SEC reaffirms tokenized stocks must follow existing securities laws

ambcryptoPublicado a 2026-01-30Actualizado a 2026-01-30

Resumen

The U.S. SEC reaffirmed that tokenized stocks must comply with existing federal securities laws, regardless of whether they are issued on-chain or off-chain. The regulator emphasized that all securities must be registered unless an exemption applies. Tokenized stocks fall into two categories: issuer-sponsored and third-party sponsored, each offering different rights and protections. Wall Street firms, including Citadel and JPMorgan, opposed broad exemptions for DeFi platforms handling tokenized securities, warning that such exemptions could undermine investor protection and cause market disruptions. They called for DeFi platforms to be regulated similarly to traditional financial institutions. Despite opposition from traditional finance, the DeFi sector has seen significant growth, with nearly 300,000 holders and total traded value approaching $1 billion. The industry continues to advocate for certain exemptions, and the final regulatory framework may reflect a compromise between these opposing views.

The U.S. regulator, the Securities and Exchange Commission (SEC), has reiterated that tokenized securities are still securities and fall under federal securities law.

In a recent statement, the regulator clarified that whether a stock is issued off-chain or on-chain, it must still comply with the relevant laws.

“Regardless of its format, the Securities Act requires that every offer and sale of a security must be registered with the Commission unless an exemption from registration is available.”

The guidance further reiterated,

“Similarly, stock is an ‘equity security’ under the Securities Act and the Exchange Act regardless of its format.”

According to the watchdog, tokenized stocks fall into two categories. The first is issuer-sponsored, which transfers rights and protections to the holder, while the second is third-party sponsored on-chain stocks that offer varied ownership rights and protections.

Securitize, one of the issuers of tokenized securities, welcomed the move, stating that it is crucial for ‘scaling’ the sector.

“Clear frameworks like this are key to responsibly scaling tokenization.”

Wall Street opposes DeFi exemptions

The statement followed the recent meeting between the regulator and Wall Street firms on how to treat tokenized securities under the current legal regime.

According to an SEC memo, representatives from Citadel, JPMorgan Chase & Co., Cahill Gordon & Reindel, Securities Industry and Financial Markets Association (SIFMA), pressed against broad exemptions for on-chain stocks.

Referencing the October flash crash and Stream Finance collapse, the TradFi group warned,

“Broad exemptions for tokenized trading activities could undermine investor protection and lead to market disruptions.”

In fact, in a December letter, Citadel Securities called for similar regulation of DeFi platforms handling tokenized securities like their traditional counterparts.

The DeFi complex has been pushing for legal exemptions, claiming their platforms are disintermediated to warrant the legal responsibility.

In a recent meeting, SIFMA and its TradFi members pushed for a new classification of tokenized securities to enable more effective regulation.

The latest SEC statement reflects some of the concerns they raised. However, it does not address broader DeFi operations. This omission may be because issues related to tokenized securities are still under discussion within the CLARITY Act.

Tokenized stocks eye $1 billion

Even so, the collective DeFi players called Citadel Securities’ push and argument ‘bassless’ and ‘flawed.’

The industry may likely advocate for DeFi exemptions of some sort in the bill. It remains to be seen whether the final framework for tokenized securities will be a compromise between these two camps.

The sector has gained strong traction, with tokenized securities holders edging close to 300K users, representing a 100% growth in January alone. Additionally, the total value of traded on-chain stocks is teetering toward the $1 billion mark.


Final Thoughts

  • The U.S. SEC clarified that tokenized securities still fall under the current federal securities law
  • Wall Street pressed against a broad DeFi exemption in tokenized securities trading.

Preguntas relacionadas

QWhat did the SEC reaffirm regarding tokenized stocks and existing securities laws?

AThe SEC reaffirmed that tokenized securities are still securities and must comply with existing federal securities laws, regardless of whether they are issued off-chain or on-chain.

QWhat are the two categories of tokenized stocks mentioned by the SEC?

AThe two categories are issuer-sponsored tokenized stocks, which transfer rights and protections to the holder, and third-party sponsored on-chain stocks, which offer varied ownership rights and protections.

QWhy did Wall Street firms oppose broad exemptions for tokenized securities trading?

AWall Street firms opposed broad exemptions because they believe it could undermine investor protection and lead to market disruptions, as evidenced by events like the October flash crash and Stream Finance collapse.

QWhat was the DeFi industry's response to Citadel Securities' call for similar regulation?

AThe DeFi industry called Citadel Securities' push and argument 'baseless' and 'flawed,' and they are likely to advocate for some form of DeFi exemptions in the bill.

QWhat growth metrics were highlighted for the tokenized securities sector in January?

AIn January alone, the number of tokenized securities holders grew by 100%, reaching nearly 300,000 users, and the total value of traded on-chain stocks is approaching the $1 billion mark.

Lecturas Relacionadas

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

AI is reshaping the labor market's value proposition. The traditional four-year college degree is losing its appeal as a guaranteed career path, while skilled blue-collar trades like electricians, welders, and plumbers are experiencing historic demand and wage premiums. This shift is driven by dual pressures: AI's displacement of certain white-collar roles and a booming need for physical infrastructure and data center construction. Data confirms the trend. In the U.S., vocational school revenue surged, and a significant portion of recent layoffs are AI-related. Surveys show a majority of Gen Z adults plan to pursue blue-collar work, citing better job security against AI automation. Vocational education interest has exploded recently. Experts cite a psychological shift as younger generations seek tangible, AI-resistant careers and avoid high student debt. In many cases, salaries for skilled trades now match or exceed those requiring a bachelor's degree. In South Korea, semiconductor vocational high schools boast near-total employment, with graduates securing high-paying roles at companies like Samsung. The shortage is structural, exacerbated by a retiring baby boomer workforce and massive infrastructure projects. Companies like JPMorgan Chase, Meta, and Lowe's are investing heavily in training programs. However, overcoming historical stigma and a "perception gap" around trade careers remains a key challenge to closing the talent gap.

marsbitHace 29 min(s)

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

marsbitHace 29 min(s)

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

Qualcomm reported its Q3 FY2026 results (ending June 2026), with revenue of $9.95B, down 4% YoY but above expectations. Gross margin declined to 53.1%, pressured by rising costs across manufacturing and memory. Key business segments showed mixed performance: Handset revenue fell 19.6% YoY to $5.09B, dragged by an 11% decline in non-Apple Android shipments and weaker high-end mix. Conversely, Automotive revenue surged 61% to $1.59B, and IoT grew 9% to $1.83B. Core operating profit dropped 41% YoY due to margin compression and higher expenses. Management's Q4 FY2026 guidance projects revenue of $9.7B-$10.5B, in line with consensus, but Non-GAAP EPS guidance of $2.05-$2.25 fell short of expectations. Amidst persistent weakness in its core handset market, Qualcomm is pursuing growth in AI, focusing on Edge AI (smartphones, PCs, automotive) and Data Center AI. Its data center strategy includes four pillars: AI accelerators (e.g., AI200), commercial CPUs (Dragonfly C1000), custom silicon, and connectivity solutions. While these initiatives initially boosted its stock, concerns over AI capital expenditure sustainability have since erased those gains. The company targets $5B in data center revenue for FY2027 and $15B for FY2029. The report concludes that with the traditional handset business still under pressure, the data center opportunity is currently viewed as a longer-term option, and a more conservative valuation based on core operations may be warranted until AI contributions materialize.

marsbitHace 33 min(s)

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

marsbitHace 33 min(s)

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

At the 2026 YC Startup School, Jeff Dean outlined his vision for AI's next phase, shifting focus from simply scaling models to building intelligent, autonomous systems. He believes AI's progress is no longer just about creating smarter models, but about integrating them into systems capable of long-term, iterative work, automated experimentation, and continuous learning. This evolution moves the competition from "who has the bigger model" to "who can best organize intelligence." Dean suggests AI capabilities are now comparable to a junior engineer, enabling the automation of complex workflows. However, the true challenge and opportunity lie in managing these AI "workers" at scale. He emphasizes the importance of **context engineering**—structuring tools, memory, and feedback loops—over raw model power. For startups, this means building deep expertise in niche domains where general models currently fail (near 0-1% success rates), leveraging proprietary data, specialized tools, and domain-specific evaluators. A recurring theme is re-examining fundamental constraints. Dean's past work, like moving Google's search index to memory or creating the TPU, stemmed from questioning outdated assumptions about hardware and cost. He sees similar inflection points today, particularly in **specialized inference hardware** to drastically reduce latency and energy consumption for real-time Agent operation. Notably, he points out that in modern AI systems, the dominant cost is often not computation but **data movement**. Reliable, long-running Agents require robust system design, borrowing concepts from distributed computing like checkpointing, state management, and parallel exploration to handle failures and maintain progress over days or weeks. As AI automates execution, the scarcest human skills will shift to **defining clear specifications**, **judging what problems are worth solving** (taste), and designing effective feedback loops. Ultimately, Dean's framework prioritizes understanding the problem deeply, identifying the true bottlenecks, and systematically building closed-loop systems where AI can not only perform tasks but also improve AI itself.

marsbitHace 33 min(s)

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

marsbitHace 33 min(s)

Trading

Spot
活动图片