证券研究报告 | 2025年10月19日 港股市场速览 优于大市 红利稳中有升，现金流策略业绩上修 股价表现：市场显著回调，红利板块较优 国信海外选股策略估值均有所回落，估值下降幅度较大的是 ROE 策略全天候 型（-6.1%至 13.5x）。 6 个行业估值上升，23 个行业估值下降。估值上升的有：钢铁（+13.5%）、 煤炭（+3.8%）、银行（+1.0%）、电力及公用事业（+0.8%）、建材（+0.4%）； 估值下降幅度较大的有：电子（-11.2%）、国防军工（-9.1%）、电力设备 及新能源（-7.0%）、计算机（-6.8%）、汽车（-6.4%）。 业绩预期：自由现金流策略 EPS 显著上修 恒生指数 EPS（动态预期 12 个月正数 EPS，后同）+0.2%；恒生综指 EPS -0.1%。 本周，恒生指数-4.0%（周五夜盘回升 2.5%），恒生综指-4.1%。风格方面， 小盘（恒生小型股-3.7%）≈中盘（恒生中型股-3.7%）＞大盘（恒生大型股 -4.2%）。 主要概念指数分化较大，表现较优的有：恒生高股息（+1.1%）、恒生消费 （+0.1%）表现较弱的有：恒生汽车（-7.6%）、恒生科技（- ...

证券研究报告 | 2025年10月19日 资金观察，货币瞭望 央行数量工具展现出呵护态度，预计10月市场利率下行 投资策略 · 固定收益 2025年第十期 证券分析师：赵婧 0755-22940745 zhaojing@guosen.com.cn S0980513080004 证券分析师：陈笑楠 021-60375421 chenxiaonan@guosen.com.cn S0980524080001 证券分析师：季家辉 021-61761056 jijiahui@guosen.com.cn S0980522010002 证券分析师：李智能 0755-22940456 lizn@guosen.com.cn S0980516060001 请务必阅读正文之后的免责声明及其项下所有内容 摘要 请务必阅读正文之后的免责声明及其项下所有内容 ➢海外货币市场指标跟踪：美联储降息25BP符合预期，美债短期利率下行； ➢国内货币市场指标跟踪——价：9月银行间和交易所回购利率均值大多小幅上 行；R001、GC001、R007和GC007月均值分别变动4BP、5BP、4BP和8BP；短期债券收 益率方面，1年期短债收益率月均值大 ...

Economic Overview - September inflation data shows a slight increase in core CPI, while PPI remains flat month-on-month and the year-on-year decline narrows[1] - Market discussions suggest a potential recovery in industrial prices similar to the strong rebound seen in 2016-2017, with expectations for PPI to turn positive by mid-next year[1] Structural Changes - Current household leverage is stable at high levels, contrasting with the rising trend seen in 2016-2017, limiting the effectiveness of stimulus policies[1] - The demand gap is significantly larger now than in previous years, making it more challenging to stimulate demand effectively[1] Policy Direction - A fundamental shift in policy focus is noted, moving from encouraging borrowing to enhancing income distribution and government spending to boost consumer confidence and spending power[2] - The economic recovery is expected to be gradual, likely following an "L-shaped" trajectory rather than a rapid "V-shaped" rebound[2] Key Economic Indicators - Fixed asset investment cumulative year-on-year growth stands at 0.50%[4] - Retail sales growth for the month is at 3.40% year-on-year[4] - Exports show a year-on-year increase of 8.30%[4] - M2 money supply growth is recorded at 8.40%[4] Market Dynamics - Real estate investment remains weak, with rebar production continuing to decline and inventory levels high[13] - Infrastructure investment shows resilience, with certain production metrics indicating ongoing strength in related sectors[13] Consumer Behavior - Overall consumer activity is stable, but there are signs of structural divergence, particularly in transportation and retail sectors[21] - Movie box office performance is weak, while automobile sales have seen a notable increase of approximately 8.5% year-on-year[21] Trade and External Factors - Global external demand recovery is slow, with port throughput showing typical fluctuations and export freight rates declining since July[28] - Increased shipping capacity is shifting towards emerging markets, reflecting changes in global trade dynamics[28] Fiscal Measures - A new 500 billion yuan local government financial support package is expected to bolster economic activity[30] - The overall fiscal deficit has reached 10 trillion yuan, with a progress rate of 84.1%[30] Monetary Policy - The willingness to leverage in the bond market is decreasing, although it remains at a high level[40] - The current monetary environment continues to be loose, with various indicators suggesting ongoing support for economic activity[40] Real Estate Market - The real estate market faces significant downward pressure, with transaction volumes in major cities remaining low[49] - Land transaction volumes show no significant improvement, indicating persistent challenges in the property sector[49]

Core Insights - The report emphasizes the importance of the CANSLIM industry rotation strategy, suggesting a focus on sectors such as steel, banking, chemicals, electric power, and construction for investment opportunities [1][4][14] - The CANSLIM composite score has shown strong performance since 2013, with an average RankIC of 11.6% and a monthly win rate of 64.7%, indicating its effectiveness in distinguishing future industry returns [5][31] Industry Rotation Factor Performance - For the period from October 9 to October 17, 2025, factors such as broker stock changes, net inflow of large orders, and analyst upgrades performed well, while volume-adjusted momentum and price-to-book (PB) ratios lagged [2][16] - Year-to-date performance shows that SUE, analyst recognition, and broker stock changes have been strong, while volume-adjusted momentum and public fund holdings have underperformed [2][16] Last Month's Portfolio Performance Review - The industry rotation portfolio yielded a return of -3.56% from October 9 to October 17, 2025, compared to -2.23% for the CITIC first-level industry equal-weight index, resulting in an excess return of -1.33% [3][21] - Year-to-date, the portfolio has returned 14.70%, while the benchmark index returned 17.59%, leading to an excess return of -2.89% [3][21] Current Portfolio Recommendations - The top five industries based on the CANSLIM composite score are steel, banking, basic chemicals, electric power and new energy, and construction [4][23] - The report provides detailed scoring metrics for each industry, highlighting the importance of various dimensions such as industry crowding, analyst expectations, and fundamental conditions [4][25] CANSLIM Industry Rotation Strategy Construction and Performance - The CANSLIM strategy has demonstrated a robust annualized return of 22.94% since 2013, outperforming the industry equal-weight benchmark by 13.80% [5][36] - The strategy's maximum drawdown is 23.75%, with an information ratio of 1.29 and a monthly win rate of 73%, indicating strong risk-adjusted performance [5][36] Strategy Overview - The CANSLIM strategy incorporates multiple dimensions including industry crowding, analyst expectations, fundamental conditions, smart money flows, price momentum, institutional views, and macroeconomic valuation adjustments [26][30] - Each dimension is quantitatively assessed to guide investment decisions, ensuring a comprehensive approach to industry rotation [26][30]

Investment Rating - The report maintains an "Outperform" rating for the agricultural sector [4] Core Views - The report is optimistic about the reversal of the livestock cycle in 2025, with both domestic and international beef and milk markets expected to rise [3] - The report highlights the support for long-term pig prices due to industry restructuring, recommending undervalued leading companies in the sector [3] - The pet consumption sector is identified as a growth area benefiting from demographic changes [3] - The report suggests that the white chicken market will see a long-term increase in consumption, while yellow chicken may benefit first from domestic demand recovery [3] Summary by Sections Livestock - Beef prices are expected to rise, with the average price on October 17 at 25.73 yuan/kg, down 0.16% week-on-week but up 8.20% year-on-year [2] - The report anticipates a significant increase in raw milk prices by the end of the year, with the average price at 3.04 yuan/kg, stable week-on-week but down 2.88% year-on-year [2] - The pig market is experiencing a price drop, with the average price at 11.10 yuan/kg, down 0.36% week-on-week and 37.32% year-on-year [1][2] Poultry - The white chicken market shows a slight increase in supply, with prices for chicks at 3.24 yuan/bird, up 0.31% week-on-week but down 24.83% year-on-year [1] - The yellow chicken supply remains at a low level, with prices for various types of yellow chicken showing mixed trends [1] Feed and Grains - Soybean meal prices are supported by a favorable supply-demand balance, with current prices at 3,010 yuan/ton, up 0.13% week-on-week [2] - Corn prices are expected to maintain a moderate increase, with current prices at 2,205 yuan/ton, down 1.12% week-on-week but up 1.10% year-on-year [2] Investment Recommendations - Recommended stocks include: - Livestock: YouRan Agriculture, Modern Farming, China Shengmu, Guangming Meat [3] - Pork: DeKang Agriculture, Muyuan Foods, Huazhong Agriculture, Wen's Food Group, and others [3] - Pet Industry: Guibao Pet, Reap Bio [3] - Feed: Haida Group [3] - Poultry: Lihua Co., Yisheng Co., and others [3]

Investment Rating - The report maintains an "Outperform" rating for the telecommunications industry [5]. Core Insights - The report highlights the acceleration of satellite internet networking in China, with a total of 116 satellites launched this year, including the successful launch of 12 low-orbit satellites on October 16 [1][12]. - The OCP summit has propelled the development of AI technologies, with the establishment of the ESUN project aimed at enhancing Ethernet as a foundational infrastructure for AI [2][20]. - TSMC reported a record net profit of 452.3 billion NTD for Q3 2025, a 39.1% year-on-year increase, driven by strong demand for AI chips [3][33]. - The report emphasizes the high growth potential in the computing power infrastructure sector, recommending continued investment in optical devices, communication equipment, and liquid cooling technologies [4]. Summary by Sections Industry News Tracking - The report notes the successful launch of the sixth batch of satellites for the Qianfan constellation, increasing the total number of satellites to 108, which enhances communication capabilities [1][16]. - The OCP summit introduced the ESUN project, which includes 12 industry players focusing on Ethernet for scale-up applications, indicating a strong consensus in the industry [2][20]. Company Performance - TSMC's Q3 2025 revenue reached 989.9 billion NTD, a 30.3% increase year-on-year, with a forecasted annual revenue growth of 35% [3][33]. - Shijia Photon reported a 102.5% year-on-year increase in revenue for Q3 2025, with a net profit growth of 242.52% [3][39]. Investment Recommendations - The report suggests focusing on the development of AI computing infrastructure, particularly in optical devices, communication equipment, and liquid cooling solutions [4]. - It recommends long-term investment in the three major telecom operators due to their stable operations and increasing dividend payouts [4]. Market Performance Review - The telecommunications index fell by 5.92% this week, underperforming compared to the broader market [50]. - Among sub-sectors, operators and satellite internet showed relatively better performance, while the overall sector faced declines [52].

- The report tracks the performance of Guosen Financial Engineering's index enhancement portfolios, which are constructed based on multi-factor stock selection models targeting benchmarks such as CSI 300, CSI 500, CSI 1000, and CSI A500 indices. The goal is to consistently outperform the respective benchmarks [11][12][14] - The construction process of the index enhancement portfolios includes three main components: return prediction, risk control, and portfolio optimization. The optimization model maximizes single-factor exposure while controlling for constraints such as industry exposure, style exposure, stock weight deviation, turnover rate, and component stock weight ratio [12][41][42] - The Maximized Factor Exposure (MFE) portfolio is used to test the effectiveness of individual factors under real-world constraints. The 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 constraints include style exposure (\(X\)), industry exposure (\(H\)), stock weight deviation (\(w_b\)), and component stock weight ratio (\(B_b\)) [41][42][43] - The report monitors the performance of common stock selection factors across different sample spaces, including CSI 300, CSI 500, CSI 1000, CSI A500, and public fund heavy-holding indices. Factors are tested using MFE portfolios to evaluate their excess return relative to benchmarks [11][15][18] - The factor library includes over 30 factors categorized into valuation, reversal, growth, profitability, liquidity, volatility, corporate governance, and analyst-related factors. Examples include BP (Book-to-Price), EPTTM (Earnings-to-Price TTM), one-month reversal, three-month reversal, one-year momentum, and others [16][17] - The report highlights the performance of specific factors in different sample spaces: - **CSI 300**: One-month reversal, three-month reversal, and EPTTM one-year percentile performed well recently, while three-month institutional coverage and standardized unexpected earnings performed poorly [1][18] - **CSI 500**: Three-month volatility, three-month reversal, and EPTTM one-year percentile performed well recently, while one-year momentum and standardized unexpected revenue performed poorly [1][20] - **CSI 1000**: One-month volatility, one-month turnover, and three-month reversal performed well recently, while executive compensation and three-month earnings revisions performed poorly [1][22] - **CSI A500**: One-month reversal, EPTTM one-year percentile, and one-month volatility performed well recently, while three-month institutional coverage and one-year momentum performed poorly [1][24] - **Public fund heavy-holding index**: Dividend yield, three-month reversal, and EPTTM performed well recently, while standardized unexpected revenue and three-month earnings revisions performed poorly [1][26][27] - The report tracks the excess returns of public fund index enhancement products, including CSI 300, CSI 500, CSI 1000, and CSI A500. For CSI 300 products, the highest weekly excess return was 0.92%, while the lowest was -3.08%, with a median of 0.01% [3][32][31] - For CSI 500 products, the highest weekly excess return was 3.20%, while the lowest was -0.48%, with a median of 0.49% [3][35][34] - For CSI 1000 products, the highest weekly excess return was 1.58%, while the lowest was -0.82%, with a median of 0.37% [3][37][36] - For CSI A500 products, the highest weekly excess return was 1.20%, while the lowest was -0.84%, with a median of 0.23% [3][40][39]

Quantitative Models and Construction Methods 1. Model Name: Excellent Fund Performance Enhancement Portfolio - Model Construction Idea: The model aims to benchmark against active equity funds instead of broad-based indices, leveraging the holdings of excellent funds and enhancing them using quantitative methods to achieve optimal selection[4][18][45] - Model Construction Process: - Benchmark against the median of active equity funds, using the active equity hybrid fund index (885001.WI) as a proxy - Consider the impact of position and transaction fees, with the portfolio position calculated based on the median position of active equity funds, which is 90% for this period[18] - Enhance the holdings of selected funds using quantitative methods to achieve optimal selection[4][18][45] - Model Evaluation: The model aims to consistently outperform the median of active equity funds by leveraging the holdings of excellent funds and enhancing them using quantitative methods[4][18][45] 2. Model Name: Exceeding Expectations Selection Portfolio - Model Construction Idea: The model selects stocks with exceeding expectations events based on research report titles and analysts' upward revisions of net profit, and then selects stocks with both fundamental support and technical resonance[5][23][51] - Model Construction Process: - Screen the exceeding expectations event stock pool based on research report titles and analysts' upward revisions of net profit - Select stocks with both fundamental support and technical resonance from the exceeding expectations stock pool to construct the exceeding expectations selection portfolio[5][23][51] - Model Evaluation: The model aims to capture significant excess returns before and after exceeding expectations events by selecting stocks with both fundamental support and technical resonance[5][23][51] 3. Model Name: Broker Golden Stock Performance Enhancement Portfolio - Model Construction Idea: The model uses the broker golden stock pool as the stock selection space and constraint benchmark, and optimizes the portfolio to control deviations in individual stocks and styles from the broker golden stock pool[6][29][56] - Model Construction Process: - Use the broker golden stock pool as the stock selection space and constraint benchmark - Optimize the portfolio to control deviations in individual stocks and styles from the broker golden stock pool[6][29][56] - Model Evaluation: The model aims to leverage the alpha potential of the broker golden stock pool and achieve stable outperformance of the active equity hybrid fund index[6][29][56] 4. Model Name: Growth and Stability Portfolio - Model Construction Idea: The model constructs a two-dimensional evaluation system for growth stocks using a "time series first, cross-section later" approach, selecting stocks based on the interval days from the scheduled disclosure date of the official financial report[7][35][61] - Model Construction Process: - Construct a growth stock pool based on research report titles and performance increases - Select stocks based on the interval days from the scheduled disclosure date of the official financial report, prioritizing stocks closer to the disclosure date - Use multi-factor scoring to select high-quality stocks when the sample size is large - Introduce weak balance mechanism, transition mechanism, buffer mechanism, and risk avoidance mechanism to reduce portfolio turnover and avoid risks[7][35][61] - Model Evaluation: The model aims to efficiently capture the excess returns of growth stocks during the golden period of excess return release by selecting stocks based on the interval days from the scheduled disclosure date of the official financial report[7][35][61] Model Backtesting Results 1. Excellent Fund Performance Enhancement Portfolio - Weekly absolute return: -3.94%[2][22] - Weekly excess return relative to active equity hybrid fund index: 0.41%[2][22] - Annual absolute return: 24.22%[2][22] - Annual excess return relative to active equity hybrid fund index: -3.30%[2][22] - Annual ranking in active equity funds: 52.75% percentile (1830/3469)[2][22] 2. Exceeding Expectations Selection Portfolio - Weekly absolute return: -6.08%[2][28] - Weekly excess return relative to active equity hybrid fund index: -1.73%[2][28] - Annual absolute return: 38.46%[2][28] - Annual excess return relative to active equity hybrid fund index: 10.94%[2][28] - Annual ranking in active equity funds: 23.23% percentile (806/3469)[2][28] 3. Broker Golden Stock Performance Enhancement Portfolio - Weekly absolute return: -5.10%[2][34] - Weekly excess return relative to active equity hybrid fund index: -0.75%[2][34] - Annual absolute return: 27.24%[2][34] - Annual excess return relative to active equity hybrid fund index: -0.27%[2][34] - Annual ranking in active equity funds: 45.06% percentile (1563/3469)[2][34] 4. Growth and Stability Portfolio - Weekly absolute return: -4.26%[3][39] - Weekly excess return relative to active equity hybrid fund index: 0.09%[3][39] - Annual absolute return: 48.25%[3][39] - Annual excess return relative to active equity hybrid fund index: 20.74%[3][39] - Annual ranking in active equity funds: 10.72% percentile (372/3469)[3][39]

Revenue and Expenditure Overview - In the first three quarters, the national general public budget revenue reached CNY 163,876 billion, a year-on-year increase of 0.5%[2] - Tax revenue amounted to CNY 132,664 billion, growing by 0.7% year-on-year, while non-tax revenue decreased by 0.4% to CNY 31,212 billion[2] - Total expenditure for the first three quarters was CNY 208,064 billion, up 3.1% year-on-year, with central government expenditure increasing by 7.3% to CNY 31,008 billion and local government expenditure rising by 2.4% to CNY 177,056 billion[2] Monthly Trends - In September, general public budget revenue increased by 2.6% year-on-year, up from 2% in the previous month, with tax revenue showing a significant rise of 8.7% compared to 3.4% previously[3] - Non-tax revenue in September fell sharply by 11.4%, worsening from a decline of 3.8% in the prior month[3] - General public expenditure in September also improved, growing by 3.1% year-on-year, compared to just 0.8% in August[3] Fiscal Policy and Economic Impact - The fiscal policy strength index indicates a continued decline in fiscal policy effectiveness, despite a rebound in major tax categories, suggesting potential economic recovery[25] - The government plans to utilize CNY 500 billion in policy financial tools and CNY 500 billion in local debt limits to stimulate the economy in Q4[26] - The total local debt limit is expected to shrink to less than CNY 800 billion by year-end, following the recent allocation of CNY 5 trillion for local government financial support[26] Budget Completion Status - As of September, the completion rate for general public budget revenue was 7.1%, higher than the same period in the previous two years[6] - Cumulative general public expenditure growth was 3.1%, below the budget target of 4.4%, necessitating a quarterly increase of approximately 7.4% in Q4 to meet the annual goal[14]

========= - The "Guosen JinGong Hong Kong Stock Selection Portfolio" aims to select stocks with both fundamental support and technical resonance from an analyst-recommended stock pool[14][15] - The portfolio's backtesting period is from January 1, 2010, to June 30, 2025, with an annualized return of 19.11% and an excess return of 18.48% relative to the Hang Seng Index[15] - The portfolio construction involves selecting stocks based on analysts' upward earnings forecasts, initial coverage, and unexpected events in analyst reports[15] Portfolio Backtesting Results - Annualized return: 19.11%[15] - Excess return relative to the Hang Seng Index: 18.48%[15] - Maximum drawdown: 23.73%[20] - Information ratio (IR): 1.22[20] - Tracking error: 14.55%[20] - Return-to-drawdown ratio: 0.78[20] Stable New High Stock Screening Method - The method screens stocks that have reached a 250-day new high in the past 20 trading days based on analyst attention, relative stock strength, stock price stability, and continuity of new highs[23][24] - The formula for the 250-day new high distance is: $$ 250 \text{ day new high distance} = 1 - \frac{Closet}{ts\_max(Close, 250)} $$ where $Closet$ is the latest closing price and $ts\_max(Close, 250)$ is the maximum closing price in the past 250 trading days[23] - Stocks are selected based on the absolute value of the past 120-day price change and the sum of the absolute values of the past 120-day price changes[23] Stable New High Stock Screening Results - The sector with the most new high stocks is the cyclical sector, followed by technology, consumer, financial, manufacturing, and pharmaceutical sectors[23] - Specific stocks that have reached stable new highs include China National Building Material, Hansoh Pharmaceutical, and others[23][29] - The screening criteria include analyst attention (at least 5 buy or hold ratings in the past 6 months), relative stock strength (top 20% in the past 250 days), and stock price stability (top 50% based on price path smoothness and new high continuity)[24] Performance of Hong Kong Stock Connect and Active Funds Investing in Hong Kong Stocks - Median return of Hong Kong Stock Connect stocks this week: -3.44%[44] - Median return of active funds investing in Hong Kong stocks this week: -3.79%[44] - Median return of Hong Kong Stock Connect stocks this year: 25.14%[44] - Median return of active funds investing in Hong Kong stocks this year: 34.50%[44] Top Performing Funds - This week: Ping An Hong Kong Stock Connect Dividend Select A (2.29%), China Merchants Bank Hong Kong and Shanghai Multi-Strategy (1.90%), Ping An Hong Kong Stock Connect Dividend Select A (1.88%)[45] - This year: China Universal Hong Kong Advantage Select A (140.23%), Bank of China Hong Kong Stock Connect Medical A (104.90%), E Fund Global Pharmaceutical Industry RMB A (93.97%)[45] =========