报告导读： 美国具有充足的安全垫机制，短期违约风险不大。美国债务风险被市场高估， 经济衰退仍是主要逻辑，当下的环境更像 2011 年，中长期来看美债配置价值优于欧日。 美国主权债务危机复盘：历史上未发生过主权债务违约，且当前有比较充足的风险垫机制，美债短期违约 风险不大。 回顾历史，美国国债未因债务上限发生过正式的债务违约，但曾有被视为技术性违约或接近违 约的案例。早在 18 至 20 世纪初期，美国曾多次因战争大量举债而最终无力偿还接近违约的案例，如 1779 年的独立战争时期和 1862 年的南北战争时期等。 20 世纪末至今则偶有几次发生技术性违约的情 况。总的来看，美国国债历史上并没有发生过真正意义上的违约（即未能按时支付本金或利息），过去几 轮技术性违约事件通常是由债务上限问题引发的，背后则是民主党和共和党对于财政扩张或财政保守之间 的政治博弈。解决方式主要是通过国会提高债务上限或采取非常规措施来维持支付能力。美联储、 TGA 账户资金和超常规措施提供安全垫，美债短期违约风险不大。 美债危机期间的资产变动：与全球经济、货币政策等因素紧密相关，衰退期间美债表现占优。 1 ） 1979 年美国经济衰退， ...

核心观点 ①越南在"革新开放"后，经济迅速腾飞。提振经济的主要动力来自于外资和外贸。②在"革新开放"后，越 南产业结构得到不断优化。尤其是制造业逐步成为外贸和外贸的重点对象。同时，越南制造业在全球的地 位也得到不断提升。③中美贸易摩擦下，全球经贸秩序面临重置，越南在全球产业链中具有重要的战略地 位。中国与越南在未来的经贸上将有更加紧密的联系。 越南：新兴市场佼佼者 "革新开放"后，越南经济迅速腾飞，在全球经贸的地位不断提升。 越南经济腾飞的动能之一就是外资，在早期经济发展中发挥重要作用。 越南经济腾飞的另一动能就是外贸，也为越南经济的发展提供较大贡献。 越南：制造业逐步崛起 "革新开放"后，越南产业结构更加优化，二、三产业地位抬升。 文章来源 本文摘自：2025年5月14日发布的 越南制造业的崛起与前景 李 俊 ，资格证书编号： S0880525040063 汪立亭 ，资格证书编号： S0880525040004 无论是投资领域还是贸易领域，核心对象均在制造业领域。 越南产业逐步升级，资本密集型产品份额抬升，制造业地位不断提升。 越南：国际新秩序机遇 越南在劳动力领域具有较大的优势；同时，在地理位置以及政策领 ...

Core Viewpoint - The article discusses the integration of return factors into an orthogonal layer within deep learning models to enhance stock selection effectiveness while maintaining low correlation with existing return factors [1][2]. Group 1: Deep Learning Model Enhancements - By incorporating return factors into the orthogonal layer, deep learning factors can maintain good stock selection performance while ensuring low correlation with these return factors [1]. - The deep learning model's black-box nature makes it challenging to manually adjust factor weights during significant market style shifts; thus, the orthogonal layer allows for easier manual adjustments without compromising stock selection effectiveness [1]. Group 2: Performance Metrics - After adding return factors to the orthogonal layer, deep learning factors still exhibit strong stock selection capabilities, achieving an Information Coefficient (IC) above 0.02 and an IC Information Ratio (IR) exceeding 6 [2]. - The combination of deep learning factors with manually constructed return factors leads to significant improvements in overall market long positions compared to using deep learning factors alone, although the enhancement varies across different index-enhanced portfolios [2]. Group 3: Correlation and Performance - The correlation between deep learning factors and multi-granularity factors remains low after integrating return factors into the orthogonal layer, with high-frequency data inputs showing a correlation of no more than 0.01 [2]. - Utilizing deep learning factors alongside multi-granularity factors can significantly enhance the performance of overall market long positions, although the deep learning factors show limited predictive capability for mid to large-cap stock returns, resulting in less noticeable improvements for index-enhanced portfolios [2].

Core Viewpoint - The financial data indicates that the policy side continues to exert efforts to stabilize growth, including accelerated issuance and utilization of government bonds, while also highlighting that the recovery speed of domestic demand, particularly in the household sector, still needs to be boosted [1][4][17]. Group 1: Social Financing and Credit - In April, new social financing amounted to 1.2 trillion yuan, a year-on-year increase of 1.2 trillion yuan, raising the social financing stock growth rate to 8.7%, the highest since March 2024 [1][4]. - The increase in social financing was significantly influenced by a low base from the previous year, where new social financing in April 2022 was -65.8 billion yuan [4]. - New credit in April was 280 billion yuan, a decrease of 450 billion yuan year-on-year, with corporate bill financing being the main support for credit in April, amounting to 834.1 billion yuan [8][10]. Group 2: Government Bonds and Fiscal Policy - From January to April, net financing of government bonds reached 4.85 trillion yuan, with April's net financing at 976.2 billion yuan, an increase of over 1 trillion yuan year-on-year [4]. - The Ministry of Finance initiated the issuance of special government bonds on April 24, with the issuance pace advanced by about one month compared to 2024, indicating ongoing support for stabilizing growth and domestic demand [4][17]. Group 3: Household Sector and Demand Recovery - In April, household loans decreased by 521.6 billion yuan, indicating a need for improvement in the willingness of households to leverage [14]. - The transaction area of commercial housing in 30 major cities saw a year-on-year growth rate drop to -12%, reflecting a cooling in market activity and the need for recovery in household balance sheets [14][17]. Group 4: Monetary Supply - M2 growth rebounded to 8.0%, up 1 percentage point from March, primarily due to a low base effect from the previous year [17]. - The decline in M1 year-on-year was slight at 1.5%, indicating a mixed trend in monetary supply [17].

Macro - The rebound in social financing growth is primarily driven by government bonds, with April's new social financing reaching 1.2 trillion yuan, a year-on-year increase of 1.2 trillion yuan, raising the stock growth rate to 8.7%, the highest since March 2024 [1] - New loans in April amounted to 280 billion yuan, a decrease of 450 billion yuan year-on-year, with corporate note financing being the main support for credit in April, contributing 834.1 billion yuan [1] - The financial data for April reflects continued policy efforts to stabilize growth, including accelerated issuance and utilization of government bonds, while internal demand, particularly from households, still requires further support [1][2] Retail - Substantial progress in US-China trade negotiations has led to a significant reduction in bilateral tariff levels, with the US committing to cancel 91% of tariffs imposed on Chinese goods and China reciprocating similarly [4] - The negotiations took place on May 10-11, with a joint statement released on May 12, indicating a temporary suspension of 24% of tariffs for 90 days while retaining 10% [4] Machinery - The Chinese gas turbine industry is expected to benefit from two main developments: improvements in domestic manufacturers' gas turbine technology and increased demand from data center construction, leading to a positive outlook for the global gas turbine market [7] - The domestic gas turbine market is seeing breakthroughs in self-developed technology, which is expected to enhance the localization rate of both complete machines and core components [7] - The global demand for gas turbines is anticipated to rise significantly due to new requirements from data centers, providing opportunities for domestic manufacturers with core component technology [7]

Core Viewpoint - The article highlights the contrasting business models of Huawei and Nvidia, with Huawei focusing on a scene-driven vertical integration approach and Nvidia adopting a platform-driven horizontal expansion strategy. It emphasizes that embodied intelligence and humanoid robots are the main battlegrounds in the US-China tech competition, with a positive outlook on Huawei's related ecosystem [1][2]. Group 1: Huawei's Strategy - Huawei's collaboration with Ubtech aims to innovate in embodied intelligence and humanoid robots, leveraging its AI infrastructure and capabilities to enhance efficiency in industrial and household applications [2][3]. - The partnership will focus on creating a "humanoid robot + smart factory" demonstration plan and developing household service humanoid robots, including bipedal and wheeled types [2][3]. Group 2: Comparison with Nvidia - Both Huawei and Nvidia center their strategies around AI large models, computing hardware, and open ecosystems, positioning themselves as foundational technology standard setters [3][4]. - Huawei utilizes its Pangu model 5.0 and Ascend chips to develop embodied intelligence models, while Nvidia employs its Project GR00T multimodal model to support cross-scenario task execution [3][4]. - The two companies have self-developed chips and computing platforms, with Huawei's Ascend series providing edge computing capabilities and Nvidia's Jetson Thor platform designed specifically for robots [3][4]. Group 3: Ecosystem Development - Huawei is establishing a global innovation center for embodied intelligence and forming strategic partnerships to create an open platform that integrates hardware manufacturing, algorithm development, and scene implementation [3][4]. - Nvidia collaborates with companies like Boston Dynamics and Xpeng to provide a comprehensive ecosystem from training to deployment through its Isaac platform [3][4]. Group 4: Key Differences - Nvidia's model emphasizes foundational platform capabilities, creating a complete technology stack from model training to hardware control, which lowers industry entry barriers [4]. - In contrast, Huawei's approach focuses on vertical integration with specific scene requirements, data accumulation, and technology iteration, emphasizing depth in particular applications [4].

Core Insights - The article emphasizes the growing maturity and market potential of exoskeleton robots, which have applications in military, industrial, medical, and consumer sectors, driven by advancements in technology and increasing demand from an aging population [1][2]. Market Overview - Exoskeleton robots originated from military needs and have evolved over a century, now achieving large-scale applications in medical and industrial fields. The market is expected to expand further due to breakthroughs in AI and materials science, as well as the increasing demand for elderly care [1][2]. - The global market for exoskeleton robots is projected to reach $6.8 billion by 2030, indicating significant growth potential [2]. Applications - In the military sector, exoskeleton robots enhance individual combat capabilities. In industrial settings, they improve efficiency and reduce injury risks, particularly in high-intensity tasks such as logistics, automotive manufacturing, and mining [2]. - In outdoor activities, exoskeleton robots enhance experiences in hiking and climbing, with testing and operations already underway in various scenic areas, and prices are becoming more consumer-friendly [2]. - In the medical field, exoskeleton robots show great promise in rehabilitation and elderly care, further expanding their application scope [2]. Industry Participation - Numerous companies are entering the exoskeleton robot market through self-research, collaborative development, establishing subsidiaries, or investing in startups, indicating a competitive and dynamic industry landscape [3].

Core Viewpoint - The article emphasizes the importance of analyzing cash flows from underlying assets as the foundation for valuing REITs, detailing the valuation logic of current REITs [1] Valuation Methods - REIT valuation methods include cost approach, market approach, and income approach, with the income approach being the primary method for valuing infrastructure projects in China's public REITs policy [1] - The income approach aligns with the stable income characteristics and mandatory dividend requirements of REITs, enhancing market transparency [1] Key Considerations in Income Approach - **Operating Cash Flow of Underlying Assets**: Different REIT sectors exhibit varying degrees of revenue cyclicality and volatility, influenced by both quantitative and qualitative factors [2] - **Measurement of Asset Residual Value**: Due to factors like operating rights duration and economic lifespan of buildings, the assumption of perpetual operation for single assets may not be sufficient, necessitating cautious residual value measurement [2] - **Adjustment from Operating Income to Distributable Amount**: The adjustment of distributable amounts significantly impacts actual dividend distribution and valuation models, with variations typically around +/-20%, and in some cases exceeding 50% or even 100% [3] - **Compensation Mechanism**: New REIT projects since 2024 have introduced income distribution adjustment mechanisms to stabilize revenue, particularly in sectors with high cyclicality [3]

华为" 1+8+N "全场景生态完善，鸿蒙 OS 生态突破 10 亿设备 。 ① 5 年来华为集结了超过 1 万名工程 师，联合 20 多家研究所，积累了 2700 余项核心专利，覆盖操作系统内核、分布式架构、安全机制等关 键领域，鸿蒙电脑的发布标志着华为" 1+8+N "全场景生态的完善。 ② 面对 Windows 生态的垄断优 势，华为采用"双轨并行"策略：初期通过"鸿蒙 + 模拟器"方案兼容主流 Windows 应用，降低用户迁移 成本；同时投入超百亿元启动"鸿蒙生态伙伴计划"，为开发者提供从技术培训到流量扶持的全链条支持 。 ③ 鸿蒙操作系统的生态已经突破 10 亿台设备，开发者数量也超过 720 万，原生应用和元服务已上架 超过 20000 个 。 报告导读： 鸿蒙 PC 从内核开始重构 OS ，生态方面有 2000+ 融合应用加速适配，预计 在 AI 和万物互联新战场占据一席之地；鸿蒙 PC 的推出同时也繁荣了整个鸿蒙 OS 生 态。 投资建议： 鸿蒙 PC 的推出将完善华为" 1+8+N "布局，有望在 AI 时代占据先机，成为万物互联时代的 入口。 鸿蒙 PC 从内核开始重构 OS 。 ① 鸿 ...

每周一景： 云南玉龙雪山 点击右上角菜单，收听朗读版 【 非银】公募新规利好非银，监管引导险资入市稳市 一、本周观点： 【非银一周观点】： 5 月 7 日中国证监会发布《公募基金高质量发展行动方案》，其中明确建立与基金业绩表现挂钩的浮动管 理费收取机制，强化业绩比较基准的约束作用，考核从重同业排名转向重业绩比较基准。 而当前非银板块 的配置比例从 1.67% 降至 1.52% ，大幅欠配 5.34Pct ；其中券商板块欠配 3.29Pct ，保险板块欠配 1.60Pct ，重视业绩比较基准下非银板块作为大幅欠配板块更为受益。 5 月 7 日，金融监管总局局长李云泽在国新办新闻发布会上表示，将充分发挥保险资金作为耐心资本和长 期资本的作用，加大入市稳市力度， 包括： 1 ）进一步扩大保险资金长期投资的试点范围，近期拟再批 复 600 亿元； 2 ）调整偿付能力监管规则，将股票投资的风险因子进一步调降 10% ； 3 ）推动长周期 的考核机制，促进"长钱长投"。我们认为上述举措有助于稳定资本市场，推动保险公司增加优质权益资产 配置，改善低利率环境下固收类资产收益下行压力，实现资产负债匹配优化。 金融科技方面，大模 ...