报告导读： 风格轮动模型方面， Q3 模型均预测准确； Q4 模型发出小盘、成长信号。行 业轮动模型方面， 9 月，复合因子策略持续获得了正超额。 10 月，单因子策略、复合因 子策略推荐配置的多头行业均涵盖计算机、通信、电子行业。 风格轮动模型方面， 2025Q3 ，中证 1000 相对沪深 300 的超额为 1.27% ，国证成长相对国证价值的超额为 30.27% ，小盘、成长风格占优，两模型均 预测正确。 Q4 ，风格轮动模型持续发出小盘、成长信号。 行业轮动模型方面 ， 复合因子策略模型在 9 月仍获得了正超额，月收益率为 3.33% ，相对基 准的超额为 2.43% 。 9 月，单因子策略、复合因子策略推荐配置的多头行业均涵盖计算机、通信、电子行业。 大小盘风格轮动 Q4 配置信号。 根据 2025 年 09 月 30 日的最新数据， 2025Q4 ，双驱轮动策略得出的综合分数为 -1 ，预测信号为小盘。 本订阅号所载内容仅面向国泰海通证券研究服务签约客户。因本资料暂时无法设置访问限制，根据《证 券期货投资者适当性管理办法》的要求，若您并非国泰海通证券研究服务签约客户，为保证服务质量、 控制投资风险 ...

Group 1 - The core viewpoint is that the non-bank financial sector is expected to outperform due to rising market trading volumes, with a focus on undervalued leading brokerage firms [1] - The industry rotation model indicates that non-bank financials are included in the long position for October, reflecting improved industry momentum expectations [1] - Leading brokerages may drive industry momentum due to their advantages in transaction amounts, as the sector benefits from increased market activity and low valuation attributes [1] Group 2 - The securities sector is characterized by strong beta attributes, with its performance closely tied to capital market conditions, which are currently favorable due to heightened market risk appetite and liquidity [1] - The securities ETF (512880) is recommended for investment opportunities, especially as it surpasses a scale of 54 billion and continues to lead in liquidity among peers [1][2]

Group 1 - The core viewpoint of the article indicates that the market is favoring small-cap and growth styles, with the style rotation model for Q3 2025 confirming this trend [1][2] - In August, the small-cap stocks outperformed large-cap stocks with a monthly excess return of 1.34%, while growth stocks outperformed value stocks with a monthly excess return of 12.76% [1][3] - The industry rotation model showed that in August, two industry combinations achieved absolute returns exceeding 12%, with excess returns above 4% [1][3] Group 2 - The dual-driven rotation strategy for Q3 2025 indicated a signal for small-cap stocks based on the latest data as of June 30, 2025, with a composite score of -3 [2] - The dual-driven rotation strategy for Q3 2025 also indicated a signal for growth stocks, with a composite score of -5 [3] - In August, the composite factor strategy achieved an excess return of 4.38%, while the single-factor multi-strategy achieved an excess return of 4.59% [3]

1. Report Industry Investment Rating No relevant content provided. 2. Core Viewpoints of the Report - Active equity fund positions have reached the highest level of the year, with continuous increases in the communication industry position. The market's broad - based indices generally rose last week, with the Shanghai Composite Index breaking through 3700 points. TMT industries performed strongly, while dividend - related industries such as banking and coal were weak. [4][12] - Active equity public funds have been continuously increasing their positions, and the overall position has reached the highest level of the year. Even relatively cautious "fixed - income +" funds have been continuously raising their positions. In terms of style, public funds have focused on the growth sector and shifted towards small - cap stocks. [4][12] - Public funds are optimistic about the communication industry, which has seen the most significant position increase in the past three months. The proportion in the consumer sector has decreased, and the allocation ratio of the food and beverage industry has reached a multi - year low. It is recommended to shift the allocation towards the growth sector. [4][12] 3. Summary According to the Table of Contents 3.1 Last Week's Market Review - **Broad - based Index Performance**: Last week (2025/8/11 - 2025/8/15), A - share broad - based indices generally rose, with the ChiNext Index rising significantly. As of 2025/8/15, the Shanghai Composite Index closed at 3696.77 points, up about 1.70% week - on - week; the Shenzhen Component Index closed at 11634.67 points, up about 4.55%; the ChiNext Index closed at 2534.22 points, up about 8.58%; and the CSI 300 closed at 4202.35 points, up about 2.37%. [13] - **Industry Index Performance**: TMT and non - banking industries performed well last week. The top - performing industries in terms of weekly returns were communication, comprehensive finance, non - bank finance, electronics, and computer, with returns of 7.11%, 7.07%, 6.57%, 6.44%, and 6.31% respectively. The bottom - performing industries included banking, steel, textile and apparel, coal, and construction, with returns of - 3.22%, - 2.00%, - 1.36%, - 0.77%, and - 0.59% respectively. [16] 3.2 Public Funds - **Net Value Performance**: The average net value change of active partial - stock funds last week was 3.47%. Among the 4468 funds, 3990 rose, accounting for 89.30%. The top five funds in terms of net value performance were Yongying Digital Economy Smart Selection Hybrid A, SDIC UBS Jinbao Flexible Allocation Hybrid, SDIC UBS Advanced Manufacturing Hybrid, SDIC UBS New Energy Hybrid A, and SDIC UBS Industry Trend Hybrid A, with weekly net value changes of 18.81%, 17.88%, 17.34%, 17.29%, and 17.01% respectively. [4][18] - **Position Calculation**: As of 2025/8/15, the average position of active equity funds was about 89.14%. Among them, the average position of common stock funds was about 91.41% (up 0.86 pct from the previous week), the average position of partial - stock hybrid funds was about 88.93% (up 1.90 pct), the average position of allocation funds was about 88.23% (up 2.61 pct), and the average position of "fixed - income +" funds was about 23.48%, up 0.43 pct from the previous week. [2][22] - **Style Trends**: Recently, public funds have mainly been allocated to the small - cap growth style. As of 2025/8/15, the positions of active partial - stock funds in large - cap growth, large - cap value, mid - cap growth, mid - cap value, small - cap growth, and small - cap value were 27.52% (up 0.19 pct from the previous week), 9.4% (down 0.69 pct), 9.51% (down 0.37 pct), 5.96% (up 0.3 pct), 43% (up 1.06 pct), and 4.62% (down 0.5 pct) respectively. [3][29] - **Industry Trends**: From the perspective of the weighted average of stock - holding market value, the industries with a significant increase in the allocation ratio of active equity funds last week were communication (about 6.19%, up 0.86 pct from the previous week), non - ferrous metals (about 4.31%, up 0.42 pct), petroleum and petrochemicals (about 1.17%, up 0.33 pct), comprehensive (about 0.52%, up 0.30 pct), and real estate (about 1.03%, up 0.24 pct). The industries with a significant decrease were food and beverage (about 3.96%, down 0.62 pct), electronics (about 15.99%, down 0.54 pct), national defense and military industry (about 5.05%, down 0.52 pct), banking (about 3.57%, down 0.43 pct), and textile and apparel (about 1.09%, down 0.32 pct). [4][32] - **ETF Market Tracking**: Last week (2025/8/11 - 2025/8/15), domestic stock ETFs had a net outflow of about 23.799 billion yuan, cross - border ETFs had a net inflow of about 16.335 billion yuan, bond ETFs had a net inflow of about 12.633 billion yuan, and commodity ETFs had a net outflow of about 1.719 billion yuan. [39] - **Newly Established Funds**: This year, 171 active equity funds have been newly issued, with a total scale of about 68.102 billion yuan, about 130.65% of the same period in 2024; 356 passive equity funds have been newly issued, with a total scale of 184.103 billion yuan, about 320.38% of the same period in 2024. [44] 3.3 Main/Active Capital Flows - **Main Capital Flow**: Last week, the main capital flowed into non - bank and electronics sectors and flowed out of national defense and military industry and machinery sectors. [5][56] - **Active Capital Flow**: The net main - buying amount last week was about - 1016.139 billion yuan. Active capital flowed into non - bank and electronics sectors. The industries with the highest net main - buying amounts were non - bank finance, electronics, computer, communication, and non - ferrous metals; the industries with significant outflows were machinery, national defense and military industry, banking, power and public utilities, and medicine. [5][56]

- The report identifies three main industry models: the industry mainline model, the industry rotation model, and the left-side inventory reversal model [1][6][8] - The industry mainline model uses the Relative Strength Index (RSI) to identify leading industries. The construction process involves calculating the price changes over 20, 40, and 60 trading days, normalizing these rankings, and averaging them to get the final RSI. If an industry shows an RSI greater than 90% by the end of April, it is likely to be a leading industry for the year [2][12][14] - The industry rotation model is based on a framework of prosperity, trend, and congestion. It suggests a balanced allocation with specific weights for different industries, such as 20% for banks, 17% for non-ferrous metals, and 15% for steel. The model has shown strong performance, with an annualized excess return of 14.1% and an IR of 1.54 [2][16][18] - The left-side inventory reversal model focuses on industries that are in a state of distress or have recently rebounded. It aims to capture the reversal in industries with low inventory pressure and high analyst expectations. The model has shown significant returns, with a 2023 absolute return of 13.4% and an excess return of 17.0% [27][28][29] - The industry mainline model's backtest results for 2024 showed that industries like coal, electric utilities, home appliances, banks, oil and petrochemicals, telecommunications, non-ferrous metals, agriculture, and automotive had significant returns when their RSI exceeded 90% [2][12][13] - The industry rotation model's backtest results showed an annualized return of 21.2%, an excess return of 14.1%, an IR of 1.54, and a maximum drawdown of -8.0%. The model's performance in 2023, 2024, and 2025 showed excess returns of 7.3%, 5.7%, and 4.1%, respectively [16][17][21] - The left-side inventory reversal model's backtest results showed an absolute return of 25.9% in 2024 and an excess return of 14.8%. In 2025, the model achieved an absolute return of 13.6% and an excess return of 3.5% [27][28][29] - The industry rotation model's ETF configuration showed an annualized excess return of 15.8% and an IR of 1.8. The model's performance in 2023, 2024, and 2025 showed excess returns of 6.0%, 5.3%, and 8.1%, respectively [21][22][26] - The industry prosperity stock selection model showed an annualized return of 25.8%, an excess return of 20.0%, an IR of 1.7, and a maximum drawdown of -15.4%. The model's performance in 2022, 2023, 2024, and 2025 showed excess returns of 10.2%, 10.4%, 4.6%, and 4.7%, respectively [22][23][24] - The recommended industries for the left-side inventory reversal model include agricultural chemicals, general steel, building decoration, precious metals, optical and optoelectronics, special materials, components, and passenger cars [27][28][29]

【免责声明】本文仅代表作者本人观点，与和讯网无关。和讯网站对文中陈述、观点判断保持中立，不对所包含内容 的准确性、可靠性或完整性提供任何明示或暗示的保证。请读者仅作参考，并请自行承担全部责任。邮箱： news_center@staff.hexun.com 注：如提及个股仅供参考，不代表投资建议。指数/基金短期涨跌幅及历史表现仅供分析参考，不 预示未来表现。市场观点随市场环境变化而变动，不构成任何投资建议或承诺。文中提及指数仅供参 考，不构成任何投资建议，也不构成对基金业绩的预测和保证。如需购买相关基金产品，请选择与风险 等级相匹配的产品。基金有风险，投资需谨慎。 每日经济新闻 （责任编辑：张晓波 ） 开源证券指出，市场交易量持续走高，中报预告超预期，稳定币带来催化，看好低估值龙头券商机 会。自营与两融业务表现稳健，财富管理转型具备差异化与长期潜力。基于行业轮动模型，8月行业组 合中非银金融板块入选，显示其短期配置价值。临近前期高点，建议关注非银、金融科技等领域的走 势。当前阶段，稳定型红利（含非银金融）在大变局下不确定性中枢上升的环境中仍具配置价值。 证券ETF（512880）跟踪的是证券公司指数（39997 ...

Group 1 - The core viewpoint of the article indicates that the style rotation model has been continuously validated, with macroeconomic factors driving large-cap and value signals in Q2 2025. In May, the market favored large-cap and value styles, with large-cap outperforming small-cap by 0.56% and value outperforming growth by 3.40% [1][2]. - In May, the single-factor multi-strategy model showed a monthly return of 3.31%, with an excess return of 0.33% relative to the benchmark [1][2]. - The dual-driven rotation strategy for large-cap and value signals received a composite score of 3, predicting a favorable outlook for large-cap and value styles in Q2 2025 [1][2]. Group 2 - The industry rotation model for May indicated that the single-factor multi-strategy outperformed with an excess return of 0.33%, while the composite factor strategy had an excess return of -0.64% [2]. - For June, the recommended long positions in the single-factor multi-strategy include non-bank financials, electronics, and banks, while the composite factor strategy recommends non-bank financials, pharmaceuticals, building materials, basic chemicals, and steel [2].

Quantitative Models and Construction 1. Model Name: Macro + Volume-Price Dual-Driver Large-Cap and Small-Cap Rotation Strategy - **Model Construction Idea**: This model integrates macroeconomic factors and micro-level volume-price factors to predict the rotation between large-cap and small-cap styles[6][7] - **Model Construction Process**: - The model uses multiple single-factor signals, including PMI seasonal average difference, social financing growth rate, monetary liquidity, US-China interest rate spread, macro adjustment momentum, and style crowding indicators[7] - Each factor is assigned a signal value: 1 for large-cap signals, -1 for small-cap signals, and 0 for no effective signal[7] - The comprehensive score is calculated by summing the signals of all factors. If the score > 0, the portfolio is fully allocated to the CSI 300 Index; if the score < 0, it is fully allocated to the CSI 1000 Index; if the score = 0, the portfolio is equally weighted between the two indices[7] - **Model Evaluation**: The model demonstrates a high backtest win rate of 82.22% as of Q1 2025, indicating strong predictive power[6] 2. Model Name: Macro + Volume-Price Dual-Driver Value-Growth Rotation Strategy - **Model Construction Idea**: This model integrates macroeconomic factors and micro-level volume-price factors to predict the rotation between value and growth styles[12][13] - **Model Construction Process**: - The model uses multiple single-factor signals, including PMI new orders seasonal average difference, PPI-CPI growth rate, 1-year government bond yield, 3-month US bond yield, macro adjustment momentum, style crowding indicators, and market sentiment[13] - Each factor is assigned a signal value: 1 for value signals, -1 for growth signals, and 0 for no effective signal[13] - The comprehensive score is calculated by summing the signals of all factors. If the score > 0, the portfolio is fully allocated to the CSI Value Index; if the score < 0, it is fully allocated to the CSI Growth Index; if the score = 0, the portfolio is equally weighted between the two indices[13] - **Model Evaluation**: The model demonstrates a backtest win rate of 77.78% as of Q1 2025, showcasing its effectiveness in predicting style rotations[12] 3. Model Name: Industry Rotation Model (Single-Factor Multi-Strategy and Composite Factor Strategy) - **Model Construction Idea**: This model evaluates industry rotation using factors from historical fundamentals, expected fundamentals, sentiment, volume-price technicals, and macroeconomics[18][19] - **Model Construction Process**: - Single-factor multi-strategy: Constructs portfolios based on individual factors and evaluates their performance[18] - Composite factor strategy: Combines multiple factors into a composite score to rank industries and construct portfolios[18] - Both strategies select the top 5 industries from the 30 first-level industries in the CITIC classification and construct equal-weighted long portfolios[18] - **Model Evaluation**: The single-factor multi-strategy outperformed the composite factor strategy in May 2025, with higher monthly absolute and excess returns[20] --- Backtest Results of Models 1. Macro + Volume-Price Dual-Driver Large-Cap and Small-Cap Rotation Strategy - **YTD Return**: -2.41%[11] - **Annualized Return**: -5.83%[11] - **Annualized Volatility**: 17.17%[11] - **Maximum Drawdown**: 10.49%[11] - **Sharpe Ratio**: -0.34[11] - **Calmar Ratio**: -0.56[11] 2. Macro + Volume-Price Dual-Driver Value-Growth Rotation Strategy - **YTD Return**: 1.79%[17] - **Annualized Return**: 4.48%[17] - **Annualized Volatility**: 18.06%[17] - **Maximum Drawdown**: 10.36%[17] - **Sharpe Ratio**: 0.25[17] - **Calmar Ratio**: 0.43[17] 3. Industry Rotation Model - **Composite Factor Strategy**: - **Monthly Absolute Return**: 2.43%[20] - **Monthly Excess Return**: -0.64%[20] - **YTD Absolute Return**: 4.81%[20] - **YTD Excess Return**: 3.98%[20] - **Single-Factor Multi-Strategy**: - **Monthly Absolute Return**: 3.31%[20] - **Monthly Excess Return**: 0.33%[20] - **YTD Absolute Return**: 4.56%[20] - **YTD Excess Return**: 3.83%[20]

Investment Rating - The report indicates a positive investment rating for the automotive industry, highlighting it as one of the sectors with significant net inflows of capital [2][9]. Core Insights - The automotive sector has seen a net inflow of 27.05 billion in the past 5 days, making it the top industry for capital inflow [9]. - The report utilizes a model that assesses industries based on six factors: capital, valuation, sentiment, momentum, overbought/oversold conditions, and earnings, with the automotive sector scoring high in these evaluations [13][14]. - The consensus stock selection model identified stocks such as Baiyang Co., Zhongchong Co., and Hunan Silver as top picks based on high-frequency capital flow and price movement similarity [16][17]. Industry Capital Inflow Statistics - In the past 5 days, the automotive industry led with a net inflow of 27.05 billion, followed by home appliances with 8.44 billion and machinery equipment with 5.26 billion [9]. - Over the past 30 days, the automotive sector experienced a net outflow of 446.97 billion, indicating a contrasting trend compared to the recent 5-day performance [10][12]. A-Share Industry Rotation Model - The A-share industry rotation model ranks the automotive sector among the top performers, alongside non-bank financials and communications, based on a composite score derived from the six factors [14][15]. - The automotive sector received a high score in capital and valuation, indicating strong investor interest and favorable market conditions [15]. Consensus Stock Selection - The consensus stock selection model highlighted industries such as feed, precious metals, and animal health II as high-performing sectors, with specific stocks selected based on their capital flow and price movement [16][17].