Grayscale Moves to Convert AAVE Trust Into ETF

TheNewsCryptoPubblicato 2026-02-14Pubblicato ultima volta 2026-02-14

Introduzione

Grayscale has filed with the SEC to convert its AAVE Trust into a spot ETF to be listed on NYSE Arca, continuing its strategy of bringing crypto products into regulated structures. The Aave protocol is a leading DeFi lending platform, and its native token, AAVE, has a market cap of around $1.8 billion. This move reflects growing institutional interest in DeFi. If approved, the ETF would charge a 2.5% sponsor fee and use Coinbase for custody, allowing traditional investors to gain exposure to AAVE without directly managing tokens. Grayscale's effort follows its successful conversion of its Bitcoin Trust into an ETF, though Bitwise also filed for similar AAVE-related products in December.

Grayscale has filed with the U.S. Securities and Exchange Commission to convert its AAVE Trust into a spot exchange-traded fund that would list on NYSE Arca. The move marks another step in the asset manager’s strategy to bring crypto-native products into regulated ETF structures.

The filing arrives as institutional interest in decentralised finance grows. Grayscale’s proposal focuses on AAVE, the native token of the Aave protocol, which dominates decentralised lending within DeFi.

AAVE currently holds a market capitalization near $1.8 billion and trades at around $119, reflecting a roughly 9% daily gain. The token reached an all-time high of $661.69 in April 2021, underscoring its volatility and growth history.

Bitwise, however, appears to have moved first. The firm filed paperwork in December for multiple crypto ETFs, including AAVE-related products. That early submission may position Bitwise ahead in the regulatory queue.

Aave’s Role in DeFi Strengthens ETF Case

Aave is the most prominent decentralised lending platform. Users lock crypto assets to earn yield or borrow against collateral without the need for intermediaries. The protocol represents a substantial value locked in DeFi applications.

Investment vehicles tied to AAVE already trade in Europe, including products from 21Shares and Global X. Grayscale’s ETF would bring a U.S.-listed version to regulated markets, expanding access for traditional investors.

Grayscale continues its broader conversion strategy. The firm previously transformed its Bitcoin Trust into a spot ETF after winning a legal battle against the SEC. This marked a paradigm shift in the U.S. ETF market and paved the way for other spot Bitcoin ETFs, which received extensive coverage in crypto regulatory news.

ETF Structure and Market Positioning

The new Grayscale AAVE ETF would charge a 2.5% sponsor fee on net asset value. The ETF would pay this fee in AAVE tokens. Coinbase would serve as both custodian and prime broker, strengthening institutional safeguards around custody and execution.

NYSE Arca plans to list the ETF, subject to SEC approval. The exchange has already hosted multiple crypto-linked ETFs, making it a logical venue for expansion into DeFi tokens.

According to regulatory filings available through the SEC, Grayscale’s strategy mirrors its earlier trust conversions. Market analysts from Bloomberg note that token-based ETFs could accelerate institutional flows into altcoins if regulators approve additional listings.

The ETF would allow investors to gain exposure to AAVE without holding tokens directly or managing private keys. That structure may attract hedge funds, asset managers, and wealth advisors seeking simplified DeFi exposure.

DeFi Enters Institutional Phase

This announcement by Grayscale marks a larger trend. The DeFi token is no longer a niche asset class but a legitimate candidate for an ETF. This is due to increased clarity and improvements in custody solutions.

Although it is still a long shot, the mere announcement of the ETF shows increased confidence in the DeFi sector’s longevity. Institutional adoption is increasing beyond Bitcoin and Ethereum to native protocol assets.

If approved, the ETF could bring increased liquidity and awareness of AAVE in traditional markets. This would further blur the lines between decentralised finance and traditional financial markets.

Highlighted Crypto News:

KuCoin Institutional Premiere 2026 Highlights Long-Term Growth and Market Resilience

Domande pertinenti

QWhat is Grayscale's recent filing with the SEC regarding its AAVE Trust?

AGrayscale has filed with the U.S. Securities and Exchange Commission to convert its AAVE Trust into a spot exchange-traded fund (ETF) that would list on NYSE Arca.

QWhat is the current market capitalization and trading price of AAVE mentioned in the article?

AAAVE currently holds a market capitalization near $1.8 billion and trades at around $119, reflecting a roughly 9% daily gain.

QWhich company is named as a competitor that filed for an AAVE-related ETF before Grayscale?

ABitwise filed paperwork in December for multiple crypto ETFs, including AAVE-related products, which may position it ahead of Grayscale in the regulatory queue.

QWhat role would Coinbase play in the proposed Grayscale AAVE ETF structure?

ACoinbase would serve as both custodian and prime broker for the Grayscale AAVE ETF, strengthening institutional safeguards around custody and execution.

QWhat is the proposed sponsor fee for the new Grayscale AAVE ETF and how would it be paid?

AThe new Grayscale AAVE ETF would charge a 2.5% sponsor fee on net asset value, and the ETF would pay this fee in AAVE tokens.

Letture associate

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.

marsbit45 min fa

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

marsbit45 min fa

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.

marsbit49 min fa

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

marsbit49 min fa

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.

marsbit50 min fa

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

marsbit50 min fa

Coldcard exploit sparks Bitcoin flight, ‘bullish’ crypto consolidation: Hodler’s Digest, August 2

A Coldcard hardware wallet exploit led to estimated losses of 1,367 BTC ($88.6 million), causing a spike in small Bitcoin transfers as users moved funds to centralized exchanges and other custody methods. In U.S. politics, the Clarity Act faces hurdles with time running out for a Senate vote, amid debates over ethics rules and crypto regulation. Major crypto firms like Coinbase reported disappointing Q2 earnings, while an analyst notes the industry is entering a significant consolidation phase, with revenue concentrating in a few dominant protocols like Hyperliquid and Pump.fun. Bitcoin's price decline continued, though some analysts suggest the market may have bottomed. Other news includes Telegram's legal troubles in Russia and Australia, layoffs at Pump.fun ahead of token distributions, and a White House staffer accused of insider betting leaving his post.

cointelegraph1 h fa

Coldcard exploit sparks Bitcoin flight, ‘bullish’ crypto consolidation: Hodler’s Digest, August 2

cointelegraph1 h fa

LATEST NEWS: Donald Trump makes a sharp statement regarding Iran! He has halted attacks

U.S. President Donald Trump announced he called off planned military strikes against Iran after Saudi Arabia, the UAE, Qatar, and Iran itself requested a delay. Trump stated the planned operation would have been large-scale and powerful but was suspended to allow time for diplomatic negotiations. He added that regional allies believe an agreement is near, with initial talks focused on security and reopening the Strait of Hormuz. Negotiations on Iran's nuclear program would follow once that is settled. The Strait of Hormuz is a vital global chokepoint for oil and gas shipments, and conflict there could significantly impact energy prices and world trade. Trump further announced that new talks with Iran will begin tomorrow. Separately, Trump commented on events involving the Japanese yen, stating the U.S. intervened in the market due to good relations with Japan, asserting Washington's consistent support for Tokyo and mutual economic benefits from the relevant rules. *This is not an investment recommendation.

cryptonews.ru2 h fa

LATEST NEWS: Donald Trump makes a sharp statement regarding Iran! He has halted attacks

cryptonews.ru2 h fa

Trading

Spot