中国基金报记者 储是 全球9家主要央行降息 美联储结束缩表周期 【 导读 】 2025年，世界 在 变奏中寻找新的平衡 2025年， 包括美国联邦储备委员会（美联储）、欧洲中央银行（欧央行）、英国央行，以及 澳大利亚 央行 、新西兰 央行 、加拿大 央行 、瑞典 央行 、挪威 央行 和瑞士央行 在内的9 家主要央行选择降息 。日本央行成为例外，在 年初和年底先后两次上调了利率。 美联储继2024年开启降息周期后，2025年持续 保持 宽松 政策 ，分别在 2025年 9月、10 月、12月进行了三次幅度各为25个基点的降息。同时，美联储官员们于10月会议官宣缩表终 止计划，自12月1日起结束为期三年半的缩表行动。 "DeepSeek时刻"令全球发现中国价值 2025年，以深度求索公司（DeepSeek）的通用人工智能模型和宇树科技在通用人形机器人 领域的突破为代表，中国在前沿科技与先进制造行业取得了全球瞩目的进展， 展现了中国科 技创新的潜力与实力 。 中国证监会主席吴清在全国两会 期间 指出，人工智能是今年两会的热词，DeepSeek在全球 人工智能领域脱颖而出，不仅使AI行业深受震撼，也让世界对中国科技创 ...

波澜壮阔的2025年即将结束。这一年，权力的更迭、科技的狂飙、货币的易位与地缘的震荡交织在一起，构成了一幅极其复杂的历史画卷。我们见 证了传统秩序的加速崩解，也捕捉到了新秩序在阵痛中萌芽的微光。 作为记录者，财联社连续第四年推出年度海外十大新闻评选，试图从纷繁复杂的碎片中，厘清这一年影响全球资本市场与命运走向的核心脉 络。 以下是财联社评选出的2025年十大海外新闻 1. 特朗普就任美国第47任总统，任期首年频挥关税大棒，全球不确定性陡增 2025年1月20日，特朗普重返白宫，正式开启了他的第二个美国总统任期。这位奉行"交易艺术"的总统在就职后的"百日新政"中，以令市 场瞠目结舌的速度兑现了一系列竞选承诺。他不仅签署了多项撤销前任政府气候与能源政策的行政令，更将矛头直指全球贸易体系，宣布对 多国实施普遍性基础关税和针对性的高额附加关税，试图以此作为逼迫制造业回流美国的终极杠杆。 这一政策在全球供应链中引发了"强震"。由于关税壁垒的陡然升高，全球跨国企业不得不重新评估其生产布局，导致短期内航运成本波动剧 烈，多国通胀压力因进口成本上升而再度抬头。欧盟、加拿大、墨西哥等美国贸易伙伴纷纷表达了强烈不满，并相继出台贸 ...

点击按钮▲预约直播 " 如今的 AI 巨头们各有分工，英伟达们埋头造芯片， OpenAI 们专注修炼 大模型 ，微软和亚马逊的云业务部门当起 AI 房东，将 GPU 数据中心租给 AI 公司使用。大家 各司其职，互有竞争与合作。而谷歌是一个稀有的全栈自研玩家。 " 文 /巴九灵（微信公众号：吴晓波频道） 蜜月 特朗普喜欢在他的社交账号上使用AI。 一张合成的照片中，他打扮成了教皇。一个合成的视频里，他身处白宫，冷眼旁观特工逮捕前总统奥巴马。夏天美国人游行抗议时，他还发了个伪 造的视频，总统先生坐在战斗机里，向抗议者们倾倒粪便。 2025年，美国的AI巨头们继续卷算力、卷参数，比拼谁家模型更聪明，技术的进步，已经能搞出以假乱真的视频和语音。内容创作成本的降低， 带来的一个后果，就是升级了特朗普的政治宣传武器。他可以更轻松直观地抹黑对手、自我加冕与歌颂、传播其政治主张。 另外一个后果，就是垃圾的批量化生产。韦氏词典和《经济学人》选出的2025年度关键词是"slop"。"slop"并非新造词，其历史可追溯至15世 纪，原意为稀烂食物或泔水。而今，它成了AI生成内容的代名词：海量、平庸、毫无个性，正在堵塞互联网。 图 ...

德银认为，当前AI热潮并非单一泡沫，而是由估值、投资、技术三重泡沫交织。公开市场巨头估值有盈利支撑，而私营公司估值已极度高企。天量投资 由现金流驱动，非债务扩张，但复杂循环融资与潜在技术瓶颈埋下风险。AI需求强劲且成本骤降，但能源与芯片供应或成最终制约。 站在2025年12月的时间节点，距离ChatGPT发布仅过去三年，市场对于"AI泡沫"的讨论已至沸点。德意志银行认为，当前AI热潮既不是完全的泡沫，也 不是毫无风险，关键在于区分不同类型的"泡沫"。 12月12日，德银在最新研报中创新性地将AI泡沫分为估值泡沫、投资泡沫和技术泡沫三个维度进行分析。 报告称， 公开市场大型科技公司的估值有盈利支撑，投资增长符合趋势且由现金流推动，技术进步仍在持续。真正的风险集中在估值过高的私营公 司、可能失控的循环融资结构，以及潜在的技术瓶颈和供应限制。 估值泡沫：估值分化揭示真实风险所在 德银的核心观点是当前AI热潮并非单一泡沫，而是由三种不同性质的泡沫构成。 在估值维度 ，报告显示希勒周期调整市盈率（Shiller Cyclically Adjusted Price/Earnings ratio）已超过40，接近2000年 ...

Summary of Key Points from the Conference Call Company: NVIDIA Core Insights and Arguments - **Share Repurchases and Shareholder Value**: Since 2018, NVIDIA reported approximately $205 billion in net income and $188 billion in free cash flow, while repurchasing $91 billion in shares. The claim that repurchases did not create shareholder value is countered by the assertion that repurchases were made below intrinsic value, boosting EPS by 5% and adding over $200 billion in market capitalization at constant P/E [4][5][7] - **Accounts Receivable Growth**: NVIDIA's Days Sales Outstanding (DSO) of 53 days is slightly above the historical average of 52 days, indicating that the company is not struggling to collect payments from customers. The claim of increasing DSO is refuted by stating that overdue accounts receivable are negligible [8][9] - **Inventory Growth and Demand**: A 32% quarter-over-quarter increase in inventory is interpreted as weak demand. However, NVIDIA argues that inventory includes raw materials and work-in-progress, and is consistent with historical trends in anticipation of future growth [10][11][12] - **Cash Flow Conversion**: NVIDIA generated $23.8 billion in cash from operations in Q3, with a free cash flow conversion rate competitive with peers. The claim of low-quality earnings is dismissed as NVIDIA's free cash flow has averaged 98% of GAAP net income since FY18 [13][15][16] - **Circular Financing**: Allegations of NVIDIA participating in a $610 billion circular financing scheme are countered by stating that strategic investments represent a small share of revenue and are transparent in financial reporting [17][18][19] - **AI Startups Financial Viability**: Concerns about AI startups losing money are acknowledged, but NVIDIA emphasizes that these companies are valued based on future growth potential rather than current earnings, with significant market opportunities anticipated [21][23] - **Historical Accounting Fraud Comparisons**: NVIDIA refutes claims that its practices resemble historical accounting frauds, asserting that its business model is sound and transparent, with no use of special purpose entities to hide debt [24][25][26][27] - **Gross Margin Decline**: A slight decline in gross margin is attributed to channel incentives and warranty reserves, with the company clarifying that margins increased sequentially [29][30] - **Depreciation Practices**: Claims that NVIDIA's depreciation is understated are countered by stating that useful life estimates are consistent with peers, and older GPUs continue to generate strong margins [31][32][33] - **Insider Selling**: Claims of significant insider selling are dismissed, clarifying that the individuals mentioned are not insiders and their investment decisions are not commented on [34][36] - **Bitcoin Price and AI Sector Stress**: The correlation between Bitcoin prices and NVIDIA's stock is noted, but NVIDIA denies any connection between cryptocurrency prices and its accounting practices [37][38] - **Threats to Hyperscale Data Centers**: Concerns about decentralized alternatives to hyperscale data centers are addressed by emphasizing the advantages of large-scale operations in AI performance and efficiency [39][40] - **SEC Scrutiny**: NVIDIA states that it is not aware of any SEC investigations and maintains compliance with all regulations [41] Other Important Points - **Future Revenue Guidance**: NVIDIA anticipates a sequential revenue increase of $8 billion to $65 billion, indicating confidence in demand despite inventory growth [12] - **Warranty Costs**: Warranty costs have increased due to the complexity of new products, which is properly accounted for in financial statements [35] - **Market Potential of AI**: The potential economic impact of AI is highlighted, with estimates suggesting a significant market opportunity that justifies high valuations for AI startups [23] This summary encapsulates the key points discussed in the conference call, providing insights into NVIDIA's financial health, market strategies, and responses to various claims and concerns.

Core Viewpoint - Nvidia is responding to competitive pressures and short-seller criticisms through unusual public and private actions, which may indicate a lack of confidence rather than quell investor concerns [2][12]. Group 1: Market Response - Nvidia's stock fell approximately 2.6% to a new closing low in over two months after a drop of more than 7% during trading, while Alphabet's stock rose 1.6%, nearing a market capitalization of $4 trillion [2]. - Nvidia's unusual communication strategy, including a public post on social media and a private memo to analysts, has been interpreted as a sign of insecurity, as a leading company typically does not need to respond to every market noise [4][11]. Group 2: Competitive Landscape - Nvidia's market share in AI chips exceeds 90%, but concerns arise as major clients like Meta consider adopting Google's custom AI chips, Tensor Processing Units (TPUs), which could indicate a weakening of Nvidia's competitive moat [7]. - Google has stated that both its TPUs and Nvidia's GPUs are experiencing growing demand, highlighting a trend among large tech companies to diversify their AI infrastructure suppliers, which is a concern for Nvidia investors [7]. Group 3: Internal Communications - Nvidia distributed a seven-page memo to Wall Street analysts to counter criticisms from notable investors like Michael Burry, who likened the current AI hype to the late 1990s internet bubble [4][8]. - The memo addressed key points raised by critics, including accounting practices, equipment depreciation, and allegations of circular financing, asserting that Nvidia's business is fundamentally sound and transparent [9][10]. Group 4: Analyst Perspectives - Analysts have noted that Nvidia's defensive actions may backfire, as a confident leader would typically let performance and products speak for themselves rather than engage in extensive rebuttals [11]. - The perception of Nvidia as "stuck" in its responses has heightened existing fears regarding uncontrolled investments in AI, increased competition, and concerns over alleged circular financing [11][12].

Core Viewpoint - Nvidia is responding to competitive pressures and short-seller criticisms through unusual public and private actions, which may indicate a lack of confidence rather than quell investor concerns [1][2]. Group 1: Market Response - Nvidia's stock fell approximately 2.6% on the day of its public statement, reaching a new closing low in over two months, while Alphabet's stock rose 1.6%, nearing a market capitalization of $4 trillion [1]. - The company's unusual communication strategy has led analysts to perceive it as "reactive," suggesting that a confident leader would rely on performance and products rather than feeling compelled to defend against every criticism [9]. Group 2: Competitive Landscape - Nvidia publicly asserted its GPU technology is "a generation ahead" of Google's offerings, emphasizing its ability to run all AI models across various computing scenarios [3]. - Concerns are growing that if major clients like Meta shift to Google's Tensor Processing Units (TPUs), it could signify a breach in Nvidia's dominant market position, which currently holds over 90% of the AI chip market [5]. Group 3: Internal Communications - Nvidia distributed a seven-page memo to Wall Street analysts to counter claims of accounting fraud, circular financing, and an AI bubble, particularly addressing criticisms from notable investors like Michael Burry [2][6]. - The memo clarified that Nvidia's accounting practices are sound and that the company does not engage in special purpose entity financing, while also defending the depreciation timelines of its GPUs [6][7].

Core Insights - Nvidia's recent earnings report, which initially caused a surge in stock price, ultimately led to a decline, indicating a shift in market sentiment and expectations [3][4] - The market's threshold for "good news" has significantly increased, with investors questioning sustainability and profitability despite Nvidia's strong performance [5][6] Market Sentiment - Wall Street is experiencing a divide between optimistic and skeptical investors, with the former viewing recent pullbacks as a temporary adjustment in a bull market [6][7] - Skeptics are concerned about high valuations and systemic risks associated with "circular financing," where major companies invest in startups that in turn purchase services from them, creating a false sense of prosperity [7][9] Financial Data - Major tech companies like Microsoft, Amazon, Meta, and Alphabet contribute over 40% of Nvidia's revenue and plan to increase capital expenditures by 34% to a total of $440 billion in the next 12 months [9] - Despite Nvidia's optimistic guidance, concerns arise regarding the ability of these companies to convert high spending on GPUs into sustainable profits [9][10] Stock Performance - CoreWeave Inc. has seen a 46% drop in stock price, while Oracle's shares fell by 24%, marking the largest monthly decline since the 2001 internet bubble burst [11][12] - The semiconductor sector is also under pressure, with related indices dropping 11% in November and popular stocks like AMD and Arm experiencing declines over 20% [16] Future Outlook - The AI investment cycle is still perceived as in its early stages, but the era of easy capital and storytelling to attract investment may be coming to an end [17][18] - Investors are urged to seek clear paths to return on investment, as the current environment is fraught with uncertainty and potential volatility [18]

Core Insights - Meta plans to invest $60 billion in AI despite reporting a net profit of $37 billion in the first three quarters of 2025, highlighting the financial challenges faced by tech giants in the AI arms race [1][2] Financing Challenges - The need for massive funding for AI infrastructure, including expensive AI chips and data centers, poses a dilemma for tech giants on how to secure funds without negatively impacting their financial statements [2][3] - Morgan Stanley estimates that "invisible debt" could reach $800 billion by 2028, representing significant liabilities that do not appear on the balance sheets of these companies [2] SPV Financing Method - The Special Purpose Vehicle (SPV) financing method allows tech giants to isolate debt and optimize their financial reports by transferring the debt to a separate entity [3][4] - This method involves creating an SPV to borrow money using the parent company's credit, allowing the SPV to purchase assets and lease them back to the parent company, thus keeping the debt off the parent company's balance sheet [4] Examples of SPV Utilization - Meta successfully utilized this SPV method to increase its debt by $30 billion on its balance sheet while leveraging it to acquire $60 billion in computing assets [4] - Google has adopted a similar strategy by providing credit guarantees to weaker companies, allowing them to secure loans for data center assets, which are then leased back to Google [5] Circular Financing - The concept of circular financing allows companies to create a closed loop of capital flow among related parties, enhancing financial efficiency [7] - For instance, xAI established an SPV to raise $20 billion for purchasing NVIDIA chips, with minimal direct debt risk, showcasing the flexibility of this financing model [7] Industry Dynamics - Major tech companies are forming strategic alliances to create a tightly-knit capital community, which can amplify their financial capabilities and market influence [9][10] - Recent collaborations among giants like OpenAI, NVIDIA, and Oracle have resulted in over $1 trillion in infrastructure and chip agreements, indicating a trend towards deeper integration in the AI sector [9] Scaling Law and Market Sentiment - The pursuit of Scaling Law drives exponential growth in computing demand, benefiting companies like NVIDIA, which has seen significant revenue increases [15] - However, industry leaders express caution regarding potential irrational exuberance in AI investments, with warnings about the risks of a bubble [15][16] Capital Market Movements - Notable investors are shifting their strategies, with significant sell-offs in NVIDIA stock while simultaneously investing in AI applications and models, indicating a transition in focus from hardware to software [16][17] - This shift suggests that while financing challenges may be temporarily addressed, the competition in the AI landscape is just beginning, with a more intense focus on applications and models ahead [17]

Core Viewpoint - The article discusses the ongoing AI arms race among major tech companies, particularly the "Big Seven" in the U.S. stock market, highlighting the significant capital expenditures being made to build AI infrastructure and the associated market concerns regarding the sustainability of these investments [1][2]. Group 1: Market Performance and Reactions - The recent sell-off in the tech sector has heavily impacted companies like Meta, while Alphabet and Apple have shown resilience, with their stock prices increasing by 6.6% and 0.4% respectively in the past month [5][4]. - The Nasdaq Composite Index has dropped by 6.1% since early November, reflecting growing investor concerns over excessive AI spending [5]. Group 2: Company Strategies and Market Sentiment - Alphabet's AI product Gemini has gained traction, particularly with the recent launches of Gemini 3 and Nano Banana Pro, contributing to positive market sentiment [5][7]. - Apple's conservative capital expenditure strategy has been validated as a means to mitigate concerns over excessive spending, allowing it to avoid the pitfalls faced by other companies [6][5]. Group 3: Competitive Landscape and Future Outlook - Google has successfully alleviated investor fears regarding AI's impact on its search business, positioning Gemini as a strong competitor to ChatGPT [7]. - Analysts suggest that if the AI bubble bursts, larger companies like Google and Apple may emerge stronger, benefiting from reduced competition and lower spending demands [8][9]. Group 4: Risks and Industry Dynamics - The article highlights the potential risks for smaller players in the AI space, as a downturn could lead to significant reductions in orders for hardware suppliers like Nvidia [11]. - The cyclical nature of investments in semiconductors and AI infrastructure is noted, indicating that these investments carry higher risks [12].