1. Report Industry Investment Rating - No relevant content provided 2. Core Viewpoints of the Report - Last week, the central bank announced a 50 billion yuan investment in November through treasury bond trading, and the November PMI rose by 0.2 to 49.2. The bond market experienced a certain degree of sell - off, and ultra - long bonds tumbled. The trading activity of ultra - long bonds increased significantly, with the term spread widening and the variety spread showing mixed changes [1][11]. - For the 30 - year treasury bond, as of December 5, the spread between the 30 - year and 10 - year treasury bonds was 41BP, at a historically low level. Considering factors such as economic pressure and low interest rates, the bond market is more likely to fluctuate, and the 30 - 10 spread is expected to face short - term pressure [2][12]. - For the 20 - year CDB bond, as of December 5, the spread between the 20 - year CDB bond and the 20 - year treasury bond was 14BP, at a historically extremely low position. Given the economic situation and market sentiment, the bond market is likely to fluctuate, and the variety spread of the 20 - year CDB bond is expected to have narrow - range fluctuations [3][13]. 3. Summary by Relevant Catalogs 3.1 Weekly Review 3.1.1 Ultra - long Bond Review - The central bank's November treasury bond trading investment and the rise in PMI led to a sell - off in the bond market and a tumble in ultra - long bonds. Trading activity increased significantly, with the term spread widening and the variety spread showing mixed changes [1][11]. 3.1.2 Ultra - long Bond Investment Outlook - **30 - year Treasury Bond**: The 30 - 10 spread is at a low level. The economy is under pressure, and the spread is expected to face short - term pressure [2][12]. - **20 - year CDB Bond**: The spread between the 20 - year CDB bond and the 20 - year treasury bond is extremely low. The bond market is likely to fluctuate, and the variety spread of the 20 - year CDB bond is expected to have narrow - range fluctuations [3][13]. 3.1.3 Ultra - long Bond Basic Overview - The balance of outstanding ultra - long bonds is 24.3 trillion yuan. Local government bonds and treasury bonds are the main varieties. The 30 - year variety has the highest proportion [14]. 3.2 Primary Market 3.2.1 Weekly Issuance - Last week, the issuance volume of ultra - long bonds dropped sharply, totaling 5.73 billion yuan. By variety, treasury bonds were 2.7 billion yuan, local government bonds were 2.88 billion yuan, and corporate bonds were 0.15 billion yuan. By term, 15 - year bonds were 1.1 billion yuan, 20 - year bonds were 0.93 billion yuan, and 30 - year bonds were 3.69 billion yuan [20]. 3.2.2 This Week's Planned Issuance - The announced issuance plan for this week is 3.47 billion yuan, all of which are ultra - long local government bonds [26]. 3.3 Secondary Market 3.3.1 Trading Volume - Last week, ultra - long bonds were very actively traded, with a turnover of 1.1346 trillion yuan, accounting for 14.6% of the total bond turnover. Compared with the previous two weeks, the turnover increased by 221 billion yuan, and the proportion increased by 3.3% [29]. 3.3.2 Yield - Due to the central bank's investment and PMI changes, ultra - long bonds tumbled. The yields of treasury bonds, CDB bonds, local bonds, and railway bonds at different terms all changed, with the 30 - year treasury bond yield rising by 7BP to 2.26% [39]. 3.3.3 Spread Analysis - **Term Spread**: The term spread of ultra - long bonds widened last week, with an absolute low level. The 30 - year - 10 - year treasury bond spread was 41BP, up 7BP from the previous two weeks, at the 24% quantile since 2010 [51]. - **Variety Spread**: The variety spread of ultra - long bonds showed mixed changes last week, with an absolute low level. The spreads of the 20 - year CDB bond and railway bond against the treasury bond were 14BP and 16BP respectively, with changes of 2BP and - 2BP from the previous two weeks, at the 11% quantile since 2010 [53]. 3.4 30 - year Treasury Bond Futures - Last week, the main contract of the 30 - year treasury bond futures, TL2603, closed at 112.51 yuan, down 1.7%. The total trading volume was 706,800 lots, and the open interest was 145,600 lots, with a significant increase in trading volume and a slight decrease in open interest [58].

证券研究报告 | 2025年12月07日 小马智行（PONY.O/2026.HK） 优于大市 单三季度收入同比增长 72%，Robotaxi 商业化运营持续推进 2025Q3 公司实现营收 2544 万美元，同比增长 72%。2025Q3，公司实现 收入为 2544 万美元，同比增长 72.0%，环比增长 18.6%，净利润为-6132 万美元（2024Q3 为-4189 万美元，2025Q2 为-5310 万美元），调整后净 利润（即加回股权激励费用后的净利润）为-5472 万美元（2024Q3 为-4121 万美元，2025Q2 为-4589 万美元）。分业务来看，1）2025Q3，公司 Robotaxi 服务收入为 670 万美元，同比增长 89.5%，其中乘客车费收入同比增长 超 200%。2）2025Q3，公司 Robotruck 服务收入为 1020 万美元，同比增 长 8.7%，随着公司第四代 Robotruck 的推出，其自动驾驶套件 BOM 成本 相比上一代降低了 70%。3）2025Q3，公司授权和应用收入为 860 万美元， 同比大幅增长 354.6%，这一增长 主要得益于 自动驾驶域控 ...

Investment Rating - The report maintains a "weaker than the market" investment rating for the U.S. stock market [4] Core Views - The market is showing a slowdown in price increases with a deepening industry divergence, as evidenced by the S&P 500's 0.3% increase and the Nasdaq's 1.0% increase this week [1] - The focus of capital flows is shifting towards technology, with significant inflows into software and services, automotive, and semiconductor sectors [2] - Earnings expectations for most industries are being revised upwards, indicating a generally stable outlook despite some sectors facing downward adjustments [3] Summary by Sections 1. Market Performance - The S&P 500 rose by 0.3%, while the Nasdaq increased by 1.0% this week, reflecting a mixed performance across sectors [1] - Small-cap growth stocks outperformed small-cap value stocks, and large-cap growth stocks outperformed large-cap value stocks [1] 2. Capital Flows - Estimated capital inflow for S&P 500 constituents was +$71.8 billion this week, down from +$214.0 billion the previous week [2] - Major inflows were seen in software and services (+$20.7 billion), automotive (+$20.6 billion), and semiconductor products (+$20.2 billion) [2] - Significant outflows occurred in utilities (-$4.6 billion) and pharmaceuticals (-$4.2 billion) [2] 3. Earnings Forecast - The dynamic future 12-month EPS expectation for S&P 500 constituents was adjusted upwards by 0.3% this week, consistent with the previous week's adjustment [3] - 22 industries saw upward revisions in earnings expectations, with notable increases in semiconductor products (+0.9%) and automotive (+0.5%) [3] - The energy sector experienced a slight downward adjustment of -0.1% [3]

证券研究报告 | 2025年12月07日 港股市场速览 优于大市 盈利预期受局部权重股压制 股价表现：市场整体上涨，结构略有分化 本周，恒生指数+0.9%，恒生综指+0.8%。风格方面，中盘（恒生中型股+1.6%） ＞大盘（恒生大型股+0.8%）＞小盘（恒生小型股基本持平）。 主要概念指数有所分化。上涨幅度较大的有恒生科技（+1.1%）；下跌幅度 较大的有恒生生物科技（-0.7%）。 国信海外选股策略均有所上涨。上涨幅度较大的是自由现金流 30（+2.4%）。 主要概念指数 EPS 预期多数下降。上修的主要有恒生消费（+0.9%）；下修 的主要有恒生互联网（-2.0%）。 国信海外选股策略 EPS 预期分化。上修的主要有红利贵族 50（+0.5%）；下 修的主要有 ROE 策略全天候型/防御型（-0.2%）。 21 个行业上涨，8 个行业下跌，1 个基本持平。上涨的主要有：有色金属 （+9.7%）、国防军工（+5.9%）、机械（+3.9%）、电子（+3.8%）、石油石 化（+3.6%）；下跌的主要有：纺织服装（-2.6%）、综合（-0.9%）、食品 饮料（-0.6%）、银行（-0.5%）、医药（-0.4%）。 ...

证券研究报告 | 2025年12月06日 宏观经济周报 解锁服务业增长的三把钥匙 中国服务业正面临"需求与收入"的经典循环困境：提振服务业是为了增加 居民就业和收入，而服务需求增长又被认为依赖后者提升，因此形成"鸡生 蛋、蛋生鸡"的悖论。然而，当前存在三条不依赖当期居民收入增长的需求 线索，正率先打破这一循环困境。 一是海外"输入型需求"。国际往来恢复带动中国在运输、旅游、信息、研 发等服务出口增长，这部分由外部购买力驱动的需求，直接创造了国内就业 与产出。 二是国内"时间稀缺"压抑的潜在需求。我国人均 GDP 已超 1.3 万美元，非 常接近高收入国家的门槛，但服务业占比却仍低于中低收入国家的水平，主 因并非支付能力不足，而是居民"无暇消费"。一旦通过制度优化释放闲暇， 文旅、健康等体验式需求将显著释放。 三是产业升级伴生的"创新需求"。发展新质生产力推动政府和企业在研发、 数字服务、专业咨询等无形资本上投入大增，这类生产性服务需求源于政府 和企业的投资与创新活动，同样不依赖于当期居民收入水平。 这"三轮驱动"能率先创造就业，尤其是青年与转岗岗位，进而增强收入预 期与消费信心，逐步激活更广泛服务消费，形成" ...

证券研究报告 | 2025年12月05日 2025年12月06日 金融工程日报 沪指午后拉升重回 3900 点，保险板块大涨、黄金概念走高 核心观点 金融工程日报 | 金融工程·数量化投资 | | --- | | 证券分析师：张欣慰 联系人：李子靖 | 021-60933159 021-60875177 zhangxinwei1@guosen.com.cn lizijing1@guosen.com.cn S0980520060001 市场表现：20251205 大部分指数处于上涨状态，规模指数中中证 2000 指数 表现较好，板块指数中北证 50 指数表现较好，风格指数中中证 500 价值指 数表现较好。非银、有色金属、国防军工、综合、机械行业表现较好，银行、 煤炭、交通运输、消费者服务、房地产行业表现较差。炒股软件、保险精选、 两岸融合、超导、福建省国资等概念表现较好，银行精选、家纺、央企银行、 熊去氧胆酸、航运精选等概念表现较差。 市场情绪：20251205 收盘时有 80 只股票涨停，有 12 只股票跌停。昨日涨停 股票今日收盘收益为 1.22%，昨日跌停股票今日收盘收益为 0.15%。今日封 板率 7 ...

Investment Rating - The investment rating for the company is "Outperform the Market" (maintained) [2] Core Insights - The company is a leading retail pharmacy chain in China, focusing on both traditional and modern medicine, with a wide coverage across 21 provinces. As of September 30, 2025, it operates 17,385 stores, including 10,356 direct-operated and 7,029 franchised stores. The company is shifting from "scale expansion" to "quality improvement" and aims to enhance its core competitiveness through digital supply chains and specialized services [3][5][13] - The retail pharmacy industry is undergoing a transformation from scale expansion to quality competition, with a market size of 929.3 billion yuan in 2023, growing by 6.5% year-on-year, although the growth rate has slowed significantly [3][46] - The company achieved a revenue of 20.068 billion yuan in the first three quarters of 2025, a year-on-year increase of 1.7%, and a net profit of 1.081 billion yuan, up 26.0% year-on-year. The third quarter alone saw a revenue of 6.546 billion yuan, growing by 2.5%, and a net profit of 283 million yuan, up 41.0% year-on-year [3][19][26] Company Overview - The company has developed into a leading retail pharmacy chain through steady internal growth and strategic acquisitions since its establishment in 1999. It has expanded its network significantly, covering major markets across China [5][13] - The ownership structure is concentrated, with the controlling shareholders being three brothers who collectively hold 55.12% of the shares, ensuring efficient decision-making [8] Industry Status - The retail pharmacy market is experiencing a decline in growth rates, with the number of retail pharmacies decreasing from 706,000 in Q3 2024 to 699,000 in Q1 2025 due to various factors including online competition and regulatory changes [46][51] - The industry is expected to see increased concentration and chain rates, with larger chains likely to gain a competitive edge over smaller pharmacies [3][46] Financial Performance - The company’s profit margins have improved, with a gross margin of 34.8% and a net margin of 5.8% in the first three quarters of 2025. The retail business achieved a gross margin of 37.7% [26][29] - The company’s revenue forecast for 2025-2027 is projected to be 27.205 billion, 30.071 billion, and 33.363 billion yuan, with corresponding net profits of 1.208 billion, 1.485 billion, and 1.798 billion yuan, indicating strong growth potential [3][113]

证券研究报告 | 2025年12月06日 港股投资周报 近期，环球新材国际等股票平稳创出新高。 按照板块来看，创新高股票数量最多的是周期板块，其次为大金融、消费、 医药、制造和科技板块，具体个股信息可参照正文。 港股市场一周回顾 宽基指数方面，本周恒生中型股指数收益最高，累计收益 1.57%；恒生小型 股指数收益最低，累计收益-0.01%。 资源股领涨，港股精选组合本年上涨 62.49% 核心观点 金融工程周报 港股精选组合绩效回顾 本周，港股精选组合绝对收益 1.12%，相对恒生指数超额收益 0.24%。 本年，港股精选组合绝对收益 62.49%，相对恒生指数超额收益 32.45%。 港股市场创新高热点板块跟踪 我们根据分析师关注度、股价相对强弱、股价路径平稳性、创新高连续性等 角度在过去 20 个交易日创出过 250 日新高的股票池中筛选出平稳创新高股 票。 本周，港股通股票收益中位数 0.00%，投资港股的主动基金收益中位数 0.91%。 本年，港股通股票收益中位数 26.16%，投资港股的主动基金收益中位数 34.48%。 行业指数方面，本周原材料业行业收益最高，累计收益 9.98%；医疗保健业 行业 ...

- The report tracks the performance of Guosen's quantitative enhanced index portfolios and public fund enhanced index products, as well as the performance of common stock selection factors in different stock selection spaces[11][12][15] - Guosen's quantitative enhanced index portfolios are constructed based on multi-factor stock selection, targeting benchmarks such as CSI 300, CSI 500, CSI 1000, and CSI A500 indices, aiming to consistently outperform their respective benchmarks[11][12] - The construction process of Guosen's enhanced index portfolios includes three main components: return prediction, risk control, and portfolio optimization[12] - The MFE (Maximized Factor Exposure) portfolio is used to test the effectiveness of individual factors under real-world constraints, such as industry exposure, style exposure, stock weight deviation, and turnover rate. The optimization model maximizes single-factor exposure while adhering to these constraints[41][42][43] - The MFE optimization model is expressed as follows: $\begin{array}{ll}max&f^{T}\ w\\ s.t.&s_{l}\leq X(w-w_{b})\leq s_{h}\\ &h_{l}\leq H(w-w_{b})\leq h_{h}\\ &w_{l}\leq w-w_{b}\leq w_{h}\\ &b_{l}\leq B_{b}w\leq b_{h}\\ &\mathbf{0}\leq w\leq l\\ &\mathbf{1}^{T}\ w=1\end{array}$ where $f$ represents factor values, $w$ is the stock weight vector, and the constraints include limits on style factor exposure ($X$), industry exposure ($H$), stock weight deviation, and component stock weight proportions ($B_b$)[41][42][43] - The report also evaluates the performance of single-factor MFE portfolios across different stock selection spaces, including CSI 300, CSI 500, CSI 1000, CSI A500, and public fund heavy-holding indices[15][18][20][22][24][26] - The factor library includes over 30 factors categorized into valuation, reversal, growth, profitability, liquidity, volatility, corporate governance, and analyst-related dimensions. Examples include BP (Book-to-Price), single-quarter ROE, one-month reversal, and three-month turnover[16][17] - The public fund heavy-holding index is constructed using the holdings of ordinary stock funds and equity-biased hybrid funds. Stocks are selected based on cumulative weight reaching 90% of the average fund holdings[44] - The report tracks the excess returns of public fund enhanced index products for CSI 300, CSI 500, CSI 1000, and CSI A500 indices. For example, in the CSI 300 enhanced products, the highest weekly excess return was 1.01%, and the highest annual excess return was 11.97%[28][32][35][37][40]

Quantitative Models and Construction Methods - **Model Name**: Excellent Fund Performance Enhancement Portfolio **Model Construction Idea**: Shift from benchmarking broad-based indices to benchmarking active equity funds, leveraging quantitative methods to enhance fund selection and achieve "best of the best" [4][18][50] **Model Construction Process**: 1. Benchmark against the median performance of active equity funds, represented by the mixed equity fund index (885001.WI) [18][50] 2. Use a performance-layered perspective to select funds, neutralizing return factors to avoid style concentration issues [50] 3. Optimize the portfolio to control deviations in individual stocks, industries, and styles relative to the selected fund holdings [51] **Model Evaluation**: Demonstrates strong stability and the ability to consistently outperform the median of active equity funds [50][51] - **Model Name**: Outperformance Stock Selection Portfolio **Model Construction Idea**: Focus on stocks with significant outperformance events, combining fundamental and technical analysis to select stocks with both fundamental support and technical resonance [5][56] **Model Construction Process**: 1. Filter stocks based on "outperformance" in research report titles and analysts' upward revisions of net profit [5][56] 2. Conduct dual-layer screening on the outperformance stock pool using fundamental and technical dimensions [56] **Model Evaluation**: Consistently ranks in the top 30% of active equity funds annually, with significant excess returns [56][57] - **Model Name**: Broker Gold Stock Performance Enhancement Portfolio **Model Construction Idea**: Use the broker gold stock pool as the stock selection space and constraint benchmark, optimizing the portfolio to control deviations in individual stocks and styles [6][31][61] **Model Construction Process**: 1. Benchmark against the mixed equity fund index and use the broker gold stock pool as the selection space [31][61] 2. Further refine the stock pool to achieve stable outperformance of the benchmark [61] **Model Evaluation**: Demonstrates strong alpha potential and consistently ranks in the top 30% of active equity funds annually [61][62] - **Model Name**: Growth and Stability Portfolio **Model Construction Idea**: Focus on the "time variable" in growth stock investments, constructing a two-dimensional evaluation system for growth stocks using a "time-series first, cross-section later" approach [7][66] **Model Construction Process**: 1. Introduce an "excess return release map" to identify the strongest excess return periods before and after positive events [66] 2. Prioritize stocks closer to their financial report disclosure dates and use multi-factor scoring to select high-quality stocks when the sample size is large [7][66] 3. Incorporate mechanisms such as weak balancing, transition, buffering, and risk avoidance to reduce turnover and mitigate risks [66] **Model Evaluation**: Consistently ranks in the top 30% of active equity funds annually, with high excess returns [66][67] Model Backtesting Results - **Excellent Fund Performance Enhancement Portfolio**: - Annualized return (2012.1.4-2025.6.30): 20.31% - Annualized excess return relative to mixed equity fund index: 11.83% - Most years ranked in the top 30% of active equity funds [52][55] - **Outperformance Stock Selection Portfolio**: - Annualized return (2010.1.4-2025.6.30): 30.55% - Annualized excess return relative to mixed equity fund index: 24.68% - Consistently ranked in the top 30% of active equity funds annually [57][59] - **Broker Gold Stock Performance Enhancement Portfolio**: - Annualized return (2018.1.2-2025.6.30): 19.34% - Annualized excess return relative to mixed equity fund index: 14.38% - Consistently ranked in the top 30% of active equity funds annually [62][65] - **Growth and Stability Portfolio**: - Annualized return (2012.1.4-2025.6.30): 35.51% - Annualized excess return relative to mixed equity fund index: 26.88% - Consistently ranked in the top 30% of active equity funds annually [67][70]