[Table_Message]2025-12-07 金融工程周报 大类资产与基金周报（20251201-20251205）—— 贵金属上涨，商品基金涨幅录得 1.03% [Table_Author] 证券分析师：刘晓锋 电话：13401163428 E-MAIL：liuxf@tpyzq.com 请务必阅读正文之后的免责条款部分 守正 出奇 宁静 致远 [Table_Title] [Table_Summary] 执业资格证书编码：S1190522090001 . 证券分析师：孙弋轩 电话：18910596766 E-MAIL：sunyixuan@tpyzq.com 内容摘要 太 平 洋 证 券 股 份 有 限 公 司 证 券 研 究 报 告 执业资格证书编码：S1190525080001 金 融 工 程 周 报 ◼ 大类资产市场概况：1）权益：本周 A 股市场中上证指数收盘 3902.81，涨跌幅 0.37%， 深证成指、中小板指数、创业板指、上证 50、沪深 300、中证 500、中证 1000、中证 2000、 北证 50 涨跌幅分别为 1.26%、0.76%、1.86%、1.09%、1.28%、0.94% ...

Investment Rating - The industry is rated positively, with expectations of overall returns exceeding the CSI 300 Index by more than 5% in the next six months [42]. Core Insights - The U.S. Department of Defense plans to invest $1 billion to procure over 300,000 suicide drones over the next two years, marking a significant shift towards low-cost unmanned systems for modern warfare [3][15]. - China's defense budget has consistently increased by around 7%, with defense spending as a percentage of GDP remaining below 1.5%, indicating substantial growth potential in the future [4][9]. - The structure of China's defense spending is expected to shift towards new domains and qualities, with military trade exports likely to open up larger market opportunities [4][9]. Summary by Sections Industry Insights - China's defense spending is projected to grow at a rate approximately 2 percentage points higher than GDP growth in the long term, driven by the evolution of modern warfare towards information and intelligence [4][9]. - The industry is anticipated to enter a rapid development phase driven by both domestic demand and foreign trade, with a focus on next-generation fighter jets, low-cost munitions, unmanned equipment, commercial aerospace, low-altitude economy, and deep-sea technology [4][9]. Market Performance - The Aerospace and Defense Index increased by 5.01% this week, while the CSI 300 Index rose by 1.53%. For the month, the Aerospace and Defense Index saw a 2.26% increase, contrasting with a 1.48% decline in the CSI 300 Index [10]. Industry News - The U.S. Navy is expanding its mine warfare training range in Hawaii, modernizing facilities to align with future conflicts and the latest weaponry [17]. - Germany's Bundestag passed a bill to modernize its conscription system, aiming to expand the military's size in response to European security challenges [18]. - The Iranian Revolutionary Guard conducted military exercises in the Persian Gulf, showcasing new defense and offensive capabilities [19]. - Blue Arrow Aerospace successfully launched the Zhuque-3 rocket, marking a significant milestone in China's reusable rocket technology [20]. Company Tracking - Huawu Co., Ltd. reported a reduction in shareholding by its controlling shareholder, impacting the overall ownership structure [22]. - Chaojie Co., Ltd. also experienced a reduction in shareholding by its major shareholder, indicating ongoing changes in ownership dynamics [24]. - North Industries Group announced a plan to reduce its shareholding by up to 3% due to funding needs [25].

- The report constructs an industry crowding monitoring model to monitor the crowding levels of Shenwan First-Level Industry Indexes on a daily basis[3] - The ETF product screening signal model is built using the premium rate Z-score model, which provides potential arbitrage opportunities through rolling calculations[4] - The industry crowding monitoring model indicates that the crowding levels of the communication and military industries were high on the previous trading day, while the crowding levels of the computer and non-bank industries were relatively low[3] - The premium rate Z-score model is used to identify potential arbitrage opportunities in ETF products, but it also warns of potential pullback risks[4] Model Backtesting Results - The industry crowding monitoring model shows significant changes in the crowding levels of home appliances, machinery, and media industries[3] - The premium rate Z-score model identifies ETF products with potential arbitrage opportunities, such as the top three ETFs with the highest net inflows and outflows on a single day[5]

Quantitative Models and Construction Methods 1. Model Name: Industry Crowding Monitoring Model - **Model Construction Idea**: This model is designed to monitor the crowding levels of Shenwan First-Level Industry Indices on a daily basis, identifying industries with high or low crowding levels to provide investment insights[3] - **Model Construction Process**: The model calculates the crowding levels of various industries based on daily trading data. It identifies industries with significant changes in crowding levels, such as petroleum, petrochemicals, and non-ferrous metals, which showed notable variations in the previous trading day[3] - **Model Evaluation**: The model provides a useful tool for identifying industry crowding trends and potential investment opportunities[3] 2. Model Name: Premium Rate Z-Score Model - **Model Construction Idea**: This model is used to screen ETF products with potential arbitrage opportunities by calculating the Z-score of their premium rates over a rolling window[4] - **Model Construction Process**: 1. Collect historical premium rate data for ETFs 2. Calculate the Z-score of the premium rate for each ETF over a specified rolling window 3. Identify ETFs with extreme Z-scores as potential arbitrage opportunities[4] - **Model Evaluation**: The model effectively identifies ETFs with potential arbitrage opportunities but also highlights the need to be cautious of potential price corrections[4] --- Model Backtesting Results 1. Industry Crowding Monitoring Model - No specific numerical backtesting results were provided for this model[3] 2. Premium Rate Z-Score Model - No specific numerical backtesting results were provided for this model[4] --- Quantitative Factors and Construction Methods No specific quantitative factors were explicitly mentioned or constructed in the report --- Factor Backtesting Results No specific backtesting results for factors were provided in the report

医药行业 证券研究报告 |深度报告 2025/12/01 水稻胚乳里的生物密码： 禾元生物重组蛋白技术的产业化革命 | 证券分析师: | 程晓东 | | --- | --- | | 分析师登记编号: | S1190511050002 | | 证券分析师: | 李忠华 | | 分析师登记编号: | S1190524090001 | P2 报告摘要 核心结论：禾元生物是国内植物源重组蛋白药物领军者，以独创水稻胚乳细胞生物反应器技术打破血浆依赖，核心产品 HY1001（重组人白蛋白）国内先发上市、美国推进III期，成本远低于血浆来源，120吨产能+全球化布局支撑2030年营 收超30亿，技术壁垒与商业化确定性突出，具备高投资价值。 一、公司与核心技术：植物源蛋白产业化闭环，指标全球领先。公司拥有二大核心技术平台：1、重组蛋白高效表达平 台：历经三代迭代，重组蛋白表达量达20-30g/kg，核心依赖胚乳特异性启动子改造等专利技术；2、蛋白纯化平台：纯 度达99.9999%，内毒素符合中美药典，纯化成本较微生物体系降30%+。 二、产品管线：HY1001领跑，多梯队支撑增长。（1）核心产品 HY1001：2025年7月 ...

Quantitative Models and Construction Methods 1. Model Name: Industry Crowding Monitoring Model - **Model Construction Idea**: This model is designed to monitor the crowding levels of industries on a daily basis, using the Shenwan First-Level Industry Index as the benchmark[3] - **Model Construction Process**: The model calculates the crowding levels of various industries by analyzing daily fund flows and changes in crowding levels. It identifies industries with high or low crowding levels and tracks significant changes in crowding over time. Specific metrics or formulas are not provided in the report[3] - **Model Evaluation**: The model provides actionable insights into industry crowding trends, helping investors identify potential opportunities or risks in specific sectors[3] 2. Model Name: Premium Rate Z-Score Model - **Model Construction Idea**: This model is used to screen ETF products by identifying potential arbitrage opportunities based on the Z-score of premium rates[4] - **Model Construction Process**: The model calculates the Z-score of the premium rate for each ETF product over a rolling window. ETFs with significant deviations in their Z-scores are flagged as potential arbitrage opportunities. The report does not provide specific formulas or detailed steps for the calculation[4] - **Model Evaluation**: The model is effective in identifying ETFs with potential arbitrage opportunities, but it also highlights the need to be cautious of potential price corrections in flagged ETFs[4] --- Model Backtesting Results 1. Industry Crowding Monitoring Model - No specific backtesting results or quantitative metrics are provided for this model in the report 2. Premium Rate Z-Score Model - No specific backtesting results or quantitative metrics are provided for this model in the report --- Quantitative Factors and Construction Methods The report does not explicitly mention any quantitative factors or their construction methods --- Factor Backtesting Results The report does not provide any backtesting results for quantitative factors --- Additional Notes - The report primarily focuses on the application of the two models mentioned above for monitoring industry crowding and screening ETF products. It does not delve into detailed quantitative metrics, formulas, or backtesting results for these models[3][4]

[Table_Message]2025-11-30 金融工程周报 大类资产与基金周报（20251124-20251128）—— 权益与黄金回升，权益基金涨幅达 3.01% [Table_Author] 证券分析师：刘晓锋 电话：13401163428 E-MAIL：liuxf@tpyzq.com 执业资格证书编码：S1190522090001 证券分析师：孙弋轩 电话：18910596766 E-MAIL：sunyixuan@tpyzq.com 执业资格证书编码：S1190525080001 内容摘要 太 平 洋 证 券 股 份 有 限 公 司 证 券 研 究 报 告 请务必阅读正文之后的免责条款部分 守正 出奇 宁静 致远 [Table_Title] [Table_Summary] . 金 融 工 程 周 报 ◼ 大类资产市场概况：1）权益：本周 A 股市场中上证指数收盘 3888.60，涨跌幅 1.40%， 深证成指、中小板指数、创业板指、上证 50、沪深 300、中证 500、中证 1000、中证 2000、 北证 50 涨跌幅分别为 3.56%、3.74%、4.54%、0.47%、1.64%、3.14 ...

- The report introduces an **industry crowding monitoring model** to track the crowding levels of Shenwan primary industry indices on a daily basis. The model identifies industries with high crowding levels (e.g., communication and electronics) and low crowding levels (e.g., automotive and non-bank financials). It also highlights significant changes in crowding levels for industries like construction decoration and military industries[3] - A **Z-score premium model** is constructed to screen ETF products for potential arbitrage opportunities. The model uses rolling calculations to identify ETFs with significant deviations in premium rates, which may indicate arbitrage opportunities or potential risks of price corrections[4] - The report provides detailed data on **ETF fund flows**, categorizing them into broad-based ETFs, industry-themed ETFs, style-strategy ETFs, and cross-border ETFs. For example, the top three net inflows for broad-based ETFs include the SSE 50 ETF (+6.60 billion yuan), A500 ETF (+5.84 billion yuan), and ChiNext 50 ETF (+2.75 billion yuan), while the top three net outflows include the ChiNext ETF (-7.26 billion yuan), CSI 500 ETF (-5.56 billion yuan), and STAR 50 ETF (-5.10 billion yuan)[5]

Group 1: Overview of the High-Value Deviation Repair Model - The basic stop-loss strategy involves calculating the relative closing price of individual industry indices against the CSI 300 and the corresponding drawdown curve [3][24] - The maximum value of the effective drawdown is selected as a threshold, and signals are generated based on the drawdown curve exceeding this threshold [3][24] - Most industries show similar performance in returns under different parameter conditions, except for agriculture, electronics, home appliances, and computer sectors [10][21] Group 2: Floating Stop-Loss Strategy - The floating stop-loss strategy calculates the relative closing price and drawdown curve similar to the basic strategy, with adjustments made to the stop-loss position based on market movements [24][40] - The strategy has shown significant improvement in the computer industry compared to the original strategy [27][39] - Industries such as agriculture, electronics, pharmaceuticals, and social services have experienced substantial drawdown compression [31][72] Group 3: Performance Analysis - The maximum drawdown compression effect is superior in the floating stop-loss strategy compared to the original strategy, particularly in the pharmaceutical and electronics sectors [41][80] - The floating stop-loss strategy has limited improvement in overall returns but has helped compress drawdown times for certain industries [84][81] - The effectiveness of the floating stop-loss strategy varies by industry, with banks and pharmaceuticals showing notable enhancements in return ratios [80][81] Group 4: Future Outlook - Future research will focus on the impact of localized stop-loss models on strategy effectiveness [87] - Improvements will be made to the secondary entry model, expanding beyond a single approach [87]

2025 年 11 月 27 日 行业日报 中性/维持 房地产 房地产 太平洋房地产日报（20251127）： 杭州 2 宗宅地出让 | 和运营 | | | --- | --- | | 房 地 产 开 发 房地产服务 | 无评级 无评级 | 推荐公司及评级 相关研究报告 <<太平洋房地产日报（20251126）：苏 州成功出让一宗高新区宅地>>-- 2025-11-26 <<太平洋房地产日报（20251125）：武 汉 12 宗地块总成交价约 39.7 亿>>-- 2025-11-25 <<太平洋房地产日报（20251124）：上 海九批次土拍收金 173.33 亿元>>-- 2025-11-24 2025 年 11 月 27 日，今日权益市场各板块多数下跌，上证综指上 涨 0.29%，深证综指下跌 0.11%，沪深 300 和中证 500 分别下跌 0.05% 和 0.20%。申万房地产指数下跌 0.63%。 个股表现： 房地产板块个股涨幅较大的前五名为万通发展、信达发展、天保 基 建 、 市 北 高 新 、 市 北 B 股 ， 涨 幅分别为 10.02%/9.89%/5.94%/4.01%/2.87%； ...