美伊突传重磅!国际油价重挫,黄金高开

投研日志Pubblicato 2026-07-27Pubblicato ultima volta 2026-07-27

Introduzione

英伟达与SK海力士建立长期合作关系,共同保障并共同开发包括HBM在内的下一代AI内存。两家公司将共同开发和优化下一代AI内存解决方案,包括HBM,以满足从大型语言模型训练到代理AI和物理AI等不断变化的基础设施需求。

据央视新闻7月26日报道,美国常驻联合国代表迈克尔·华尔兹当天表示,为给外交谈判留出更多空间,美国总统特朗普已暂停对伊朗的军事打击。华尔兹没有透露谈判相关具体情况。

另据央视新闻报道,多名美国官员透露,美国总统特朗普24日在与高级助手和内阁高官开会讨论扩大对伊朗军事行动时,遭到副总统万斯和美军参谋长联席会议主席丹·凯恩及多数幕僚的担忧和反对,会后特朗普决定,暂不恢复对伊朗大规模打击。多名官员担忧恢复对伊朗大规模打击将进一步消耗美军本已吃紧的弹药库存。

受美国称暂停对伊朗军事打击的影响,国际油价重挫,黄金、白银高开。

7月27日,WTI原油期货主力合约开盘跌超6%,一度跌破84美元/桶;布伦特原油期货主力合约跌超5%。截至发稿,WTI原油期货主力合约跌4.79%,报85.03美元/桶;布伦特原油期货主力合约跌4.2%,报87.83美元/桶。

同日,伦敦现货黄金、白银跳空高开。截至发稿,伦敦金涨0.79%,报4084.67美元/盎司;伦敦银涨1.97%,报59.329美元/盎司。

高盛对冲基金业务主管Tony Pasquariello认为,当前黄金投机性多头已被清洗,叠加央行购金重启、金价多次在4000美元附近获得支撑,当前是建立黄金结构性多头头寸的合适时机,黄金中期价格预测风险偏向上行。

此外,本周全球市场看点不断,美英日央行将先后公布利率决议。财报方面,微软、苹果、亚马逊、Meta四大科技巨头携手SK海力士、三星电子、铠侠等日韩存储芯片巨头集中放榜。

伊朗外交部:伊美间信息交流

及斡旋方活动仍在进行

当地时间7月26日,伊朗外交部发言人巴加埃表示,伊朗与美国之间的信息交流仍在持续,斡旋方也正继续开展相关工作。

巴加埃说,对伊朗而言,当前的首要任务是维护国家主权和领土完整,保护伊朗人民免受美国所犯“战争罪行”的侵害。

他同时表示,伊美谅解备忘录并不是一份篇幅冗长、内容复杂的文件,而是一份仅包含14项条款的简短谅解备忘录。国际社会原本期待美国“至少这一次”能够履行自身承诺,但美国的所作所为公然严重违反了该谅解备忘录的多项内容,使外交努力“第三次遭到背弃”。

美联储7月加息悬念将揭晓

美联储将于北京时间7月30日凌晨2点公布议息决议,市场总体预期联邦基金利率维持3.50%—3.75%区间不变。市场核心关注点在于,政策声明中是否释放9月加息25个基点的线索。

荷兰国际集团(ING)分析师詹姆斯·奈特利在报告中写道,美联储主席沃什一贯回避前瞻指引、偏好简短政策声明,投资者或难以获得明确信号。叠加此前美国CPI、PPI、就业数据均不及预期,本次会议释放强硬信号的动力有限。但能源价格飙升、AI产业需求推升通胀的潜在风险,仍会让市场押注9月加息。

油价飙升、通胀压力持续,加之沃什彻底抛弃前任惯用的前瞻指引做法,也令本周的美联储决议结果存在一定不确定性。据CME Group联邦基金期货数据,市场目前定价美联储本周加息25个基点的概率约为38%,较一周前的13%大幅跳升。同时,利率互换市场显示加息概率约为30%,维持不变的概率约为70%。如此接近会议日期仍存在如此大的分歧,在近年来极为罕见。

美国银行美国利率策略主管Mark Cabana表示,当前货币政策是否具有限制性,本身就是一个很大的疑问。而油价现在又在重新上涨。PGIM首席美国经济学家Robert Sockin则将本周会议形容为“几乎是五五开”。

半导体、存储科技股财报集中放榜

市场本周迎来财报季高峰:7月29日,微软、Meta、SK海力士发布财报;7月30日,苹果、亚马逊、三星电子登场;7月31日,铠侠公布业绩。高通、希捷科技、西部数据、康宁、Bloom Energy、安费诺、Rambus等半导体和AI产业链关键企业也将发布财报。

美日韩存储芯片巨头(SK海力士、三星电子、铠侠、西部数据、希捷科技)集中放榜,市场关注HBM等AI用高端存储出货及通用存储定价趋势。微软、苹果、亚马逊、Meta四家MAG7科技巨头的业绩将检验AI商业化成效——云服务增速、AI功能落地和广告复苏是核心看点。此外,康宁和Amphenol作为AI基础设施硬件供应链的重要环节,Bloom Energy作为AI数据中心清洁能源供应商,其订单情况将从侧面反映数据中心资本开支景气度。

日韩存储公司方面,市场将重点关注SK海力士HBM3E出货、HBM4量产及主要客户的长期订单安排,同时关注服务器DRAM和企业级固态硬盘价格能否延续上涨,以及后续资本开支计划。

在三星电子即将发布的财报中,利润来源将得以明确,公司的HBM业务进展或也有望同步披露。据悉,三星正在加快HBM4及后续产品的认证和量产,市场希望看到,公司缩小与SK海力士的差距。与前两家公司相比,铠侠的财报更能反映NAND闪存及企业级固态硬盘市场景气度。

韩媒发布的一份行业分析报告显示,今年第二季度SK海力士的营业利润有望创下64.1万亿韩元的历史新高,同比增幅高达596%,比一季度增长超70%。上述财报,或将影响下一阶段芯片股的走势。

三星电子、SK集团与美企

签下9500亿美元半导体大单

上周末,韩国总统政策办公室主任金容范在新闻发布会上宣布,三星电子和博通公司签署了一份谅解备忘录,就代工合作达成协议,将在未来五年内供应价值2000亿美元的先进存储半导体,并生产人工智能芯片;SK集团决定在未来五年内,与包括英伟达在内的全球大型科技公司开展总价值7500亿美元的先进存储半导体长期供应合作。报道称,数据中心合作也将启动。

其中,SK集团与英伟达通过一项涵盖人工智能工厂和下一代内存的5000亿美元以上战略合作项目,进一步扩大战略合作。

英伟达与SK海力士建立长期合作关系,共同保障并共同开发包括HBM在内的下一代AI内存。两家公司将共同开发和优化下一代AI内存解决方案,包括HBM,以满足从大型语言模型训练到代理AI和物理AI等不断变化的基础设施需求。

Crypto di tendenza

Letture associate

A 'Difficult Midsummer' for Stock Market Bulls: $100 Oil, AI Backlash, and Tariff Resumption

Global equities face a triple threat this summer: surging oil prices, a burgeoning AI capex crisis, and resurgent tariffs, pressuring the core pillars of the current bull market. Brent crude topped $100/barrel amid Middle East and Red Sea supply disruptions, while proposed U.S. tariffs fueled inflation fears, pushing the 10-year Treasury yield to 4.66%. Simultaneously, the tech rally faltered as Alphabet's steep AI capex hike sparked concerns over returns, dragging down mega-caps and contributing to a weekly S&P 500 decline. The "Goldilocks" narrative of resilient profits, controlled inflation, and endless AI expansion is cracking. Rising oil prices threaten to reignite persistent inflation, forcing a repricing of interest rate risks. In tech, massive debt-fueled AI investments are facing investor scrutiny as higher rates raise the required return threshold. Fears are growing that the AI spending boom may be unsustainable, especially with moves toward cheaper, open-source models. Next week brings a crucial test with key central bank meetings and earnings from major tech firms like Microsoft and Apple. Technical indicators are deteriorating, with selling pressure mounting and assets like gold and the dollar gaining on避险 sentiment. Analysts warn that elevated valuations and compressed risk premiums leave markets vulnerable, with significant potential downside if the current headwinds persist.

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A 'Difficult Midsummer' for Stock Market Bulls: $100 Oil, AI Backlash, and Tariff Resumption

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Three 'Reflexivity' Shadows Hang Over the Market

Global markets are currently enveloped by three mutually reinforcing "reflexive" loops: oil price politics, outsized capital expenditure by hyperscale cloud providers, and AI debt risks. According to Goldman Sachs, the combined negative feedback from these factors places the market in a fragile and precarious state. The first loop involves the two-way feedback between surging oil prices and rising interest rates. Brent crude's brief breach of $100 per barrel tests expectations of a U.S. policy response to curb prices and inflation. However, the delay in such intervention forces markets to increasingly price in the risks themselves. Higher energy costs are already impacting corporate earnings, as seen with an airline's profit warning, and threaten to fuel broader inflation. The second loop concerns the massive, escalating capital expenditure (capex) by major tech firms like Google, which recently raised its 2026 capex forecast significantly. The market's tolerance for viewing such spending as a cost-free growth signal is waning, shifting focus to investment returns. This competitive capex spiral pressures the entire cloud and semiconductor sector. Furthermore, the competitive gap in AI between leading closed-source and Chinese open-source models is narrowing rapidly, threatening the economic rationale behind massive investments. The third reflexive danger lies in the financing structures supporting this expansion. Bond prices for entities funding AI infrastructure, such as a Meta financing vehicle, have fallen sharply from issue price. While hyperscale balance sheets remain strong, soaring capex is eroding free cash flow conversion. There is a growing risk that today's capacity build-out leads to future oversupply and significant depreciation charges. Key near-term tests for these dynamics include Microsoft's upcoming earnings, which will scrutinize its balance of growth, spending, and cash flow, and the IPO of Chinese memory chipmaker CXMT, a major new competitor. The current environment is characterized by reflexivity, where each variable is both a cause and an effect, creating a self-reinforcing cycle of uncertainty.

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Three 'Reflexivity' Shadows Hang Over the Market

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Claude Doesn't Submit Code Directly After Writing It: Runs 4 Skills for Self-Check, Fixes Issues, Then Comes Back to You

Claude No Longer Submits Code Directly: 4 Self-Check Skills to Run Before Coming Back to You AI already writes code, but the burden of reviewing it still falls on you. To address this, Anthropic has built a "verification loop" into Claude Code. After writing code, Claude now runs four self-check skills before delivering the work: * `/code-review`: Finds potential bugs and provides review feedback. * `/simplify`: Cleans up the diff, removing redundant or over-complex implementations to reduce future maintenance costs. * `/verify`: Performs end-to-end validation, actually running the application to confirm the feature works, not just appears to. * `/design`: Used only for UI changes; cross-references the implementation against the project's DESIGN.md file. This loop extends the AI agent's workflow from "gather context → execute" to "gather context → execute → auto-verify → fix → re-verify." It tackles the new bottleneck in AI-assisted development: the speed of verifying code now outpaces human review. These skills are built on Claude Code's existing verification foundation (like running apps and using linters). Teams can create their own custom verification skills by documenting their repetitive manual checks in plain language as Markdown files. Verification can be triggered at four levels: manually (Standalone), embedded in a task, chained with other skills, or automatically on every PR (On every PR). The shift signifies that competition in AI programming is moving from code generation to robust verification and self-correction. Well-built verification loops allow AI agents to run longer and more autonomously with less human supervision. Skills, which encapsulate team knowledge and workflows, are becoming a cross-vendor standard, meaning a team's efficiency gap will depend less on the AI model and more on their investment in these automated workflows and verification mechanisms.

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Claude Doesn't Submit Code Directly After Writing It: Runs 4 Skills for Self-Check, Fixes Issues, Then Comes Back to You

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How Has Beijing Become a 'Global High Ground'?

How did Beijing become a "global highland"? In the first half of the year, Beijing's GDP grew by 5.4%, with growth in Q1 reaching 5.9%. Key drivers were not consumption or real estate, but hardcore sectors like chips, robotics, computing power, and large AI models. Investment concentrated sharply in tech, with high-tech manufacturing investment up 36% and technology services investment up 87.2%. Nearly 90% of venture capital flowed into hard tech. Output figures were strong: integrated circuit production rose 17.8%, industrial robots 75.5%, and service robots surged 230%. Companies like Qianxun AI and Galaxy General Robotics are deploying robots in real-world logistics and manufacturing, moving beyond demonstrations. The services sector is also being reshaped by tech, with software, IT, and finance growing faster than the sector average. Beijing leads in AI and embodied intelligence. Galaxy General Robotics secured significant funding, including from state-backed funds. The city released foundational AI models and its independent AI ecosystem, FlagOS, is expanding. Companies like Jiuzhang Yunjie provide neutral computing power and base models, supporting the broader ecosystem. Infrastructure is expanding, with Beijing aiming to add over 70,000 Petaflops of intelligent computing power annually. A "Beijing R&D, surrounding training" model is emerging, with computing resources being allocated to regions like Hebei and Tianjin. Efforts to deepen integration within the Beijing-Tianjin-Hebei region include industrial relocation and improved transport links. To bridge the gap between lab and market, Beijing is establishing pilot-scale production platforms. The underlying trend is the convergence of computing power, capital, talent, and real-world applications. While challenges remain in commercialization and regional integration, Beijing's focus on strengthening these interconnected elements is building the foundation for its claim as a global innovation hub.

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How Has Beijing Become a 'Global High Ground'?

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How Did the Target Price of 116 Yuan and a Market Cap of 7.9 Trillion for CXMT Come About?

Nomura's inaugural coverage report on ChangXin Memory Technologies (CXMT) gives a 'Buy' rating with a highly aggressive target price of 116 RMB, implying a 1239.5% upside from the IPO price of 8.66 RMB. The valuation is derived by applying a 20x P/E multiple to projected 2028 EPS of 5.79 RMB. The 20x multiple combines Micron's historical valuation with a premium for Chinese A-shares. The report's financial forecasts are exceptionally bullish. It projects revenue to soar from 62B RMB in 2025 to 773B RMB in 2028, with net profit surging to 393B RMB. A key, and arguably unsustainable, assumption is gross margin expanding to over 90% by 2028, driven almost entirely by price increases with minimal cost growth. This optimism is rooted in a forecast that global DRAM demand will grow over 7x from 2026 to 2030 (CAGR >60%), fueled by agentic AI. Nomura argues that supply growth (30-40% CAGR) will lag far behind demand, creating a persistent shortage. Bottlenecks in cleanroom space, equipment, materials, and skilled engineers will constrain rapid industry expansion. For CXMT, Nomura expects capacity to reach 550k wafers/month by 2028. The company's bit output is forecast to grow 40-45% annually, allowing its global market share to rise from ~10% to ~18%. While CXMT's technology lags leaders by about five years, limiting its wafer ASP, it benefits from supportive domestic procurement policies. Key risks include the cyclicality of memory pricing, with the 90% margin assumption representing a peak-cycle scenario rather than a sustainable norm.

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How Did the Target Price of 116 Yuan and a Market Cap of 7.9 Trillion for CXMT Come About?

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