ETF от BlackRock накопил под управлением более 800 тыс. биткоинов

cryptonews.ruPubblicato 2025-10-19Pubblicato ultima volta 2025-10-19

Спотовый биржевой фонд на биткоин IBIT стал самым прибыльным среди всех подобных инструментов

Чистые активы спотового биржевого фонда (ETF) на биткоин IBIT от компании BlackRock превысили отметку 800 тыс. BTC. Это около 3,8% от всего предложения биткоина, ограниченного 21 млн монет.

За эту неполную неделю чистый приток средств в IBIT составил $2,3 млрд (18,8 тыс. BTC), по данным SoSoValue. По итогам последней торговой сессии 8 октября фонд BlackRock владел биткоинами на $99,08 млрд (812 тыс. BTC по текущему курсу биткоина $122 тыс.).

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Для сравнения: активы BlackRock, принадлежащие клиентам ее фонда, значительно превосходят активы ведущей компании по управлению биткоинами Strategy Майкла Сэйлора, которая владеет 640 031 BTC на сумму около $78 млрд, что составляет 3,1% от общего предложения BTC.

Притоки капитала в IBIT значительно превышают притоки в другие биткоин-ETF. Только в октябре фонд BlackRock привлек $3,96 млрд, тогда как общая сумма поступлений в американские ETF (сервис отслеживает 12) составила $4,81 млрд.

IBIT — самый прибыльный ETF среди множества фондов более 1 тыс. компаний по всему миру, по данным аналитиков рынка ETF в Bloomberg Intelligence Эрика Балчунаса и Джеймса Сейффарта. Фонд взимает комиссию в размере 0,25%, получает годовой доход в размере более $240 млн, что является выдающимся достижением для ETF, считают эксперты.

Bloomberg назвал главу Polymarket самым молодым self-made миллиардером

Letture associate

Why former Bank of America strategist sees an Ethereum ‘tactical bottom’

Stephen Suttmeier, former Bank of America strategist, identifies a potential "tactical bottom" for Ethereum (ETH), contingent on the price holding above $1690-$1700 and reclaiming $1800. A decisive move above $1800, turning the 50-day moving average into support, could target the 200-day MA near $2200, implying a 25% upside. This technical view finds some support from other analysts and a double-bottom pattern on the daily chart. However, on-chain data shows significant headwinds. Exchange selling pressure has surged, with over 220K ETH moved to exchanges recently, and whale selling persists. Furthermore, U.S. spot ETH ETFs, after days of inflows, recorded a $52 million net outflow due to macro risks like U.S.-Iran tensions and bond market volatility. In summary, while technicals suggest a bullish reversal is possible if ETH sustains above $1800, sustained selling pressure and macroeconomic risks threaten to invalidate the optimistic "tactical bottom" thesis.

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Why former Bank of America strategist sees an Ethereum ‘tactical bottom’

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Injective software package hit by malicious supply chain attack – Details

In a software supply chain attack, malicious actors compromised the Injective Labs TypeScript SDK (@injectivelabs/sdk-ts v1.20.21) by uploading a tainted version to the npm registry. The attackers gained access to a legitimate contributor's GitHub account to distribute malicious commits. The compromised package, disguised as a routine update, contained malware that activated only when developers used specific wallet generation functions, stealing private keys and mnemonic seed phrases. This breach impacted approximately 50,000 weekly downloads and spread through transitive dependencies in 17 other Injective packages. While a clean version (v1.20.23) was later released, the malicious package remained accessible. Affected users are advised to rotate credentials, create new wallets, and move their funds.

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Injective software package hit by malicious supply chain attack – Details

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After Aave's Exit and TVL's Sharp Fluctuation, Where Does MegaETH's Valuation Anchor Lie?

Following the withdrawal of Aave and a sharp drop in its Total Value Locked (TVL), the valuation of the high-performance DeFi blockchain MegaETH faces scrutiny. Once a highly anticipated project with a fully diluted valuation (FDV) reaching around $2 billion, MegaETH saw its TVL plummet from a May peak of $245 million to just over $30 million in July, a roughly 70% decline. Its native token, MEGA, currently trades around $0.048 with a market cap of approximately $54 million and an FDV of about $480 million. The report identifies a core vulnerability: MegaETH's TVL was heavily dependent on a single protocol, Aave V3, which at its peak contributed around 90% of the chain's TVL. A significant portion of this capital is attributed to leveraged yield-farming strategies involving stablecoins like USDe. When the profitability of these strategies diminished, capital rapidly exited, exposing the lack of diversified, sustainable activity. Three key mismatches between MegaETH's valuation and its fundamentals are highlighted: 1. **Valuation vs. Real Usage:** With an FDV of ~$4.8B but only ~$1M in annualized protocol revenue and ~2,600 daily active addresses, the valuation appears disconnected from current economic activity. 2. **Token Narrative vs. Ecosystem Reality:** Despite its DeFi narrative, nearly 80% of the chain's recent protocol revenue comes from a trading card game, Monster, not from core DeFi applications like Aave. The chain's native stablecoin, USDM, also shows low trading volume and a declining market cap. 3. **Short-Term Hype vs. Long-Term Delivery:** Initial hype from token generation, blue-chip integrations, and influencer support has faded. Major protocols like Uniswap now hold minimal TVL on the chain, indicating that early capital was largely transient and driven by incentives rather than organic demand. The situation reflects a broader market trend where investors are becoming less tolerant of valuations based on inflated TVL and narrative, demanding clearer evidence of sustainable transactions, revenue, and ecosystem development. While MEGA's price may experience short-term rebounds from market sentiment, a fundamental re-rating likely depends on the team's ability to convert its remaining resources into tangible, user-retaining applications and genuine ecosystem growth.

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After Aave's Exit and TVL's Sharp Fluctuation, Where Does MegaETH's Valuation Anchor Lie?

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Goldman Sachs In-Depth Report: Who Will Be the Long-Term Winners in China's AI Large Model Industry?

Goldman Sachs Report: China's AI Models at an Inflection Point China's open-source/open-weight large language models (LLMs) have reached performance parity with top global proprietary models, according to a Goldman Sachs report. This is driven by architectural innovations and higher parameter efficiency, allowing Chinese models to achieve comparable capabilities at 2%-10% the parameter size and significantly lower cost. The market is evolving into a two-tiered structure: a high-end segment (e.g., GLM5.2, Qwen3.7 Max) with premium pricing and a low-end, price-sensitive segment for global SMEs and individual users. Key points: * **Cost & Performance:** Innovations like Mixture of Experts (MoE) enable high performance with smaller models. Projects like Meituan's LongCat 2.0, trained on domestic hardware, highlight progress in tech self-sufficiency. * **Open-Source Strategy:** Most Chinese players use open-source/open-weight models for flexibility and ecosystem growth. However, Goldman notes this may underreport actual deployment and revenue. A shift toward "open-weight + community license" models with revenue sharing (e.g., MiniMax) could improve monetization. * **Market Shift & Global Expansion:** Enterprise AI adoption is shifting from "token maximization" to "ROI-first." International expansion, especially in non-US markets, is a major growth driver. Chinese models are increasingly available on global platforms like AWS Bedrock and Microsoft Copilot. * **Competitive Landscape:** Using a framework based on pricing power, cost advantage, and financial strength, Goldman identifies **Zhipu AI and DeepSeek** as the strongest in foundational text models, and **ByteDance** as the leader in multimodal/video generation. The report maintains Buy ratings on MiniMax and Kuaishou. * **Market Growth:** China's AI model API and subscription revenue is projected to grow from an estimated ¥35 billion in 2026 to ¥879 billion by 2030.

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Goldman Sachs In-Depth Report: Who Will Be the Long-Term Winners in China's AI Large Model Industry?

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Goldman Sachs Deep Dive Report: Who Will Become the Long-Term Winners in China's AI Large Model Industry?

Goldman Sachs Report: Who Will Be the Long-Term Winners in China's AI Large Model Industry? China's AI large model sector is at a historic inflection point. Goldman Sachs argues that the intelligence of Chinese open-source/open-weight models is approaching top global proprietary models. Rapid adoption by domestic enterprises and global SMEs is creating a data flywheel effect that will further drive model iteration. The evolution is summarized as moving from "DeepSeek's cost-efficiency moment last year to GLM's model-intelligence moment this year." Chinese models achieve near-state-of-the-art performance at significantly lower cost, primarily due to architectural innovations like Mixture of Experts (MoE) and higher parameter efficiency. Models like DeepSeek V4 Pro (1.6T params), GLM5.2 (0.7T), and MiniMax M3 (0.4T) are much smaller than global leaders. Recent advancements in coding capability are attributed to better data curation and RLHF. Landmarks like Meituan's LongCat 2.0, trained fully on domestic AI chips, demonstrate progress in hardware stack independence. The market is forming a "two-tiered structure." The high-end tier (e.g., GLM5.2, Alibaba's Qwen3.7 Max) prices around $1 per million tokens, about 10-25% of US top models, with estimated inference gross margins of 10-20%. The low-end tier (priced as low as $0.06-$0.2 per million tokens) targets price-sensitive global SMEs and individuals. MiniMax derives 60-70% of revenue overseas. Goldman forecasts China's AI model API/subscription revenue to grow from an estimated RMB 35bn in 2026 to RMB 879bn by 2030. Most Chinese players adopt open-source/open-weight strategies for deployment flexibility and community feedback, though this limits monetization as deployments on third-party platforms (e.g., Alibaba Cloud) may not generate direct revenue. A shift towards "open-weight + community license" models with revenue-sharing agreements (like MiniMax's approach) could improve unit economics. International expansion, particularly in non-US markets, is the key growth driver. The global enterprise AI paradigm is shifting from "token maximization" to "ROI prioritization." Chinese models are already hosted on major global platforms like AWS Bedrock and are under consideration for integration into Microsoft Copilot. Using a competitive framework based on pricing power, cost advantage, and financial strength, Goldman identifies the strongest players: In foundational text models, Zhipu AI (initiated coverage) and DeepSeek lead. In multimodal/video generation, ByteDance's Seed is the frontrunner, with Kuaishou's Kling and MiniMax's Hailuo also well-positioned. Goldman maintains a Buy rating on MiniMax, citing its attractive valuation.

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Goldman Sachs Deep Dive Report: Who Will Become the Long-Term Winners in China's AI Large Model Industry?

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