Core Viewpoint - The article discusses the performance of six AI trading models during a turbulent market period in October 2025, highlighting their different strategies and outcomes in a real trading environment [2][9]. Group 1: AI Trading Experiment Overview - The AI-Trader project, led by Professor Huang Chao's team at the University of Hong Kong, began real trading tests amidst market volatility [3][4]. - The project received significant attention, garnering nearly 8,000 stars on GitHub within a week, indicating strong community interest in AI-driven trading technologies [4]. - Each of the six AI models started with $10,000 and operated independently in the Nasdaq 100 market, adhering to strict rules without external assistance [5][6]. Group 2: Performance of AI Models - The performance of the AI models varied significantly, with DeepSeek-Chat-V3.1 achieving the highest return of +13.89%, followed by MiniMax-M2 at +10.72% [7]. - In contrast, Gemini-2.5-Flash recorded a loss of -0.54%, illustrating the impact of trading strategies on performance [7]. - The Nasdaq 100 ETF (QQQ) only increased by +2.30% during the same period, highlighting the relative success of the AI models [7]. Group 3: Key Strategies and Insights - DeepSeek-Chat-V3.1 utilized a contrarian strategy, increasing positions in NVDA and MSFT during market panic, which proved effective with a return of +13.89% [14]. - MiniMax-M2 maintained a balanced portfolio with low turnover, resulting in a stable return of +10.72%, demonstrating the importance of consistency in high-volatility environments [15][16]. - Claude-3.7-Sonnet focused on long-term holdings, achieving a return of +7.12%, reflecting a classic value investment approach [17]. Group 4: Behavioral Finance Insights - The experiment served as a behavioral finance study, emphasizing the significance of trading discipline and market patience in achieving successful outcomes [10][11]. - The findings revealed that excessive trading and emotional decision-making can lead to poor performance, as seen with Gemini-2.5-Flash's high trading frequency and negative returns [22][24]. - The results suggest that effective investment decisions stem from managing uncertainty rather than attempting to predict market movements perfectly [31]. Group 5: Implications for AI in Finance - The success of the Chinese-developed models, DeepSeek and MiniMax, indicates a shift in AI capabilities from conversational skills to practical task execution in complex financial scenarios [32]. - The article posits that financial trading provides an ideal environment for validating AI decision-making capabilities, with potential applications extending to supply chain optimization and urban management [33]. - Future developments will require further validation in areas such as regulatory compliance and risk management to ensure stability in real-world applications [34].

证券研究报告·海外公司点评·计算机 微软（MSFT） ◼ 业绩概览：公司 FY26Q1 收入、EPS 好于预期。收入为 777 亿美元， 同比增长 18%（按固定汇率计算同比增长 17%），高于一致预期。经 营利润率 49%，同比提升 2pct。EPS 为 4.13 美元，同比增长 23%（按 固定汇率计算同比增长 21%），超出预期。公司指引 FY26Q2 收入将 达 795-806 亿美元。 ◼ FY2026Q1 公司 PBP、IC 和 MPC 业务均好于预期： 生产力与商业流程（PBP）：收入 330 亿美元，同比增长 17%（按固 定汇率计算同比增长 14%），高于市场预期，主要贡献来自于 Microsoft 365 商用云。 智能云（IC）：收入 309 亿美元，同比增长 28%（按固定汇率计算同 比增长 27%），高于市场预期。其中 Azure 和其他云服务收入同比增 长高达 40%（按固定汇率计算同比增长 39%），增速高于市场预期。 更多个人计算（MPC）：收入 138 亿美元，同比增长 4%，高于市场 预期，主要得益于 Windows OEM（原始设备制造商）业务以及搜索和 新闻广告业务。 ...

Group 1 - The article provides a market analysis focusing on Microsoft Corporation and IREN Ltd, highlighting their performance and investment potential [1] - Microsoft Corporation continues to show strong growth in cloud services, contributing significantly to its overall revenue [1] - IREN Ltd is noted for its strategic initiatives in the energy sector, which may present new investment opportunities [1] Group 2 - The analysis includes financial metrics and projections for both companies, indicating a positive outlook for Microsoft and a cautious optimism for IREN Ltd [1] - Market trends affecting both companies are discussed, including technological advancements and regulatory changes in the energy sector [1] - The article emphasizes the importance of monitoring these companies for potential shifts in market dynamics that could impact investment strategies [1]

Group 1 - The report anticipates that liquidity easing will continue until the first half of 2026, with a shift towards cyclical economic recovery in the second half of the year [2][5][67] - The current technology market is compared to the late 1990s, with a concentration in high-quality large-cap stocks, raising concerns about potential market bubble [4][28][47] - The K-shaped economic recovery is expected to persist in 2026, but the driving factors will be more balanced compared to previous years [5][58][67] Group 2 - The MAG7 companies (Apple, Microsoft, Amazon, Google, Meta, Tesla, Nvidia) represent over 30% of the S&P 500's total market capitalization and contributed nearly 50% of the market expansion since 2023 [3][11][14] - The report suggests focusing on profitable leading companies within the technology sector while gradually increasing exposure to cyclical sectors as the economy recovers [6][68][69] - It is noted that the capital expenditure (CAPEX) of MAG7 is at a historical high, but growth is expected to slow down in 2026 [59][66][67]

The "everything store" might have secured its biggest customer yet.On Monday, Amazon announced that it had signed a $38 billion deal with OpenAI, offering the ChatGPT maker access to Amazon Web Services' infrastructure.On the one hand, the move isn't too surprising — a continuation of OpenAI's spending spree as it looks to secure resources to run its power-hungry artificial intelligence models.On the other, OpenAI's turn to Amazon shows that the firm is diversifying from its reliance on Microsoft, which had ...

Core Viewpoint - Investment executives from major Wall Street asset management firms suggest that investors should prepare for a potential market correction of over 10% within the next 12 to 24 months, viewing such adjustments as a healthy market development rather than a sign of a bear market [1][2]. Group 1: Market Valuation and Performance - Mike Gitlin, CEO of Capital Group, indicates that while corporate earnings are strong, market valuations are high, with most investors perceiving the market as between fair and expensive [1][2]. - Ted Pick, CEO of Morgan Stanley, acknowledges that while the market appears optimistic, a correction of over 10% is a normal trend, emphasizing the need to focus on fundamental earnings data in the coming years [2][3]. - David Solomon, CEO of Goldman Sachs, notes that while tech stocks are highly valued, this does not apply to the entire market, advising clients to maintain a global investment perspective [2][3]. Group 2: Market Dynamics and Sentiment - Solomon mentions that 10% to 15% market corrections often occur during bull market cycles, allowing investors to reassess asset classes [3]. - Ed Yardeni, founder of Yardeni Research, expresses concern over the extreme bullish sentiment in the U.S. stock market, particularly regarding major tech companies, predicting a potential short-term correction of 5% to 10% by year-end [3][4]. - The S&P 500 index has surged 37% since early April, with such rapid increases being rare historically, leading to skepticism about the sustainability of this growth [4][5]. Group 3: Risks and Market Behavior - The significant weight of major tech stocks in the market raises concerns about the potential for a sharp decline if unexpected events occur, as the market may have already priced in optimistic expectations [5]. - The Nasdaq 100 index is currently trading 17% above its 200-day moving average, indicating a potential irrational market trend [4][5].

Core Insights - Microsoft plans to significantly expand its data center footprint in the UAE through partnerships with local companies, announcing a total investment exceeding $15 billion [2][5] - The company has partnered with Group42, committing over $7.3 billion, with more than half allocated to capital expenditures for data center infrastructure [2] - The investment will enhance local data center computing capacity to the equivalent of 81,900 H100 chips, nearly quadrupling its current capabilities [2] Investment Details - The new investment in the UAE amounts to $7.9 billion, which will be used to upgrade data center infrastructure [2] - Microsoft has received approval from the U.S. Department of Commerce for the export of new GPUs to the UAE, including the advanced GB300 super chip [3] - The infrastructure investment is expected to incur $2.4 billion in local operating expenses and sales costs [3] Collaboration with Lambda Labs - Microsoft has engaged in a partnership with Lambda Labs to build AI infrastructure worth several billion dollars, involving thousands of GPUs [3][5] - Lambda's cloud platform reportedly contains over 250,000 GPUs, and the company raised $480 million from a consortium including NVIDIA [3] Previous Partnerships - Microsoft previously signed a similar AI infrastructure agreement with CoreWeave, expecting to invest $10 billion on that platform by the end of the century [4][5]

人工智能巨头正面临一个新瓶颈：电力。微软CEO Satya Nadella透露，公司已采购的芯片因电力和数据中心不足而闲 置。Altman指出，科技公司面临两难：若现在锁定长期电力合同，未来可能因新能源技术的突破而蒙受损失；若投资不 足，又可能无法满足AI需求的爆炸式增长。 硬·AI 作者 | 龙 玥 编辑 | 硬 AI 人工智能竞赛的焦点正从算力转向电力。科技行业领袖们承认，他们正努力应对一个根本性的不确定性： 未来的人工智能究竟需要消耗多少能源。 长期以来，市场普遍认为获取先进的图形处理器（GPU）是部署人工智能服务的最大障碍。然而， Nadella的言论证实，瓶颈已经转移。当科技公司斥巨资采购的芯片无法被点亮时，算力优势便无从谈 起。 这一现象反映了习惯于快速迭代的软件和芯片公司，在面对能源和房地产等重资产、长周期行业时所遭遇 的挑战。在美国，数据中心的电力需求在过去五年中急剧上升，打破了此前长达十年的平稳态势，其增长 速度已超过了公共事业公司的发电容量规划。 这迫使数据中心开发商寻求"电网外"（behind-the-meter）供电方案，即绕过公共电网，直接从发电设施 获取电力。 02 需求迷雾：AI ...

/ CONTENTS 01 02 03 04 05 2 / 3 / 01 DeepSeek AI 图：Deepseek日活高速增长 图：Deepseek多项基准测试性能对标国际顶尖AI模型 图：豆包日均token用量高速增长 | Benchmarks | DeepSeek-R1- | OpenAl- | Gemini-2.5- | Owen3- | DeepSeek-R1 | | --- | --- | --- | --- | --- | --- | | | 0528 | o3 | Pro-0506 | 235B | | | AIME 2024 数学资源 pass@1 | 91.4 | 91.6 | 90.8 | 85.7 | 79.8 | | AIME 2025 数学見賽 pass@1 | 87.5 | 88.9 | 83.0 | 81.5 | 70.0 | | GPQA Diamond 科学测试 pass@1 | 81.0 | 83.3 | 83.0 | 71.1 | 71.5 | | LiveCodeBench 代码生成 pass@1 | 73.3 | 77.3 | 71.8 | 66.5 | 63.5 ...

Core Insights - Microsoft announced a total investment of $15.2 billion in artificial intelligence (AI) and related projects in the UAE [1] Investment Details - From 2023 to the end of this year, Microsoft plans to invest over $7.3 billion in the UAE, which includes a $1.5 billion equity investment in G42 Group and over $4.6 billion in capital expenditures for AI and cloud data centers [1] - From early 2026 to the end of 2029, Microsoft will continue to invest more than $7.9 billion in related projects in the UAE [1] AI Utilization in UAE - A report from Microsoft indicates that the UAE ranks first globally in AI utilization per capita, with 59.4% of the population using generative AI, surpassing Singapore's 58.6% [1] Collaboration with ADNOC - Microsoft signed an agreement with the Abu Dhabi National Oil Company (ADNOC) to jointly develop and deploy AI applications, aiming to promote smart transformation in the energy sector [1] - Under the agreement, Microsoft will provide AI tools and employee training programs to ADNOC, and both parties will explore establishing a joint innovation ecosystem to develop transformative smart solutions for the energy industry [1]