Report Industry Investment Rating - Not provided in the given content Core Viewpoints - According to Wind data, among the bonds traded at a discount, "24 Chanrong 08" had a relatively large deviation in bond valuation price. Among the bonds with rising net prices, "H2 Vanke 04" had a relatively high degree of deviation in valuation price. Among the Tier 2 and perpetual bonds with rising net prices, "25 Chongqing Three Gorges Bank Perpetual Bond 01" had a relatively large deviation in valuation price; among the commercial financial bonds with rising net prices, "25 Xiamen International Bank Bond 02" had a relatively high degree of deviation in valuation price. Among the bonds with a trading yield higher than 5%, real estate bonds ranked high. The changes in credit bond valuation yields were mainly distributed in the [-5,0) range. The trading terms of non-financial credit bonds were mainly distributed between 2 and 3 years, with the 3 - 4 year term variety having the highest proportion of discounted trades; the trading terms of Tier 2 and perpetual bonds were mainly distributed between 4 and 5 years, with the variety with a term of less than 1 year having the highest proportion of discounted trades. By industry, the bonds in the commercial and retail industry had the largest average deviation in valuation price [3]. Summary by Relevant Catalogs 1. Discounted Bond Trading Tracking - Bonds such as "24 Chanrong 08", "24 Chanrong 06", "24 Chanrong 04" in the non - banking financial industry and "24 Puzhi 03", "26 Puzhi 01" in the urban investment industry had relatively large deviations in valuation price and were traded at a discount. The trading scale of "23 AVIC Chanrong MTN001 (Sci - tech Innovation Note)" was 64.08 million yuan, which was relatively large among the discounted bonds [5]. 2. Tracking of Bonds with Rising Net Prices - "H2 Vanke 04", "H2 Vanke 06", "H2 Vanke 02" in the real estate industry and "26 Runtou V1" in the commercial and retail industry had relatively large positive deviations in valuation price and rising net prices. The trading scale of "26 Runtou V1" was 362.83 million yuan, which was relatively large among the bonds with rising net prices [6]. 3. Tracking of Tier 2 and Perpetual Bond Trading - "25 Chongqing Three Gorges Bank Perpetual Bond 01", "25 Luzhou Bank Perpetual Bond", "25 Beibu Gulf Bank Perpetual Bond 01" and other Tier 2 and perpetual bonds had a certain degree of deviation in valuation price. The trading scale of "25 Zhonghang Secondary Capital Bond 03A(BC)" was 433.483 million yuan, which was relatively large among the Tier 2 and perpetual bonds [7]. 4. Tracking of Commercial Financial Bond Trading - "25 Xiamen International Bank Bond 02", "25 CITIC Bank Green Bond 01BC", "25 Zheshang Bank Green Bond 01BC" and other commercial financial bonds had a certain degree of deviation in valuation price. The trading scale of "24 Nanjing Bank 02" was 613.72 million yuan, which was relatively large among the commercial financial bonds [8]. 5. Tracking of Bonds with a Trading Yield Higher than 5% - Bonds such as "H2 Vanke 04", "H2 Vanke 06", "H2 Vanke 02" in the real estate industry and "24 Chanrong 05", "23 Chanrong 10" in the non - banking financial industry had a trading yield higher than 5%. The trading scale of "23 AVIC Chanrong MTN001 (Sci - tech Innovation Note)" was 64.08 million yuan, which was relatively large among the high - yield bonds [9]. 6. Distribution of Credit Bond Valuation Deviations - The changes in credit bond valuation yields were mainly distributed in the [-5,0) range [3]. 7. Distribution of Non - financial Credit Bond Trading Terms - The trading terms of non - financial credit bonds were mainly distributed between 2 and 3 years, with the 3 - 4 year term variety having the highest proportion of discounted trades [3]. 8. Distribution of Tier 2 and Perpetual Bond Trading Terms - The trading terms of Tier 2 and perpetual bonds were mainly distributed between 4 and 5 years, with the variety with a term of less than 1 year having the highest proportion of discounted trades [3]. 9. Discounted Trading Proportion and Trading Scale of Non - financial Credit Bonds by Industry - The bonds in the commercial and retail industry had the largest average deviation in valuation price [3].

2026 年 3 月 9 日 胜遇信用周报 2026年3月2日-2026年3月8日 目录： 一、本周重要信用事件 二、新增违约 三、评级变动 四、本周新增非标违约 五、下周关注 六、信用债发行情况 2026 年 3 月 9 日 一、本周重要信用事件 （1）2026 年 3 月 3 日，泸州发展控股集团有限公司公告称，拟将直接持有的四川省蜀 泸能源有限责任公司 81.46%股权，及下属子公司持有的泸州市聚合资产管理有限公司 100% 股权、泸州市聚清资产管理有限公司 100%股权无偿划转至泸州市国资委，账面价值合计 16.37 亿元。此次划转将导致公司合并口径净资产减少 16.37 亿元，占 2024 年末经审计净资 产的 6.16%。该事项已通过董事会审议，协议暂未签署，资产未完成过户。 （5）2026 年 3 月 4 日，陕建股份公告，公司及子公司涉及 40 起诉讼仲裁案件，涉案 金额合计 30.62 亿元。其中 27 起为原告，涉案金额 28.54 亿元；13 起为被告，涉案金额 2.08 亿元。目前 1 起调解结案，其余均在审理中。 （6）2026 年 3 月 4 日，吉林省信用融资担保投资集团有限公司 ...

胜遇信用日报 2026年3月9日 | | | | 有限公司、尹洪卫、古钰塘分别提供连带责任保证和抵质押担保,具体金额, 期限、担保方式以最终签订的相关合同为准。上述担保事项在该年度担保额度 预计范围内，担保预计额度已经公司第五届董事会第三十二次会议及 2024 年 | | --- | --- | --- | --- | | | | | 年度股东大会审议通过。目前上述贷款已逾期。公司债券曾于 2024 年 8 月 发生实质违约。 | | | | | 遂宁市富源实业有限公司公告称，将持有的 97%遂宁富程工程管理股份有限 | | | | | 公司股权、子公司遂宁富升资产管理有限公司持有的 3%该公司股权无偿划转 | | | | 转让子公司股 | 至遂宁经济技术开发区国资与审计中心，资产规模（2024年末）15.10亿元， | | 6 | 遂宁市富源实业有限公司 | 权 | 本次划转已完成工商变更。2024年末，无偿划转标的资产占公司当期总资产。 | | | | | 净资产、营业收入和净利润比重分别为 6.53%、7.66%、0.01%和 12.16%。 | | | | | 截至目前，公司存续债 7 只，金额 25 ...

金融工程 证 券 研 究 报 告 【点评报告】 量化看市场系列之六：OpenClaw 金融行业必备 Skills 推荐与实战应用 ❖ 摘要 随着 OpenClaw 越来越广泛的应用，相信会有更多 Skills 被分享出来。 ❖ 风险提示： Skills 安装前需要先查看 MD 文件的内容，避免安装存在恶意代码或者隐含泄 露本地文件的 Skills；本报告相关介绍及方法仅供参考，不构成任何投资建议。 ❖ 点评报告 2026 年 03 月 09 日 华创证券研究所 证券分析师：王小川 邮箱：wangxiaochuan@hcyjs.com 执业编号：S0360517100001 相关研究报告 《量化看市场系列之四：使用"OpenClaw"搭建 属于自己的私域 AI 助理》 2026-02-03 证监会审核华创证券投资咨询业务资格批文号：证监许可（2009）1210 号 ⚫ 本文介绍了四种在 OpenClaw 中安装 Skills 的方法，用好 Skills，可以实 现从"每次都给 AI 当老师"变成"AI 替你当专家"。同时介绍了 10 种 金融行业推荐使用的 Skills。最后利用多种 Skills 完成了四种实 ...

[Table_Page] 投资策略周报|房地产 证券研究报告 [Table_Title] 房地产开发与服务 26 年第 10 周 详解两会地产定调，小阳春数据持续走强 [Table_Summary] 核心观点： （以上文字段落：五号，仅小标题加粗，段前段后 0 行，单倍行距） [Table_Grade] 行业评级 买入 前次评级 买入 报告日期 2026-03-08 [Table_PicQuote] 相对市场表现 [分析师： Table_Author]郭镇 SAC 执证号：S0260514080003 SFC CE No. BNN906 021-38003639 guoz@gf.com.cn 分析师： 邢莘 SAC 执证号：S0260520070009 021-38003638 xingshen@gf.com.cn 分析师： 谢淼 SAC 执证号：S0260522070007 SFC CE No. BVB342 021-38003637 xiemiao@gf.com.cn 分析师： 李怡慧 SAC 执证号：S0260524040001 SFC CE No. BVI219 021-38003636 liyihu ...

摘要 折价幅度靠前 50 只 AA 城投债（主体评级）中，"25 腾冲 01"估值价格偏离程度最大。净价跌幅靠前 50 只个券中， "23 发展 01"估值价格偏离幅度最大。净价上涨幅度靠前 50 只个券中，"23 万科 MTN001"估值价格偏离幅度最大。 净价上涨幅度靠前 50 只二永债中，"24 交行二级资本债 02B"估值价格偏离程度最大。 风险提示 固定收益动态(动态) 图表1：折价幅度靠前 50 只 AA 城投债（主体评级） | 债券名称 | 剩余期限 | 估值价格 | 估值净价 | 估值收益率 | 当日估值 | 票面利率 | 隐含 | 主体 | 成交日期 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | | (年) | 偏离(%) | (元) | 偏离(bp) | 收益(%) | (%) | 评级 | 评级 | | | 25 腾冲 01 | 4.31 | -0.17 | 103.83 | 4.47 | 3.81 | 4.80 | AA- | AA | 2026/3/5 | | 25 佳鑫 01 | 4.17 | - ...

行 业 及 产 业 行 业 研 究 / 行 业 点 评 证 券 研 究 《房地产行业 2026 年投资策略：潮平待 风起，扬帆更远航》 2025/11/17 《好房子的另类破局之道，引领核心城市 五重共振——好房子专题报告系列之三》 2025/09/10 证券分析师 袁豪 A0230520120001 yuanhao@swsresearch.com 顾铮 A0230525120002 guzheng@swsresearch.com 研究支持 顾铮 A0230525120002 guzheng@swsresearch.com 联系人 顾铮 A0230525120002 guzheng@swsresearch.com 2026 年 03 月 08 日 着力稳定房地产市场，增加居民财产性收入， 灵活高效运用降准降息 看好 —— 地产及物管行业周报（2026/2/28-2026/3/6） 本期投资提示： 请务必仔细阅读正文之后的各项信息披露与声明 本研究报告仅通过邮件提供给 博时基金 博时基金管理有限公司(researchreport@bosera.com) 使用。1 报 告 房地产 相关研究 ⚫ 地产行业数据：新房 ...

Core Insights - The release of GPT-5.4 by OpenAI is set to revolutionize white-collar jobs, with capabilities that could replace many knowledge-based roles, including those in consulting and investment banking [2][7][11] - The model features a 1 million token context and native computer use, significantly enhancing its performance and applicability in various tasks [2][12][13] Group 1: Technological Advancements - GPT-5.4 has demonstrated a remarkable increase in performance, with its Excel plugin achieving a benchmark score of 87.3%, up from 43.7% [4][8] - The model's ability to handle complex operations in Excel through natural language processing transforms it into a conversational data analysis platform [4][5] - The integration of reasoning and coding within a single model can reduce context switching by approximately 80%, enhancing productivity [12] Group 2: Impact on Employment - The technology sector has seen a net reduction of 12,000 jobs in the last month, with a total of 57,000 jobs lost over the past year, indicating a significant shift in employment dynamics due to AI [26][31] - Despite the overall decline in tech jobs, demand for AI-related positions is rising, suggesting a transition rather than a contraction in the workforce [31] - The current job market reflects a trend where companies are replacing multiple employees with a single individual and AI, leading to a lack of alternative employment options for those displaced [31][33] Group 3: Economic Implications - Joseph Stiglitz warns that without proper management of AI, it could exacerbate existing inequalities, as profits become concentrated at the top while risks are offloaded onto workers [33][37] - The perception of human labor as a cost center is reinforced by the capabilities of AI, which promises to eliminate the need for human employees [36][37] - The rapid advancements in AI capabilities signal that the replacement of white-collar jobs is not a distant possibility but an ongoing reality [40][41]

Core Viewpoint - The Chinese real estate industry is transitioning towards high-quality development, focusing on the construction of "good houses" and enhancing delivery quality in response to changing consumer demands for comfort, safety, and smart living experiences [1][29]. Group 1: Industry Transition and Policy Support - By 2025, the real estate sector aims to achieve a successful transition of old and new growth drivers, with a focus on delivering quality housing and meeting the evolving demands of consumers [1]. - Policies surrounding the construction of "good houses" are being continuously refined, with the Ministry of Housing and Urban-Rural Development raising residential height standards to no less than 3 meters [1]. - The dual drivers of policy guidance and market demand are prompting major real estate companies to enhance their product offerings and delivery quality [1]. Group 2: Delivery Performance and Transparency - In 2025, major real estate companies are expected to disclose their annual delivery data, with a noticeable increase in the number of companies sharing this information compared to the previous year [3]. - Companies like Poly Developments and China Overseas Property have reported significant delivery numbers, with Poly delivering 130,000 units and China Overseas achieving 100% timely delivery of 133,200 units [4]. - Transparency in delivery information is crucial for building market credibility and boosting consumer confidence, especially in a year where delivery performance is closely scrutinized [4]. Group 3: Quality and Customer Satisfaction - The trend of early delivery has become common in 2025, with many companies exceeding basic delivery standards, showcasing their strong project management capabilities [5]. - High occupancy rates and customer satisfaction are emerging as key characteristics of the industry, with companies like China Railway Real Estate achieving over 95% delivery attendance rates [6]. - Leading companies are taking proactive measures to ensure delivery, with Country Garden delivering 170,000 units and maintaining high delivery standards [6]. Group 4: Standardization and Process Improvement - Real estate companies are developing proprietary delivery standard systems to ensure quality, with Poly's "6321 Delivery Power System" being a notable example [8]. - China Overseas has launched the "China Overseas Good House Living OS System," which encompasses a comprehensive standardization framework for housing delivery [10]. - Companies are implementing rigorous quality control mechanisms and engaging third-party inspections to enhance delivery experiences [11]. Group 5: Customer Engagement and Post-Delivery Services - Transparency in the delivery process is becoming a key strategy for companies to alleviate buyer anxiety and build trust, with initiatives like Vanke's smart construction site system allowing real-time monitoring of construction progress [14]. - Pre-delivery inspections involving homeowners are being organized to address concerns before final handover, exemplified by Build Development's proactive approach [18]. - Post-delivery services are being enhanced, with companies like China State Construction and China Resources providing comprehensive support to ensure a seamless transition for homeowners [20][27]. Group 6: Future Assessment and Industry Outlook - The 2025 Delivery Capability Assessment is underway, evaluating the overall delivery strength of companies and projects, with results expected to be published in March [29][31]. - The industry's shift from a growth model focused on scale to one emphasizing quality is evident, with companies demonstrating their commitment to delivering high-quality housing and meeting consumer expectations [29].

Group 1 - The core viewpoint of the article is that Vanke A is a pioneer in the TOD (Transit-Oriented Development) model in China, showcasing its extensive project experience and comprehensive development capabilities [1] - The company has specific projects implemented in major cities such as Beijing, Shanghai, Guangzhou, Shenzhen, Hangzhou, Chengdu, Wuhan, Nanchang, and Changsha [1] - In Shenzhen, the company collaborates with Shenzhen Metro Group on two above-ground projects, namely the Zhenwanhui in the Shenzhen Super General Base area and the Huilong Business Center in the Shenzhen North Station area [1]