Liquid staking under the lens after Nasdaq files JitoSOL ETF rule change – Details

ambcryptoОпубліковано о 2026-02-27Востаннє оновлено о 2026-02-27

Анотація

Nasdaq has filed with the SEC to list the Vaneck JitoSOL ETF, which would be the first Solana spot ETF fully backed by a liquid staking token (LST). The fund aims to track the price of JitoSOL, a tradable asset users receive for staking SOL, allowing them to earn rewards without managing validators. The filing argues that JitoSOL is economically comparable to SOL, citing extremely high hourly price correlations (over 0.997) on major exchanges. This suggests the ETF introduces no new pricing risks beyond existing Solana ETFs. The SEC has 45 to 90 days to review the proposal. If approved, staking rewards would be reflected in the fund’s net asset value rather than distributed separately. This is the first U.S. filing for an LST-backed fund, though other products offering combined spot and staking exposure, like the REX-Osprey Solana ETF, already trade.

Nasdaq has submitted a filing to the U.S Securities and Exchange Commission (SEC), proposing a rule change to list the Vaneck JitoSOL ETF. This fund was announced on 22 August 2025 as the first Solana [SOL] Spot ETF 100% backed by a liquid staking token (LST). It aims to track the price of JitoSOL, which it achieves using the MarketVector JitoSol VWAP Close Index.

In liquid staking, users receive a tradable asset in return for staking crypto. Users staking SOL receive JitoSOL in return. These can be traded while still earning the on-chain rewards from the staked SOL. These users don’t need to run validators or manage their on-chain staking.

Correlation data cited to show JitoSOL as analogous to SOL

The goal of the Nasdaq filing was to allow the listing and trading of the Vaneck JitoSOL ETF, which would hold JitoSOL directly. It submitted the proposal under Nasdaq Rule 5711(d), “which governs the listing and trading of Commodity-Based Trust Shares on the Exchange.”

The exchange relied on the “generic listing standards” the SEC approved in September. By demonstrating a high price alignment and correlation between JitoSOL and SOL, with hourly price correlations of approximately 0.9979 on OKX and 0.9985 on Coinbase, it argues that JitoSOL is economically comparable to SOL.

Therefore, the JitoSOL ETF does not bring new pricing risks not already present in the already-approved Solana ETF market.

The SEC’s review process gives the agency 45 days to approve or disapprove this proposal. This deadline can be extended to 90 days.

According to Jito Foundation president Brian Smith, staking rewards would not be distributed separately if the fund is approved. Instead, the rewards would reflect on the fund’s net asset value.

In August, JitoSOL had revealed that the Vaneck ETF filing was a result of months of collaborative policy outreach efforts with the SEC. This filing is still in the SEC’s exchange review stage. No liquid staking token fund is trading in the United States.

Other products that allow exposure to spot and staking rewards exist though. The REX-Osprey Solana + Staking ETF (SSK) began trading in early July. The REX-Osprey ETH + Staking ETF (ESK) was launched in September.

Grayscale introduced staking for its Ethereum and Solana ETFs in October too.

Final Summary

  • The Nasdaq filing to the SEC is aimed at allowing the listing and trading of the Vaneck JitoSOL.
  • High price alignment between JitoSOL and SOL means the two assets are economically comparable.

Пов'язані питання

QWhat is the purpose of the rule change filing submitted by Nasdaq to the SEC?

AThe purpose of the Nasdaq filing is to propose a rule change to allow the listing and trading of the Vaneck JitoSOL ETF, a fund that would be 100% backed by the liquid staking token JitoSOL.

QWhat is the Vaneck JitoSOL ETF designed to track, and how does it achieve this?

AThe Vaneck JitoSOL ETF is designed to track the price of JitoSOL, which it achieves by using the MarketVector JitoSol VWAP Close Index.

QWhat key data did Nasdaq cite in its filing to argue that JitoSOL is economically comparable to SOL?

ANasdaq cited high hourly price correlations of approximately 0.9979 on OKX and 0.9985 on Coinbase between JitoSOL and SOL to demonstrate their economic comparability.

QHow would staking rewards be handled for investors if the Vaneck JitoSOL ETF is approved?

AAccording to Jito Foundation president Brian Smith, staking rewards would not be distributed separately but would instead be reflected in the fund's net asset value.

QWhat is the current status of the Vaneck JitoSOL ETF filing and are there any similar funds trading in the U.S.?

AThe filing is currently in the SEC's exchange review stage, and no liquid staking token fund is currently trading in the United States.

Пов'язані матеріали

Stablecoins Finally Find Real Yield: An In-Depth Look at On-Chain Reinsurance Re | A Conversation with Re Founder Karan Saroya

Stablecoin Real Yield Found: A Deep Dive into On-Chain Reinsurance with Re's Karan Saroya As stablecoin supply exceeds $170 billion, the search for sustainable, non-speculative yield intensifies. Re, an on-chain reinsurance platform, provides an answer: connecting stablecoin capital to the trillion-dollar traditional reinsurance market. Re operates as a regulated reinsurer, accepting stablecoin deposits as collateral to back US insurance companies. These insurers pay premiums, generating yield that flows back to on-chain depositors. Currently supporting 35 insurers and underwriting $500 million, Re projects scaling to over $1 billion soon. Key insights from a Bankless podcast with founder Karan Saroya and investor Avichal of Electric Capital: 1. **Uncorrelated, Real-World Yield:** Re offers stablecoin holders access to reinsurance returns (targeting 12-14%+), an asset class entirely separate from crypto or equity markets. 2. **Operational Efficiency via Smart Contracts:** Re replaces traditional, labor-intensive capital fundraising with smart contracts, allowing a ~12-person team to compete with industry giants. 3. **Regulatory Leverage:** For every $1 of collateral, regulations allow backing $5-7 in written premiums. This leverage amplifies returns from the underlying risk-free rate. 4. **DeFi Integration:** Depositors receive receipt tokens, which can be used in protocols like Morpho for "looping," potentially pushing yields to 18-20%+. 5. **The "DeFi Mullet" Model:** A compliant front-end (regulated reinsurer) paired with a decentralized back-end (smart contracts, DeFi capital markets). 6. **RE Governance Token:** Modeled on Lloyd's of London, the token governs the central capital pool's allocation, counterparty acceptance, and parameters. 7. **Real Economic Impact:** Capital funds real-world productivity (factories, clinics, businesses) via insurance, moving beyond crypto's internal loops. The discussion highlights a pivotal moment: DeFi's supply-side infrastructure is now met by real demand for productive yield, potentially kickstarting a flywheel where vast on-chain stablecoin capital seeks these real-world returns.

链捕手31 хв тому

Stablecoins Finally Find Real Yield: An In-Depth Look at On-Chain Reinsurance Re | A Conversation with Re Founder Karan Saroya

链捕手31 хв тому

1996 or 1999? Walsh's First Test is 'How to View AI'

"1996 or 1999? Wall's First Big Test Is 'How to View AI'" Federal Reserve Chairman Wall's initial challenge is not whether to raise or cut rates, but a more fundamental judgment: what kind of boom is the current AI boom? This will determine the Fed's policy path and define his legacy. Economics is split between two opposing views, according to reporter Nick Timiraos. One sees imminent productivity gains that will increase supply and cool inflation, allowing the Fed to hold steady. The other argues that while productivity benefits are distant, demand shocks are here now, and waiting for data confirmation risks missing the intervention window, forcing sharper rate hikes later. Wall has signaled a leaning toward the first view, echoing 1996-era Alan Greenspan, who embraced strong, productivity-driven growth without fear of inflation. However, Wall faces a different macro environment than Greenspan did, with tariff pressures, expanding fiscal deficits, and diminishing globalization benefits, which could force more significant inflation pressures even if AI benefits materialize. Wall's logic, expressed before taking office, is that AI-driven productivity gains won't show in official data for years. If the Fed waits for confirmation, it might mistakenly tighten policy and choke off the very growth that could suppress inflation. This argues for using forward-looking narratives over lagging data. Chicago Fed President Austan Goolsbee presents a key counter-argument. He distinguishes between expected and unexpected productivity booms. A widely anticipated boom, like the current AI wave, can cause people to spend future wealth gains in advance, overheating the economy before productivity actually rises, thus requiring preemptive rate hikes. He cites rising costs for AI data centers as evidence of such overheating. Fed Governor Christopher Waller offers a rebuttal to Goolsbee, noting the "expected spending" mechanism only works if people can borrow against future income, which many households cannot do due to borrowing constraints. Wall also faces a paradox related to his desire to reduce the Fed's use of "forward guidance" (pre-announcing policy moves). This practice was established in 1999 when Greenspan began signaling hikes to avoid market shocks. If the economy follows a less optimistic path, Wall may be forced to choose between using the guidance he wants to abolish or risking market volatility by staying silent. The ultimate question defining Wall's first major test remains: Is this 1996 or 1999?

marsbit1 год тому

1996 or 1999? Walsh's First Test is 'How to View AI'

marsbit1 год тому

Ethereum Q1 2026 Report: Fees Decline, Users and Transaction Volume Hit New Highs

Ethereum Q1 2026 Report: Fees Down, Users & Transactions Hit New Highs Token Terminal's Q1 2026 report on Ethereum presents a pivotal development: the network achieved record highs in monthly active users (13.2M, +85.9% YoY), total transactions (200.4M, +81.5% YoY), and throughput (25.78 TPS), while transaction fees on the mainnet plummeted by 47.9% quarter-over-quarter. This shift is attributed to the network's strategic move into a "low fees for scale" phase, exemplified by the Fusaka upgrade which increased data capacity and lowered block space costs, releasing pent-up demand (a manifestation of Jevons's Paradox). The report highlights a core narrative shift for Ethereum: from a DeFi-centric blockchain to a global financial settlement layer. It maintains a dominant position in tokenized assets, holding majority market shares among top chains in stablecoins (61.8%), tokenized funds (73.0%), and tokenized commodities (84.0%). Growth in tokenized funds (+73.1% YoY) and commodities (+325.9% YoY) was particularly strong, driven by institutions like BlackRock and JPMorgan entering the space. Contrasting these usage gains, several USD-denominated value metrics declined in Q1: fully diluted market cap fell 30.3% QoQ, total value locked (TVL) dropped 11.0%, and ecosystem transaction volume decreased 24.0%. The report interprets this as Ethereum prioritizing long-term network expansion and cementing its role as the default settlement layer for finance over short-term fee capture. The commentary from Etherealize argues that, much like the early internet, Ethereum's open, permissionless model is poised to win over closed alternatives as institutional tokenization accelerates.

marsbit3 год тому

Ethereum Q1 2026 Report: Fees Decline, Users and Transaction Volume Hit New Highs

marsbit3 год тому

Intel CEO Liwu Chen's First Podcast Interview: Our Goal is '10x in 5-10 Years', Betting on Advanced Packaging, Glass Substrate, and Synthetic Diamond

Intel CEO Chen Liwu outlines a bold vision for the company's transformation in a podcast interview, targeting a "10x return in 5-10 years." He emphasizes a strategic shift beyond traditional process node scaling, focusing on advanced packaging (like EMIB), new materials (glass substrates, GaN, SiC, InP, synthetic diamond), and system-level integration. Key to this is Intel's foundry business, where he prioritizes building trust through superior yield, defect density, and cycle times. Chen sees strong CPU demand resurgence driven by agent AI and inference workloads. He details the Terafab collaboration with Elon Musk to address semiconductor infrastructure gaps and stresses the strategic importance of U.S.-based advanced manufacturing. Acknowledging Intel is still in the "crawl" phase of his crawl-walk-run framework, Chen believes the company's full potential—extending from its PC base into edge computing and physical AI—will become apparent by 2030-2032.

marsbit3 год тому

Intel CEO Liwu Chen's First Podcast Interview: Our Goal is '10x in 5-10 Years', Betting on Advanced Packaging, Glass Substrate, and Synthetic Diamond

marsbit3 год тому

He Just Raised 2.7 Billion, and Li Fei-Fei Also Invested

Pete Florence, a former senior research scientist at Google DeepMind and a key contributor to the Vision-Language-Action (VLA) model architecture, is deliberately distancing his startup, Generalist AI, from the trendy "world model" label. He argues that the industry should prioritize concrete goals over buzzwords. His goal is to create robots that can perform a vast range of unseen tasks with high speed and success rates, without needing task-specific training data. Recently, his company raised $400 million (¥2.7 billion) at a $2 billion valuation. Notable investors include NVIDIA's NVentures, Bezos Expeditions, NFDG, as well as Xiaomi co-founder Lin Bin, Zoom founder Eric Yuan, and renowned AI scientist Fei-Fei Li. Florence's approach stems from his academic background at MIT under Professor Russ Tedrake, focusing on understanding the physical world. After joining DeepMind, he developed models like Transporter Network and co-created the VLA framework. He left in 2025 to found Generalist AI. The company has launched two models: GEN-0, which demonstrated that scaling laws apply to physical motion, and GEN-1. GEN-1 was trained on over 500,000 hours of physical interaction data collected via a specialized wearable device. It achieves a 99% success rate on precise mechanical tasks like folding boxes and maintains performance three times faster than its predecessor. Florence believes GEN-1 is reaching a commercial utility threshold similar to the GPT-3 inflection point. The substantial funding round, following GEN-1's release, signifies strong investor confidence in Generalist AI's practical, goal-driven path to creating versatile, useful robots, regardless of the "world model" terminology.

marsbit3 год тому

He Just Raised 2.7 Billion, and Li Fei-Fei Also Invested

marsbit3 год тому

Торгівля

Спот
Ф'ючерси
活动图片