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%）。 ...

Group 1: Economic Insights - China's service industry faces a classic "demand and income" cycle dilemma, where boosting service demand is believed to depend on increased resident income, creating a paradox[1] - Three key demand drivers are identified that do not rely on current resident income growth: overseas "input demand," domestic "time-scarcity" suppressed demand, and "innovation demand" from industrial upgrades[1] - The service export growth driven by international exchanges has significantly contributed to domestic employment and output since Q3 2023[10] Group 2: Employment and Consumption - The "three drivers" can create jobs, particularly for youth and those transitioning between jobs, enhancing income expectations and consumer confidence[2] - This process is expected to activate broader service consumption, forming a virtuous cycle of "employment—income—consumption" that supports current growth stabilization[2] - Consumer indicators show signs of weakness, with logistics delivery growth slowing to 2.6% year-on-year, reflecting weakened demand[22] Group 3: Key Economic Data - Fixed asset investment has decreased by 1.70% year-on-year, while retail sales have increased by 2.90% year-on-year[3] - Exports have declined by 1.10% year-on-year, and M2 growth stands at 8.21%[3] - Port cargo throughput reached a record high of 286 million tons, with a month-on-month increase of 8.43%, indicating strong external demand[25]

- The report does not contain any quantitative models or factors for analysis[1][2][3]

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]

- The report introduces a quantitative model based on the "250-day new high distance" to track market trends and identify investment hotspots. The calculation formula is: $ 250\text{-day new high distance} = 1 - \frac{\text{Close}_{t}}{\text{ts\_max(Close, 250)}} $ where $\text{Close}_{t}$ represents the latest closing price, and $\text{ts\_max(Close, 250)}$ is the maximum closing price over the past 250 trading days. If the latest closing price hits a new high, the distance is 0; otherwise, it is a positive value indicating the degree of fallback [11][19][26] - The model evaluates the effectiveness of momentum and trend-following strategies, referencing studies by George (2004), William O'Neil's CANSLIM framework, and Mark Minervini's "Stock Market Wizard," which emphasize the importance of stocks near their 52-week highs as potential leaders in market uptrends [11][18][21] - A screening method for "stable new high stocks" is introduced, focusing on factors such as analyst attention, relative stock strength, price path smoothness, and sustained new highs. Key metrics include: - Analyst attention: At least 5 buy or overweight ratings in the past 3 months - Relative stock strength: Top 20% in 250-day returns - Price path smoothness: Evaluated using metrics like price displacement ratio - Sustained new highs: Average 250-day new high distance over the past 120 days - Trend continuation: Average 250-day new high distance over the past 5 days [26][28][29] - The report identifies 41 "stable new high stocks" based on the above criteria, with the majority belonging to cyclical and manufacturing sectors. Notable industries include non-ferrous metals and machinery [29][30][32] - Backtesting results show that cyclical and manufacturing sectors have the highest number of stocks achieving new highs, with cyclical stocks leading in non-ferrous metals and manufacturing stocks excelling in machinery [19][20][29]

Investment Rating - The report maintains an "Outperform" rating for the industry [2] Core Insights - The current financial system in China is significantly exhibiting characteristics of a "Big Central Bank," with the People's Bank of China reshaping the asset management industry's ecology and operational logic through various monetary tools and macro-prudential management frameworks [4] - By 2026, the bond market is expected to see a structural shift where large commercial banks will enhance their market pricing influence due to closer liquidity ties with the central bank, while public funds and smaller banks will face constraints in bond investment, particularly in long-term securities [4] - The equity market is anticipated to maintain a slow bull trend, supported by a continued trend of "deposit migration" among residents, potentially bringing in an incremental capital of 4-5 trillion yuan into asset management products and direct market investments [4] Summary by Sections Central Bank and Banking - The central bank is narrowing the interest rate corridor by introducing the 7-day reverse repurchase rate as the main policy rate, which allows for more flexible monetary control [8][12] - The central bank's operations, including the buying and selling of government bonds, are aimed at stabilizing long-term bond rates and managing market expectations [13][14] Banking Wealth Management - The trend of "deposit migration" is expected to benefit the growth of wealth management scale, as traditional savings rates decline and residents seek higher returns [66] - The scale of bank wealth management products is projected to continue growing, with the current estimated size around 33 trillion yuan [70] - Despite a downward trend in performance benchmarks for newly issued wealth management products, they are still expected to remain above deposit rates, driving banks to enhance their middle-income business [75] Insurance Asset Management - The report highlights the potential for "low guaranteed + high floating" products, particularly dividend insurance, to thrive in a low-interest-rate environment, as they help insurers manage liability costs effectively [108] - By 2025, insurance capital is expected to increase its allocation to equity assets, with a focus on high-dividend investment opportunities and long-term bonds to mitigate asset-liability duration mismatch risks [123][124]

Quantitative Models and Construction Methods Model Name: 250-Day New High Distance Model - **Model Construction Idea**: The model is based on the concept that stocks nearing their 52-week high tend to outperform those further away from their highs, as supported by prior research and methodologies like CANSLIM and momentum strategies[11][18] - **Model Construction Process**: The 250-day new high distance is calculated as follows: $ 250 \text{-day new high distance} = 1 - \frac{\text{Closet}}{\text{ts\_max(Close, 250)}} $ - **Closet**: The latest closing price - **ts\_max(Close, 250)**: The maximum closing price over the past 250 trading days If the latest closing price reaches a new high, the distance is 0. If the price has fallen from the high, the distance is a positive value representing the degree of decline[11] - **Model Evaluation**: The model effectively identifies stocks and indices that are leading the market trends, serving as a useful tool for tracking momentum and market hotspots[11][18] Model Name: Stable New High Stock Selection Model - **Model Construction Idea**: This model focuses on identifying stocks with smooth price paths and consistent momentum, as smoother momentum stocks tend to outperform those with jumpy price paths[26] - **Model Construction Process**: Stocks are selected from those that have reached a 250-day new high in the past 20 trading days, based on the following criteria: 1. **Analyst Attention**: At least 5 "Buy" or "Overweight" ratings in the past 3 months 2. **Relative Strength**: Top 20% in 250-day price performance 3. **Price Stability**: - **Price Path Smoothness**: Measured by the ratio of price displacement to total price movement - **Sustained New Highs**: Average 250-day new high distance over the past 120 days 4. **Trend Continuity**: Average 250-day new high distance over the past 5 days, with the top 50 stocks selected based on rankings[26][28] - **Model Evaluation**: The model emphasizes smooth momentum and sustained trends, which are less likely to attract excessive attention, potentially leading to stronger momentum effects[26] --- Model Backtesting Results 250-Day New High Distance Model - **Indices' 250-Day New High Distances**: - Shanghai Composite: 3.14% - Shenzhen Component: 4.21% - CSI 300: 3.44% - CSI 500: 5.98% - CSI 1000: 4.00% - CSI 2000: 2.50% - ChiNext Index: 6.47% - STAR 50 Index: 13.84%[12][33] Stable New High Stock Selection Model - **Selected Stocks**: 41 stocks were identified as stable new high stocks, including Zhongji Xuchuang, Guangku Technology, and Yaxiang Jicheng[29][34] - **Sector Distribution**: - Cyclical Sector: 17 stocks, with the majority in the non-ferrous metals industry - Manufacturing Sector: 13 stocks, with the majority in the machinery industry[29][34] --- Quantitative Factors and Construction Methods Factor Name: 250-Day New High Distance - **Factor Construction Idea**: Measures the relative position of a stock's latest closing price compared to its 250-day high, capturing momentum and trend-following characteristics[11] - **Factor Construction Process**: $ 250 \text{-day new high distance} = 1 - \frac{\text{Closet}}{\text{ts\_max(Close, 250)}} $ - **Closet**: The latest closing price - **ts\_max(Close, 250)**: The maximum closing price over the past 250 trading days[11] Factor Name: Price Path Smoothness - **Factor Construction Idea**: Quantifies the smoothness of a stock's price movement, as smoother paths are associated with stronger momentum effects[26] - **Factor Construction Process**: - Calculated as the ratio of price displacement to the total price movement over a given period[26] Factor Name: Sustained New Highs - **Factor Construction Idea**: Tracks the consistency of a stock's ability to maintain new highs over time, reflecting sustained momentum[26] - **Factor Construction Process**: - Average 250-day new high distance over the past 120 days[28] Factor Name: Trend Continuity - **Factor Construction Idea**: Measures the short-term continuation of a stock's trend, emphasizing recent momentum[26] - **Factor Construction Process**: - Average 250-day new high distance over the past 5 days, with stocks ranked and selected based on this metric[28] --- Factor Backtesting Results 250-Day New High Distance Factor - **Indices' 250-Day New High Distances**: - Shanghai Composite: 3.14% - Shenzhen Component: 4.21% - CSI 300: 3.44% - CSI 500: 5.98% - CSI 1000: 4.00% - CSI 2000: 2.50% - ChiNext Index: 6.47% - STAR 50 Index: 13.84%[12][33] Price Path Smoothness Factor - **Selected Stocks**: 41 stocks were identified, with the majority belonging to the cyclical and manufacturing sectors[29][34] Sustained New Highs Factor - **Selected Stocks**: Stocks with consistent new highs over the past 120 days were prioritized, with examples including Zhongji Xuchuang and Guangku Technology[29][34] Trend Continuity Factor - **Selected Stocks**: Stocks with the highest rankings in 5-day trend continuity were included, emphasizing short-term momentum[28][29]