2025 年的市场在年末和年初的表现存在显著波动。2024 年底，市场在最后一 天突然拉出了一根中阴线，导致 1 月初连续下跌，直到 2 月初才企稳向上。1 月 13 日后启动了一轮春季攻势，特别是春节后 Deepseek 加入带来了明显的 上涨。 今年（2025 年）3 月，在经历了 Deepseek 带来的上涨后，市场如期 回调，但 4 月初特朗普关税战引发大幅下跌，中断了之前的行情。然而，从 4 月 7 日开始，市场强势反弹，没有出现二次探底。6 月下旬全球窗口交易期间， 市场直接上行，再次展现出小概率事件。 9 月中旬至 10 月初期间，大金融与 泛科技板块走出丝滑走势，但券商被压制后资金转向双创板块，使创业板指数 和科创 50 指数明显上扬。12 月 16 日出现中阴线，但 12 月 17 日神秘资金流 入 A500 ETF，使得原本预期的调整变为上涨趋势。 短期市场向上趋势明显，但需关注驱动因素的可持续性及年底资金退潮 风险。中线来看，整体趋势向上，高点 4,034 预计难以阻挡，长期目标 可看至 4,130。 2025 年行业轮动策略表现最佳，超额收益 20 多个点。展望 2026 年， 需做好 ...

Core Insights - The report highlights the current industry allocation positions, with non-bank financials at 11.7%, banks at 9.6%, and transportation at 9.2% among others [1] - The average weekly return for the CITIC primary industries was 0.1%, with the best-performing sectors being non-bank financials (3.7%), retail (2.3%), and defense (2.3%) [3][10] - The composite strategy achieved a cumulative return of 0.4% this week, outperforming the CITIC primary industry equal-weight benchmark by 0.4% [3] - Year-to-date, the composite strategy has gained 28.0%, compared to the benchmark's 22.4%, resulting in an excess return of 5.7% [3] Industry Performance Review - The best-performing sectors over the past week were non-bank financials (3.7%), retail (2.3%), and defense (2.3%), while the worst were real estate (-2.4%), electric equipment and new energy (-2.3%), and comprehensive (-1.8%) [10][11] - The average monthly return for the past month was -1.1% across 30 CITIC primary industries [10] Valuation Risk Warning - The report indicates that the current PB (Price-to-Book) valuations for retail, computer, non-ferrous metals, defense, and petrochemicals are above the 95% percentile of their historical valuations, triggering a high valuation warning [13][14] Single Strategy Rankings and Recent Performance - The top three industries based on the high prosperity industry rotation strategy are machinery, coal, and non-bank financials [15][16] - The implied sentiment momentum strategy ranks the top three industries as communication, electronics, and electric equipment and new energy [20] Macro Style Rotation Strategy - The macro style rotation strategy identifies the top six industries based on current macro indicators as banks, home appliances, electric utilities, petrochemicals, transportation, and construction [23][24] Long-term Reversal Strategy - The long-term reversal strategy combines factors of 2-3 year reversal, 1-year momentum, and low turnover rates to select the top five industries for allocation each month [26]

金融工程 | 证券研究报告 — 周报 2025 年 12 月 14 日 中银量化多策略行业轮动 周报 – 20251211 当前（2025 年 12 月 11 日）中银多策略行业配置系统仓位：通信 （9.6%）、银行（9.5%）、交通运输（9.1%）、非银行金融（8.0%）、 食品饮料（7.7%）、电力设备及新能源（7.2%）、钢铁（6.7%）、机械 （6.2%）、基础化工（4.7%）、石油石化（4.7%）、家电（4.4%）、综 合 （3.5% ）、农林牧渔（ 3.5% ）、综合金融（ 3.5% ）、有色金属 （3.5%）、建材（3.4%）、电子（2.4%）、电力及公用事业（1.2%）、 建筑（1.2%）。 相关研究报告 《中银证券量化行业轮动系列（七）：如何把 握市场"未证伪情绪"构建行业动量策略》 20220917 《中银证券量化行业轮动系列（八）："估值泡 沫保护"的高景气行业轮动策略》20221018 《中银证券宏观基本面行业轮动新框架：对传 统自上而下资产配置困境的破局》20230518 《中银证券量化行业轮动系列（九）：长期反 转-中期动量-低拥挤"行业轮动策略》20240914 《中银证券量化行 ...

Report Industry Investment Rating No relevant content provided. Core Viewpoints - In 2025, the CSI Cash Flow Index performed excellently, with an excess return of 11.2% compared to the CSI Dividend Index as of the end of November, mainly coming from the second half of the year. The index can stably outperform the CSI Dividend Index in the long - term, and its relative excess return does not depend on the dominance of growth or value styles [5][8]. - The adjustment of constituent stocks contributed good returns to the index. The high - frequency and high - proportion adjustment of constituent stocks in the past year has brought good performance, especially the 49 stocks included on June 16, with an average return of 27.1% in 90 days after inclusion, much higher than the 11.9% of the excluded stocks. The index also showed significant industry timing ability [5][15]. - The industry rotation strategy based on the industry distribution of the CSI Cash Flow Index had an annualized return of 12.8% and an annualized excess return of 1.9% since 2014. The index's industry allocation ability can bring significant excess returns in the value - dominant style, but the excess return is prone to large drawdowns in the growth - dominant style [5][20]. Summary by Directory 2025 CSI Cash Flow Index Performed Excellently - At the beginning of 2025, free - cash - flow index funds became a hot topic in the market. As of November 30, 59 new cash - flow index funds were issued, tracking multiple cash - flow - related indexes. The cash - flow index was questioned due to high - frequency constituent stock updates, over - fitting risks, and opaque historical data. From January to February, it significantly underperformed the dividend index, causing doubts about its excess - return stability [8]. - As of the end of November 2025, the excess return of the CSI Cash Flow Index compared to the CSI Dividend Index reached 11.2%, mainly from the second half of the year. In the first half, it underperformed by 2.5 percentage points, but from mid - July, it significantly outperformed, with a cumulative excess return of 14.1% in the second half [5][8]. - At the beginning of the value - to - growth style switch, the cash - flow index is prone to underperform the dividend index, which is in line with historical rules. During the value - to - growth style switch starting from September 2024, the CSI Cash Flow Index underperformed the CSI Dividend Index by 7.2 percentage points from November 13, 2024, to April 8, 2025 [11]. - The cash - flow index performed well both when the market rose significantly and the growth style dominated from July to September, and when the market adjusted and the value style dominated from October to November. Since July, it has achieved significant excess returns compared to the dividend index [12]. Component Stock Adjustment Contributed Good Returns to the Index - The CSI Cash Flow Index has a high - frequency and often high - proportion adjustment of constituent stocks. In the past year, the adjustment of constituent stocks contributed good returns. The index conducts quarterly adjustments in March, June, September, and December. In 2025Q3, 2025Q2, 2025Q1, and 2024Q4, the number of changed constituent stocks was 39, 49, 8, and 44 respectively. Except for the 8 stocks included on March 17, the average return of included stocks was higher than that of excluded stocks in other adjustments [15]. - In June, the index significantly increased its holdings in non - ferrous metals, power equipment and new energy, and machinery industries, showing significant industry timing ability. The non - ferrous metals (increased by 5.6%), agriculture, forestry, animal husbandry and fishery (increased by 5.3%), machinery (increased by 3.1%), and power equipment and new energy (increased by 2.7%) industries that were significantly increased in June had gains of 44%, 12%, 27%, and 43% respectively in the third quarter [16][17]. Industry Rotation Strategy Based on the Industry Distribution of the CSI Cash Flow Index - Since the free - cash - flow index has significant alpha returns, and industry allocation and timing ability are important sources of its excess returns, an industry rotation strategy is constructed based on the industry distribution of the CSI Cash Flow Index to verify its industry allocation ability. Due to the limited public data of the index's constituent stocks, the self - calculated constituent stocks since December 2013 are used [19]. - The industry rotation strategy based on the industry distribution of the CSI Cash Flow Index has an annualized return of 12.8% and an annualized excess return of 1.9% since 2014. The accumulation of excess returns has significant periodic characteristics. The index's industry allocation ability can bring more significant excess returns in the value - dominant style, while the excess return is prone to large drawdowns in the growth - dominant style [20].

1. Report Industry Investment Rating - No relevant information provided 2. Core Viewpoints of the Report - The Financial Street Securities Research Institute constructed a strategic portfolio of industry and theme ETFs based on two strategy reports: "Strategy Portfolio Report under Industry Rotation: Quantitative Analysis from the Perspective of Industry Style Continuity and Switching" (20241007) and "Research on the Overview and Allocation Methods of the Stock - type ETF Market: Taking the ETF Portfolio Based on the Industry Rotation Strategy as an Example" (20241013) [2] - From 20251201 - 20251205, the cumulative net return of the strategy was about 0.55%, and the excess return relative to the CSI 300 ETF was about - 0.81%. From October 14, 2024, to the present, the out - of - sample cumulative return of the strategy was about 24.26%, and the cumulative excess return relative to the CSI 300 ETF was about 3.20% [3] - In the week of 20251208, the model recommended the allocation of sectors such as aviation equipment, software development, gaming, communication equipment, and communication services. In the coming week, the strategy would newly hold products such as Aerospace ETF, Computer ETF, Gaming ETF, Cloud Computing ETF, and Central Enterprise Science and Technology Innovation ETF [12] 3. Summary of Relevant Catalogs 3.1 Strategy Construction - The strategy was constructed based on two reports: "Strategy Portfolio Report under Industry Rotation: Quantitative Analysis from the Perspective of Industry Style Continuity and Switching" (20241007) and "Research on the Overview and Allocation Methods of the Stock - type ETF Market: Taking the ETF Portfolio Based on the Industry Rotation Strategy as an Example" (20241013) [2] 3.2 Performance Tracking - During 20251201 - 20251205, the strategy's cumulative net return was about 0.55%, and the excess return relative to the CSI 300 ETF was about - 0.81%. From October 14, 2024, to the present, the strategy's out - of - sample cumulative return was about 24.26%, and the cumulative excess return relative to the CSI 300 ETF was about 3.20% [3] 3.3 Portfolio Adjustment - In the week of 20251208, products like Aerospace ETF (159227), Computer ETF Southern (159586), Gaming ETF (159869), Cloud Computing ETF (516510), Central Enterprise Science and Technology Innovation ETF (159335) etc. were recommended to be newly held, while products such as Real Estate ETF (159768), Grain ETF (159698), Petrochemical ETF (159731) etc. were to be removed from the portfolio [3][12] 3.4 Timing Signals - The timing signals were price - volume indicators, where 1 indicated a bullish signal, 0 indicated a neutral signal, and - 1 indicated a bearish signal. For example, the weekly and daily timing signals for Aerospace ETF (159227) were 0 and 1 respectively [3]

《中银证券量化行业轮动系列（七）：如何把 握市场"未证伪情绪"构建行业动量策略》 20220917 金融工程 | 证券研究报告 — 周报 2025 年 12 月 5 日 中银量化多策略行业轮动 周报 – 20251204 当前（2025 年 12 月 4 日）中银多策略行业配置系统仓位：非银行金融 （11.9%）、银行（9.7%）、交通运输（9.3%）、通信（9.2%）、食品饮 料（7.8%）、有色金属（7.6%）、钢铁（6.9%）、石油石化（4.8%）、 基础化工（4.7%）、家电（4.5%）、农林牧渔（3.5%）、综合金融 （ 3.5% ） 、 综 合 （ 3.5% ） 、 建 材 （ 3.4% ） 、 电 力 设 备 及 新 能 源 （3.4% ）、机械（ 1.9% ）、轻工制造（ 1.9% ）、电力及公用事业 （1.2%）、建筑（1.2%）。 相关研究报告 《中银证券量化行业轮动系列（八）："估值泡 沫保护"的高景气行业轮动策略》20221018 《中银证券宏观基本面行业轮动新框架：对传 统自上而下资产配置困境的破局》20230518 《中银证券量化行业轮动系列（九）：长期反 转-中期动量-低拥挤"行 ...

Core Insights - The report suggests a shift towards a balanced strategy in response to external disturbances and internal market conditions, emphasizing the importance of equilibrium in investment approaches [2][4][29] - Four industries identified as having "low position + marginal improvement" potential, which are expected to benefit from low valuations and improving economic conditions [2][4] Industry Recommendations - **Low Position Recovery (Dynamic)**: The recommended sectors include Beauty Care, Transportation, Other Power Equipment, Semiconductors, Automotive, Bioproducts, Traditional Chinese Medicine, and Home Appliances [4][6] - **Low Position + Marginal Improvement (Dynamic)**: The sectors highlighted are Beauty Care, Transportation, Other Power Equipment, and Semiconductors [4][6] Market Analysis - The A-share market experienced significant adjustments in November due to three main factors: 1. Federal Reserve liquidity expectations were disrupted by the U.S. government shutdown, leading to market uncertainty regarding the December interest rate meeting [4] 2. The intensifying debate over AI narratives and technical corrections in high-performing stocks, particularly in the AI sector, caused a decline in market sentiment [4] 3. A rebalancing of market styles, with funds shifting from high-volatility growth stocks to low-valuation, high-dividend sectors, resulting in a rise in bank and oil sectors [4] Sector-Specific Insights - **Beauty Care**: The sector is expected to see a revival in new consumption themes towards the end of the year, with a 17.95% year-on-year increase in retail sales for cosmetics [6][10] - **Transportation**: Valuations are low, and improved U.S.-China relations are anticipated to boost export demand, leading to a recovery in shipping [6][10] - **Other Power Equipment**: Increased investments in power grid and supply equipment due to AI-related electricity shortages are expected [4][6] - **Semiconductors**: Continuous demand for AI computing power and a chip shortage in the automotive sector are driving a super cycle in storage [4][6] Economic Indicators - The report provides detailed indicators for the identified sectors, showing positive trends in various metrics such as retail sales, average prices, and investment levels [6][10][22]

Strategy Logic - The report introduces the "Shouzheng Chuq" investment sentiment indicator, which aims to identify potential investment opportunities in the A-share market by analyzing industry rotation phenomena [1][5] - The strategy combines three main dimensions: investment sentiment, volume-price indicators, and analyst expectations, resulting in 12 detailed industry rotation indicators [1][5] - The investment sentiment indicator utilizes market data and alternative data to create positive and negative screening factors, capturing market momentum and sentiment [5][6] Strategy Performance - In November, the overall industry benchmark return was -0.95%, while the "Shouzheng Chuq" sentiment indicator long portfolio returned -1.24% [2][6] - The combined "Expectation Resonance" model long portfolio achieved a return of 0.98%, resulting in an excess return of 1.93% [2][6] - Year-to-date, the "Shouzheng Chuq" sentiment indicator long portfolio has shown robust performance with a return of 30.29% and an excess return of 8.05% [2][12] Latest Recommendations - The top recommended industries based on the latest data include non-bank financials, automotive, food and beverage, home appliances, transportation, and banking according to the "Shouzheng Chuq" model [3][21] - The "Expectation Resonance" model ranks non-bank financials, banking, home appliances, transportation, automotive, and electronics as the leading industries [3][21] - Detailed scores for recommended industries and corresponding ETFs are provided, indicating strong performance in non-bank financials and home appliances [21][22]

Core Viewpoint - Industry profit forecasting has a positive effect on stock price performance, with long-term returns decomposed into dividend yield, profit growth rate, and price-earnings ratio changes [3][9] Group 1: Industry Profit Forecasting - Profit growth rate is the core driver of stock value growth and is more predictable than price-earnings ratio changes [3][9] - Forecasting profit growth can enhance the performance of industry portfolios, with a hypothetical high-growth portfolio outperforming equal-weighted and low-growth portfolios [3][9] - The industry prosperity model reflects future industry profit status through demand and supply indicators, providing support for stock price return predictions [3][11] Group 2: LLM Empowerment in Model Construction - LLM improves the efficiency of constructing industry prosperity models by enhancing qualitative analysis and indicator selection [4][5] - A structured process using LLM for qualitative screening and quantitative testing results in a reliable industry prosperity index that predicts profit growth [5][17] - The constructed prosperity index shows predictive capability for future profit growth, with average and median rank correlation coefficients around 0.25 across different industry levels [5][26] Group 3: Application of Industry Prosperity Index - The industry prosperity index has various applications, including industry timing, rotation, stock selection, and risk warning [6][38] - High-prosperity industry portfolios demonstrate superior long-term performance compared to equal-weighted portfolios, with annualized excess returns of 2.4%, 2.9%, and 2.8% for different industry levels [6][7] - Sensitivity tests indicate that high-prosperity portfolios maintain stable excess returns over time, outperforming low-prosperity and equal-weighted portfolios [50][43]

Group 1 - The article recommends several high-quality original public accounts in the fund investment field, emphasizing their valuable content and the investment methods and opportunities learned from them [1][2] - The accounts mentioned include "复来指数投资," which focuses on index fund investment and offers practical strategies such as intelligent investment strategies and industry rotation strategies [3] - "阡陌说" is highlighted for its data analysis and ability to discover lesser-known but excellent fund managers, providing clear and detailed articles [4] Group 2 - "投资闲记" is noted for its deep insights into value investing and index investment, sharing unique market perspectives and historical patterns [4] - "小鱼量化" presents a diversified investment system suitable for ordinary investors, focusing on low-cost, high-dividend, and convertible bond investments [5] - "懒人养基" promotes a long-term, steady, and value investment approach, encouraging research before buying and minimal management afterward [6]