CME Group Explores Launching Its Own Digital Token To Enable 24/7 Crypto Trading

TheNewsCryptoPublished on 2026-02-05Last updated on 2026-02-05

Abstract

CME Group is exploring the creation of its own digital token to enable 24/7 cryptocurrency trading and improve settlement processes. CEO Terry Duffy confirmed the initiative during the company's Q4 2026 earnings call, though the project remains under review with no set launch date. The token would function primarily as collateral for crypto futures and options, facilitating margin payments and settlements within CME’s regulated ecosystem—not as a general-purpose cryptocurrency. This move aims to address the mismatch between crypto markets, which trade continuously, and traditional finance hours. CME is also advancing tokenized cash initiatives with Google Cloud and plans to launch 24/7 trading for crypto derivatives in Q2 2026. The exchange has seen significant growth, with crypto trading volumes averaging $12 billion in 2025 and new futures products expanding to include assets like Solana, XRP, Cardano, Chainlink, and Stellar.

CME Group is considering creating its own digital token to support 24/7 cryptocurrency trading and to enhance the settlement process for trades. Terry Duffy, CEO of CME, has confirmed this idea during the company’s fourth quarter earnings call on February 4, 2026. Currently, the project is still under review, and no launch date has been announced.

Reason Behind This Idea

The Idea came from the challenges the large institutions are facing in trading crypto futures and options on the regulated exchanges like CME. Crypto markets trade all day, but the traditional finance market closes on weekends and holidays. The current finance system is designed for limited trading hours. CME strongly believes that the tokenized collateral could help to solve the problem. It mainly focuses on enabling the round-the-clock margin and settlement, to reduce the delays in posting the collateral, and to improve capital efficiency for institutional traders.

According to the CME executives, the CME token would not be used as a common crypto like Bitcoin and ETH; it would be used as collateral for the crypto futures and options, can be used as margin payments between clearing members, and for the settlement infrastructure inside CME’s regulated ecosystem. CEO Terry Duffy noted that CME would prefer tokens issued by the regulated institutions.

CME focuses on Tokenized cash and 24/7 Trading

CME is also working on tokenized cash, meaning turning the traditional money into a digital form that can be moved instantly on the blockchain. CME is working with Google Cloud on a separate tokenized cash initiative and is expected to launch in later 2026, which supports the future digital settlement tools.

CME prepares to move its crypto business to full 24/7 trading. It has previously stated its plan to launch the 24/7 trading for the crypto futures and options in Q2 2026, which helps the traders to manage risk at any time.

CME is steadily increasing its growth in the crypto market. The average crypto trading volume has reached $12 billion in 2025, and new futures products were launched for Solana and XRP. On February 9, 2026, CME is set to launch additional futures for Cardano, Chainlink, and Stellar. CME’s growth shows that the larger institutions want regulated and secure ways to trade crypto.

Highlighted Crypto News:

Bybit’s Mantle Vault Surpasses $150M AUM in Record Four-Week Growth

TagsCME GroupCRYPTOCURENCY

Related Questions

QWhat is CME Group considering launching to support 24/7 cryptocurrency trading?

ACME Group is considering creating its own digital token to support 24/7 cryptocurrency trading and enhance the settlement process for trades.

QWhat problem does CME aim to solve with its proposed digital token?

ACME aims to solve the problem of institutional traders facing challenges due to crypto markets trading 24/7 while traditional finance markets have limited hours. The token would enable round-the-clock margin and settlement, reduce collateral posting delays, and improve capital efficiency.

QHow would the CME token be primarily used, according to the article?

AThe CME token would be used as collateral for crypto futures and options, for margin payments between clearing members, and within CME's regulated settlement infrastructure. It would not function as a common cryptocurrency like Bitcoin or ETH.

QWhat other major initiative is CME working on with Google Cloud?

ACME is working with Google Cloud on a separate tokenized cash initiative, which involves turning traditional money into a digital form that can be moved instantly on the blockchain. This is expected to launch in late 2026.

QWhen does CME plan to launch 24/7 trading for its crypto futures and options?

ACME has previously stated its plan to launch 24/7 trading for crypto futures and options in Q2 of 2026.

Related Reads

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

Silicon Valley investor and "Godfather of Startups" Steve Hoffman warns that combining Web3 with AI is likely a trap, not a promising venture. In an interview, Hoffman argues that while AI is a foundational technology touching all industries, Web3 adds complexity, friction, and regulatory risk without solving mainstream consumer or business needs. He advises founders to focus on deep, specialized applications where startups can out-iterate giants, rather than on generic features easily replicated by large tech companies. Hoffman observes that Silicon Valley will lead foundational AI research, while China excels at rapid, large-scale application and commercialization, particularly in robotics. He stresses that AI-driven autonomous agents capable of collaborative, multi-step tasks are 2-4 years away, which will cause significant job displacement. The solution is not to slow AI but to redesign business models around human-AI collaboration and reform social systems like education and retraining. For startups, Hoffman recommends focusing on vertical, expertise-heavy domains to build defensibility. He sees major opportunities in AI fraud detection and cybersecurity. Key founder mindsets include systemic thinking over feature-focus, relentless customer centricity, building adaptive teams, and deeply understanding AI's capabilities and limits. Hoffman is also leading a non-profit initiative to establish university centers aimed at training future leaders in responsible, human-value-aligned AI innovation.

marsbit1h ago

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

marsbit1h ago

Token Inefficient, Economy Tokenless

The article "Tokens Aren't Economical, Economics Aren't Tokenized" analyzes a pivotal shift in the AI industry from a technology-driven narrative to one dominated by capital efficiency. It highlights two concurrent trends: a severe capital shortage due to the exorbitant and recurring costs of compute (e.g., OpenAI's high burn rate) and a wave of corporate spin-offs where major tech companies are separating their AI units (like Kuaishou's Kling and Baidu's Kunlunxin). The core argument is that AI's "anti-internet" business model, where user growth increases costs rather than profits, has created a disconnect between high valuations and actual cash flow. Spin-offs address this by allowing AI assets to be valued independently. Within a parent company, they are seen as cost centers, but as standalone entities, they are priced based on their growth potential and scarcity in the primary market, leading to massive valuation premiums (e.g., Kling's estimated value tripling post-spin-off). The industry is at an inflection point, moving from "model worship" to "value realization." The competition is evolving from a pure compute (GPU) race to a broader focus on systemic efficiency and full-stack engineering (involving CPUs and orchestration) to achieve viable commercialization. The year 2026 is framed as a critical moment where the industry must definitively answer how to economically translate AI capability into tangible business value, reshaping the sector's future power structure.

marsbit1h ago

Token Inefficient, Economy Tokenless

marsbit1h ago

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

In 2026, a historic shift occurred in AI as major cloud providers' inference spending surpassed training spending for the first time, signaling a move from "building large models" to "using large models." This shifts the core challenge from computing power to the "memory wall"—the bottleneck of data movement (model weights, activations, KV Cache) between external DRAM and processors, where energy and latency from data transfer far exceed computation itself. Companies like Nvidia face GPU idle time due to bandwidth limits. In contrast, Cerebras Systems adopts a radical "wafer-scale" approach with its Wafer-Scale Engine (WSE). Instead of cutting a silicon wafer into many chips, Cerebras uses almost the entire wafer as one massive chip (WSE-3). This design provides 44GB of on-chip SRAM, delivering memory bandwidth thousands of times higher than traditional HBM (e.g., 21 PB/s vs. Nvidia B200). For LLM inference, weights are streamed layer-by-layer from external MemoryX storage to the chip, avoiding HBM bottlenecks. This results in token generation speeds 1.5–5 times faster than Nvidia's B200 in some models and significant advantages in first-token latency and long-context tasks. Additionally, Cerebras's architecture offers much lower interconnect power consumption (0.15 pJ/bit vs. GPU's ~10 pJ/bit). However, Cerebras faces challenges: SRAM scaling has slowed with advanced nodes, limiting future capacity gains; the chip requires specialized liquid cooling and custom software stacks; and its external I/O bandwidth (150 GB/s) is low compared to NVLink, hindering multi-system scaling for very large models. Competition is intensifying. Major players are pursuing three paths: 1) Developing proprietary inference ASICs (e.g., Google TPU, Microsoft Maia), 2) Leveraging advanced packaging (e.g., TSMC's SoW) to democratize wafer-scale-like integration, potentially eroding Cerebras's process advantage within a few years, and 3) Exploring optical interconnects for ultimate bandwidth. Commercially, Cerebras is transitioning from a hardware vendor to a service provider, facing the immense challenge of building high-power, specialized data centers to meet large contracts (e.g., 250MW/year from 2026–2028). In conclusion, the AI inference era presents a fundamental architectural trade-off. Cerebras opts for extreme physical optimization for low-latency, single-task performance, while Nvidia prioritizes versatility and massive cluster throughput. The path forward remains uncertain, with technology and business models still evolving in the race toward advanced AI.

marsbit1h ago

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

marsbit1h ago

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

**Title: Has Bitcoin's Rebound Ended, Entering the Late Bear Market Phase?** **Summary:** Bitcoin's price has declined by 13% this week, signaling a potential return to late-stage bear market conditions. The price fell to around $67k, positioned between the Realized Price and Realized Cap Weighted Average. For the first time since early 2022, the Short-Term Holder cost basis has dropped below this key average, confirming a hallmark of late-cycle bear markets. Profitability metrics have collapsed sharply. The 7-day average of the Realized Profit/Loss ratio plummeted from a local high of 3.16 to 0.29, mirroring the February panic sell-off. Critically, the 90-day average never breached the threshold of 2, indicating the recent rally to $82k was a bear market bounce, not a structural shift. Realized losses surged to $1.35 billion daily, with $770 million coming from Long-Term Holders selling at a loss. This accelerating redistribution of supply from weak to strong hands is a necessary but ongoing process for a market bottom. The rally stalled almost precisely at the aggregate cost basis (~$83k) of US spot Bitcoin ETF investors, turning that level into strong resistance and leaving the average ETF holder underwater again. Spot market flows have turned decisively negative, showing sellers are dominating order books despite the price drop. While a significant futures long liquidation event cleared over $400 million in leverage, providing a potential reset, sustained spot demand is yet to materialize. Options markets continue to price in higher future volatility (Implied Volatility) than recent price action (Realized Volatility) has shown, with a persistent skew towards put options, indicating ongoing demand for downside protection. In conclusion, multiple metrics point to a fragile market structure. Resistance at the ETF cost basis, accelerating realized losses, dominant spot selling, and cautious options pricing all suggest the bear market trend persists. A sustainable recovery likely requires a resurgence of spot demand, ETF holders returning to profit, and a clear reduction in selling pressure.

marsbit1h ago

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

marsbit1h ago

Trading

Spot
Futures
活动图片