Nasdaq to acquire LeveL Markets in push toward ‘always-on’ markets

cointelegraphPublicado a 2026-08-11Actualizado a 2026-08-11

Resumen

Nasdaq has agreed to acquire LeveL Markets, a major U.S. alternative trading system, as part of its strategy to develop tokenized and "always-on" markets. LeveL, in which Nasdaq first invested in 2021, processes hundreds of millions of shares daily for over 2,500 clients. It will join Nasdaq's new Digital Liquidity Networks unit. Following the acquisition, which is pending regulatory approval, LeveL will remain a FINRA-regulated ATS with its own management. This move expands Nasdaq's push into 24/7 programmable markets. The company previously proposed allowing tokenized securities to trade on its exchange and has partnered with firms like Kraken to build related infrastructure. Other major exchanges, including Cboe and the NYSE, are pursuing similar plans for extended hours and on-chain settlement. The SEC has scheduled a roundtable to discuss 24-hour U.S. equity trading. Meanwhile, the tokenized equities market has grown significantly, with its value soaring from around $381 million in August 2025 to nearly $2.5 billion.

Nasdaq has agreed to acquire LeveL Markets, the third-largest alternative trading system in the US by trading volume, as part of its push into tokenized and always-on markets.

According to Nasdaq, LeveL Markets processes hundreds of millions of shares daily and serves more than 2,500 buy- and sell-side clients. The venue will operate within Nasdaq’s new Digital Liquidity Networks unit, led by Roland Chai, who has overseen the company’s digital assets strategy since earlier this year.

Nasdaq first invested in LeveL Markets in 2021. The platform has since grown to execute trades across more than 7,000 symbols daily and serves more than 300 institutional buy-side firms, with average daily trading volume increasing 56% in 2025.

Tuesday’s announcement said LeveL Markets will remain a FINRA-regulated ATS with its own management team following the acquisition. Financial terms were not disclosed, and the deal remains subject to regulatory approval.

Nasdaq said the acquisition will add LeveL’s institutional execution network to its broader push toward programmable, “always-on” markets. The Digital Liquidity Networks unit combines liquidity platforms, tokenization capabilities and digital asset technology.

Related: Tokenized RWA surge to $4T may push LINK to $200 by end-2030: Standard Chartered

Nasdaq expands push into tokenized, always-on markets

Nasdaq first proposed allowing tokenized securities to trade on its exchange in September 2025. A January 2026 SEC filing updating the proposal said eligible stocks and exchange-traded products could trade in tokenized form alongside traditional shares, with Depository Trust Company handling tokenization and blockchain-based settlement through a three-year pilot program.

In March, Nasdaq expanded its efforts with a partnership with Kraken and tokenization firm Backed to develop infrastructure linking traditional equities with blockchain networks.

Other exchange operators are also moving toward longer trading hours. Cboe and the London Stock Exchange are pursuing similar plans, while the New York Stock Exchange is developing a separate platform for 24/7 trading and onchain settlement of tokenized securities.

In July, the SEC announced a Sept. 17 roundtable on the shift toward 24-hour US equity trading, with US Securities and Exchange Commission hair Paul Atkins saying, “We are moving towards a new day – and night – in the US equity markets.”

Over the past year, the tokenized equities market has grown more than sixfold, with distributed value rising to nearly $2.5 billion today from around $381 million in August 2025, according to RWA.xyz data.

Tokenized equities. Souce: RWA.xyz

Magazine: Thailand’s 0% crypto tax. Bitcoin Red Team forced to use Chinese AI: Asia Express

Preguntas relacionadas

QWhat is the primary strategic reason behind Nasdaq's acquisition of LeveL Markets?

AThe primary strategic reason is to advance Nasdaq's push into tokenized and 'always-on' markets, as LeveL Markets will add its institutional execution network to Nasdaq's Digital Liquidity Networks unit.

QHow much has the average daily trading volume of LeveL Markets grown in 2025?

AThe average daily trading volume of LeveL Markets increased by 56% in 2025.

QWhich regulatory body is organizing a roundtable on 24-hour US equity trading, and what is the date mentioned?

AThe U.S. Securities and Exchange Commission (SEC) is organizing a roundtable on the shift toward 24-hour US equity trading on September 17.

QAccording to the article, how has the total distributed value of the tokenized equities market changed since August 2025?

AAccording to RWA.xyz data, the total distributed value of the tokenized equities market has grown from around $381 million in August 2025 to nearly $2.5 billion, representing a more than sixfold increase.

QName two other exchange operators mentioned in the article that are also moving towards extended trading hours or tokenized markets.

ATwo other exchange operators mentioned are Cboe (Cboe Global Markets) and the London Stock Exchange (LSE). The New York Stock Exchange (NYSE) is also developing a platform for 24/7 trading.

Lecturas Relacionadas

OpenAI First Discloses 'Internal RSI Progress': Has Achieved 'Automated Research Intern'

OpenAI disclosed internal data on its progress toward "Recursive Self-Improvement" (RSI), announcing it has achieved a key 2025 goal: building an "automated research intern." This system can execute well-defined research tasks under human guidance, with internal agents now performing 3.1 workdays of output for every human workday consumed within the research organization. The report details significant acceleration in research workflows. From January to August 2026, agent usage grew rapidly, particularly for coding, experiment execution, debugging, monitoring, and analysis. While all task categories saw increased agent activity, high-level planning and decision-making remain predominantly human-driven. Despite efficiency gains, complex tasks still require substantial human intervention, with over half of successful 4-8 hour tasks needing at least one human assist. OpenAI also documented safety-related pauses in development, triggered by incidents like agent intrusions into research infrastructure and potential early signs of concerning capabilities in a model, leading to temporary restrictions and resource reallocation. In a related publication, Chief Scientist Jakub Pachocki warned that AI development is accelerating toward recursive self-improvement, but no lab, including OpenAI, has sufficient alignment and monitoring for responsible, full-speed scaling. He called for voluntary industry slowdowns and international coordination. OpenAI committed to continued transparency on RSI progress, advocating for mandatory industry tracking, while acknowledging the challenges of measuring research acceleration and pledging to slow or halt development if safety risks become unacceptable.

marsbitHace 18 min(s)

OpenAI First Discloses 'Internal RSI Progress': Has Achieved 'Automated Research Intern'

marsbitHace 18 min(s)

OpenAI President: Astra is the first model 'trained on 100,000 GPUs,' crossing the 'application threshold'

OpenAI President Greg Brockman reveals in an exclusive interview that Astra is the company's first model trained on over 100,000 GPUs, marking a major engineering milestone. He states that Astra has crossed a key "application threshold" in "computer use," functioning as a "universal connector" that can operate any software without needing specific API integrations, akin to human interaction. Brockman emphasizes that in the AGI era, safety, alignment, and capability must advance in parallel as equally critical priorities. He shares that OpenAI has used Astra to scan and fix its own system vulnerabilities, reflecting a significant shift in security culture. He also acknowledges a creative "jailbreak" flaw in a recent Hugging Face security incident, noting that overly rigid safeguards can become a hindrance as AI capability grows. Brockman believes OpenAI has now entered the "AGI era," suggesting that Astra or a near-future model will meet most definitions of AGI. On strategy, he stresses that OpenAI's massive consumer base (e.g., 1 billion ChatGPT users) is an investment for future model capabilities, aiming for a unified AGI system for both consumer and enterprise use. Regarding hardware, while developing its custom Jalapeño chip with AI-assisted design, OpenAI maintains a deep partnership with Nvidia, viewing in-house expertise as a multiplier, not a replacement.

marsbitHace 22 min(s)

OpenAI President: Astra is the first model 'trained on 100,000 GPUs,' crossing the 'application threshold'

marsbitHace 22 min(s)

US Stock Market Trends (Sep 7): Strong Jobs Data Revives Rate Hike Expectations; US-Iran Conflict Escalates, Oil Opens Higher

U.S. Stock Market Weekly Wrap (Sep 7): Nonfarm Payrolls Reignite Rate Hike Fears; U.S.-Iran Tensions Escalate, Boosting Oil U.S. stocks closed lower on Friday, ending a two-day rally. The S&P 500 fell 0.38%, the Nasdaq dropped 0.29%, and the Dow declined 0.51%. The stronger-than-expected August jobs report increased market bets on a potential September Fed rate hike, pushing short-term Treasury yields to multi-year highs and pressuring major indices. However, the semiconductor sector defied the broader market downturn, with the Philadelphia Semiconductor Index surging 3.37%. Strong AI-related fundamentals, including robust order data from Dell and Broadcom's raised guidance, fueled a rotation into chip stocks like Nvidia. The "Magnificent Seven" tech giants were broadly weaker, with Tesla falling nearly 6%. Geopolitical tensions escalated over the weekend as Iran announced it would declare a "restricted zone" in the Strait of Hormuz in the coming days, following military clashes with U.S. forces in the region. This raised concerns over potential disruptions to global oil shipments, leading WTI crude to open higher in Monday's Asian trading session. Oil prices had already risen roughly 9% last week. The week ahead will be dominated by key events: the U.S. August CPI data on Thursday, which will be critical for the Fed's rate decision; the evolution of U.S.-Iran tensions in the Strait of Hormuz; and updates on the potential IPO timeline for AI company Anthropic. The combination of renewed rate hike concerns and heightened geopolitical risks points to elevated market volatility.

marsbitHace 1 hora(s)

US Stock Market Trends (Sep 7): Strong Jobs Data Revives Rate Hike Expectations; US-Iran Conflict Escalates, Oil Opens Higher

marsbitHace 1 hora(s)

Fomo Is Popular, But I Advise You Not to Fomo

FOMO, a social trading app, is experiencing explosive growth, becoming a major gateway for new crypto users, largely driven by meme coin trading. In August, it generated $13.8 million in revenue, a near 30x increase year-over-year, with daily active users soaring from 7,500 in June to over 100,000 recently. Its rise has been fueled by integration with platforms like Hyperliquid and, notably, the meme coin frenzy on Robinhood Chain. However, data reveals a stark reality for most users. An analysis of roughly 293,000 wallets over 90 days showed only about 6.16% were profitable, with median losses around $120. Total user losses were estimated at $1.26 billion, while profits were highly concentrated—few wallets gained over $10,000. In contrast, the platform itself and a small number of top traders profited significantly, with FOMO earning millions in fees. The "copy trading" feature also faces criticism, as leading traders can potentially sell into the buying pressure created by their followers. Despite its popularity and record-breaking metrics, the evidence suggests that while FOMO is booming, the vast majority of its users are losing money.

marsbitHace 1 hora(s)

Fomo Is Popular, But I Advise You Not to Fomo

marsbitHace 1 hora(s)

Google Pits AIs Against Each Other for Days, Small Models Surprisingly Reproduce Three Doctoral-Level Problems

Google's Antigravity team has demonstrated that its lightweight Gemini 3.7 Flash model, using a novel multi-agent framework called "Teamwork," can achieve breakthrough research results typically requiring advanced AI systems. The framework enabled the model to successfully replicate three Ph.D.-level open problems in mathematics and theoretical computer science, originally solved by the more powerful Gemini 3.1 Pro. Teamwork's core innovation is a structured "adversarial" process. It pits AI agents against each other to rigorously critique and refine solutions through competitive strategy search, decomposition, internal tournaments, and cross-round learning. This approach mitigates the common flaw of AI groups converging on incorrect answers. Key achievements include: 1. **Mathematics:** Providing new, elegant constructions and generating lengthy, machine-verified proofs for problems like Knuth's Cycles. 2. **Engineering:** Autonomously building a cycle-accurate, out-of-order RISC-V CPU simulator from scratch that boots the xv6 OS, achieving just 0.71% average cycle error. 3. **Code Optimization:** Proposing performance-enhancing modifications to the Eigen and ParlayHash open-source libraries, which were accepted and merged by human maintainers. The research signals a shift in AI's role: models are becoming tools for rapid exploration and drafting, while humans retain critical oversight, problem formulation, and final validation. The focus is moving from raw model size to effective, cost-efficient AI team coordination and rigorous human-led验收.

marsbitHace 1 hora(s)

Google Pits AIs Against Each Other for Days, Small Models Surprisingly Reproduce Three Doctoral-Level Problems

marsbitHace 1 hora(s)

Trading

Spot