大肆吸金!贝莱德旗下比特币现货ETF规模已超百亿,耗时不到两个月

金十Опубліковано о 2024-03-05Востаннє оновлено о 2024-03-05

比特币现货ETF自上市以来大受欢迎,助长了一股市场狂热,并将这种加密货币的价格一度推近历史高点。

自1月11日推出以来,投资者以历史性的速度涌入这些基金,市场上10只美国比特币现货ETF的总资产规模膨胀至近500亿美元。

贝莱德旗下的iShares比特币信托上周四的资产规模超过100亿美元,是有史以来最快达到这一里程碑的新ETF。富达的基金目前拥有超过60亿美元的资产,已经是这家资产管理公司的第三大ETF,占今年ETF净流入的大部分。

VettaFi研究主管Todd Rosenbluth表示:

“这是一波持续的需求浪潮。这些产品一上市就很强劲,而且一直保持强劲。”

这些基金允许日常投资者通过他们直接投资数字资产,而不必去加密货币交易所或通过期货合约对比特币进行投资。

一些分析师预计,这些资金最初的巨大投入将随后放缓,但随着比特币价格接近创纪录水平,近几周资金流入的速度反而加快了。

周一下午,比特币交易价格超过6.7万美元,略低于2021年11月创下的68990.90美元的纪录。截至2023年,比特币才接近4万美元,一年前在2.3万美元左右徘徊。

许多分析师将比特币在去年下半年的上涨归因于对比特币现货ETF将获得批准的预期。他们说,现在投资者对基金的追捧除了创造新的需求外,还推动了更多的看涨情绪。Rosenbluth补充道,“这是基础资产价格与基金挂钩的罕见情况之一,比特币的表现很难量化,但它的表现与人们对其可用性提高的希望息息相关。这是一个循环的好处。”

市场需求还能增加?

贝莱德旗下的这只比特币现货ETF已超越了许多其他ETF,数据显示,在美国上市的3000多只ETF中,资产规模超过100亿美元的只有约4%。

今年1月,有9只比特币基金是新上市的,而灰度的比特币信托在其他基金推出的当天就转换成了一只拥有近300亿美元现有资产的ETF,即GBTC。

自那以来,投资者已从该基金撤资逾80亿美元,因其收取的费用远高于竞争对手。如果GBTC的平均资产保持在目前水平附近,1.5%的年费将为这家资产管理公司带来约4亿美元的年收入。

贝莱德在所谓的“促销期”结束后仅收取0.25%的费用,而大多数规模较小的资产管理公司收取的费用甚至更低。

当然,并非所有资产管理公司都认为这些产品适合个人投资者。先锋集团曾表示,不打算提供一个比特币ETF,不会在其经纪业务平台提供投资加密货币的渠道。这家资产管理巨头在最近的一篇博客文章中称比特币“更像是一种投机,而不是一种投资”。

注册投资顾问在引导资金流向ETF方面具有巨大影响力,但他们目前接触比特币现货ETF基金的机会有限。摩根士丹利、美银美林、瑞银和富国银行的财富管理平台以非请求方式提供比特币基金,即顾问不能主动向客户推销比特币基金,但可以为提出要求的客户购买比特币现货ETF。

如果这种情况发生变化,分析师预计会有更多资金流入比特币现货ETF。CFRA Research ETF数据和分析主管Aniket Ullal表示:

“顾问平台一直没有涉足这一资产类别,现在这种情况可能会改变,我们预计需求会增加。”

市场对比特币ETF的“适应程度”令人惊讶

在吸纳新资金方面,一些新的比特币基金正与其他资产类别的行业重量级基金展开正面交锋。贝莱德的比特币现货ETF 2月份在美国ETF“吸金榜”排名第三,以微弱优势超过标普500指数ETF。

富达的比特币现货ETF排名第八,2月份最受欢迎的基金是先锋集团旗下的标普500指数基金及其信息技术基金。

目前还缺乏有关谁在购买这些基金的数据。在大型投资者在季度披露中报告其基金持仓情况后,华尔街将了解更多情况。

不过,近期比特币现货ETF的交易活动最近有所加速。据外媒称,上周三约有80亿美元的交易量,是迄今为止成交量最大的一天。

投资者接受这些新基金的速度令人惊讶。这是一种非常不寻常的情况,”Ullal表示。他表示,ETF通常需要更长的时间来吸引资产,因为它们需要等待不同的顾问平台将它们上市。

Пов'язані матеріали

Why Does 'AGI Godfather' Ben Goertzel Believe the Future of AI Relies on Blockchain?

Ben Goertzel, known as the "AGI Godfather," argues that the future of Artificial General Intelligence (AGI) must be built on blockchain to prevent its control by a few corporations or venture capital firms. He believes the core AGI code should be free and open-source, but that this alone is insufficient without a decentralized infrastructure to run it affordably. His blockchain project, SingularityNET, and the broader Artificial Superintelligence Alliance aim to create a user-owned, decentralized network for hosting and deploying AGI, contrasting with the closed models of companies like OpenAI and Anthropic. Goertzel criticizes the shift of other labs from open to closed development. He argues that while a closed path is simpler, an open, decentralized model—akin to Linux and the internet—is both possible and ultimately better for humanity. He envisions an "Agent economy" where individuals orchestrate teams of AI agents to perform tasks, including transactions, on an open network rather than corporate clouds. While his current model relies on cryptocurrency, plans include offering paid AI services to businesses with the decentralized blockchain as the backend. Goertzel predicts human-level AGI could arrive by 2029 and warns that a gap in understanding and access to AGI could drastically worsen inequality. The first test of his decentralized approach will be the upcoming release of the Agent Omega Claw.

Foresight News7 хв тому

Why Does 'AGI Godfather' Ben Goertzel Believe the Future of AI Relies on Blockchain?

Foresight News7 хв тому

A Company Once on the Brink of Bankruptcy Just Surpassed Bitcoin in Market Cap

On June 22nd, driven by rising stock prices, SK Hynix’s market capitalization reached $1.35 trillion, surpassing Bitcoin's total market cap of approximately $1.29 trillion. This temporarily made it South Korea's highest-valued company. The core driver of this surge is HBM (High Bandwidth Memory), for which SK Hynix is the primary supplier to NVIDIA, holding over 60% market share. AI's demand for high memory bandwidth has translated into immense profitability, with SK Hynix reporting a 72% operating profit margin in Q1. The company's success follows a 13-year bet on HBM technology, beginning in 2009. It nearly failed after the 2001 dot-com bubble, was acquired by SK Group in 2012, and was subsequently recapitalized to continue its long-term HBM development. The article contrasts this with the Crypto AI narrative. Capital currently favors AI infrastructure players like SK Hynix due to "real orders, physical barriers, and quantifiable profit margins." In comparison, Crypto AI projects, promising decentralized compute and data markets, remain largely conceptual with limited tangible progress. Examples include Bittensor, whose core mechanisms are still under development, and Bitcoin miners transitioning to AI, who face significant funding gaps and execution challenges. The piece cites analysis suggesting the AI sector has absorbed nearly all new market liquidity since 2022, leaving little for crypto. It concludes that the current AI infrastructure红利 is captured by entities with proven technical barriers and supply capabilities, while crypto networks still need to define their concrete role in the value chain.

链捕手47 хв тому

A Company Once on the Brink of Bankruptcy Just Surpassed Bitcoin in Market Cap

链捕手47 хв тому

Bittensor Moves Towards Ultimate Decentralization: The Critical 18 Months for the TAO Ecosystem is Here?

Bittensor, a decentralized AI protocol, is accelerating its transition to full decentralization over the next 18 months, as outlined in a recent post by co-founder Const. The project currently operates in a "semi-decentralized" state: ownership and network participation are open and permissionless, with TAO distribution based on competitive contribution. However, protocol upgrades and governance have remained under core team control to enable rapid iteration in the fast-evolving AI sector. This strategic shift comes as the ecosystem matures, boasting 128 subnets and a large community. Const argues that continued centralization now poses risks, including single points of failure and regulatory scrutiny. The upcoming decentralization roadmap includes optimizing validator competition, opening liquidity pools, introducing governance rights for Alpha holders, and refining economic models. The move could fundamentally reshape TAO's value proposition, adding governance premiums to its existing valuation based on AI narrative and scarcity. It also signals a potential maturation of the AI crypto sector, where competition may shift from hype to sustainable protocol design and real economic activity. Bittensor positions itself not just as another AI token, but as foundational infrastructure aiming to decentralize intelligence production—analogous to Bitcoin's role in decentralizing money—with the goal of creating a resilient "Millennium Intelligence Federation."

marsbit59 хв тому

Bittensor Moves Towards Ultimate Decentralization: The Critical 18 Months for the TAO Ecosystem is Here?

marsbit59 хв тому

Japan's AI Dark Horse Emerges: How a 7B Small Model Challenges Fable and Mythos?

In June 2026, Sakana AI's new model Fugu caused a stir in the AI community. Its Fugu Ultra variant achieved scores of 73.7 on SWE-Bench Pro and 82.1 on TerminalBench 2.1, surpassing GPT-5.5 and Claude Opus 4.8, and was claimed to be comparable to export-restricted models like Fable 5 and Mythos Preview. Remarkably, the core of this high-performance system is not a massive model, but a small 7B-parameter RL Conductor model. Fugu operates as a multi-agent orchestrator: the 7B model acts as a "foreman," dynamically analyzing user tasks and delegating subtasks to a pool of top-tier global models (e.g., GPT-5, Gemini 3.1 Pro). It then synthesizes and verifies their outputs. This architecture represents a paradigm shift from monolithic models to an expert-team approach. It enhances performance in complex, multi-step engineering tasks like code review and security testing by enabling cross-validation from specialized models, improving long-session stability and token efficiency. However, Fugu's strengths come with trade-offs: it faces inherent latency due to multiple API calls, relies heavily on underlying US model APIs (creating dependency risks), and its benchmark comparisons with Fable/Mythos are based on reported scores, not head-to-head testing. For Japan's AI ecosystem, which lacks the massive compute and data resources of the US or China, Fugu exemplifies an "asymmetric breakthrough" strategy. Instead of competing directly in parameter scale, it focuses on intelligent orchestration of existing global models, offering a degree of AI sovereignty and resilience. While a significant system-level innovation, its ultimate capability is still bounded by the underlying models it coordinates.

marsbit1 год тому

Japan's AI Dark Horse Emerges: How a 7B Small Model Challenges Fable and Mythos?

marsbit1 год тому

Торгівля

Спот
Ф'ючерси
活动图片