Stablecoins Could Soon Back US Derivatives Trades Under New CFTC Plan

ccn.comPublicado em 2025-09-24Última atualização em 2025-09-24

Key Takeaways

Acting CFTC Chair Caroline Pham has proposed allowing stablecoins to be used as collateral in U.S. derivatives markets.
The initiative builds on recommendations from February’s Crypto CEO Forum.
If adopted, the move could unlock trillions in new liquidity for futures, swaps, and options.

The U.S. Commodity Futures Trading Commission (CFTC) is weighing one of the most consequential shifts in decades for America’s derivatives markets: permitting stablecoins such as USDT and USDC to serve as collateral.

Acting Chair Caroline D. Pham unveiled the proposal last week, describing it as a “measured step” toward aligning the CFTC’s regulatory framework with the realities of modern finance.

If approved, the change would allow tokenized assets to sit alongside cash and U.S. Treasurys as acceptable margin—potentially reshaping a market with a notional value in the quadrillions.

New Trending Crypto Wallet Offers

Safepal

promotions

Trusted, Secure and Crypto Friendly

Coins

–

Claim Offer

BitBox

promotions

Trusted, Secure & Crypto Friendly

Coins

–

Claim Offer

Blockstream

promotions

Trusted, Secure & Crypto Friendly

Coins

–

Claim Offer

From Forum Idea to CFTC Policy Proposal

The push to recognize stablecoins as collateral traces back to the February 2025 Crypto CEO Forum , where industry leaders floated the idea as a way to unlock liquidity and modernize risk management.

It also builds on findings from the President’s Working Group on Digital Assets and recommendations from the CFTC’s Global Markets Advisory Committee.

Under the plan, tokenized non-cash assets would be tested in a pilot “sandbox” program, drawing from the CFTC’s long track record of controlled innovation dating back to the 1990s.

Public comments are open until Oct. 20, with regulators specifically seeking input on valuation standards, custody, settlement mechanics, and necessary rule amendments.

Stablecoins Move Into the Mainstream

The timing underscores how quickly Washington’s posture on crypto has changed under the Trump administration.

After years of treating digital assets as speculative or fringe, both chambers of Congress recently passed the GENIUS Act, establishing a regulatory framework for stablecoins.

Allowing stablecoins in derivatives markets could extend their utility far beyond exchanges and payments.

Traders would be able to post collateral in USDC or USDT instantly, avoiding conversion to fiat and lowering barriers for both institutional desks and retail investors.

Analysts argue the shift could release trillions in dormant crypto capital into the broader financial system.

Top Picks for Ethereum

Was this Article helpful? Yes No

Leituras Relacionadas

Precious Metals Decline Alongside, What Signal is Gold Sending to the Market?

Gold and silver prices have declined recently, moving in tandem with a sell-off in risk assets like South Korean semiconductor stocks. This is unusual, as gold typically rises when equities fall due to its safe-haven status. The synchronized drop signals a shift in market focus: it's not about finding safety, but about the rising cost of holding assets that do not yield interest. This cost is the real interest rate. The key driver is a change in Federal Reserve policy expectations under new Chair Kevin Warsh. Despite holding rates steady, the Fed's rhetoric has turned more hawkish, emphasizing persistent inflation risks. This has led markets to price in a "higher for longer" rate environment, increasing the appeal of cash and bonds while pressuring zero-yield assets like gold and tech stocks with high future cash flow valuations. Technically, gold breached the $4,100/oz support level, approaching the critical $4,000 psychological and technical zone. A break below could trigger accelerated selling from momentum traders and ETFs. While long-term supportive factors like central bank buying and geopolitical risks remain, short-term price action is dominated by liquidity and opportunity cost dynamics. The South Korean market meltdown, driven by crowded AI-trade unwinding, is a symptom—not the cause—of this broader macro repricing. Both markets are reacting to the same pressures: higher real rates and a stronger US dollar. In summary, the concurrent decline in equities and precious metals highlights that diverse assets can share exposure to a common macro variable—the price of money. The near-term path for gold and silver depends primarily on the persistence of Fed hawkishness, dollar strength, and real yields, which currently override their traditional safe-haven narratives.

marsbitHá 5m

Precious Metals Decline Alongside, What Signal is Gold Sending to the Market?

marsbitHá 5m

Chip Stocks Lead U.S. Market Decline: Is AI Trading Being Hit by Both Interest Rates and Returns?

Chip stocks led a broad decline in US markets, with the Nasdaq dropping 2.2% and the S&P 500 falling 1.4%. This selloff reflects a dual challenge for the once-high-flying AI hardware trade: rising interest rate expectations and growing investor impatience for clear returns from massive AI capital expenditures. The pressure was most acute on hardware leaders. Nvidia fell about 4%, dipping below a $5 trillion market cap, while Micron plunged 13.2% ahead of its earnings report. Declines across memory, storage, AI, and mobile chips indicated a sector-wide retreat. The selloff spread globally, with South Korea's KOSPI index dropping nearly 10% as key suppliers SK Hynix and Samsung recorded double-digit losses. Investors appeared to be taking profits from the most crowded trades first. Macro headwinds intensified as market expectations shifted toward a more aggressive Federal Reserve. Forecasts for multiple rate hikes in 2026 pressured high-valuation tech stocks, which rely on long-term growth projections that become less attractive as discount rates rise. Concurrently, investors are scrutinizing the profit potential of the immense AI spending by cloud giants like Alphabet, Amazon, and Meta. While these expenditures drive demand for chips and hardware, the market is now questioning whether AI services will generate sufficient returns to justify the ongoing costs. This adjustment is not necessarily a bubble burst but a recalibration. AI demand fundamentals remain, but the narrative of endless growth can no longer fully offset concerns over higher interest rates and a longer path to profitability. Near-term direction may hinge on Micron's upcoming earnings guidance and incoming inflation data, which will influence both the AI demand outlook and the Fed's policy path. The market is transitioning from blindly buying growth to demanding clearer visibility on returns.

marsbitHá 1h

Chip Stocks Lead U.S. Market Decline: Is AI Trading Being Hit by Both Interest Rates and Returns?

marsbitHá 1h

OpenAI's New Paper: How to Train an AI that "Doesn't Deteriorate Under Pressure"?

OpenAI's new paper "Reinforcement Learning Towards Broadly and Persistently Beneficial Models" explores training AI to maintain safe, helpful, and honest behavior even under pressure, in unseen scenarios, or after being fine-tuned for harmful purposes. Moving beyond simple rule-based "don'ts," the research focuses on cultivating "beneficial traits" like honesty, risk-awareness, corrigibility, and transparency. It investigates if reinforcement learning (RL), often prone to "reward hacking" where models exploit loopholes, can instead be used to instill robust, generalized positive behaviors. Researchers created a multi-domain synthetic dialogue dataset covering areas like healthcare and law. They trained a model by replacing 5% of standard RL data with "beneficial trait" data. This model outperformed the baseline in 83% of 53 evaluations, showing average gains of 9.1% in alignment, safety, and helpfulness. Crucially, improvements generalized: a model trained only on healthcare "good behavior" data also performed better in 17 out of 19 non-healthcare alignment tests. The paper also tests "alignment persistence." When subjected to adversarial prompts or harmful fine-tuning, the beneficial trait model showed greater resilience, with smaller performance drops and less "spillover" of bad behavior to unrelated tasks. While not a complete solution, this work suggests a shift from post-hoc correction to proactively shaping robust, principled AI behavior, a critical step for deploying models in high-stakes, complex decision-making scenarios.

marsbitHá 1h

OpenAI's New Paper: How to Train an AI that "Doesn't Deteriorate Under Pressure"?

marsbitHá 1h

Goldman Sachs Revisits the State of the AI Boom: Strong Earnings Will Override Valuation Concerns Until the Investment Cycle Peaks, Volatility to Rise Further

Goldman Sachs discusses the current AI investment boom, arguing it is not a simple repeat of the 1999-2000 bubble. Unlike the dot-com era, current valuations are not wildly out of control because earnings expectations are rising in tandem with stock prices. The key issue is that market prices have already priced in substantial optimism, making them sensitive to any narrative shifts. The core risk has shifted from "valuation bubble" to "earnings bubble." While strong profits from companies in semiconductors, cloud infrastructure, and data centers currently outweigh valuation concerns, this is dependent on the ongoing capital expenditure cycle. The true test will be whether these robust earnings can be sustained after the investment cycle peaks. Current market prices imply optimistic assumptions, such as faster AI adoption, higher productivity gains, and a larger share of economic profits going to capital owners. The AI boom may also be masking relative weakness in the non-AI sectors of the economy. As a result, market volatility is expected to rise. Goldman recommends that investors consider maintaining exposure while adding downside protection, such as put options, to manage potential drawdowns.

marsbitHá 1h

Goldman Sachs Revisits the State of the AI Boom: Strong Earnings Will Override Valuation Concerns Until the Investment Cycle Peaks, Volatility to Rise Further

marsbitHá 1h

Zuckerberg Enters the Prediction Market

Mark Zuckerberg's Meta has entered the predictive markets arena with a new app called "Arena." Currently in an early experimental phase, Arena will initially operate as a standalone app using a points-based system where users can predict outcomes on politics, sports, and world events without real money. Meta plans to leverage its vast daily active user base for growth. The move comes as the predictive market industry sees explosive growth, with platforms like Polymarket and Kalshi handling hundreds of billions in volume. While a points system avoids initial regulatory hurdles, Meta hasn't ruled out introducing real-money betting later. The strategy aligns with Meta's pattern of adopting popular trends, though challenges remain, including regulatory scrutiny and the historically mixed success of its standalone apps.

Foresight NewsHá 1h