two numbers are not directly comparable until those assumptions are reconciled.

An Anthropic employee or early investor holding actual shares would have a different legal position. Private share transfers can require approval and may be subject to restrictions. A perp trader has an exchange position with collateral, funding and liquidation terms. It can move in the same direction as an eventual IPO price, but it is not a substitute for a shareholder vote, distributions or a legally enforceable claim on Anthropic’s assets.

Entropy defines the market that appears on Hyperliquid
Hyperliquid’s HIP 3 documentation says an independent deployer sets a market’s definition, oracle and specifications and operates its oracle prices, leverage limits and settlement. The base platform supplies an order book and margin infrastructure. For io:ANTH, Entropy is the deployer. Calling it simply a Hyperliquid listing can hide the company that chooses the key contract terms.

The documentation says a deployer must maintain 500,000 HYPE staked and can be slashed through validator voting for certain irregular actions affecting protocol operation. That mechanism is relevant to malicious or disruptive deployer behavior; it is not a guarantee that the Anthropic valuation is accurate. Hyperliquid’s own guidance cautions that an oracle is most suitable when there is a well defined external price hard to manipulate. A private company’s value is precisely the case where external observations are sparse.

Entropy’s interface terms describe perpetual futures as synthetic and warn that oracle feeds can be stale or manipulated, that funding changes, and that a leveraged position can lose its collateral through liquidation. The terms do not promise best execution. Such provisions should be read as actual product conditions, not dismissed as generic crypto boilerplate when the underlying company has no public stock price.

The operator can run a market before an IPO because buyers and sellers can take opposing positions in a collateralized contract. No Anthropic employee needs to sell a share into the venue. The system only has to keep those positions margined and define how gains, losses and a possible final settlement are calculated. The hard part is choosing a credible price path when no public underlying trade resolves the disagreement.

BREAKING: Anthropic picks Nasdaq for IPO at a potential $2T valuation

The move would put Anthropic above SpaceX’s reported $1.75T valuation, as the AI company heads toward a major public debut amid renewed debate over AI safety and extinction risks. pic.twitter.com/Oio2oho0Yh

— crypto.news (@cryptodotnews) September 13, 2026

The oracle has to use the market it helps govern
The FalconX analysis describes Entropy’s pre IPO oracle as a blend of external private market information and the contract’s own order book. The weight given to the local market depends on executable two sided depth near the midprice, while an external component remains. Private transactions and funding round marks can be intermittent, and their economic rights may differ from those of ordinary common shares.

This creates a feedback problem. A deep order book can be a useful price discovery venue, but if the oracle starts to rely more on that book, its own participants have a greater role in the reference used for funding and margin. Liquidity around the midprice must be executable, not just displayed orders that vanish before a trade. The deployer’s methodology, parameter updates and market data matter more than a one day percentage move.

The Hyperliquid developer rules describe oracle submissions and the mark calculation, including order book inputs and limits on update frequency and abrupt mark changes. The platform’s ordinary BTC spot oracle, described elsewhere in its docs, is not automatically the oracle for an independently deployed private company perp. Confusing those designs would give io:ANTH a false aura of external exchange price verification.

If a thin book pushes the displayed trade far from a private market reference, funding payments and risk rules can pull positions toward the contract’s mark over time. They cannot prove the mark equals what a buyer would pay for actual private shares. A prospective IPO may eventually supply a public trading reference, but there can be important differences between the contract’s settlement formula and the first listed share price.

Anthropic’s briefing supplies news, not a settlement price
Reuters reported on the investor presentation, citing people who attended. The report said Anthropic disclosed third quarter revenue growth of 45% from the preceding quarter. Prospective investors can use such figures in negotiations, and perp traders can react to the report. A presentation does not produce a continuous stock price or an obligation for Anthropic to honor the perpetual market’s valuation.

Different interpretations of the financials can justify very different implied company values. Revenue is not profit; quarterly growth does not automatically continue for years; capital spending, competition and share terms matter. A private round may give investors preferences that ordinary shares or a synthetic perp do not have. A headline valuation can be a negotiation outcome for a particular security class, not a universally executable price for all company ownership.

Markets can sometimes anticipate a public valuation. Traders who follow the company closely may aggregate information faster than a static funding round mark. FalconX argues that pre IPO derivatives can contribute to price discovery around a listing. The opposing case is serious: a liquid, competitive book can be more current than a months old private transaction. Its strength depends on depth, independent participants and how closely the eventual settlement mechanism is tied to a real public market.

The October 15 turnover is evidence of trading interest, not proof of pricing accuracy. A market can trade frequently at a price that later looks wrong. Some participants may be hedging exposure elsewhere, some expressing a directional view, and others trading funding or volatility. Public notional turnover does not reveal their identities or whether a single position is being repeatedly opened and closed.

Earlier Anthropic markets make the distinction important
Crypto.news’s report on the Ventuals team’s move noted that a previous Hyperliquid based Anthropic and OpenAI market experiment had been shut down. The current io:ANTH contract is operated by Entropy under its own specifications. The existence of one market in the past does not preserve its quotes, open interest or settlement terms in a later deployer’s product.

The HIP 3 product explainer explains that outside teams can create perps. Such openness expands the range of tradable exposures, but means a user must identify which team deployed the particular market. Different Anthropic contracts on different platforms may use a different unit, oracle, leverage cap or resolution rule while sharing a company name.

An investor buying a tokenized private share through a regulated special purpose structure would have yet another claim: potentially a contractual interest in an entity holding shares, with custody and transfer restrictions. That is not what io:ANTH represents. The phrase tokenized Anthropic can blur equity backed exposure and a cash settled forecast. Product documents, not the ticker, determine what the holder owns.

If Anthropic does list, a perp may transition toward a listed market reference or settle under its rules. The timing, share class, first trading session and final reference could all matter. No October 15 MarketWatch price is a promise that future public investors will pay the same valuation. The operator’s current specifications and any later notices should be checked before claiming a one to one conversion.

Leverage turns a small valuation move into a large account move
A trader posts collateral for exposure larger than the cash committed. If a position has three times exposure, a 5% adverse move in its reference price corresponds to about 15% of initial collateral before funding, fees and maintenance margin. Liquidation can arrive before an eventual recovery or a future IPO clarifies the company’s value. That example uses simple arithmetic, not the live terms of a particular user’s position.

Funding payments can accumulate even if the indicative company value does not change. Long and short traders exchange payments under a formula designed to keep a perpetual market aligned with its reference. A thin or uncertain external anchor can alter that relationship. The trade is therefore about the path of the market, not only the final belief about Anthropic’s eventual public valuation.

A sharp news event can strain a book with relatively modest executable depth. A stop or liquidation is governed by the mark and margin system, and the price at which a trader can exit depends on actual bids and offers. Turnover of $21 million over a day says nothing precise about the amount available within 1% of the current price for a large order. Order book depth and slippage should accompany any claim that the market is a reliable valuation signal.

Earlier reporting on a SK Hynix perp dislocation illustrates how a synthetic company market can produce contentious marks and liquidations. It concerns a different asset and operator. It is relevant as a mechanical warning, not evidence that the same error occurred in io:ANTH today. No incident is showed by the October 15 decline alone.

What the price can and cannot tell an IPO investor
The $1.95 trillion mark reports a marginal price within Entropy’s Anthropic contract at a particular time. It is an observable expression of the traders participating there. It cannot show Anthropic’s issued share count, its enterprise value after debt and cash, the terms of a future offering or the price at which actual shareholders can sell. A valuation may be a useful signal without becoming an independent appraisal.

A better comparison would put dated private funding or tender terms, any IPO filing and the perp’s implied value side by side, adjusting for share rights and timing. If the gap persists after a public share begins trading under a reliable oracle, the contract’s basis and funding will explain whether convergence occurred. Until then, a large nominal mark attached to relatively small turnover should be described as this market’s indication, not the company’s settled worth.

The named operator matters in any dispute. Hyperliquid provides settlement infrastructure, Entropy sets the market specific inputs, and traders supply bids, asks and collateral. Anthropic is the subject of the wager but is not a counterparty. A holder seeking a correction to an oracle or clarification of settlement would need the deployer’s published process, not Anthropic investor relations.

The $21 million turnover does not fund the company
Consider two traders exchanging a contract with $10,000 of notional exposure. The same position can be bought and sold repeatedly, adding to volume on every execution, without a share moving or Anthropic receiving any cash. Gross 24 hour notional is therefore a measure of trading activity, not capital invested in the underlying company. Open interest counts positions that remain outstanding; executable order book depth indicates what can trade near the mark now. Each metric answers a different question.

The implied market value is especially easy to misread because Entropy’s quote compresses billions of dollars into a single index point. A 1% move near $1.95 trillion corresponds to roughly $19.5 billion in the quotation convention. If only millions of dollars of derivative notional changed hands, the market has repriced a reference, not transferred $19.5 billion between buyers and sellers. Traders’ actual gains and losses depend on their exposure size, entry price, funding and fees.

Nor is the mark an offer to acquire Anthropic in full. A negotiated acquisition would involve control, liabilities, approvals and shareholders with distinct rights. A funding round prices a specific security with its own preferences. The perp expresses the marginal balance of buyers and sellers in one synthetic instrument. Comparing those values may be interesting, but treating them as interchangeable prices erases the terms each one measures.

A reader seeing two different Anthropic valuations in the same week should ask whether they refer to a private funding round, an IPO target, a derivative market cap unit or an enterprise value calculation. A headline number can be correct within its convention while being wrong as a statement that the company has been sold. Precise attribution protects the distinction.

An oracle dispute would reach the deployer first
Crypto.news coverage of HIP 3 access controls describes how deployers can set additional conditions for their markets. The HIP 3 rules put the price input and market operation with Entropy. Hyperliquid validators apply protocol rules and can vote on slashing for irregular behavior affecting the system, but its documentation says the system should not intervene in every subjective disagreement about an oracle. A trader convinced that a private valuation input is too high does not automatically have a protocol level remedy. The trader may simply take the other side in the market, subject to margin and liquidity.

The external component of Entropy’s blend is hard for outsiders to reproduce if it draws on private deal indications and market making quotes. The local order book is more visible, yet displayed depth can change quickly. An audit of a sharp mark move would need the dated input prices, the depth calculation, parameter settings and the deployer’s signed oracle updates. Public onchain actions can show what the deployer submitted; they cannot by themselves prove the undisclosed private market data were representative.

One concern is circularity: a derivative mark influences funding and liquidation, while the same derivative book partly informs that mark. The stronger counterargument is that a live book with meaningful two sided depth can contain fresher information than a stale private funding round. Entropy’s weighting design aims to let the market speak more when that depth exists. Whether it succeeds is observable around independent news and, eventually, a public listing reference.

A change to the upper or lower valuation bounds could matter even when no company news occurs. FalconX described operator discretion over some parameters and a scheduled resolution if the company remains private. A holder should verify the current contract specification, not assume a screenshot from August still governs an October position. Any material change should be dated against open interest and communicated before readers are asked to treat a price series as continuous.

A public listing might not settle every disagreement
A conventional share price becomes observable when Anthropic lists, but a derivative tied to market capitalization still needs a share count and rules for which shares and session count. IPO shares could trade differently from restricted pre IPO holdings. A first day print may be volatile or thin compared with a later closing average. The contract’s documentation, not a generic definition of an IPO, determines whether it transitions to a public oracle, closes positions or continues with adjusted terms.

If Anthropic delays a listing, the synthetic market may remain active while external evidence stays sparse. FalconX described a scheduled end and cash settlement path for Entropy’s pre IPO contracts. A long horizon exposes traders to funding and operator decisions before any company event. The final formula could rely on a trailing average of the contract’s own mark, which would be a settlement to the market’s internal history rather than to a verified sale of shares.

This explains why a hedge with io:ANTH is imperfect for an actual private shareholder. The shareholder’s economic interest can change with the terms of its shares, dilution, transfer restrictions and an eventual public conversion. The perp’s reference can diverge, and its collateral can be liquidated before that shareholder can sell. A trader can still use it to express a view on value, but the basis risk remains even if the headline valuation looks similar.

The decisive evidence arrives when a public filing details share count, financials and offer terms, then when shares trade with enough depth to anchor a reference. Until that sequence, the market supplies a price for its contract. It does not supply a title deed for a piece of Anthropic.

Today’s valuation has more than one denominator
Reuters’s report on Anthropic’s investor briefing gives a financial event that actual IPO buyers may weigh. A derivative market can react to it immediately while investors in a future offering negotiate access, allocation and share terms. The same revenue headline might raise expectations of growth and concern about spending on computing at once. Without detailed costs and the final capital structure, a price to revenue multiple inferred from the $1.95 trillion mark is at best an illustration.

The accounting unit also matters. Entropy quotes a company value convention directly, while a conventional stock market price multiplies a share price by a disclosed diluted share count. A new issue in an IPO increases the number of shares and brings cash into the company. Employee options and other convertibles can add dilution. A pre IPO synthetic mark can be close to a quoted IPO target yet differ materially from a properly diluted public equity value when the documents arrive.

A public filing may reveal classes with different voting or economic rights, commitments to investors or a reserve of shares for employees. Private holders can face lockups after a listing. A perp trader’s position has none of those rights or restrictions in the same form; it has its own collateral and funding rules. Explaining those differences is not a claim that the market is useless. It locates what the market is pricing and what a reader cannot infer from it.

The reported four percent fall on October 15 is not a standalone referendum on the briefing. It coincides with public reporting and wider market conditions, while the derivative’s own funding and order flow can move its mark. A causal claim would need a time series comparing the news release, quotes across venues and changes in depth. The MarketWatch snapshot alone provides the price change and turnover, not who sold or why.

Distinguishing risk from a bad prediction
A trader could accurately anticipate Anthropic’s eventual IPO valuation and still lose money on a leveraged pre IPO perp. A temporary drawdown can liquidate the account. Funding can drain collateral while the prediction takes months to play out. A contract may resolve under a trailing average before the desired company event or change parameters under its published governance. Accuracy about the company is therefore insufficient; the timing and contract path matter.

The reverse is possible. A trader might profit from buying an underpriced contract and selling it weeks later even if Anthropic ultimately lists below the earlier mark. The profit would be a transfer from another derivative participant, not evidence that the initial price correctly described the private company’s long term worth. A functioning speculative market can have valuable price discovery and still produce many wrong interim prices.

FalconX’s research presents the positive case that liquid pre IPO trading can precede and help anticipate a public market. Its historical examples are informative, but Anthropic has a different investor base, growth profile and disclosure schedule. A market that predicts one listing does not have a guarantee on the next. A comparison after Anthropic’s actual listing would have to date each derivative quote and account for differences in contract units and share terms.

The contract’s operator and exchange infrastructure can publish enough information for that comparison. Dated oracle inputs, funding history, executable depth, open interest and any contract updates would allow outsiders to assess how the indicated valuation was formed. Without those records, the $1.95 trillion figure risks being repeated as a company fact when it is a venue specific market mark.

What to watch

Entropy specifications: Any change to io:ANTH’s oracle, leverage, valuation unit, funding or resolution terms.
Executable depth: Bid and ask amounts near the mark, alongside volume and open interest at a dated snapshot.
External evidence: Anthropic’s actual offering documents or verified private share transactions with comparable rights.
Oracle behavior: The gap between local book, published oracle and mark during major news or low liquidity.
Listing event: Whether a public share price becomes available and how the contract’s stated settlement process uses it.

FAQ

Can I buy Anthropic stock through the io:ANTH perp?
No. The Entropy contract is a synthetic perpetual on implied valuation. It conveys no Anthropic share or ownership rights.

What did the $1.95 trillion number mean?
It was MarketWatch’s October 15 snapshot of the valuation implied by the Hyperliquid linked market, not a completed sale of Anthropic at that price.

Did Anthropic receive the $21 million traded?
No. The reported amount was 24 hour notional turnover in a derivative market. It was not a company capital raise.

Who operates io:ANTH?
Entropy operates the market as a HIP 3 deployer using Hyperliquid’s trading infrastructure. The deployer sets market specific oracle and risk parameters.

How is a price possible without public shares?
Traders bid and offer a synthetic contract, while its operator defines a reference using market and external inputs. No public stock sale is needed for the derivative to trade.

Is the quote a per share price?
No. A point in io:ANTH’s price corresponds to $1 billion of implied company value under the contract’s convention.

Can a trader be liquidated before an IPO?
Yes. A leveraged perpetual position is margined continuously and can be closed under exchange risk rules after an adverse mark move, regardless of a later listing.

Is this a verified valuation of Anthropic?
No. It is a price in a particular synthetic market whose liquidity and oracle design should be evaluated. This is educational analysis, not investment advice.

Disclaimer: This article is for information and educational purposes only and does not constitute financial or investment advice. Figures reflect regulatory filings and reporting available at the time of writing and change with each disclosure. Nothing here is a recommendation to buy, sell, or hold any security or asset. Always do your own research. Information is accurate as of October 15, 2026.

Ripple Prime, the prime brokerage unit of Ripple, has added real-world asset (RWA) perpetual swaps for institutional clients, with the products referencing perpetual futures listed by Trade.xyz on Hyperliquid.

The swaps cover more than 100 reference markets across equities, equity indices, exchange-traded funds, metals, energy and foreign exchange, Ripple said Thursday, adding that trading and settlement are available around the clock, including weekends.

RWA perpetual swaps are crypto derivative contracts that let users trade traditional financial assets using leverage without an expiration date. Market maker Virtu is among the institutional clients already trading the products, Ripple said.

"Virtu is ramping up across emerging liquidity pools, and Ripple Prime's 24/7 cross-margining across asset classes helps us expand our presence more efficiently as markets move toward round-the-clock access,” said Scotte Moegling, head of business development for digital assets at Virtu.

Ripple Prime acts as the principal in the trades, while the value of the swaps is linked to the Trade.xyz perpetual futures listed on Hyperliquid.

RLUSD accepted as collateral Clients can use Ripple's RLUSD stablecoin as collateral for the RWA swaps, although its availability may differ by jurisdiction, Ripple said.

Ripple Prime also lets clients manage margin across different assets, meaning they may need less collateral if some positions reduce the risk of others.

Ripple said clients can manage their trading through one counterparty and see their margin requirements and risks across their entire portfolio in one place.

Ripple Prime was formed after Ripple completed its $1.25 billion acquisition of non-bank prime broker Hidden Road last year. The platform supports digital assets, foreign exchange, fixed income, derivatives and swaps through one institutional account.

Ripple Prime added support for Hyperliquid in February, allowing institutional clients to access the decentralized derivatives venue while managing margin alongside their other positions.

The new RWA swaps are currently offered through Ripple Prime's CIV BVI license. Ripple said it plans to make them available from more regions, but did not give a timeline or name the next markets.

The Funding newsletter:  Stay on top of the latest crypto VC funding and M&A deals, news, and trends with my free bi-monthly newsletter, The Funding. Sign up here!

On October 15, 2026, Ripple announced that Ripple Prime had launched real-world asset perpetual swaps for institutional clients. The products reference more than 100 markets and can be traded and settled 24/7. Ripple did not identify a launch time, contract identifier, trading volume or notional amount in the announcement.

The reference markets span equities, equity indices, exchange-traded funds, metals, energy and foreign exchange. Virtu is among the institutional clients already trading the products, according to Ripple. The announcement names the client and product scope, but does not disclose Virtu’s positions, collateral balance or trade size.

How the swaps connect to Hyperliquid Ripple Prime is the principal in the RWA swaps. The swaps reference perpetual futures contracts listed by Trade.xyz on Hyperliquid, which Ripple described as a decentralized derivatives venue. This means a Ripple Prime client faces Ripple Prime through a single counterparty relationship while the product’s reference contracts come from a separate venue.

That structure is narrower than a claim that the institutions themselves are trading directly on Hyperliquid. Ripple’s wording places the client transaction inside its prime brokerage: the swaps are traded through Ripple Prime as principal. It places the referenced perpetual futures on Hyperliquid through Trade.xyz. The announcement does not say the RWA swaps are issued on the $XRP Ledger, and it provides no $XRP Ledger transaction or contract address.

The product extends access beyond the operating hours of the traditional markets represented by the contracts. Ripple said the reference markets trade continuously, including weekends. A client can therefore manage exposure to the named traditional asset classes outside normal exchange hours without waiting for the relevant cash market to reopen.

The derivatives do not transfer the referenced shares, funds, metals, energy products or currencies to the client. The release describes swaps that take their reference from perpetual futures. It does not describe delivery or tokenization of the underlying assets. For practitioners, that distinction determines what can be independently checked: Trade.xyz’s listed contracts provide the market reference, while Ripple Prime remains the stated principal for the institutional swap.

The reference design also separates three roles. Trade.xyz lists the perpetual futures, Hyperliquid is the derivatives venue named by Ripple, and Ripple Prime enters the RWA swap as principal with its client. A user evaluating venue risk and counterparty risk therefore needs to assess the referenced market and the prime-broker relationship separately. The release confirms the arrangement but does not publish the contractual fallback used if a reference market is unavailable.

Margin, collateral and counterparty setup Ripple Prime said clients can cross-margin the RWA swap exposures against other asset classes supported by the prime broker. The company also said clients can use Ripple USD, or $RLUSD, as collateral for RWA swap transactions. Together, those features put the new positions into the same counterparty, risk-management and margin framework as a client’s other supported exposures.

Cross-margining is the practical capital change in the release. An institution does not have to treat each RWA swap position as a completely separate collateral account if Ripple Prime supports the other offsetting or related asset class. Ripple describes the result as consolidated margin across the client’s portfolio. The release does not publish the applicable haircuts, margin formulas, liquidation thresholds or eligible offset rules, so a client still needs those terms from Ripple Prime before comparing the product with direct venue access.

The $RLUSD collateral option has a jurisdictional limit. Ripple states that $RLUSD availability may differ by jurisdiction and directs clients to their Ripple Prime representative. The release does not say whether $RLUSD is the sole stablecoin accepted for these swaps, what collateral conversion rules apply, or whether availability matches every market covered by the CIV BVI offering.

Virtu described the cross-margining feature from the client side. Scotte Moegling, its head of business development for digital assets, said Ripple Prime’s “24/7 cross-margining across asset classes helps us expand our presence more efficiently as markets move toward round-the-clock access.” Ripple did not identify any other participating institution in the announcement.

Ripple framed continuous access as a way for institutions to respond to market developments, manage positions and deploy capital across traditional and digital asset markets. That ability may matter most outside the hours of the referenced cash market. The announcement does not explain how Ripple Prime handles price formation, risk limits or collateral calls when a cash market is closed but its related perpetual market continues trading.

Availability and what remains open The offering is currently available through Ripple Prime’s CIV BVI license. Ripple said it intends to offer the product from additional regions in the near future, but it did not name those regions or provide a date. The current legal entity matters because access, client eligibility and the availability of $RLUSD collateral can differ across jurisdictions.

The announcement says institutional clients can respond to market developments, manage positions and deploy capital across traditional and digital asset markets on a continuous schedule. It also says the same setup gives clients centralized risk management through one counterparty. Those are product capabilities claimed by Ripple, not evidence that every referenced market has continuous liquidity at the same depth or spread. The release provides no order-book statistics, open interest, execution costs or weekend liquidity data.

For operators, the immediate diligence questions are concrete. They need the list of more than 100 reference markets, the contract specifications used by Trade.xyz, Ripple Prime’s margin and liquidation terms, and the rules governing $RLUSD collateral in their jurisdiction. None of those detailed schedules appears in the release. They also need to know whether portfolio offsets remain available during stressed markets and how the prime broker values a referenced contract when the corresponding traditional venue is closed.

The next milestone is regional expansion, although Ripple supplied no date. Until it names the additional regions and publishes their eligibility and collateral terms, the verified scope remains the CIV BVI offering, with Ripple Prime as principal, Trade.xyz perpetual futures on Hyperliquid as references, and 24/7 trading and settlement for the institutional RWA swaps.

Bitcoin rebounds to break through $81,000

According to HTX market data, Bitcoin has rebounded to break through the $81,000 level, with its 24-hour decline narrowing to 2.89%.

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Elon Musk: Experienced roughly 6 "AI psychotic episodes" over the past year, stunned by AI’s demonstrated aesthetic capabilities.

Dongcha Beating AI News Flash: Elon Musk recently stated at an X Takeover event that he has experienced roughly six instances of so-called "AI psychosis" over the past year, adding that his immersion in AI may be "quite severe." What most shocked him was that AI began showing an understanding of aesthetics and taste. Musk said he found it hard to believe when he noticed AI seemed capable of judging what is beautiful and what constitutes good taste. This reaction stems more from the cognitive shock of AI capabilities exceeding expectations rather than a formal medical diagnosis. "AI psychosis" is not a medical term with a unified clinical definition. On one hand, it is used to describe the risk that AI interactions may reinforce users’ unrealistic perceptions; on the other, it has gradually become a popular meme in Silicon Valley’s tech circle, used to tease practitioners’ extreme optimistic expectations driven by the rapid advancement of AI capabilities.

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BlackRock CEO Warns: U.S. Economy Will Fall Into Recession If Data Center Construction Is Halted, National Debt Reaches $40 Trillion

BlackRock CEO Larry Fink said in an interview with CNBC on Wednesday that the U.S. would enter a recession if it imposes some form of moratorium on data center construction. He pointed out that current U.S. economic growth is highly dependent on capital expenditure related to data centers, and restricting such construction would not only hit the stock market, but also impact multiple industrial sectors including construction workers, energy infrastructure, and AI computing hardware. Fink argued that some concerns over data centers' environmental impact and energy costs are rooted in "misinformation", stressing that "data centers are not the problem". According to Moody's estimates, U.S. data center capital expenditure planned for this year is around $700 billion, with cumulative spending projected to reach $2.4 trillion to $2.48 trillion by 2030, while global related spending could hit $7 trillion at that time. Fink also warned that U.S. national debt has surged from $8 trillion in 2000 to $40 trillion in 2026, and the government's expanding borrowing needs are exerting significant pressure on credit markets, with Treasury auction sizes also growing. He called for unlocking more private capital to help the U.S. economy achieve 3% growth.

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Trader Loracle turns multiple US stock short positions from losses to profits, logging around $3.76 million in daily gains.

According to TradingBeats, after the release of the U.S. September CPI data, the Loracle address (starting with 0xefe4) posted a single-day profit and loss (PnL) of approximately $4.72 million, an increase of about $3.76 million compared to the nearest snapshot taken before the CPI announcement. Meanwhile, all six U.S. stock contract short positions held by this address—SNDK, NVDA, ORCL, CRWV, MU, and PLTR—are in profit, with a total position value of roughly $48.28 million and an unrealized gain of around $4.55 million. In September, the total unrealized loss on the three U.S. stock short positions (SNDK, MU, and NVDA) held by the address stood at approximately $7.23 million. Currently, both the SNDK and NVDA short positions have turned to unrealized profit, while the loss on the MU short position has narrowed significantly. The address currently holds the following U.S. stock perpetual contract short positions: - SNDK: ~15,800 shares, position value ~$21.28 million - NVDA: ~88,500 shares, position value ~$19.41 million - MU: ~10,400 shares, position value ~$9.13 million - ORCL: ~41,900 shares, position value ~$5.39 million - PLTR: ~23,000 shares, position value ~$4.56 million - CRWV: ~34,300 shares, position value ~$2.19 million

1 seconds ago

A crypto whale opened a 25x leveraged long position on Ethereum (ETH) worth $7.05 million.

According to TradingBeats monitoring, a whale address starting with 0x007d opened a 3,000 ETH long position 4 hours ago, using 25x full leverage. Its average entry price is approximately $2,400, with the current position value at around $7.05 million, an unrealized loss of about $150,000, and a position return of roughly -53%. ETH on Hyperliquid is currently trading at approximately $2,349, down roughly 2.1% from the address's average entry price.

1 seconds ago

Policy uncertainty under the Trump administration has driven central banks to reallocate gold reserves, as gold holdings in London vaults approach 10,000 tons.

The Financial Times reported that U.S. policy uncertainty, tariff risks, and the precedent of frozen overseas sovereign assets are prompting some central banks to re-evaluate the locations of their gold reserves, with London emerging as one of the beneficiaries. New York still dominates gold futures and derivatives trading, but London’s advantages in physical gold storage, over-the-counter (OTC) trading, and central bank reserve management have become more prominent. The Netherlands’ central bank moved around 86 tons of gold from the U.S. and Canada to London between March and August this year, lifting London’s share in its total gold reserves of 612.4 tons from 18.1% to 32.1%. The Dutch central bank said the move aims to improve the tradability and accessibility of its gold in the event of severe crises. Data from the London Bullion Market Association (LBMA) shows that as of the end of September 2026, commercial vaults in London and the Bank of England’s vaults held a total of 9,821 tons of gold, up 1.96% month-on-month, worth about $1.3 trillion. London’s mature OTC system allows gold lending, swaps, and trading without physically moving bullion, boosting the liquidity of physical gold. The freezing of Russia’s overseas sovereign assets after the Russia-Ukraine conflict has also made countries pay more attention to the jurisdiction of reserve assets and their availability in extreme cases. However, there are currently no signs that central banks are fully withdrawing from the U.S. gold custody system. Asian financial hubs such as Singapore and Hong Kong are also accelerating the construction of gold storage and trading infrastructure, and the global gold market is taking shape with New York leading derivatives, London focusing on physical gold, and Asia accelerating its development.

1 seconds ago

Not financial or tax advice. PANews content is strictly educational and informational and is not investment advice, financial advice, tax advice, legal advice, or a solicitation to buy or sell any digital asset, security, or financial product. Do your own research and consult qualified advisers.

Disclosure. PANews may publish sponsored content, partner content, advertisements, affiliate links, event promotions, and market commentary involving Web3 projects, service providers, or financial products. PANews personnel, contributors, or affiliates may hold digital assets or other interests related to covered topics. See our Terms of Service.

This site is protected by reCAPTCHA.

Making Millions in 2 Years: Here’s How This Hyperliquid (HYPE) Trader Did It

Bitcoin rebounds to break through $81,000

According to HTX market data, Bitcoin has rebounded to break through the $81,000 level, with its 24-hour decline narrowing to 2.89%.

1 seconds ago

Elon Musk: Experienced roughly 6 "AI psychotic episodes" over the past year, stunned by AI’s demonstrated aesthetic capabilities.

Dongcha Beating AI News Flash: Elon Musk recently stated at an X Takeover event that he has experienced roughly six instances of so-called "AI psychosis" over the past year, adding that his immersion in AI may be "quite severe." What most shocked him was that AI began showing an understanding of aesthetics and taste. Musk said he found it hard to believe when he noticed AI seemed capable of judging what is beautiful and what constitutes good taste. This reaction stems more from the cognitive shock of AI capabilities exceeding expectations rather than a formal medical diagnosis. "AI psychosis" is not a medical term with a unified clinical definition. On one hand, it is used to describe the risk that AI interactions may reinforce users’ unrealistic perceptions; on the other, it has gradually become a popular meme in Silicon Valley’s tech circle, used to tease practitioners’ extreme optimistic expectations driven by the rapid advancement of AI capabilities.

1 seconds ago

BlackRock CEO Warns: U.S. Economy Will Fall Into Recession If Data Center Construction Is Halted, National Debt Reaches $40 Trillion

BlackRock CEO Larry Fink said in an interview with CNBC on Wednesday that the U.S. would enter a recession if it imposes some form of moratorium on data center construction. He pointed out that current U.S. economic growth is highly dependent on capital expenditure related to data centers, and restricting such construction would not only hit the stock market, but also impact multiple industrial sectors including construction workers, energy infrastructure, and AI computing hardware. Fink argued that some concerns over data centers' environmental impact and energy costs are rooted in "misinformation", stressing that "data centers are not the problem". According to Moody's estimates, U.S. data center capital expenditure planned for this year is around $700 billion, with cumulative spending projected to reach $2.4 trillion to $2.48 trillion by 2030, while global related spending could hit $7 trillion at that time. Fink also warned that U.S. national debt has surged from $8 trillion in 2000 to $40 trillion in 2026, and the government's expanding borrowing needs are exerting significant pressure on credit markets, with Treasury auction sizes also growing. He called for unlocking more private capital to help the U.S. economy achieve 3% growth.

1 seconds ago

Trader Loracle turns multiple US stock short positions from losses to profits, logging around $3.76 million in daily gains.

According to TradingBeats, after the release of the U.S. September CPI data, the Loracle address (starting with 0xefe4) posted a single-day profit and loss (PnL) of approximately $4.72 million, an increase of about $3.76 million compared to the nearest snapshot taken before the CPI announcement. Meanwhile, all six U.S. stock contract short positions held by this address—SNDK, NVDA, ORCL, CRWV, MU, and PLTR—are in profit, with a total position value of roughly $48.28 million and an unrealized gain of around $4.55 million. In September, the total unrealized loss on the three U.S. stock short positions (SNDK, MU, and NVDA) held by the address stood at approximately $7.23 million. Currently, both the SNDK and NVDA short positions have turned to unrealized profit, while the loss on the MU short position has narrowed significantly. The address currently holds the following U.S. stock perpetual contract short positions:
- SNDK: ~15,800 shares, position value ~$21.28 million
- NVDA: ~88,500 shares, position value ~$19.41 million
- MU: ~10,400 shares, position value ~$9.13 million
- ORCL: ~41,900 shares, position value ~$5.39 million
- PLTR: ~23,000 shares, position value ~$4.56 million
- CRWV: ~34,300 shares, position value ~$2.19 million

1 seconds ago

A crypto whale opened a 25x leveraged long position on Ethereum (ETH) worth $7.05 million.

According to TradingBeats monitoring, a whale address starting with 0x007d opened a 3,000 ETH long position 4 hours ago, using 25x full leverage. Its average entry price is approximately $2,400, with the current position value at around $7.05 million, an unrealized loss of about $150,000, and a position return of roughly -53%. ETH on Hyperliquid is currently trading at approximately $2,349, down roughly 2.1% from the address's average entry price.

1 seconds ago

Policy uncertainty under the Trump administration has driven central banks to reallocate gold reserves, as gold holdings in London vaults approach 10,000 tons.

The Financial Times reported that U.S. policy uncertainty, tariff risks, and the precedent of frozen overseas sovereign assets are prompting some central banks to re-evaluate the locations of their gold reserves, with London emerging as one of the beneficiaries. New York still dominates gold futures and derivatives trading, but London’s advantages in physical gold storage, over-the-counter (OTC) trading, and central bank reserve management have become more prominent. The Netherlands’ central bank moved around 86 tons of gold from the U.S. and Canada to London between March and August this year, lifting London’s share in its total gold reserves of 612.4 tons from 18.1% to 32.1%. The Dutch central bank said the move aims to improve the tradability and accessibility of its gold in the event of severe crises. Data from the London Bullion Market Association (LBMA) shows that as of the end of September 2026, commercial vaults in London and the Bank of England’s vaults held a total of 9,821 tons of gold, up 1.96% month-on-month, worth about $1.3 trillion. London’s mature OTC system allows gold lending, swaps, and trading without physically moving bullion, boosting the liquidity of physical gold. The freezing of Russia’s overseas sovereign assets after the Russia-Ukraine conflict has also made countries pay more attention to the jurisdiction of reserve assets and their availability in extreme cases. However, there are currently no signs that central banks are fully withdrawing from the U.S. gold custody system. Asian financial hubs such as Singapore and Hong Kong are also accelerating the construction of gold storage and trading infrastructure, and the global gold market is taking shape with New York leading derivatives, London focusing on physical gold, and Asia accelerating its development.

1 seconds ago

Bitcoin rebounds to break through $81,000

According to HTX market data, Bitcoin has rebounded to break through the $81,000 level, with its 24-hour decline narrowing to 2.89%.

1 seconds ago

Elon Musk: Experienced roughly 6 "AI psychotic episodes" over the past year, stunned by AI’s demonstrated aesthetic capabilities.

Dongcha Beating AI News Flash: Elon Musk recently stated at an X Takeover event that he has experienced roughly six instances of so-called "AI psychosis" over the past year, adding that his immersion in AI may be "quite severe." What most shocked him was that AI began showing an understanding of aesthetics and taste. Musk said he found it hard to believe when he noticed AI seemed capable of judging what is beautiful and what constitutes good taste. This reaction stems more from the cognitive shock of AI capabilities exceeding expectations rather than a formal medical diagnosis. "AI psychosis" is not a medical term with a unified clinical definition. On one hand, it is used to describe the risk that AI interactions may reinforce users’ unrealistic perceptions; on the other, it has gradually become a popular meme in Silicon Valley’s tech circle, used to tease practitioners’ extreme optimistic expectations driven by the rapid advancement of AI capabilities.

1 seconds ago

BlackRock CEO Warns: U.S. Economy Will Fall Into Recession If Data Center Construction Is Halted, National Debt Reaches $40 Trillion

BlackRock CEO Larry Fink said in an interview with CNBC on Wednesday that the U.S. would enter a recession if it imposes some form of moratorium on data center construction. He pointed out that current U.S. economic growth is highly dependent on capital expenditure related to data centers, and restricting such construction would not only hit the stock market, but also impact multiple industrial sectors including construction workers, energy infrastructure, and AI computing hardware. Fink argued that some concerns over data centers' environmental impact and energy costs are rooted in "misinformation", stressing that "data centers are not the problem". According to Moody's estimates, U.S. data center capital expenditure planned for this year is around $700 billion, with cumulative spending projected to reach $2.4 trillion to $2.48 trillion by 2030, while global related spending could hit $7 trillion at that time. Fink also warned that U.S. national debt has surged from $8 trillion in 2000 to $40 trillion in 2026, and the government's expanding borrowing needs are exerting significant pressure on credit markets, with Treasury auction sizes also growing. He called for unlocking more private capital to help the U.S. economy achieve 3% growth.

1 seconds ago

Trader Loracle turns multiple US stock short positions from losses to profits, logging around $3.76 million in daily gains.

According to TradingBeats, after the release of the U.S. September CPI data, the Loracle address (starting with 0xefe4) posted a single-day profit and loss (PnL) of approximately $4.72 million, an increase of about $3.76 million compared to the nearest snapshot taken before the CPI announcement. Meanwhile, all six U.S. stock contract short positions held by this address—SNDK, NVDA, ORCL, CRWV, MU, and PLTR—are in profit, with a total position value of roughly $48.28 million and an unrealized gain of around $4.55 million. In September, the total unrealized loss on the three U.S. stock short positions (SNDK, MU, and NVDA) held by the address stood at approximately $7.23 million. Currently, both the SNDK and NVDA short positions have turned to unrealized profit, while the loss on the MU short position has narrowed significantly. The address currently holds the following U.S. stock perpetual contract short positions:
- SNDK: ~15,800 shares, position value ~$21.28 million
- NVDA: ~88,500 shares, position value ~$19.41 million
- MU: ~10,400 shares, position value ~$9.13 million
- ORCL: ~41,900 shares, position value ~$5.39 million
- PLTR: ~23,000 shares, position value ~$4.56 million
- CRWV: ~34,300 shares, position value ~$2.19 million

1 seconds ago

A crypto whale opened a 25x leveraged long position on Ethereum (ETH) worth $7.05 million.

According to TradingBeats monitoring, a whale address starting with 0x007d opened a 3,000 ETH long position 4 hours ago, using 25x full leverage. Its average entry price is approximately $2,400, with the current position value at around $7.05 million, an unrealized loss of about $150,000, and a position return of roughly -53%. ETH on Hyperliquid is currently trading at approximately $2,349, down roughly 2.1% from the address's average entry price.

1 seconds ago

Policy uncertainty under the Trump administration has driven central banks to reallocate gold reserves, as gold holdings in London vaults approach 10,000 tons.

The Financial Times reported that U.S. policy uncertainty, tariff risks, and the precedent of frozen overseas sovereign assets are prompting some central banks to re-evaluate the locations of their gold reserves, with London emerging as one of the beneficiaries. New York still dominates gold futures and derivatives trading, but London’s advantages in physical gold storage, over-the-counter (OTC) trading, and central bank reserve management have become more prominent. The Netherlands’ central bank moved around 86 tons of gold from the U.S. and Canada to London between March and August this year, lifting London’s share in its total gold reserves of 612.4 tons from 18.1% to 32.1%. The Dutch central bank said the move aims to improve the tradability and accessibility of its gold in the event of severe crises. Data from the London Bullion Market Association (LBMA) shows that as of the end of September 2026, commercial vaults in London and the Bank of England’s vaults held a total of 9,821 tons of gold, up 1.96% month-on-month, worth about $1.3 trillion. London’s mature OTC system allows gold lending, swaps, and trading without physically moving bullion, boosting the liquidity of physical gold. The freezing of Russia’s overseas sovereign assets after the Russia-Ukraine conflict has also made countries pay more attention to the jurisdiction of reserve assets and their availability in extreme cases. However, there are currently no signs that central banks are fully withdrawing from the U.S. gold custody system. Asian financial hubs such as Singapore and Hong Kong are also accelerating the construction of gold storage and trading infrastructure, and the global gold market is taking shape with New York leading derivatives, London focusing on physical gold, and Asia accelerating its development.

1 seconds ago

Bitcoin rebounds to break through $81,000

According to HTX market data, Bitcoin has rebounded to break through the $81,000 level, with its 24-hour decline narrowing to 2.89%.

1 seconds ago

Elon Musk: Experienced roughly 6 "AI psychotic episodes" over the past year, stunned by AI’s demonstrated aesthetic capabilities.

Dongcha Beating AI News Flash: Elon Musk recently stated at an X Takeover event that he has experienced roughly six instances of so-called "AI psychosis" over the past year, adding that his immersion in AI may be "quite severe." What most shocked him was that AI began showing an understanding of aesthetics and taste. Musk said he found it hard to believe when he noticed AI seemed capable of judging what is beautiful and what constitutes good taste. This reaction stems more from the cognitive shock of AI capabilities exceeding expectations rather than a formal medical diagnosis. "AI psychosis" is not a medical term with a unified clinical definition. On one hand, it is used to describe the risk that AI interactions may reinforce users’ unrealistic perceptions; on the other, it has gradually become a popular meme in Silicon Valley’s tech circle, used to tease practitioners’ extreme optimistic expectations driven by the rapid advancement of AI capabilities.

1 seconds ago

BlackRock CEO Warns: U.S. Economy Will Fall Into Recession If Data Center Construction Is Halted, National Debt Reaches $40 Trillion

BlackRock CEO Larry Fink said in an interview with CNBC on Wednesday that the U.S. would enter a recession if it imposes some form of moratorium on data center construction. He pointed out that current U.S. economic growth is highly dependent on capital expenditure related to data centers, and restricting such construction would not only hit the stock market, but also impact multiple industrial sectors including construction workers, energy infrastructure, and AI computing hardware. Fink argued that some concerns over data centers' environmental impact and energy costs are rooted in "misinformation", stressing that "data centers are not the problem". According to Moody's estimates, U.S. data center capital expenditure planned for this year is around $700 billion, with cumulative spending projected to reach $2.4 trillion to $2.48 trillion by 2030, while global related spending could hit $7 trillion at that time. Fink also warned that U.S. national debt has surged from $8 trillion in 2000 to $40 trillion in 2026, and the government's expanding borrowing needs are exerting significant pressure on credit markets, with Treasury auction sizes also growing. He called for unlocking more private capital to help the U.S. economy achieve 3% growth.

1 seconds ago

Trader Loracle turns multiple US stock short positions from losses to profits, logging around $3.76 million in daily gains.

According to TradingBeats, after the release of the U.S. September CPI data, the Loracle address (starting with 0xefe4) posted a single-day profit and loss (PnL) of approximately $4.72 million, an increase of about $3.76 million compared to the nearest snapshot taken before the CPI announcement. Meanwhile, all six U.S. stock contract short positions held by this address—SNDK, NVDA, ORCL, CRWV, MU, and PLTR—are in profit, with a total position value of roughly $48.28 million and an unrealized gain of around $4.55 million. In September, the total unrealized loss on the three U.S. stock short positions (SNDK, MU, and NVDA) held by the address stood at approximately $7.23 million. Currently, both the SNDK and NVDA short positions have turned to unrealized profit, while the loss on the MU short position has narrowed significantly. The address currently holds the following U.S. stock perpetual contract short positions:
- SNDK: ~15,800 shares, position value ~$21.28 million
- NVDA: ~88,500 shares, position value ~$19.41 million
- MU: ~10,400 shares, position value ~$9.13 million
- ORCL: ~41,900 shares, position value ~$5.39 million
- PLTR: ~23,000 shares, position value ~$4.56 million
- CRWV: ~34,300 shares, position value ~$2.19 million

1 seconds ago

A crypto whale opened a 25x leveraged long position on Ethereum (ETH) worth $7.05 million.

According to TradingBeats monitoring, a whale address starting with 0x007d opened a 3,000 ETH long position 4 hours ago, using 25x full leverage. Its average entry price is approximately $2,400, with the current position value at around $7.05 million, an unrealized loss of about $150,000, and a position return of roughly -53%. ETH on Hyperliquid is currently trading at approximately $2,349, down roughly 2.1% from the address's average entry price.

1 seconds ago

Policy uncertainty under the Trump administration has driven central banks to reallocate gold reserves, as gold holdings in London vaults approach 10,000 tons.

The Financial Times reported that U.S. policy uncertainty, tariff risks, and the precedent of frozen overseas sovereign assets are prompting some central banks to re-evaluate the locations of their gold reserves, with London emerging as one of the beneficiaries. New York still dominates gold futures and derivatives trading, but London’s advantages in physical gold storage, over-the-counter (OTC) trading, and central bank reserve management have become more prominent. The Netherlands’ central bank moved around 86 tons of gold from the U.S. and Canada to London between March and August this year, lifting London’s share in its total gold reserves of 612.4 tons from 18.1% to 32.1%. The Dutch central bank said the move aims to improve the tradability and accessibility of its gold in the event of severe crises. Data from the London Bullion Market Association (LBMA) shows that as of the end of September 2026, commercial vaults in London and the Bank of England’s vaults held a total of 9,821 tons of gold, up 1.96% month-on-month, worth about $1.3 trillion. London’s mature OTC system allows gold lending, swaps, and trading without physically moving bullion, boosting the liquidity of physical gold. The freezing of Russia’s overseas sovereign assets after the Russia-Ukraine conflict has also made countries pay more attention to the jurisdiction of reserve assets and their availability in extreme cases. However, there are currently no signs that central banks are fully withdrawing from the U.S. gold custody system. Asian financial hubs such as Singapore and Hong Kong are also accelerating the construction of gold storage and trading infrastructure, and the global gold market is taking shape with New York leading derivatives, London focusing on physical gold, and Asia accelerating its development.

1 seconds ago

Not financial or tax advice. PANews content is strictly educational and informational and is not investment advice, financial advice, tax advice, legal advice, or a solicitation to buy or sell any digital asset, security, or financial product. Do your own research and consult qualified advisers.

Disclosure. PANews may publish sponsored content, partner content, advertisements, affiliate links, event promotions, and market commentary involving Web3 projects, service providers, or financial products. PANews personnel, contributors, or affiliates may hold digital assets or other interests related to covered topics. See our Terms of Service.

This site is protected by reCAPTCHA.

Hyperliquid is expanding its presence in traditional financial markets as tokenized equities gain traction across the crypto industry.

The decentralized exchange already offers perpetual futures tied to stocks and indexes through Trade[XYZ], allowing traders to speculate on equity prices around the clock without owning the underlying shares. Meanwhile, tokenized stock issuers Ondo Finance and xStocks have expanded into the Hyperliquid ecosystem, bringing traditional equity exposure to its blockchain infrastructure.

Now, EQX Labs has announced plans to launch 11 tokenized US stocks and ETFs directly on Hyperliquid’s HyperCore order book, adding another spot equity offering to the platform.

The initial markets will include tokenized versions of Apple, Nvidia, Microsoft, Amazon, Alphabet, Meta, Tesla, Micron, and SpaceX, alongside products tracking the S&P 500 and Nasdaq 100 through ETFs.

The tokens will trade as HIP-1 assets against USDC, giving eligible traders access to the markets 24 hours a day, seven days a week.

The company has not announced an exact launch date.

EQX promises share backing and zero issuer fees According to the company’s documentation, each token will be backed on a one to one basis by shares held through custodians connected to the Depository Trust Company.

The custodians include Alpaca, StoneX, and Clear Street. EQX also plans to publish custody information so traders can verify the shares backing the tokens.

The assets will be issued by EQX SPC Ltd., a British Virgin Islands segregated portfolio company. Each ticker will have a separate portfolio holding its underlying shares.

However, the tokens will not represent direct ownership of the underlying securities. Instead, holders will own limited recourse debt instruments backed by those shares, with contractual claims against the issuer.

EQX also plans to pass through certain economic benefits of stock ownership. Dividends will automatically be reinvested into additional shares after applicable withholding, while holders will be able to submit voting instructions through wallet signatures.

In addition, EQX will not charge fees for issuing, redeeming, or holding tokens. Traders will only pay Hyperliquid’s standard spot trading fees.

The company said its business will be funded through a share of those trading fees, reducing its reliance on additional charges or spreads.

Creation and redemption will be available to eligible authorized participants, while other traders will access the tokens through Hyperliquid’s order book. The products will not be offered to US persons.

Tokenized equities expand across blockchain networks The announcement comes as competition intensifies among issuers seeking to bring traditional stocks onto blockchain networks.

In August, xStocks launched tokenized US equities on HyperCore, initially introducing five assets, including Nvidia, Micron, and ETFs tracking the S&P 500 and Nasdaq 100.

Meanwhile, Ondo Finance has expanded its tokenized stock infrastructure to Hyperliquid’s HyperEVM, allowing users to transfer assets from Ethereum and BNB Chain into the ecosystem.

EQX aims to compete through its custody structure and fee model while making Hyperliquid a larger venue for equity price discovery.

The company also plans to support additional use cases, including using tokenized stocks as collateral in lending markets, hedging positions with equity perpetuals, and integrating the assets into trading strategies.

Its planned launch adds to the growing overlap between decentralized trading infrastructure and traditional equity markets, as issuers seek to extend stock trading beyond conventional exchange hours.

Disclosure: This article was edited by Estefano Gomez. For more information on how we create and review content, see our Editorial Policy.

The share-backed tokens would trade on HyperCore against USDC, with US persons excluded under EQX’s eligibility rules.

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Evernorth plans to deploy around 473 million XRP via an institutional strategy, with a current value of approximately $648 million.

U.S. public company Evernorth has selected Ripple, Kraken, Coinbase, and BitGo as its first institutional partners, and plans to deploy its approximately 473 million XRP holdings starting in the fourth quarter via institutional strategies. The holdings are currently valued at around $648 million. Evernorth went public via a SPAC merger and will also expand into lending on the XRP Ledger and on-chain DeFi strategies in the future.

1 minutes ago

Ahead of the CPI release, the probability that the U.S. Federal Reserve will hold interest rates steady in October stands at 78.4%.

According to CME Group’s FedWatch data, ahead of today’s release of U.S. September CPI figures, the probability that the Federal Reserve will hold interest rates steady in October stands at 78.4%, while the chance of a cumulative 25 basis point rate hike is 21.6%. For December, the likelihood of the Fed keeping rates unchanged is 12%, the probability of a cumulative 25 basis point hike is 69.7%, and the probability of a cumulative 50 basis point hike is 18.3%.

1 minutes ago

Strive increases its Bitcoin holdings by another 2,822 coins at an average price of approximately $83,266.

Bitcoin treasury firm Strive filed an 8-K document today disclosing that it added 2,822 Bitcoin to its holdings between October 12 and 13, at an average price of approximately $83,266 per coin. The acquisition cost $235 million, bringing its total Bitcoin position to 35,600 coins.

1 minutes ago

Tether AI Research has unveiled its on-device speech recognition model TranscribePsy, designed for smart glasses and humanoid robots.

Tether AI Research has released an open-source multilingual automatic speech recognition (ASR) model named QVAC TranscribePsy, which has around 254 million parameters and can run fully on-device—no audio upload to the cloud required. The company noted the model can process audio from smart glasses connected via Bluetooth or Wi-Fi in near real time, and also operate on onboard processors of humanoid robots. On the Core ML version for iPhone 17 Pro Max, transcribing 10 minutes of audio takes roughly 1.65 seconds. According to its published benchmark data, TranscribePsy achieves a word error rate (WER) of 8.02% on the Open ASR Leaderboard, 6.58% on Multilingual LibriSpeech, and 21.56% on Common Voice. Among six tested smartphones, it is the fastest in speed, approximately 2.6 times faster than the second-fastest model. The model supports 25 European languages for laptops and 8 European languages for mobile phones, with model weights and builds in formats including GGUF and Core ML released under the Apache 2.0 license. Tether CEO Paolo Ardoino stated that he hopes advanced speech AI can run locally on users’ own devices, ensuring data does not leave the device.

1 minutes ago

Physical Intelligence opens its robot model API: Picking strawberries, assembling servers, new actions can be trained in just 4 days.

Beating AI News Flash: U.S.-based robotics AI firm Physical Intelligence (Pi) has launched the beta version of its Pi API, opening access to its foundational robotics model to more enterprises. Developers only need to upload robot operation data to fine-tune the model on Pi’s cloud computing power, then control their own robots via the API. There’s no need to train models from scratch or build complex training and inference infrastructure independently. Pi showcased real-world use cases from multiple partners, including AgRobotics’ strawberry-picking robots, autonomous loaders for self-driving trucks, and robots for food processing and server assembly. Among these, startup Almond used the Pi API to get its dual-arm robot to learn polishing the parts required for its own assembly after just 4 days of iterative training and testing. Pi had previously open-sourced robotics models such as π0 and π0.5, but developers still had to deploy and train them on their own. This time, the company has further packaged model fine-tuning, computing power, and inference services into an API, aiming to become a shared intelligent foundation for various robots. However, test access is still by application only, and pricing has not been announced yet.

1 minutes ago

Spark: Q3 Net Protocol Revenue Surpasses $4 Million, Stablecoin Swap Layer Hits Over $14 Billion in Trading Volume in Its First Month

DeFi lending protocol Spark has disclosed that its net protocol returns exceeded $4 million in the third quarter of 2026. In the first half of the year, DeFi lending spreads narrowed significantly, with lending capital profitability turning negative in the second quarter. After driving growth for Spark Savings USDT in Q3, related returns rebounded above capital costs. During the same period, Spark partnered with Uniswap and Sky to launch a stablecoin swap layer, which went live with $150 million in USDS liquidity, offering stablecoin swap services to banks, fintech firms and payment companies, and recorded over $14 billion in trading volume in its first month.

1 minutes ago

5 hours ago

According to TradingBeats monitoring, trader Boomer (X handle: solanadoomer1) closed 5,000 ETH short positions via his Hyperliquid address 0xbf73 in the early hours of today, with the closing trade totaling around $12.6 million. He then opened a ZEC long position at an average entry price of approximately $1,222. As of now, the address holds 8,000 ZEC long positions, employs 10x full leverage, has a position value of roughly $10.01 million, an unrealized profit of about $235,000, and a position return rate of around 24%.

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3 min read

S&P 500 options are hot on Hyperliquid-based Hypercall exchange. (TyliJura/Pixabay)Summary

Hypercall has recorded $640 million in notional volume since June 1, with more than 80% coming from S&P 500 options.The platform offers daily, weekly and monthly expiries around the clock, settles contracts in USDC and has seen trading concentrate in options expiring the next day.Hypercall’s growth reflects rising demand for blockchain-based access to traditional markets, though its volume remains small compared with established options venues.Talk about options on the S&P 500 index, and you are discussing a beast of a market that trades trillions of dollars in notional volume every day. Crypto traders now appear to want to access it over a blockchain.

Hypercall illustrates the demand. The options platform built on Hyperliquid, the eighth-largest blockchain by total value locked (TVL), went live in June, and more than 80% of the $640 million in notional volume since then has come from S&P 500 options, the exchange told CoinDesk. Open interest, the value of contracts still outstanding, is about $49 million, of which $47 million is in S&P 500 options.

While the numbers are small next to traditional markets and Deribit's crypto options business, which started shortly after the platform’s 2016 debut and now routinely sees billions of dollars in daily volume and open interest, they illustrate a growing trend: the desire to access financial instruments when conventional markets are closed. Hypercall lists daily, weekly and monthly expiries, including over weekends.

"The volume is concentrated in options expiring the following day," Jake Sylvestre, founder of Hypercall, said in an email interview. "Traders can take a view on the next day's move or hold a position further out."

Traders are gravitating to blockchains for exposure to traditional markets, including derivatives. Hyperliquid’s decentralized exchange (DEX), also known as Hyperliquid, has become a go-to venue for placing trades and managing risk through perpetual futures, especially on weekends when conventional markets are closed and geopolitical tensions have repeatedly escalated.

The draw of 24/7Hypercall takes Hyperliquid’s perpetual futures into the options arena. An option is a contract that pays out if an asset ends up above or below — depending on the details — a set price by a specified date. A call option pays off when the asset finishes above that price at expiry. A put option works the other way round. Traders use both to hedge against price swings and bet on direction, volatility and time.

Each Hypercall contract has a $1 multiplier, which means each index point is worth $1 at settlement. A call with a 7,000 strike pays $100 if the index settles at 7,100. Contracts settle in USDC, a dollar-pegged stablecoin, against the average price over the final 30 minutes for Hyperliquid's S&P 500 perps.

Trading around the clock is the draw. "Hyperliquid has become the best venue for trading these markets outside exchange hours," Sylvestre said.

Hypercall’s exchange's market makers, the firms that quote prices, "hedge on Hyperliquid's perpetual futures, including on weekends when the cash equity market is closed," Sylvestre said. Earnings, economic data and company news can move an underlying asset while its home exchange is closed, and makers "have to price those events around the clock."

Hypercall isn't pitching itself as a replacement for Deribit, the Coinbase Global COIN-owned biggest crypto options venue, which mostly lists bitcoin BTC$83,212.45 and ether ETH$2,508.47 options.

"Most of our traders aren't leaving Deribit; they're trading markets Deribit doesn't list," Sylvestre said.

Two market makers are active and three more are being onboarded.

"We haven't named them publicly yet and expect to over the next few weeks," Sylvestre said. "User collateral is held on-chain," it said, but "order matching is off-chain only." Parts of margining and liquidation also run off-chain.

Individual stocksIndex options aren't the only draw. Options on SpaceX SPCX, Nvidia NVDA, Micron Technology (MU) and SanDisk (SNDK) make up more than half of all trades, followed by Apple AAPL, Microsoft MSFT, Meta META, Alibaba (BABA), ether and bitcoin.

"The breadth is in single names," Sylvestre said.

Other platforms are adding stock options too. Bybit began offering 24/7-trading on options on stock perpetuals on Sept. 17, starting with SpaceX and Nvidia. Binance, the largest crypto exchange by value traded, offers options on more than 1,000 U.S. stocks and ETFs to eligible users outside the U.S.

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Evernorth plans to deploy around 473 million XRP via an institutional strategy, with a current value of approximately $648 million.

U.S. public company Evernorth has selected Ripple, Kraken, Coinbase, and BitGo as its first institutional partners, and plans to deploy its approximately 473 million XRP holdings starting in the fourth quarter via institutional strategies. The holdings are currently valued at around $648 million. Evernorth went public via a SPAC merger and will also expand into lending on the XRP Ledger and on-chain DeFi strategies in the future.

1 seconds ago

Ahead of the CPI release, the probability that the U.S. Federal Reserve will hold interest rates steady in October stands at 78.4%.

According to CME Group’s FedWatch data, ahead of today’s release of U.S. September CPI figures, the probability that the Federal Reserve will hold interest rates steady in October stands at 78.4%, while the chance of a cumulative 25 basis point rate hike is 21.6%. For December, the likelihood of the Fed keeping rates unchanged is 12%, the probability of a cumulative 25 basis point hike is 69.7%, and the probability of a cumulative 50 basis point hike is 18.3%.

1 seconds ago

Strive increases its Bitcoin holdings by another 2,822 coins at an average price of approximately $83,266.

Bitcoin treasury firm Strive filed an 8-K document today disclosing that it added 2,822 Bitcoin to its holdings between October 12 and 13, at an average price of approximately $83,266 per coin. The acquisition cost $235 million, bringing its total Bitcoin position to 35,600 coins.

1 seconds ago

Tether AI Research has unveiled its on-device speech recognition model TranscribePsy, designed for smart glasses and humanoid robots.

Tether AI Research has released an open-source multilingual automatic speech recognition (ASR) model named QVAC TranscribePsy, which has around 254 million parameters and can run fully on-device—no audio upload to the cloud required. The company noted the model can process audio from smart glasses connected via Bluetooth or Wi-Fi in near real time, and also operate on onboard processors of humanoid robots. On the Core ML version for iPhone 17 Pro Max, transcribing 10 minutes of audio takes roughly 1.65 seconds. According to its published benchmark data, TranscribePsy achieves a word error rate (WER) of 8.02% on the Open ASR Leaderboard, 6.58% on Multilingual LibriSpeech, and 21.56% on Common Voice. Among six tested smartphones, it is the fastest in speed, approximately 2.6 times faster than the second-fastest model. The model supports 25 European languages for laptops and 8 European languages for mobile phones, with model weights and builds in formats including GGUF and Core ML released under the Apache 2.0 license. Tether CEO Paolo Ardoino stated that he hopes advanced speech AI can run locally on users’ own devices, ensuring data does not leave the device.

1 seconds ago

Physical Intelligence opens its robot model API: Picking strawberries, assembling servers, new actions can be trained in just 4 days.

Beating AI News Flash: U.S.-based robotics AI firm Physical Intelligence (Pi) has launched the beta version of its Pi API, opening access to its foundational robotics model to more enterprises. Developers only need to upload robot operation data to fine-tune the model on Pi’s cloud computing power, then control their own robots via the API. There’s no need to train models from scratch or build complex training and inference infrastructure independently. Pi showcased real-world use cases from multiple partners, including AgRobotics’ strawberry-picking robots, autonomous loaders for self-driving trucks, and robots for food processing and server assembly. Among these, startup Almond used the Pi API to get its dual-arm robot to learn polishing the parts required for its own assembly after just 4 days of iterative training and testing. Pi had previously open-sourced robotics models such as π0 and π0.5, but developers still had to deploy and train them on their own. This time, the company has further packaged model fine-tuning, computing power, and inference services into an API, aiming to become a shared intelligent foundation for various robots. However, test access is still by application only, and pricing has not been announced yet.

1 seconds ago

Spark: Q3 Net Protocol Revenue Surpasses $4 Million, Stablecoin Swap Layer Hits Over $14 Billion in Trading Volume in Its First Month

DeFi lending protocol Spark has disclosed that its net protocol returns exceeded $4 million in the third quarter of 2026. In the first half of the year, DeFi lending spreads narrowed significantly, with lending capital profitability turning negative in the second quarter. After driving growth for Spark Savings USDT in Q3, related returns rebounded above capital costs. During the same period, Spark partnered with Uniswap and Sky to launch a stablecoin swap layer, which went live with $150 million in USDS liquidity, offering stablecoin swap services to banks, fintech firms and payment companies, and recorded over $14 billion in trading volume in its first month.

1 seconds ago

Aave, Ethena and Hyperliquid founders name their biggest rivals at TOKEN2049

Starknet launches shadow accounts, enabling users to anonymously link their main wallets with DeFi activities.

According to an official announcement, Starknet has launched Shadow Accounts, allowing users to participate in public DeFi activities via an independent, self-controlled address while keeping the link between this address and their main wallet confidential. Shadow Accounts are independent pseudonymous addresses on Starknet, funded by users’ protected STRK20 balances. The first integration will launch tomorrow. While the balance, transaction history, and application positions of Shadow Accounts remain publicly visible on-chain, STRK20 protects the connection between these accounts and users’ main wallets. This means users do not need to hide their DeFi activities themselves, while reducing the likelihood that external observers can trace those activities back to their main wallets.

1 hours ago

Applied Materials forecasts its services business revenue will grow by more than 20% by 2026, and top $12 billion by 2030.

Applied Materials (AMAT.O) said it targets a non-GAAP gross margin of 54% and operating margin of 40% by 2030. It projects its services business revenue will grow by over 20% in 2026, and exceed $12 billion by 2030. The company plans to expand its R&D labs and manufacturing capacity to more than double current levels by 2030, return 80% to 100% of its free cash flow to shareholders by 2030, and lift its wafer fabrication equipment (WFE) market share by more than 2 percentage points between 2025 and 2030.

1 hours ago

Perspective: Bitcoin investors who accumulated positions at high levels have their cost prices capping upside potential, with selling pressure having notably eased.

Glassnode stated that the cost basis of investors who purchased Bitcoin at high levels continues to cap its upside potential. Following Bitcoin’s rebound to around $88,000, investors with 1 to 2-year holding periods sold off heavily, and this price level is also near the break-even point for investors who have held Bitcoin for 6 to 12 months. Bitcoin’s price subsequently faced resistance below this level, and this selling pressure has now eased significantly.

1 hours ago

21Shares Launches Synthetic Anthropic ETP on the Vienna Stock Exchange

21Shares has launched a synthetic Anthropic ETP on the Vienna Stock Exchange, trading under the ticker CLAU, providing investors with non-leveraged exposure linked to the pre-IPO implied valuation of the artificial intelligence startup. The ETP does not grant investors direct ownership of Anthropic shares, either before or after the firm goes public. The product accesses this exposure via total return swaps (TRS), tracking a reference rate compiled by Kaiko, which is calculated based on Anthropic’s perpetual futures prices on Binance.

1 hours ago

Ripple partners with Stripe-owned Privy to introduce embedded wallet functionality for the XRP Ledger.

Ripple has partnered with Stripe-owned wallet infrastructure firm Privy to integrate support for the XRP Ledger (XRPL) into Privy’s developer platform. The integration eliminates the need for developers to build their own wallet infrastructure, allowing them to add XRPL wallets to their applications with features including wallet creation and management, transaction signing, plus support for XRP, Ripple’s RLUSD stablecoin, and other assets on the network.

1 hours ago

Hyperliquid Assistance Fund Buys 48 Million HYPE for $1.36 Billion

Hyperliquid 3 Min Log Return (Topic 90) brings high-frequency log return predictions to the Allora Forge. Every 3 minutes, inference workers submit predictions over a three-minute time interval for a broad cross-section of the Hyperliquid perp market. The Allora inference network aggregates these into a synthesized prediction for each asset, designed to outperform the individual constituents over time. The Allora whitepaper explains how inference synthesis works.

Directional short-term alpha signals are an integral part of many execution and market making operations. For detailed background on how short-term directional predictions integrate with high-frequency market making systems, see Álvaro Cartea, Sebastian Jaimungal, and José Penalva, Algorithmic and High-Frequency Trading, Cambridge University Press, 2015. Sourcing these predictions through Allora makes this step easier for consumers and enables our community to deliver the secret sauce and earn.

Multi-output Topics
Allora’s recent network upgrade enables multi-output topic types. Instead of one topic per asset, we can now group many assets into a single topic. For topic 90, workers submit labeled arrays, where each element corresponds to a three-minute log return prediction for an asset.

In the Python example, your prediction callback returns a dictionary, and the SDK handles the labeled submission:

predictions = {
"btc": 0.00042,
"eth": -0.00018,
"sol": 0.00073,
}
These are illustrative log returns, not prices or probabilities: 0.00042 is approximately a +0.042% price move. Labels are lowercase asset names such as btc and eth.

Since this is a new blockchain rollout, we’ve capped each submission at 100 asset labels. Aim to submit the 100 assets with the most trailing 30-day volume. Workers will be scored on the top 90. If an asset is unavailable for a round, submit the predictions you do have; one missing asset shouldn’t kill the whole inference.

Data
Allora is now serving and supporting the Hyperliquid universe with one-minute OHLCV candle data through Atlas, our in-house data platform. At any time you can discover the universe through the dedicated current_hl_universe dataset:

curl -fsSG 'https://forge-data.allora.run/api/rows/' \
-H "X-API-Key: $ALLORA_API_KEY" \
--data-urlencode 'dataset_name=current_hl_universe' \
--data-urlencode 'limit=1000' |
jq '[.results[].values
| select(.status == "consumable" and .market_group == "perp")
| .candle_dataset_name] | sort'
This returns Atlas identifiers such as hl_btc_1min and hl_eth_1min. The market_group == "perp" filter keeps us in the native perp universe and excludes XYZ markets.

We’ve also extended the Atlas rows API to receive updates for multiple assets at the same time. That means one HTTP request for the batch, instead of a separate request per ticker. In our example runs, a routine refresh across roughly 178 assets took about 0.4 seconds, including the in-memory cache update. The full inference pass took a few seconds; transaction submission adds its own time.

For example, this requests the latest minute candle for both BTC and ETH:

curl -fsSG 'https://forge-data.allora.run/api/rows/' \
-H "X-API-Key: $ALLORA_API_KEY" \
--data-urlencode 'dataset_names=hl_btc_1min,hl_eth_1min' \
--data-urlencode 'limit=1' \
--data-urlencode 'ordering=-timestamp'
The response groups rows by dataset. Here is a shortened BTC row from an actual response, with metadata and the ETH group omitted:

{
"dataset_id": 1196859,
"timestamp": "2026-10-09T17:19:00Z",
"values": {
"open": 82615, "high": 82623, "low": 82614, "close": 82622,
"volume": 0.08883, "num_trades": 12
}
}
The timestamp is the candle’s opening time. The latest row may still be a partial candle. Increase limit to request more rows per asset, which is useful for refreshing an overlapping slice of recent history.

Builder kit integration
Corresponding to the new Atlas data endpoint, we’ve extended the Atlas data manager with some convenience methods.

AtlasDataManager.discover_hl_universe(): Atlas-specific discovery returning a list of exact dataset names for fresh, consumable native perps.
AtlasDataManager.get_bulk_1min_candles(symbols, limit=10): one multi-dataset HTTP request returning raw minute candles with asset identity preserved.

The ML workflow still works as before. Users configure AlloraMLWorkflow, call backfill() and get_full_feature_target_dataframe(), train models, evaluate through PerformanceEvaluator, and save serialized artifacts for the existing deployment flow.

The workflow already accepts multiple tickers, produces a dataframe indexed by ticker and time, shares historical/live feature extraction, and dispatches target construction through target_type.

Keep target_type="log_return". Existing multi-ticker historical dataset construction supplies the required training data with interval="3m" and target_bars=1. The following short snippet creates data, containing the input features and target for supervised ML:

import os
from pathlib import Path
import pandas as pd
from allora_forge_builder_kit import AtlasDataManager, AlloraMLWorkflow
LOOKBACK = 10 # Configurable number of past three-minute candles.
end = pd.Timestamp.now(tz="UTC").floor("3min")
start = end - pd.DateOffset(months=6)
atlas = AtlasDataManager(
api_key=os.environ["ALLORA_API_KEY"],
base_dir=Path("data"),
interval="3m",
)
universe = atlas.discover_hl_universe()
workflow = AlloraMLWorkflow(
tickers=universe,
target_type="log_return",
interval="3m",
target_bars=1,
number_of_input_bars=LOOKBACK,
data_manager=atlas,
)
workflow.backfill(start=start)
data = workflow.get_full_feature_target_dataframe(start_date=start, end_date=end)
The full example builds this dataset one asset at a time to reduce peak memory, removes unusable rows, and splits it chronologically before training.

Training and live inference
Training uses fixed, non-overlapping three-minute candles. The default input is a window of past normalized candles and the target is the close of the next unobserved candle, expressed as a log return. We pool the rows across tickers to train one model for all assets. The example uses one chronological holdout, keeping the latest 20% of observed timestamps for validation and excluding training labels that resolve after that boundary.

The example gives a light randomized search over LightGBM parameters, using six months of available historical data. In our October 8 run with a 10-candle lookback, that produced about 11.70 million training rows and 3.05 million validation rows across 178 assets. Counts depend on available history and your lookback. Tree-count checkpoints let us compare smaller and larger models without restarting each fit. The top three distinct trials are selected by lowest validation MSE, retrained on all usable data, and exported for live inference.

Our leading model passed five of the seven criteria in the pooled offline validation report, with participation assumed to be full. That’s a starting point, and this is where our community is going to help push the needle. These are validation results used during model selection; live performance is the next test. The example also reports metrics per asset and their equal-weight averages so we can compare that view with pooling all the data together.

Since inference workers are queried asynchronously, the current network scoring adopts the following conventions.

Inference resamples the historical one-minute data to the target start. Let T be the minute boundary starting the evaluation interval; the target ends at T + 3 minutes. Build the input bars backward from T so the final completed three-minute bar ends exactly at T. This aligns the live prediction with our training setup.

Example: the submission window opens at 12:01:27 UTC. The target starts at the preceding minute boundary, 12:01:00, and ends at 12:04:00. At window opening, 27 seconds of that target interval have already elapsed. The approximately 30-second submission window closes around 12:01:57; the prediction horizon still ends at 12:04:00.

The last completed input candle is labeled 11:58, covering [11:58, 12:01). The 12:01-labeled candle is separate: if Atlas has it, its latest close tells us how much the price has already drifted since the target started. The worker adds that realized log return to the model’s prediction. Each asset is checked independently; if its partial candle is missing, the worker assumes zero drift for that asset.

The worker keeps recent minute candles in memory, tops them up before opening the listener, and refreshes them in bulk when queried. Our example waits ten seconds before that refresh to let newer Atlas updates arrive, leaving roughly twenty seconds for prediction and submission. The target boundary stays fixed throughout.

The logic for adjusting raw candles for inference in real time has been designed and implemented in the topic 90 working example, in the Allora Forge Builder Kit.

The example exports the top three models found during hyperparameter search. Then use the WorkerManager for deployment and monitoring:

python notebooks/testnet/topic_90_hyperliquid_3min_logreturn/deploy_managed_example.py \
--model-run notebooks/testnet/topic_90_hyperliquid_3min_logreturn/results/model_search/RUN_TIMESTAMP \
--deploy
Replace RUN_TIMESTAMP with the run directory printed by the training script. WorkerManager allocates one address per model and starts each worker with its own in-memory data buffer. The workers keep running after the launching terminal closes. Use python -m allora_forge_builder_kit.workerctl dashboard to monitor them.

Contributing
The new topic can be found on the Allora Forge. Use the ticker dropdown to switch between assets and explore their predictions, all within the same topic.

Hyperliquid (HYPE) has experienced declining prices in recent sessions, with CoinGecko data showing its market capitalization close to $18.04 billion and a daily trading volume around $918 million. These figures highlight the token’s significant market presence and recent surge in trading activity, despite underperforming the broader cryptocurrency market, which fell 3.9% over the last week. The current downturn in HYPE appears linked to overall market liquidations, an over-the-counter (OTC) distribution of tokens, and persistent selling pressure. No single event has been confirmed as the direct cause.

Price drop accompanied by high trading activityRecent Hyperliquid price action points to considerable volatility. Over the latest 24-hour period, HYPE traded in a range between $79.52 and $85.73, indicating sharp fluctuations amid increased trader activity. The daily trading volume, nearing $918 million, is substantial relative to the total market value of the token.

CoinGecko’s data from October 13 recorded daily volume reaching close to $950 million, a 43.6% increase from the preceding day. While this spike indicates strong interest, it does not clarify how much of the selling was from major holders or whether capital was flowing out of the protocol overall.

HYPE’s price closed at $91.91 on October 6 and slid to $80.97 by October 12, marking an 11.9% decline over this period. At last check, the token traded at $81.09, remaining well below its recent highs and suggesting a sustained recovery has yet to emerge.

Trading volume surged to nearly $950 million on October 13, up 43.6% from the previous day, reflecting heightened activity during HYPE’s price decline.

Macro pressures and liquidation eventsThe broader digital asset market has also endured significant selling. Bitcoin, for example, dipped below $83,000 on October 12 as investors responded to US dollar strength, rising bond yields, and energy market uncertainty. CoinReporter noted that over $770 million in crypto positions were liquidated during this period, with the majority being forced closures of leveraged long positions.

Leveraged trading can amplify market swings, as falling below margin requirements triggers automatic liquidations, accelerating price drops and further liquidations in a feedback loop.

Analysis by CoinStats on October 13 indicated that $11.46 million in HYPE derivatives positions were liquidated within 24 hours, with long positions representing 98.2% of this total. These figures suggest that many bullish HYPE traders faced forced closures as prices dropped, but liquidations are highly dynamic across changing market conditions.

Investor attention remains on macroeconomic uncertainty as the US Consumer Price Index report is due on October 14. This inflation reading could influence expectations for US Federal Reserve policy and appetite for cryptocurrencies, likely increasing volatility but not serving as a conclusive cause for HYPE’s recent losses.

Separately, Hyperliquid Labs completed an OTC transaction involving 3.75 million HYPE tokens—valued at approximately $330 million—over October 7 and 8. The transfer included five wallets, each receiving 375,000 tokens, following a weeklong unstaking period.

The team clarified to FXStreet that these tokens would not be sold through public exchanges. While such a transaction draws attention due to its size, it does not confirm that large-scale selling occurred on the open market. The OTC transaction took place several days before HYPE’s drop, raising more questions about supply than providing a simple explanation for market weakness.

Mini dictionary: OTC (Over-the-counter) transactions are trades arranged directly between parties rather than on public exchanges, allowing large amounts to change hands discreetly.

Platform activity and market outlookDespite the drop in HYPE’s price, underlying trading activity on the Hyperliquid platform remains strong. As an on-chain ecosystem specializing in perpetual futures and spot trading, Hyperliquid reported approximately $7.04 billion in total value locked, $3.3 million in daily fees, and $2.68 million in project revenue over the most recent 24 hours.

A single day of high fees and revenue does not guarantee continued demand for the HYPE token but does indicate ongoing protocol use. The distinction between platform health and token performance remains key: increased uncertainty over supply or leverage can impact HYPE even if trading remains active.

MetricValue (Latest 24h)Total value locked$7.04 billionFees generated$3.3 millionProject revenue$2.68 millionTrading volume$918 millionPrice range$79.52 – $85.73Market watchers are monitoring possible levels for a turning point, particularly the $79.50 area as a recent low and $85.70 as a near-term high. Sustained recovery above the upper level would signal stronger buying activity.

Additionally, analysts continue to watch trading volume and derivative liquidations as indicators of whether selling pressure is subsiding or if volatility remains high. The market’s reaction to US inflation data on October 14, as well as any updates on institutional demand and token transfers, will likely shape short-term sentiment for HYPE.

The available market data point to a combination of leveraged liquidations, elevated trading activity, and uncertainty following a major OTC transaction as factors behind HYPE’s recent downward move.

In summary, Hyperliquid’s latest decline reflects overlapping market pressures rather than a single clear catalyst. Attention remains on the balance between sustained platform engagement and supply-related uncertainty as the token seeks to regain investor confidence.

Not financial or tax advice. PANews content is strictly educational and informational and is not investment advice, financial advice, tax advice, legal advice, or a solicitation to buy or sell any digital asset, security, or financial product. Do your own research and consult qualified advisers.

Disclosure. PANews may publish sponsored content, partner content, advertisements, affiliate links, event promotions, and market commentary involving Web3 projects, service providers, or financial products. PANews personnel, contributors, or affiliates may hold digital assets or other interests related to covered topics. See our Terms of Service.

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The increasing integration of AI agents into cryptocurrency markets is expected to fundamentally reshape how activity is conducted by 2028, according to a report by Fortune. The prediction suggests that AI systems will outpace human market participants, a shift that has already begun with platforms like Coinbase introducing AI-driven execution tools. Current AI systems, while still operating under human-set strategies, are progressively becoming more autonomous, indicating a trend towards AI dominance in the landscape. This potential shift is drawing attention to how platforms such as Hyperliquid could be impacted.

Market data for Hyperliquid suggests a significant drop in confidence regarding its price reaching $100 by the end of 2026. The likelihood of this outcome has decreased from 76% a week ago to 46.5% currently. This decline reflects a broader uncertainty about the platform’s ability to capitalize on the anticipated AI-driven efficiencies that could influence market sentiment positively. Market behavior indicates that while there is optimism around AI’s transformative impact, participants remain cautious about its immediate effects on specific assets like Hyperliquid.

Key Takeaways

Fortune’s report suggests a shift towards AI-driven market activity by 2028, potentially impacting market dynamics significantly.
Current market pricing for Hyperliquid reaching $100 by year-end has decreased, reflecting caution among participants.
The trend towards AI agents may indicate potential growth opportunities for platforms that can effectively integrate such technologies.

What to Watch
The progression of AI integration into crypto platforms will be closely monitored, with potential announcements from major exchanges like Coinbase or Binance potentially influencing sentiment. Developments in AI capabilities and regulatory responses will also be critical in shaping market expectations. Observers will be keen to see if Hyperliquid can leverage AI-driven efficiencies to regain market confidence and meet its year-end price target.

Term Structure

Contract
Odds
Δ since publish
Volume 24h

December 31
46.5%
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January 1 2027
1.9%
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January 1 2027
1.4%
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January 1 2027
2.9%
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January 1 2027
1.4%
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January 1 2027
5.7%
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January 1 2027
3.6%
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January 1 2027
4%
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January 1 2027
12.5%
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January 1 2027
6.5%
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A crypto whale closed out its long position in CBRS after losing approximately $6.95 million, and shifted to taking long positions in GOOGL and GME.

According to TradingBeats' monitoring, Hyperliquid whale address 0x30af…393e liquidated long positions worth approximately $36.51 million in CBRS between last night and early this morning, incurring a trading loss of around $6.95 million. During the same period, the address opened roughly 116,100 long positions in GOOGL and 607,400 long positions in GME, with the total current position value standing at about $57.42 million. The GOOGL and GME long positions currently use 20x and 10x isolated margin leverage respectively; their liquidation reference prices are approximately $344.56 and $25.56, which are around 2.37% and 5.67% lower than the current mark prices.

1 seconds ago

Morgan Stanley: Storage stocks appear to have the lowest valuations at the cycle peak, but are actually in the most dangerous situation.

Morgan Stanley’s latest report notes that Samsung and SK Hynix currently have a forward price-to-earnings (P/E) ratio of just 3 to 4 times—seemingly cheap but potentially masking a valuation trap at the cycle’s peak. Historically, storage stocks have tended to top out ahead of earnings peaks: leading by roughly 4 months in 2008 and 2012, and about 8 months in 2018. While the AI-fueled storage supercycle remains intact, tight supply-demand, rising prices, and improving earnings still offer support. But with sharp stock price gains and concentrated upward revisions to earnings forecasts, bullish expectations are already fully priced in, leaving further upside under pressure. Morgan Stanley argues that the stronger the storage sector’s fundamentals, the more easily cycle-top risks are underestimated—high growth may not translate to sustained excess returns. The report warns that high profits will eventually draw new production capacity, with supply set to gradually hit the market from the second half of 2027, potentially triggering a new cycle inflection point. Asian storage stocks have rallied roughly 9 times cumulatively since their September 2025 rally, with average consensus earnings per share (EPS) forecasts revised up by 432%. Samsung and SK Hynix’s low P/E ratios may be a classic trap for cyclical stocks near earnings peaks. To justify the upside implied by current share prices, DRAM contract prices would need to rise around 70% quarter-on-quarter—a tall order. Separately, evolving data center architectures could reshape industry chain benefit distribution: in NVIDIA’s NVL72, storage makes up ~29% of a single rack, falling to 19% when expanded to 8 interconnected racks, while network equipment’s share jumps from 10% to 20%—meaning storage makers may not proportionally benefit from AI infrastructure investment growth.

1 seconds ago

Gemini 4 Argon embedded in the new Antigravity version: three inference tiers are ready but still non-functional.

Beating AI News Flash: Google’s AI coding tool Antigravity’s 2.23.0 update has uncovered the full model identifier for Gemini 4 Argon, including three inference configurations: Low, Medium, and High. The previous 2.22.0 version lacked these elements, while the new update added 4 model IDs and 3 model selection menu names. However, these configurations are currently hidden in the program code, so regular users cannot directly select Gemini 4 Argon yet. Antigravity has also removed multiple old models simultaneously. Gemini 3.1 Pro, 3.6 Flash, and 3.7 Flash were marked for retirement on October 12; the next day, users noticed that only Gemini 3.8 Flash remained in the model list. Another developer found that the three Argon tiers are already ranked among the top three in the client’s recommended model order, but requests to their corresponding interfaces still return 404 errors. Google released Argon as early as September 30, but it is currently mainly available to vetted cybersecurity partners, with plans to later expand access to paid API and Google AI Ultra users.

1 seconds ago

Fed Governor Waller: Trump’s threat to the Federal Reserve’s independence has not yet succeeded.

Fed Governor Christopher Waller: Trump’s threat to the independence of the Federal Reserve has not yet succeeded.

1 seconds ago

Semiconductor and storage sectors were broadly lower in U.S. pre-market trading, with SanDisk and Micron down more than 3% each, and SK Hynix ADR dropping 5%.

According to market data from BIT (bit.com), semiconductor and storage sectors are broadly lower in pre-market US trading: Seagate Technology (STX) down 3.4%; Western Digital (WDC) down 3.8%; SanDisk (SNDK) down 3.3%; Micron Technology (MU) down 3.03%; SK Hynix ADR down 5%; NVIDIA (NVDA) down 0.8%; Intel (INTC) down 0.95%; Advanced Micro Devices (AMD) down 1.84%.

1 seconds ago

A crypto whale transferred 5,170 ETH to Tornado Cash, valued at $12.82 million.

According to on-chain analyst Ai Yi (@ai_9684xtpa), a whale that accumulated 5,147 ETH at an average price of $1,886.7 between August 12 and 13 transferred 5,170 ETH (valued at $12.82 million) to Tornado Cash five hours ago. The batch of tokens has an unrealized profit of $3.056 million, and the purpose of the transfer remains unknown.

1 seconds ago