Core Insights - UBS reports that the global data center equipment market shows no signs of cooling, with current construction capacity reaching 25GW and operational capacity at approximately 105GW [1] - The industry is expected to grow by 25-30% by 2025, with strong momentum continuing into 2026 [1][4] - UBS raises mid-term growth expectations, forecasting a market growth rate of 20-25% in 2026, supported by low vacancy rates and strong construction data [1][4] Market Growth Projections - Following a projected 25-30% growth in 2025, the growth rate for 2026 is expected to remain high at 20-25%, with 15-20% growth anticipated in 2027 and 10-15% from 2028 to 2030 [4] - Vacancy rates in North America, Europe, and Asia-Pacific are at historical lows of 1.8%, 3.6%, and 5.8% respectively, indicating a supply-demand imbalance [4] Cooling Technology and Capital Expenditure - The cooling market is expected to perform exceptionally well, with a projected 20% compound annual growth rate (CAGR) by 2030, and liquid cooling technology leading with a 45% growth rate [7] - AI data centers are experiencing a structural change in construction costs, with costs per megawatt increasing by approximately 20% compared to traditional data centers, primarily due to upgrades in cooling and power infrastructure [8] AI Revenue and Market Dynamics - Annual recurring revenue (ARR) from major AI-native applications has reached $17 billion, accounting for 6-7% of the current SaaS market [10] - The adoption rate of generative AI (GenAI) is unprecedented, with companies reporting an average revenue growth of 3.6% and cost reductions of 5% over the past year [10] Technological Shifts - The transition to 800V direct current (DC) architecture is expected to reshape the competitive landscape, with widespread deployment anticipated by late 2028 to early 2029 [16] - Demand for medium voltage (MV) equipment is expected to remain stable, while low voltage (LV) AC equipment may face risks from higher voltage DC distribution [16]

Group 1 - IBM is advancing one of its largest acquisition deals in history, aiming to accelerate its strategic transformation in the artificial intelligence (AI) sector, with negotiations to acquire data infrastructure company Confluent for approximately $11 billion [1][2] - The acquisition of Confluent, which has a market value of about $8 billion, would be nearly double the size of IBM's previous acquisition of HashiCorp for $6.4 billion, highlighting IBM's aggressive push into the rapidly growing cloud and AI markets [2] - Confluent's technology focuses on real-time data stream management, essential for operating large AI models, as demand for real-time data processing capabilities is exponentially increasing with the acceleration of AI application deployment by enterprises [2][3] Group 2 - IBM is undergoing a significant restructuring, including plans to lay off thousands of employees by the end of the year, in line with other tech companies, to reposition its business for the AI era [1][2] - The company's strategy reflects a typical transformation path in the tech industry during the AI era: optimizing internal operations through AI technology, reducing traditional roles, and rapidly acquiring key technological capabilities through external mergers and acquisitions [2] - The tech sector has become one of the most active industries for mergers and acquisitions this year, with notable deals including Alphabet's $32 billion acquisition of Wiz and Palo Alto Networks' $25 billion acquisition of CyberArk [3]

美国市场表现成为焦点，此前泡泡玛特在三季度财报中披露美国销售同比增长超1200%，令投资者对海 外扩张充满期待。 但最新迹象显示增长动能正在减弱。伯恩斯坦驻香港亚洲消费股分析师Melinda Hu指出，股价疲软"很 可能是受11月份北美线下销售趋势下滑推动"，她预计公司本季度美国销售增速将放缓至500%以下。 晨星分析师Jeff Zhang警告，潜在的美国销售疲软可能削弱市场对泡泡玛特增长的信心，海外销售势头 此前一直是投资者紧密追踪的关键指标。 泡泡玛特股价周一遭遇重挫，投资者对这家潮玩制造商在美国市场的增长势头产生疑虑。在公司此前公 布美国市场超预期增长后，市场正密切关注其销售动能能否维持。 周一，泡泡玛特港股盘中一度暴跌9%，为逾一个月最大跌幅，较8月高点累计回撤约40%。市场担忧其 在美国"黑五"促销期间的销售可能未达预期，打击了投资者信心。 股价承压之际，做空力量持续集聚。据标普全球数据，截至上周四，泡泡玛特的卖空股份已升至流通股 的6.3%，创2023年8月以来最高水平。 光大证券国际策略师Kenny Ng表示，投资者对泡泡玛特销售势头放缓存在担忧，同时卖方的一些谨慎 观点也打压了股价。 从增长1 ...

Group 1 - The core view is that by 2026, going long on commodities will be the best trading theme, with all commodity charts expected to show upward trends similar to gold, driven by a shift in global economic policy from "monetary easing + fiscal tightening" to "fiscal easing + de-globalization" post-pandemic [1][3] - The report highlights that the combination of excessive fiscal easing and a relatively smaller degree of monetary easing after the pandemic, along with the end of globalization, will allow commodities to outperform bonds in the 2020s characterized by populism and inflationary growth [3][5] - The Latin American stock market has seen a significant increase of 56% year-to-date, indicating a broader breakout in natural resources and metals [3][5] Group 2 - Hartnett emphasizes that the oil and energy sectors, long overlooked by the market, represent the best "hot trade" contrarian investment opportunities, influenced by the economic policies of the Trump administration and geopolitical changes [5] - Historical patterns indicate that after the nomination of a new Federal Reserve Chair, bond yields typically rise, with an average increase of 65 basis points for 2-year yields and 49 basis points for 10-year yields within three months [6][9] - The current market is cautious about bonds due to the anticipated "hot" economic policies, with the potential for significant market movements concentrated in the first half of 2026 [12] Group 3 - The stock market is exhibiting a more complex and differentiated pattern compared to the overall pressure in the bond market, with liquidity peaks corresponding to credit spread lows [13] - In the AI sector, the focus is on adopters of AI technology rather than spenders, with mid-cap stocks expected to perform well in 2026 due to potential economic stimulus from the Trump administration [16] - Specific sectors such as cyclical "Main Street" industries (homebuilders, retail, paper, transportation, and REITs) are seen as having the best relative upside potential, supported by anticipated domestic economic support [16]

Group 1: Core Insights - Morgan Stanley's annual outlook report predicts that by 2026, global markets will be profoundly reshaped by three core forces: uneven monetary policy, a surge in AI adoption, and increasing multidimensional market and economic divergence [1] - Despite a complex macro environment, Morgan Stanley maintains a positive outlook on global equity markets, setting a target price of 7,500 points for the S&P 500 index by the end of 2026, with potential for it to exceed 8,000 points if the Federal Reserve eases policies due to improved inflation [1][3] Group 2: Monetary Policy - Morgan Stanley forecasts that the Federal Reserve will lower interest rates by 25 basis points in December this year and January next year, pausing thereafter while maintaining this "asymmetric bias" in the first half of 2026 [3] - This policy path is expected to create significant divergence among developed market central banks, with the Fed and the Bank of England anticipated to cut rates, while others like the Eurozone and Australia are expected to remain unchanged [3][5] Group 3: AI Supercycle and Economic Divergence - The report identifies 2026 as a pivotal year for AI adoption, driving a global capital expenditure boom, with investments expanding across various sectors including banking, healthcare, and logistics [4] - Morgan Stanley describes a "K-shaped economy," where corporate capital expenditure remains strong while household consumption shows significant divergence, indicating a split economic recovery [4] Group 4: Economic Growth Projections - Global GDP growth is projected at 2.5% for 2026, slightly down from 2.7% in 2025, with the U.S. GDP growth expected to hold at 2.0% and the Eurozone declining to 1.3% [4] - The report emphasizes that the global growth outlook remains resilient, supported by loose monetary and fiscal policies and reduced market concerns regarding U.S. policies [4] Group 5: Cross-Asset Strategy - Morgan Stanley has a clear stance on cross-asset allocation, recommending a bearish outlook on oil due to supply-demand imbalances, while maintaining a bullish view on gold, setting a target price of $5,000 per ounce by Q4 2026 [6][8] - The firm anticipates U.S. 10-year Treasury yields to experience a dip followed by a rise, with a mid-year target of 4.25% and an end-of-year target of 4.35% [6] Group 6: Currency Outlook - The firm maintains a bearish outlook on the U.S. dollar, expecting the Federal Reserve's asymmetric policy bias in the first half of 2026 to suppress dollar strength [8] - In emerging markets, Morgan Stanley is optimistic about high-yield currencies such as the Brazilian real, Mexican peso, and South African rand [8]

Group 1: AI Adoption Trends - The adoption rate of artificial intelligence (AI) among U.S. companies has reached 17.4%, with large enterprises showing particularly strong willingness to implement AI technologies [1][2] - 40% of large enterprises expect to deploy AI technology within the next six months, significantly higher than the overall industry average [2] - Industries leading in AI adoption include information technology, professional services, education, finance, insurance, real estate, healthcare, and entertainment [1] Group 2: Early Adopters and Investment Returns - Early adopters of generative AI are reporting positive investment returns and significant productivity improvements, encouraging more companies to invest in AI [3] - Surveys from consulting firms and business associations indicate that early adopters have realized actual benefits from generative AI applications [3] Group 3: Employment Market Impact - The surge in AI adoption is contributing to adjustments in the employment market, with October layoffs reaching the highest level since 2003 [4] - Many companies cite cost-cutting measures and AI adoption as reasons for layoffs, posing challenges for workers in industries with high AI adoption rates [4] - The trend of technology replacing human labor may accelerate in sectors leading in AI application, such as information technology, professional services, and finance [4]

印度央行正通过难以预测的干预策略应对卢比跌至历史新低的困境。这场保卫战在隔音房间内展开，专 职交易员接收秘密指令——有时是每分钟抛售1亿美元，有时是不计代价打压至目标水平，有时则是完 全观望。 报道指出，接受采访的银行家、交易员和前央行官员透露，印度央行的干预方式高度保密且不可预测， 导致市场波动性居高不下。贸易逆差扩大、美国对印度商品征收50%惩罚性关税以及外资流出，都在给 卢比施加压力。 这种策略既要遏制单边押注，又要避免耗尽外汇储备和银行系统流动性。康奈尔大学经济学教授、IMF 前中国部门负责人Eswar Prasad表示，Malhotra似乎愿意采取"逆风而行"的方式，不完全抵抗市场压力， 但在边际上进行干预以限制短期波动。 隔音房间里的秘密行动 印度央行的干预决策每天早晨在孟买南部总部做出。财政市场委员会由不同部门官员组成，讨论汇率面 临的各种压力。据一位前央行官员透露，必要时他们一天会召开多次会议，最终由行长拍板。 报道称，一旦决定干预，电话通常会打给大型国有银行的高级交易员。这些交易员驻守在密封房间内的 专门交易台，配备独立的、不被录音的电话线。 央行不会提前通知交易员，也不会透露订单深度。为使 ...

风险提示及免责条款 中共中央政治局召开会议，分析研究2026年经济工作，审议《中国共产党领导全面依法治国工作条 例》。（新华社） 市场有风险，投资需谨慎。本文不构成个人投资建议，也未考虑到个别用户特殊的投资目标、财务状况或需要。用户应考虑本文中的任何 意见、观点或结论是否符合其特定状况。据此投资，责任自负。 ...

Group 1 - Japan's 5-year government bond yield has risen to 1.44%, the highest level since June 2008 [1] - The 10-year government bond yield in Japan has increased to 1.955%, marking the highest level since July 2007 [1] - The 30-year government bond yield in Japan has risen by 2.5 basis points to 3.380% [1] Group 2 - The November economic outlook index for Japan is at 50.3, significantly below the expected 53.1 [1] - Japan's third-quarter GDP has contracted more than expected [1]

Core Insights - The transition to liquid cooling in data centers is becoming essential due to the rising power consumption of AI chips, marking a significant structural change in the industry [1][2][4] - The global market for direct liquid cooling (DLC) is projected to grow from $1.138 billion in 2024 to $31.599 billion by 2030, driven by the doubling of liquid cooling value per rack [12] Group 1: Market Dynamics - The shift to liquid cooling is not just a hardware upgrade but a strategic necessity driven by intense competition in AI chip development [1] - The liquid cooling market is expected to experience a super cycle worth $31.191 billion, reshaping the global supply chain and opening opportunities for domestic manufacturers [1][12] - The efficiency of traditional air cooling systems diminishes significantly when cabinet power density exceeds 30-40 kW, making liquid cooling a more viable option [5][4] Group 2: Technological Advancements - AI accelerators are pushing thermal design power (TDP) to unprecedented levels, with NVIDIA's GPUs projected to reach up to 7000W in the future [2][10] - Cold plate technology remains dominant for applications below 3500W, while micro-channel lid (MCL) technology is expected to become standard for higher power chips [9][10] - Liquid cooling technology can achieve a cooling capacity 4-9 times greater than air cooling, making it a more effective solution for modern data centers [7] Group 3: Supply Chain Evolution - NVIDIA is shifting its supply chain strategy from a closed model to an open ecosystem, allowing more manufacturers to enter its supply chain [14][16] - This change enables domestic suppliers to either enter as secondary suppliers or potentially become primary suppliers as their technologies mature [16] - The market for liquid cooling systems required for ASIC chips is projected to reach 35.3 billion RMB by 2026, with NVIDIA's platform requiring even more [16]