Strategy bought 950 bitcoin for roughly $75.7 million last week and paid for it from cash on hand rather than new stock sales, according to an 8-K filing dated Sept. 21. The company, formerly known as MicroStrategy, now holds 846,000 BTC, its highest reported total since June.

The filing covers purchases made between Sept. 14 and 20 at an average price of $79,670 per coin. Across all holdings, Strategy has spent about $63.8 billion, an average of $75,416 per bitcoin.

A change in how the buying is funded

What marks this filing out is the funding. Strategy’s recent accumulation runs have typically been financed through at-the-market equity offerings, selling new shares to raise cash. This time the company said the purchases came from its USD Cash reserve, which stood at $1.05 billion as of Sept. 20. A second bucket, the USD Reserve, held $5.04 billion on the same date.

The same filing shows Strategy repurchased 1,771,238 shares of its STRC preferred stock for $174 million, and used $57.4 million of the USD Reserve to pay preferred dividends and interest on outstanding debt. It reported no bitcoin sales under its at-the-market offering during the week.

The shift matters because it suggests the company is no longer leaning on new share issuance to fund the treasury, after a stretch in which its preferred stock traded below par and reserve money went to servicing it. The filing discloses the buyback but not its rationale.

Mark-to-market figures from the week put the holdings at around $71.9 billion, implying roughly $8.1 billion in paper gains. Those numbers move with bitcoin’s price and should be read as a snapshot, not a balance.

846,000 BTC is more than 4% of bitcoin’s 21 million supply cap. The company’s reported peak was 847,363 BTC in June, before it sold 1,363 coins.

The U.S. Commodity Futures Trading Commission (CFTC) has issued a warning to regulated exchanges about “mention markets,” a type of prediction contract that settles based on whether a person says or does something. In a Tuesday advisory, the regulator said these contracts carry a heightened risk of manipulation and should only be listed in limited circumstances under the Commodity Exchange Act.

The guidance comes as prediction market activity draws growing regulatory scrutiny, particularly after enforcement actions tied to allegations that traders benefited from non-public information. For exchanges weighing whether to list event contracts tied to an individual’s specific words or conduct, the CFTC’s letter lays out a framework for assessing settlement verifiability and oversight readiness.

Key takeaways

• The CFTC says “mention markets” present a heightened manipulation risk because settlement depends on a person’s discrete conduct, which may not be verifiable or independently generated.
• The commission advised that there are only “limited circumstances” where mention markets can be listed consistently with the Commodity Exchange Act.
• Exchanges should evaluate oversight capabilities to detect manipulation and whether settlement criteria are independently verifiable.
• External pressure that could influence the subject’s conduct—and any related obligations the subject may have—are part of the CFTC’s review.
• The warning follows enforcement involving prediction contracts tied to political speeches, underscoring the regulator’s focus on information advantage and settlement conduct.

Why “mention markets” drew a regulator warning

In its advisory, the CFTC’s Division of Market Oversight said mention markets—contracts based on whether an individual will say certain words, attend or appear at an event, or interact with another person—may be inconsistent with the Commodity Exchange Act except in narrow cases.

The regulator’s central concern is that the settlement mechanism relies on conduct that can be neither independently generated nor externally verifiable. According to the CFTC, that structure “presents a heightened risk of manipulation” because it can make it easier for market participants to affect outcomes or profit from information advantages related to someone’s future actions.

The CFTC press release about the advisory is available via the regulator’s website: https://www.cftc.gov/PressRoom/PressReleases/9302-26.

Enforcement history is shaping the regulator’s approach

The CFTC’s warning arrives amid a string of allegations and cases where traders were accused of using privileged information to profit in prediction markets. One prominent example cited in the report involves a former White House teleprompter operator who was ordered last month to return $107,539 in profits and pay a $65,000 civil penalty related to contracts tied to then-President Donald Trump’s speeches.

Earlier coverage from Cointelegraph discussed that case in the context of how politically tied prediction contracts can intersect with information access. See: https://cointelegraph.com/news/trump-teleprompter-operator-made-100k-betting-kalshi-markets-tied-to-speeches-abc.

By emphasizing the risks tied to “discrete conduct” and limited verifiability, the CFTC’s guidance signals that settlement design matters as much as trading behavior. Even if a contract’s price action reflects legitimate market views, the regulator appears concerned when the contract outcome can be influenced—or when market participants can act on information about what a person will do or say before that conduct becomes public.

What exchanges are expected to consider

According to reporting by CNBC, the CFTC letter outlines four factors that exchanges listing mention markets should consider:

• Whether there are adequate oversight measures in place to detect manipulation.
• Whether the words or actions used for settlement are independently verifiable.
• Whether external pressure could influence the subject’s conduct, potentially affecting whether the event occurs as expected.
• What outside obligations the subject of the mention market may have, which could shape their behavior or the likelihood that the contract condition will be met.

This checklist frames mention markets not just as a novel product category, but as a compliance and risk-management challenge. Exchanges that previously treated these contracts as straightforward event bets may now need to demonstrate stronger controls around how outcomes are determined and how manipulation could realistically occur.

CFTC leadership ties the advisory to “regulatory clarity”

CFTC Chair Mike Selig publicly welcomed the guidance in an X post on Tuesday, saying that “regulatory clarity drives sound markets.” In the post, he referenced staff reminding designated contract markets (DCMs) of their obligation to list only contracts that are not readily susceptible to manipulation.

The chair’s post is available at: https://x.com/ChairmanSelig/status/2102500746834874859?s=20.

While the advisory is addressed to regulated entities, the implications extend across the broader prediction market ecosystem. As more contracts are designed around human behavior—rather than purely observable, externally confirmed outcomes—platforms may face tighter scrutiny on whether the settlement criteria can be verified without ambiguity and whether market structure could incentivize gaming of the subject’s conduct.

What to watch next for prediction markets

Exchanges considering mention markets will likely need to document how their oversight can identify manipulation and how settlement conditions can be verified. The most immediate uncertainty for market participants is how broadly regulators will interpret the “limited circumstances” standard—particularly as more politically or socially contingent contracts come under review.

The Commodity Futures Trading Commission advised some of its regulated entities on Tuesday that prediction markets’ “mentions” contracts are at greater risk of manipulation. 

In a press release announcing the letter it sent to designated contract market entities, the CFTC said that the contracts are more susceptible to exploitation “because their settlement turns on the discrete conduct of a person that may be neither independently generated nor externally verifiable.”

The letter noted that the agency was not creating new obligations that regulated exchanges need to follow, but rather advising entities on when mention markets may be listed consistent with the Commodity Exchange Act, the law that governs the assets that the CFTC regulates. 

Mention markets — which are made up of contracts that ask traders what specific words will be used in a speech, a corporate earnings call or during a television broadcast — have come under scrutiny by the CFTC. CNBC reported in August that the agency was conducting an internal review into the contract type, and that platform Kalshi pulled its sports-related mention markets in response to the inquiry. 

Kalshi is one of the few U.S. regulated platforms that features mention markets. Its chief rival, Polymarket, only features them on its international exchange, which is not regulated by the CFTC.

“We’ve addressed this guidance based on a prior discussion with the CFTC,” Kalshi spokesperson Elisabeth Diana said in a statement.

Mention markets also generated headlines in July after news reports that a longtime teleprompter operator for President Donald Trump profited off of trades on Kalshi related to contracts on mention markets that were tied to the president’s statements. Gabriel Perez, the teleprompter operator, settled with the CFTC in August and was forced to pay a $172,539 fine for insider trading on a prediction market. 

In the letter, the CFTC advised that exchanges listing mention markets should consider four factors: what outside obligations the subject of the mention market may have; external pressure that could influence the subject’s speech or conduct; whether the words or actions used for settlement are independently verifiable; and whether there are adequate oversight measures in place to detect manipulation on the contracts. 

The CFTC added that it encourages exchanges to engage with the agency’s division of market oversight while in the early phases of designing mention market contracts on how to mitigate manipulation risks. 

Disclosure: CNBC and Kalshi have a commercial relationship that includes customer acquisition and a minority investment.

Artificial intelligence is getting better at doing more than answering questions. AI systems are now helping with coding, research, analysis and other tasks that were once handled almost entirely by people. That raises a new question: what happens when AI starts playing a bigger role in building the next generation of AI?

OpenAI is now calling for international standards to help answer that question. In a September 21 post titled “Building standards for the next phase of AI,” OpenAI proposed a US-led international effort to create common technical standards for frontier AI. The company says these standards could help countries measure AI capabilities, evaluate risks, test safeguards and report serious incidents using more consistent methods.

Key Takeaways

• OpenAI wants international standards for evaluating frontier AI.
• The proposal covers capabilities, risks, safeguards and incident reporting.
• OpenAI says fully autonomous recursive self-improvement is not happening today.
• The company wants human control to remain central as AI becomes more capable.
• Existing AI safety organizations could help develop common technical standards.

Openai Wants a Common Framework for Frontier AI

The basic idea is fairly simple. It is not necessary for each country to create an entirely different methodology for evaluating the dangers posed by advanced AI. According to OpenAI, standardizing technical approaches can provide nations, researchers and the AI community an effective way to assess their increasingly sophisticated AI. This becomes all the more relevant when AI-related incidents happen across borders.

The company is not proposing a single global AI law. Instead, it wants countries to develop compatible standards that governments can later decide how to use within their own regulatory systems. This difference is significant since the suggested standards do not immediately become requirements for licensure or certification for all artificial intelligence technologies. Rather, governments retain the power to determine how the standards will apply within their jurisdictions.

Recursive Self-Improvement Is Part of the Conversation

One of the more interesting parts of OpenAI’s proposal is its discussion of recursive self-improvement (RSI). The concept describes a future in which AI systems could increasingly help researchers develop more capable AI systems. In simple terms, AI could become part of the process of improving AI itself.

That could potentially speed up AI research. But it also creates a difficult safety question: how much human oversight should remain in the loop if AI systems become heavily involved in developing future models?

OpenAI says fully autonomous recursive self-improvement is not happening today. It also argues that such a direction should not be pursued unless it can be done safely while maintaining human control. That makes evaluation and safety testing more important as AI systems become capable of handling increasingly complex research and development tasks.

AI Safety Standards Could Become More Important

OpenAI also points to existing AI safety organizations and networks around the world as potential building blocks for this effort. The company specifically references AI safety institutes and related organizations across countries including the US, UK, Canada, France, Germany, Japan, South Korea, Singapore, India, Kenya and Australia.

Rather than every country developing its own completely separate technical approach, OpenAI wants these groups to work toward standards that can complement one another. The proposal also calls for participation from AI developers, researchers, academics and independent technical experts. OpenAI says the standards should be designed around technical measurements rather than the interests of a particular company or country.

Why This Matters

The timing is notable. AI companies are building systems that can increasingly perform multi-step tasks with less direct human input, while governments are still working out how to regulate the technology.

Reuters reported that OpenAI wants the United States to take a leading role in developing international technical standards for advanced AI. The bigger challenge may be getting countries and companies to agree on exactly what those standards should measure and how they should be applied.

For now, OpenAI’s proposal is focused on creating a common technical foundation before frontier AI becomes even more capable. As AI starts doing more of the work involved in developing AI itself, having a shared way to measure capabilities, risks and safeguards could become an increasingly important part of the conversation.

Although AI is fundamentally changing cybersecurity, Bartley Richardson thinks the hackneyed IT refrain still rings true: “The best security is the security you don’t have to think about.” Richardson, a former Nvidia engineer who joined cybersecurity company CrowdStrike in June as its chief AI and autonomous systems officer, says his title perfectly reflects his belief that once consumers trust AI, they’ll stop regarding it as “AI.” Instead, it will be just another autonomous tool making life better in the background, like a grammar check in word processing. 

Richardson is shepherding that transition as leader of CrowdStrike’s new Cyber Superintelligence Lab. An AI research lab dedicated to building autonomous cybersecurity systems, its first release is SafeMind, an agentic system that combats AI attacks by pairing an offensive cybersecurity model with a defensive one, creating an autonomous loop of learning and remediation. “An attacker has to be right once, but the defender has to be right all the time,” Richardson says. “We’re giving the advantage back to the defender, and we’re doing that with … better automation.”

Arch Lending is preparing to move deeper into credit markets for tokenized equities, with plans to offer loans backed by onchain representations of stocks and exchange-traded funds (ETFs). Speaking on Cointelegraph’s Chain Reaction podcast, Arch co-founder and chief revenue officer Himanshu Sahay said the lender wants to enter “pretty soon,” citing a growing need for borrowing against tokenized stock assets.

Sahay pointed to rapid expansion in tokenized equities over the past year, while also arguing that lending against those assets remains limited today. He predicted that more lenders will follow, especially as tokenized stocks issued by platforms such as Superstate, Robinhood, and Securitize become more widely used in collateral frameworks.

Key takeaways

• Arch Lending plans to launch loans backed by tokenized equities “pretty soon,” aiming to address limited credit availability for onchain stock assets.
• Sahay said tokenized equities have expanded quickly over the past year, but lending usage still lags the pace of issuance and experimentation.
• Arch’s current loan book is still dominated by crypto collateral: Sahay said Bitcoin makes up more than 80% of exposure.
• Interest in using XRP as collateral is reportedly growing among US borrowers.
• Tokenized equities lending is already emerging via platforms like Ondo Finance and infrastructure providers tied to Ethereum-based lending protocols.

Arch’s shift from crypto-only lending to onchain stocks

While Arch’s core business is rooted in crypto-backed lending, Sahay emphasized that the lender is actively looking for additional collateral categories as the tokenized equities ecosystem matures. The company has already expanded beyond cryptocurrencies into real-world assets (RWAs), offering loans backed by tokenized gold and stablecoin-linked gold products issued by Paxos and Tether, according to Sahay.

Even with that progress, Sahay described Bitcoin as the dominant collateral in Arch’s current lending operations, accounting for more than 80% of the lender’s existing loan book. That detail underscores a transition phase: Arch is expanding its collateral menu, but crypto remains the base business while the market for tokenized equities develops deeper liquidity and clearer credit pathways.

Sahay also noted an uptick in demand for XRP collateral, particularly from borrowers in the United States. For lenders, the relevance of a collateral asset hinges on custody, valuation reliability, liquidation mechanics, and borrower appetite—so increases in specific collateral usage often signal that risk models and market plumbing are becoming more robust.

Tokenized equity credit is already taking shape

Arch would not be the first lender to attempt credit exposure to tokenized equities. Over the past year, tokenized stocks and ETFs have begun appearing across lending and collateral products, suggesting the industry is converging on Ethereum-based rails and DeFi-compatible collateral workflows.

In February, Ondo Finance launched DeFi lending markets for two of its tokenized ETFs through an integration with lending protocol Morpho. Ondo’s tokenized versions of the SPDR S&P 500 ETF and Invesco QQQ can be used as collateral for borrowing on Ethereum.

Beyond dedicated lending venues, other firms have also moved toward broader composability of tokenized equities. Kraken made its 10 xStocks eligible to support futures and margin positions in July. Meanwhile, Coinbase’s B20 stocks launched on Base in August, using price-feed infrastructure designed to support use cases that include DeFi borrowing and lending.

For investors and borrowers, these steps matter because they reduce friction: if tokenized equities can be used across multiple systems—rather than being confined to a single application—then lenders get more reliable access to collateral and liquidation workflows, while borrowers can more easily integrate the assets into existing strategies.

What’s driving demand: the onchain stocks market is growing

The push toward equity-backed lending aligns with expansion in the underlying tokenized equities market. According to RWA.xyz data cited in Cointelegraph’s coverage, distributed tokenized stock value has risen to about $3.15 billion, up from roughly $630 million a year earlier.

That magnitude of growth helps explain why lenders are considering tokenized equities more seriously. However, growth in issued or distributed token value does not automatically translate into deep lending markets. Lenders still need mechanisms to price the collateral, manage volatility, and execute liquidations efficiently—especially if the tokenized asset references traditional equities with their own settlement and liquidity characteristics.

Arch’s stated intent to add equity-collateral loans fits this broader pattern: as tokenized equities scale, the next layer of adoption is typically finance infrastructure—credit, margin, and yield—provided risk teams can support it. The “limited” lending described by Sahay suggests that, despite issuance momentum, the market still has room for additional lenders to compete on terms, collateral support, and risk management.

Why Arch’s timing could matter

Arch’s move comes at a moment when tokenized stocks and ETFs are increasingly being treated as collateral across multiple platforms and use cases. If tokenized equities continue to attract liquidity, lenders that expand collateral coverage earlier may capture relationships with borrowers seeking diversified collateral strategies—particularly when crypto-only borrowing is constrained by liquidity or collateral concentration concerns.

At the same time, the transition is not instantaneous. Sahay’s comments indicate that Arch’s current exposure remains largely tied to crypto, with Bitcoin still representing the vast majority of the existing loan book. That suggests Arch will likely approach tokenized equity lending with caution—building the operational and risk infrastructure needed to support assets with distinct market behavior compared with traditional crypto benchmarks.

For now, readers should watch whether Arch’s tokenized equity lending plans translate into actual launch details—such as which tokenized equities will be supported first, how collateral valuation and liquidation are handled, and whether demand from borrowers grows alongside the broader tokenized equities market. The combination of issuance expansion and the still-limited state of lending could determine how quickly this segment becomes a standard offering for credit providers.