“新美联储通讯社”前瞻FOMC会议:3月降息的可能性无法完全排除

金十数据Published on 2024-01-31Last updated on 2024-01-31

Abstract

鲍威尔可能会面临这些讨论如何展开的问题。一个核心考虑因素将是量化紧缩何时会开始对难以捉摸但重要的隔夜贷款市场造成干扰。

“美联储传声筒”Nick Timiraos最新撰文展望了美联储周四凌晨的政策会议,以下是该文章中的详细内容:

美联储官员本周将让利率维持在23年来的高点,会议的重点在于他们对于何时可能降息的看法(如果有的话)。

在过去的三次会议上,官员们都没有改变政策利率,但就是否必须进一步加息进行了辩论。现在,官员们正在将注意力转向何时可能降低利率,尽管一些人已表示他们并不着急。

美联储将在北京时间凌晨三点发布新的政策声明。由于没有经济或利率预测,美联储主席鲍威尔于半个小时后举行的新闻发布会将受到更广泛的关注,市场希望寻找有关美联储今年何时以及如何改变政策立场的迹象。

具体来看,投资者需要注意的事项包括:

政策声明

为了应对四十年来最高的通胀,美联储在2022年3月至2023年7月期间以40年来最快的速度将基准联邦基金利率上调至5.25%至5.5%之间。

此后,官员们一直保持利率稳定,而通胀下降速度超出了许多人的预期。这引发了一场关于何时降低名义利率以防止经通胀调整后的利率(实际利率)进一步上升的争论。去年12月的经济预测摘要显示,大多数官员预计2024年将进行三次降息。

由于预计本周不会出现政策变化,关键问题是鲍威尔和负责利率制定的联邦公开市场委员会(FOMC)是否会为其未来几个月的计划提供任何指导。

至少,美联储的政策声明预计将撤销所谓的“紧缩倾向”,即加息的可能性大于降息的可能性。部分原因是几乎所有美联储官员都表示他们认为不需要再次加息,因此维持紧缩倾向可能会令人困惑。

新闻发布会

最近几天,利率市场投资者认为美联储在3月19日至20日的后续会议上降息的可能性约为50%。随着政策声明中的指引淡化,焦点将转向鲍威尔如何强烈地抵制这些预期。

一些官员表示,尽管预计通胀率将继续下降,但他们认为降息的紧迫性并不大。由于经济表现良好,“我们可以花些时间确保我们做得正确,”美联储理事沃勒本月早些时候表示。他说,只要经济活动稳健,官员们降息的具体会议就不那么重要,因为美联储每六周开会一次。

在3月20日之前,美联储有充足的时间了解更多有关经济状况和劳动力市场的信息。因此,分析师表示,即使就那次会议而言,也没有理由坚定降息预期或排除降息的可能性。

前美联储高级经济学家、耶鲁大学管理学院教授威廉·英格利希(William English)表示:“是时候尽可能少地施加限制了,因此(鲍威尔)基本上不希望提供太多指导。”

此外,一些美联储官员对投资者因为响应鲍威尔12月新闻发布会而加大对2024年降息押注的程度感到惊讶。一些分析师认为,这可能导致鲍威尔周三更加谨慎。

风险管理

闭门辩论对于决定官员们在未来几周如何传达政策前景可能特别重要。一些人认为,美联储应该非常不愿意发出任何放松政策的信号 ,因为如果商品价格停止下跌,未来几个月通胀可能会回升。

美国消费者支出一直很强劲,GDP在第四季度出人意料地以3.3%的年化增长率增长。经济的持续强劲可能会让官员们对很快降息感到不安,因为他们已经表示不希望降息后又不得不迅速再次加息。

周三,美国劳工部将发布第四季度就业成本数据,美联储认为该数据是衡量工资增长最全面的指标,而工资增长是通胀的关键因素。

对冲基金Citadel全球固定收益经济研究主管Angel Ubide表示:“如果FOMC成员完全相信服务业通胀将会下降,以及商品反通胀将会持续,那么他们可能会在3月份开始降息。但如果其中任何一项仍然令人担忧,那么再等几个月也没什么损失。”

其他人则表示,即使美联储不太可能发出3月份降息的信号,官员们也不应该准备排除这种可能性。瑞银首席美国经济学家Jonathan Pingle表示:“通胀下降的速度比他们预测的要快得多。这表明,在未来的会议上,将通过几次降息来重新调整名义利率。”他认为美联储有理由在3月份降息。

从2007年到2023年初担任芝加哥联储主席的查尔斯·埃文斯(Charles Evans)表示,尽管经济的强劲势头给利率的实际限制程度带来了不确定性,但“你应该开始对好运能持续多久感到有点紧张。”

鲍威尔去年12月表示,美联储的政策利率“已完全进入限制性区域”。自那次会议以来,通胀持续下降。根据美联储首选的通胀指标,12月份扣除波动较大的食品和能源价格的通胀同比涨幅降至2.9%。相比之下,美联储上次会议时可获得的最新数据为10月份的3.5%。

“如果说有什么不同的话,那就是利率的限制性更强了,因为通胀已经下降。那么这是他们(政策制定者)想要的方向吗?我不这么认为,”埃文斯说。

资产负债表

尽管美联储已于去年夏天停止加息,但它正在通过另一个渠道悄悄收紧货币政策:将其7.7万亿美元的资产负债表每月缩减约800亿美元。

官员们可能会在本周开始考虑放慢(但不会结束)所谓的量化紧缩政策。虽然政策变化不会迫在眉睫,但官员们上个月表示,他们希望提前向公众传达有关资产负债表管理的任何变化。

鲍威尔可能会面临这些讨论如何展开的问题。一个核心考虑因素将是量化紧缩何时会开始对难以捉摸但重要的隔夜贷款市场造成干扰。

Trending Cryptos

Related Reads

Two Legends Lost in Three Days: Is Google's AI Talent Dam Cracking?

In three days, Google lost two AI legends. On June 18, Noam Shazeer, co-author of the seminal "Attention is All You Need" paper and Gemini co-lead, left for OpenAI. Just 48 hours later, John Jumper, 2024 Nobel laureate and AlphaFold lead, departed DeepMind for Anthropic. This follows Andrej Karpathy joining Anthropic in May. These moves highlight a structural trend: top AI talent is concentrating at mission-driven, pre-IPO firms like OpenAI and Anthropic, while Google becomes a primary source. The exodus stems from a core mission mismatch. Google's ad-centric model often subordinates AI research to product and revenue goals, creating friction for pioneers like Shazeer, who returned in 2024 only to leave again. In contrast, OpenAI and Anthropic offer singular focus on pushing AI boundaries, whether towards AGI or safety-aligned models, which deeply appeals to top researchers like Jumper. Financial incentives amplify the pull. With both OpenAI and Anthropic nearing IPO, employees stand to gain immensely from equity, an upside Google's mature stock cannot match. Furthermore, the 2023 merger of Google Brain and DeepMind, intended to consolidate strength, has instead created cultural tension and slowed the path from research to product, as evidenced by Gemini's pace. This talent redistribution is reshaping the AI landscape. While Google retains vast data and compute resources, its true crisis is the quiet, continuous loss of the people who define the field's future. The real moat in AI is not infrastructure, but the concentration of brilliant minds—a battle Google is currently losing.

marsbit1h ago

Two Legends Lost in Three Days: Is Google's AI Talent Dam Cracking?

marsbit1h ago

Behind the AI Report Card, Lies a Chinese 'Exam Setter'

Beyond the familiar performance charts like MMLU-Pro and MMMU, which major AI models strive to ace, stands a key "examiner": Chinese-Canadian researcher Wenhu Chen. An assistant professor at the University of Waterloo and founder of TIGERLab, Chen addresses the crucial need for more rigorous AI evaluation. As models like GPT-4 began scoring near-perfect results on older benchmarks like MMLU, it became difficult to distinguish their true capabilities. In response, Chen introduced MMLU-Pro in 2024, featuring harder, more reasoning-focused questions with more answer choices, successfully reintroducing meaningful performance gaps. His work extends to multi-modal evaluation with MMMU and its enhanced version, MMMU-Pro. These benchmarks test a model's ability to understand and reason with complex information from images, charts, and text across diverse academic subjects, exposing the significant challenges even top models face in genuine comprehension. Chen's background in complex QA, table reasoning, and his experience at Google DeepMind on projects like Gemini inform his approach. He understands that effective benchmarks must anticipate how models might "cheat" by memorizing data or avoiding visual analysis. His lab also actively researches video understanding and generation models (e.g., UniVideo, Vamba), ensuring his evaluation work is grounded in practical model-building challenges. Now at Meta's Super Intelligence Lab, Chen continues his focus on multi-modal data and evaluation, representing the deep yet often unseen contributions of Chinese talent in shaping the fundamental tools of the AI industry.

marsbit1h ago

Behind the AI Report Card, Lies a Chinese 'Exam Setter'

marsbit1h ago

Alliance Co-founder's Letter to Entrepreneurs: Written at the Moment Cursor Sold for $600 Billion

Alliance Co-founder's Letter to Entrepreneurs: On Cursor's $60 Billion Sale Many aspiring founders see massive exits like Cursor's $60B sale and wonder why they can't achieve the same, often concluding opportunities are exhausted. But great companies aren't built in obvious, crowded spaces. Cursor, like Stripe, Figma, and Shopify before it, started with a non-consensus belief about the future. Before ChatGPT, they believed AI would transform knowledge work. They focused on a genuinely exciting domain, became their own customer, and obsessed over power users. Their journey involved years of "glass-chewing" effort before the market was ready. The pattern is consistent: identify a long-term technological shift, find a missed entry point, and execute for years before the trend becomes obvious. First-generation products (PayPal, Adobe, Amazon) prove a market exists. Second-generation winners (Stripe, Figma, Shopify) rebuild that market around new insights, technology, or changing customer behaviors. Founders must identify their phase in the cycle. Early entrants like Coinbase or Cursor focus on making new technology usable for power users. Later entrants find the "yin" to the established "yang"—the blind spots incumbents miss as they grow distant from individual users. The key is deep market immersion. Use every product in your space. Talk to users. Build an audience. Stop looking for ideas and start *seeing* them everywhere. Then, choose one. The idea must offer a 10x improvement or solve a "hair-on-fire" pain point—something severe enough that users are already crafting workarounds. When building, avoid feature bloat. Ask: why would someone switch? Great startups rarely force new behaviors; they improve familiar workflows with drastically lower friction (e.g., Cursor forked VS Code instead of creating a new editor). Distribution is the underestimated moat. Before product-market fit, achieve distribution-market fit. How do customers discover new tools? Founders like those at Airbnb, Stripe, and Cursor did unscalable, manual work to recruit early users. The final, unteachable ingredient is resilience. Cursor built for years pre-market, faced rejection, and persisted. So did Airbnb, Nvidia, and Rain (which launched post-FTX collapse). The lesson isn't that these founders were smarter, but that they stayed in the game long enough for their insights to compound. Framework: Spot technological cycles. Cultivate unique insight. Obsess over your market. Talk to customers. Find a hair-on-fire problem. Build the simplest wedge. Win your distribution channel. Above all, don't quit when it gets hard. Most people won't do these things consistently. The few who do build the next generation of great companies. Go build.

marsbit1h ago

Alliance Co-founder's Letter to Entrepreneurs: Written at the Moment Cursor Sold for $600 Billion

marsbit1h ago

Weekly Editor's Picks (0613-0619)

Weekly Editor's Picks (0613-0619): Market Insights & Analysis This weekly digest curates in-depth analysis often lost in the information flow, focusing on key insights across macro trends, investment, and technology. **Macro & Geopolitics:** With the Strait of Hormuz reopening and military conflict shifting to negotiation, markets are pivoting from "war shock" to "supply restoration." Trades include shorting crude risk premiums, longing airlines/tourism, Asian energy importers, and bond duration, while shorting inflation expectations. LNG, fertilizer, and chemical chains are also being repriced. **Investment & VC:** Ray Dalio advises against betting on concentrated AI giants dominating indices, advocating for diversified portfolios of high-quality, low-correlation assets instead. Analysis covers the 4-year crypto cycle, predicting the core surviving product by 2029 will be asset trading markets. Current BTC metrics suggest a potential bottoming zone, presenting a patient accumulation window. SpaceX's high-profile IPO at a $2.1T valuation faces scrutiny over fundamentals, with key watchpoints being its likely inclusion in the Nasdaq index and Q2 earnings. Concerns are raised about potential "gamma squeeze" and systemic risks if its narrative-driven valuation gets amplified by passive index funds. Robinhood (HOOD) is noted for breaking its high correlation with crypto, bolstered by its stock trading and new underwriting business. **Web3 & AI:** A warning highlights ~$1.8T in off-balance-sheet AI infrastructure commitments (purchase commitments, leases) as a potential systemic risk if AI monetization lags. AI models are being used for World Cup predictions, adding a new layer for betting markets. A cost breakdown of a $20 AI subscription reveals the supply chain from model companies to cloud, GPUs, and power. **Prediction Markets:** The emergence of prediction market "concept stocks" is noted, with Robinhood developing its own platform, Rothera, signaling a shift from market competition to a "channel war" for user access. **CeFi & DeFi:** The SpaceX IPO tested perpetual contract mechanisms for pre-IPO assets, highlighting challenges in handling corporate actions like stock splits on-chain. The de-pegging of STRC (Strategy's preferred share) to ~$89 reflects market concerns over MicroStrategy's capital structure and BTC-backed leverage model. BlackRock's covered-call Bitcoin ETF (BITA) offers yield but caps upside, appealing to yield-seeking institutions. **Ethereum:** An opinion piece argues Ethereum's core strength is its vast developer community and composability, solidifying its role as the default operating system for the financial internet. **Weekly Hot Topics:** Include the US-Iran deal reopening the Strait of Hormuz, Fed's hawkish hold, Anthropic restricting model access, SpaceX acquiring Cursor, and a humorous stock surge for "Liuliumei" due to its "LLM" ticker.

marsbit1h ago

Weekly Editor's Picks (0613-0619)

marsbit1h ago

Alliance's Co-Founder's Letter to Entrepreneurs: Written on the Occasion of Cursor's $60 Billion Sale

In this letter to entrepreneurs, Alliance reflects on the success of Cursor's $60 billion sale to Elon Musk, using it as a case study to counter the misconception that opportunities in crowded fields like AI or crypto are exhausted. The piece argues that great companies like Cursor, Stripe, Figma, and Shopify are not built by geniuses with perfect ideas, but by founders who start with a non-consensus belief about the future and build for years before that future becomes obvious to everyone. They identify long-term shifts, find overlooked entry points, and execute relentlessly. The framework for success involves: 1. **Identifying your place in the technology cycle**: Early-stage opportunities focus on making new tech usable for power users (e.g., Coinbase, Cursor). Later-stage opportunities involve finding the "yin" to an existing "yang"—the blind spots of first-generation players (e.g., Stripe vs. PayPal, Figma vs. Adobe). 2. **Cultivating unique insights**: Immerse yourself deeply in the market. Use every product, talk to users, and build an audience. Insights will emerge naturally from deep engagement. 3. **Finding a "hair-on-fire" problem**: Look for a 10x improvement or a severe, urgent pain point. The strongest signal is people already building clumsy workarounds. 4. **Building a focused MVP**: Don't just add features because you can. Ask why users would abandon their current tool for yours. The best startups rarely force new behaviors; they improve familiar workflows with drastically lower friction. 5. **Winning a distribution channel**: Distribution is often the moat. Before product-market fit, achieve channel-market fit. Find where your customers are and build an engine to reach them, even through unscalable, manual efforts initially. 6. **Persistence**: The final, unteachable ingredient is resilience. Success stories like Cursor, Airbnb, and Nvidia involved years of grinding, rejection, and perseverance when the path forward seemed unclear. The conclusion is that there is no secret. Most people fail to consistently execute these steps over the long term. The few who do build the companies that define the next era. The world is yours to create.

链捕手1h ago

Alliance's Co-Founder's Letter to Entrepreneurs: Written on the Occasion of Cursor's $60 Billion Sale

链捕手1h ago

Trading

Spot
Futures

Hot Articles

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of ETH (ETH) are presented below.

活动图片