星球日报 | 美国大选辩论后特朗普相关概念股普跌;美国核心CPI符合市场预期(9.12)

Odaily星球日报Publicado em 2024-09-12Última atualização em 2024-09-12

Resumo

美国8月季调后核心CPI月率0.3% ,预期0.20% ,前值0.20%。

星球日报 | 美国大选辩论后特朗普相关概念股普跌;美国核心CPI符合市场预期(9.12)

头条

美国大选辩论后特朗普相关股和加密货币概念股普跌

美国大选辩论后,特朗普媒体科技集团(DJT.O)美股盘前下跌 13% 。区块链概念股普跌,微策略(MSTR.N)、Riot Platforms(RIOT.O)跌约 3% ,Coinbase(COIN.O)跌 2% 。

美国核心 CPI 符合市场预期,美元指数 DXY 短线拉升超 20 点

美国 8 月未季调核心 CPI 年率为 3.2% ,与上月数据持平,符合市场预期,此前连续四个月走低。美元指数 DXY 短线拉升超 20 点,现报 101.67 。

美国 8 月季调后核心 CPI 月率 0.3% ,预期 0.20% ,前值 0.20% 

美国 8 月季调后核心 CPI 月率 0.3% ,预期 0.20% ,前值 0.20% 。

行业新闻

马斯克:哈里斯口头表现超出很多人预期,但仍相信特朗普在具体事务处理会做得更好

马斯克于 X 平台发文对早些时候的美国总统大选辩论评论道:“虽然我认为辩论主持人对特朗普不公平,但哈里斯在今晚(的口头表现确实)超出了大多数人的预期。也就是说,在处理具体事务时,不仅仅是说一些听起来好听的话,我坚信特朗普会做得更好。毕竟,如果哈里斯能做出了伟大的成就,为什么她还没有做到?拜登(现在已经)很少工作,所以她基本上已经掌权了。这个问题可以归结为:你想要当前的趋势继续 4 年还是想要改变?”

高盛 CEO 所罗门:目前猜测美联储首降 25 基点,预计将看到两次甚至三次降息

高盛 CEO 所罗门表示,随着秋季的到来,预计将看到两次,甚至可能三次美联储降息。银行的前景预期略显疲软,我仍然认为软着陆是最可能的结果,目前的猜测是美联储将首降 25 个基点,但 50 个基点仍有可能。

英政府提交法案,拟将 NFT、代币化 RWA 等加密资产定义为个人财产

英国政府向议会提交了一项法案,旨在明确数字资产的法律地位,包括加密货币、NFT 和代币化 RWA,根据英国法律将被定义为个人财产。
拟议的立法为法律界在离婚等所有权纠纷案件中提供指导方针,并为受到欺诈或诈骗影响的加密货币所有者提供保护。该法案引入了一种新的财产类别,超越了现有的“占有物”(如金钱和汽车)和“动产”(如债务和股票)类别。

FTX/Alameda 关联钱包 7 小时前从 Solana PoS 质押中赎回 177693 枚 SOL,约合 2375 万美元

据链上分析师余烬监测,FTX/Alameda 关联钱包 H 4 y...gFZ 在 7 小时前从 Solana PoS 质押中赎回 177, 693 枚 SOL(2375 万美元),可能会在后续将 SOL 转移至 CEX。
H 4 y...gFZ 地址目前仍有高达 705.7 万枚 SOL (9.43 亿美元)处于质押中。

灰度:Grayscale Sui Trust 已向寻求投资 SUI 的合格投资者开放

灰度在 X 平台上发文宣布,旗下 SUI 信托基金 Grayscale Sui Trust 已向寻求投资 SUI 的合格投资者开放。

摩根士丹利:CPI 数据已符合 25 个基点的降息预期

摩根士丹利 E*Trade 的 Chris Larkin 表示,市场普遍预期美联储将在下周降息 25 个百分点,今天的 CPI 数据或多或少与目标持平,符合 25 个基点的降息预期。那些希望降息幅度更大的投资者可能会感到失望,但随着通胀似乎得到控制,市场可能会将注意力转回到经济增长方面,尤其是就业情况。

行情预测

Matrixport:比特币走势或不受美国大选影响

Matrixport 发布图表称,虽然大家关注下一任美国总统对比特币的影响,但实际上,影响可能更多体现在比特币生态系统的监管上,而非比特币本身。
在共和党(2016-2020 年)和民主党(2020-2024 年)执政期间,加密货币都经历了强劲上涨。因此,尽管媒体热议即将到来的大选,但无论谁入主白宫,比特币都可能会保持积极表现。

项目要闻

Polymarket 8 月访问量创纪录达 1380 万次,远超 Uniswap 访问量

加密分析师 The DeFi Investor 于 X 平台发文表示,预测市场平台 Polymarket 在 8 月份的访问量达到创纪录的 1380 万次,显著超过了 Uniswap 同期 370 万的访问量,Polymarket 是本周期的杀手级应用。

StarkWare 生态主管提醒 Fractal 或存在安全问题

StarkWare 生态主管在 X 平台发文表示,Fractal Bitcoin 或存在安全问题。
1.RPC 凭据是硬编码的,无法通过环境变量进行配置,并且 RPC 服务器公开暴露容易受到攻击;
2.允许来自任何 IP 地址的 RPC 连接也非常危险,会使用户的节点面临来自任何地方的潜在攻击;
3.某些设置允许来自任何 IP 的 ZeroMQ 连接会带来安全风险;消除连接数量的限制可能会导致资源耗尽;
4.官方 GitHub 组织或仓库难以识别等。

BounceBit:将从白名单系统转为无许可链

BounceBit 发布公告表示,明天将发布一项治理提案,BounceBit 将从白名单系统转变为对所有开发者和用户开放的无许可区块链。
在白名单阶段,BounceBit 专注于开发 CeDeFi 和 BounceClub。在新阶段中,BounceBit 团队将继续开发新的 DApp 和基础设施,同时提供丰富的开发者资源,包括私有 RPC、文档和技术支持。

Cyvers Alerts:印尼加密交易平台 indodax 钱包疑遭攻击,总损失约 1820 万美元

据 Cyvers Alerts 监测,印尼加密交易平台 indodax 的钱包在不同网络上进行了超过 150 笔可疑交易,总损失约 1820 万美元,可疑地址正在将各种代币兑换为以太坊。

Leituras Relacionadas

Leading Players in Large Models Drain the Primary Market

The AI industry is witnessing an unprecedented concentration of capital into a handful of leading players, signaling what insiders call the "eve of a final shakeout." A staggering funding surge exceeding $7 billion hit just three Chinese companies in May alone—Kimi, StepFun (接近完成融资), and DeepSeek—with the latter's valuation reaching $45-$50 billion. Globally, giants like OpenAI, Anthropic, and SpaceX (set to merge with xAI) are preparing for public listings, collectively eyeing valuations over $3 trillion. This capital is no longer fueling a broad "hundred-model war" but is being funneled to "refuel" the final few contenders, following a sector-wide attrition rate exceeding 90%. This frenzy is driven by a fundamental shift in industry logic. The focus has moved from比拼模型智商 (competing on model intelligence) to "token factory economics." The explosion of long-context AI agents has massively increased token consumption per task. With token supply constrained by bottlenecks in HBM memory and power infrastructure—key factors in production costs—dominance now hinges on owning and efficiently operating large-scale compute resources. Major tech firms are investing hundreds of billions annually in this AI "power grid." Consequently, competition pivots to three core areas: 1) **Monetization** as the "AGI premium" cools, forcing a shift from user growth to revenue; 2) **Cost efficiency**, where reducing inference costs becomes the ultimate KPI as model capabilities commoditize; and 3) **Strategic path divergence** between enterprise-focused AI (prioritizing integration and reliability) and consumer-facing applications (betting on scale and user engagement). The message is clear: the final capital injections are determining the endgame lineup. Success will depend not just on technical prowess, but on transforming technology into a sustainable, profitable business model with demonstrable return on massive compute investments.

marsbitHá 7m

Leading Players in Large Models Drain the Primary Market

marsbitHá 7m

AI Giants Queueing Up for IPOs: Is This the 'Last Dance' for the U.S. Stock Market?

A massive wave of IPOs from AI giants like OpenAI, Anthropic, and SpaceX is taking shape, potentially reshaping the U.S. stock market. OpenAI is reportedly preparing for a historic IPO, targeting a valuation over $1 trillion and raising roughly $60 billion, which would dwarf previous records. Anthropic is also advancing its own IPO plans, projecting significant revenue growth and achieving quarterly operating profit. However, their financial profiles starkly differ. While Anthropic is nearing profitability with a focus on enterprise clients, OpenAI continues to report substantial losses, with a negative operating margin and expectations for positive cash flow only by 2029-2030. Analysts warn these listings could trigger a major "passive fund reshuffle," forcing index funds to sell holdings in established tech giants to make room for the new entrants, potentially pressuring the broader market. Some observers view the IPO rush as a "risk transfer," allowing early private investors to cash out at peak valuations while passing future financial uncertainty to public market investors. The divergent paths of Anthropic's near-term profitability versus OpenAI's long-term, high-cost growth narrative present a critical choice for investors. The outcome of these IPOs is seen as a major swing factor for risk assets in 2026, testing whether this surge marks a new cycle or a potential peak.

marsbitHá 15m

AI Giants Queueing Up for IPOs: Is This the 'Last Dance' for the U.S. Stock Market?

marsbitHá 15m

The Richest Fed Chair in 112 Years Is Here: Kevin Warsh Is Rewriting the Rules

Kevin Warsh, with a personal fortune exceeding $130 million, became the 112nd and wealthiest Chair of the U.S. Federal Reserve on May 22nd. A former Wall Street investment banker and key figure during the 2008 financial crisis, Warsh lacks a traditional academic background for a central banker but brings deep market experience. He proposes an unconventional policy approach of simultaneously reducing the Fed's balance sheet ("quantitative tightening") while cutting interest rates, arguing that a smaller balance sheet would allow for more effective rate policy. His ascent marks a potential regime change at the Fed. Warsh aims to reform the institution's decision-making processes, tighten communication discipline among officials, and reduce reliance on forward guidance like the "dot plot." This shift responds to the Fed's current dilemma: fiscal policy is expanding the government's balance sheet through deficits, while monetary policy's ability to shrink its own $6.7 trillion balance sheet is severely constrained, creating pressure on long-term interest rates. Analysts expect Warsh's tenure to sustain high volatility in the U.S. Treasury market due to persistent supply pressures. Furthermore, his leadership coincides with a gradual, structural erosion of dollar dominance, evidenced by its declining share in global reserves and cracks in the petrodollar system, with increased use of alternatives like the Chinese yuan in oil trade. For investors, this environment underscores the importance of portfolio diversification, including assets like gold and Chinese sovereign bonds, amid a fluctuating dollar credit anchor.

链捕手Há 29m

The Richest Fed Chair in 112 Years Is Here: Kevin Warsh Is Rewriting the Rules

链捕手Há 29m

τ Scaling: Huawei's New Growth Engine Designed for the Post-Moore Era

**Tau Scaling: Huawei's New Growth Engine for the Post-Moore Era** For 60 years, progress in semiconductors was driven by Moore's Law – making transistors smaller, denser, and cheaper. This path has now stalled due to plummeting returns below 7nm, astronomical lithography costs, and rising per-transistor expenses. After six years and testing 381 production chips, Huawei’s semiconductor team proposes a fundamental shift: **stop competing on size, start competing on time**. This is the core of their "τ (Tau) Scaling" theory. It treats *time* as the key optimization metric, compressing characteristic delays (τ) across all levels – from transistor switching (picoseconds) to data center tasks (seconds), spanning 12 orders of magnitude. **What is τ Scaling?** It holistically minimizes delay/time constants (τ) across four layers: transistors (switching speed), circuits (signal delay), chips (compute/memory access), and systems (end-to-end communication). The goal is to align optimization from process and circuit design to architecture and systems using this unified metric. **Mobile Application: LogicFolding** Without advancing the process node, this technique vertically stacks chips using ultra-precision hybrid bonding, distributing critical paths across layers ("stacking floors"). Results include a 55% transistor density increase, 41% better energy efficiency, over 40% higher SRAM frequency, and a roadmap targeting 4GHz by 2029. **AI Data Center Application: Full-Link Latency Compression** With 80% of AI cluster energy and 70% cost spent on data movement, the focus is slashing communication time. Key innovations include: 1. **Unified Bus:** Cuts multi-layer protocols, reducing remote access latency from microseconds to ~100 nanoseconds – 500x faster. 2. **Hi-ONE Optical Interconnect:** Replaces copper with fiber, enabling 8Tb/s per module and scaling distances from 1m to 100m for 10,000-chip clusters. 3. **3D Folding:** Solves the "interface bottleneck" of 2.5D packaging by vertically integrating memory, power, and optical I/O alongside compute, predicting over 100x integration density gain by 2035. **Re-fusion of Logic and Memory** The AI era, where data movement is more critical than computation, demands tight 3D integration of logic and memory, shifting industry influence towards memory and advanced packaging. **Remaining Challenges** include adapting EDA tools for 3D design, optimizing wafer-to-wafer process variation and vertical interconnect losses, and establishing new energy efficiency and benchmarking standards. **Conclusion:** The era of scaling physical dimensions is over. The era of scaling time has begun. By leveraging 3D stacking, system architecture, and interconnect optimization—rather than solely chasing advanced lithography—performance and efficiency can continue to advance. This is poised to be the semiconductor industry's core roadmap for the next decade.

marsbitHá 1h

τ Scaling: Huawei's New Growth Engine Designed for the Post-Moore Era

marsbitHá 1h

NodeStrategy: The First Ordinals DAT Project, Bringing the Strategy Treasury Narrative to NFTs

**Summary: The Fundamental Flaws of NodeStrategy, the 'First Ordinals DAT'** NodeStrategy presents itself as the first Ordinals Digital Asset Treasury (DAT) on Bitcoin. Its model mirrors MicroStrategy's treasury narrative but for NFTs, specifically targeting the NodeMonkes collection (not officially affiliated). The project's core mechanism is a four-step flywheel: a 10% fee on all trades (90% to treasury, 10% to radFi/Bound marketplace) is used to buy NodeMonkes. These NFTs are then listed for sale on Satflow, with 100% of the sale proceeds used to buy back and burn the project's token, NODESTRAT, aiming to create a perpetual value cycle. However, the design contains critical, self-defeating flaws: 1. **Platform Lock-In:** As a Bitcoin Rune, NODESTRAT lacks smart contract functionality and cannot natively enforce the 10% fee. The fee can only be collected on the radFi/Bound marketplace itself. This makes the entire flywheel dependent on a single platform. If liquidity moves elsewhere, fee revenue drops to zero, halting the mechanism. 2. **Self-Suffocating Economics:** The 10% fee acts both as the flywheel's fuel and a major drag on demand. A buy/sell roundtrip incurs a 20% cost, creating a massive hurdle for traders. This strangles the very trading volume needed to generate fees. 3. **Ineffective Value Support:** The flywheel is starved. Low daily volume (~$9K) generates minimal fees for NFT purchases. The NFT "ladder" sales are slow and unpredictable (only 39 total sold), meaning buybacks are infrequent. While 30.77% of the supply has been burned, this supply reduction cannot lift price without corresponding demand, which is suppressed by the high transaction tax. 4. **Meaningless NAV:** The Net Asset Value (NAV), currently at a 0.46x discount to market cap, is merely a marketing figure. There is no redemption mechanism for token holders to claim the underlying NodeMonkes assets. Price is set by market liquidity flows, not by this theoretical backing. In essence, NodeStrategy's design forces its revenue source (trading fees) to simultaneously cripple the demand and liquidity required for its own success, trapping the project in a stagnant state.

marsbitHá 1h

NodeStrategy: The First Ordinals DAT Project, Bringing the Strategy Treasury Narrative to NFTs

marsbitHá 1h

Trading

Spot
Futuros
活动图片