2025 年 08 月 11 日 申万金工 ETF 组合 202508 相关研究 证券分析师 沈思逸 A0230521070001 shensy@swsresearch.com 邓虎 A0230520070003 denghu@swsresearch.com 研究支持 白皓天 A0230525070001 baiht@swsresearch.com 联系人 沈思逸 (8621)23297818× shensy@swsresearch.com 权 益 量 化 研 究 证 券 研 究 报 告 请务必仔细阅读正文之后的各项信息披露与声明 本研究报告仅通过邮件提供给 中庚基金 使用。1 量 化 策 略 - ⚫ 宏观行业组合：针对所有标记为"行业主题"的 ETF，选择成立时间 1 年以上、当期规模 2 亿以上的产品跟踪的行业主题指数，每个月根据历史数据计算经济、流动性、信用的敏 感性得分，然后根据最新的经济、流动性、信用判断指标调整得分方向后进行加总，最终 得到排名前 6 的行业主题指数，然后取对应规模最大的 ETF 进行等权配置。当前经济转弱、 信用仍较好，选择偏向成长。 ⚫ 宏观+动量行业组合：基于宏观类配置策略主 ...

Quantitative Models and Construction Methods 1. Model Name: Volume Timing Signal - **Model Construction Idea**: The core idea is that "the decline in a shrinking volume market is significantly greater than the rise in a shrinking volume market, so avoiding shrinking volume signals can achieve higher trading odds"[3][22][24] - **Model Construction Process**: 1. Calculate the rolling 60-day average and standard deviation of the turnover and turnover rate of the index or market[23] 2. Standardize the daily turnover data: - If the turnover is within ±2 standard deviations, map the score to -1~+1 - If the turnover exceeds ±2 standard deviations, assign a score of +1/-1 3. Combine the scores of turnover and turnover rate equally[23] 4. Generate signals based on the combined score: - Method 1: Go long if the score > 0, stay out if the score < 0 - Method 2: Use the rolling 5-year or 3-year percentile of the score; go long if above the 50th percentile, stay out if below[23] 5. The report adopts the simpler method of directly judging whether the score is greater than 0[23] - **Model Evaluation**: The model is not a high-win-rate strategy but achieves relatively high odds by avoiding significant market adjustments during shrinking volume periods[24] 2. Model Name: Growth-Value Style Rotation Model - **Model Construction Idea**: The model evaluates the relative attractiveness of growth and value styles based on macroeconomic cycles, valuation differences, and market sentiment[52][54] - **Model Construction Process**: 1. **Fundamentals**: - Growth is favored when the profit cycle slope is steep, interest rate levels are low, and the credit cycle is rising - Value is favored under the opposite conditions[52] 2. **Valuation**: - Growth is favored when the PE and PB valuation differences between growth and value are in the lower percentiles and mean-reverting upward[52] 3. **Sentiment**: - Growth is favored when turnover and volatility differences between growth and value are low[52] 4. Combine signals from fundamentals, valuation, and sentiment to determine the allocation between growth and value[52] - **Model Evaluation**: The model has shown significant improvement over the benchmark in terms of annualized returns and risk-adjusted performance[53][55] 3. Model Name: Small-Cap vs. Large-Cap Style Rotation Model - **Model Construction Idea**: The model evaluates the relative attractiveness of small-cap and large-cap styles based on macroeconomic cycles, valuation differences, and market sentiment[56][58] - **Model Construction Process**: 1. **Fundamentals**: - Small-cap is favored when the profit cycle slope is steep, interest rate levels are low, and the credit cycle is rising - Large-cap is favored under the opposite conditions[56] 2. **Valuation**: - Large-cap is favored when the PE and PB valuation differences between small-cap and large-cap are in the higher percentiles and mean-reverting downward[56] 3. **Sentiment**: - Small-cap is favored when turnover differences are high - Large-cap is favored when volatility differences are mean-reverting downward[56] 4. Combine signals from fundamentals, valuation, and sentiment to determine the allocation between small-cap and large-cap[56] - **Model Evaluation**: The model has shown significant improvement over the benchmark in terms of annualized returns and risk-adjusted performance[57][60] 4. Model Name: Four-Style Rotation Model - **Model Construction Idea**: Combines the conclusions of the growth-value and small-cap-large-cap rotation models to allocate across four styles: small-cap growth, small-cap value, large-cap growth, and large-cap value[61][63] - **Model Construction Process**: 1. Use the growth-value model to determine the allocation between growth and value 2. Use the small-cap-large-cap model to determine the allocation between small-cap and large-cap 3. Combine the two models to allocate across the four styles[61] - **Model Evaluation**: The model has shown significant improvement over the benchmark in terms of annualized returns and risk-adjusted performance, with consistent outperformance in most years[61][63] --- Model Backtest Results 1. Volume Timing Signal - **Win Rate**: 47.34%[24] - **Odds**: 1.75[24] - **Annualized Excess Return**: 6.87% (based on next-day open price)[34] - **Maximum Drawdown**: 31.40%[34] - **Return-to-Drawdown Ratio**: 0.4634[34] 2. Growth-Value Style Rotation Model - **Annualized Return**: 11.76%[55] - **Annualized Volatility**: 20.77%[55] - **Maximum Drawdown**: 43.07%[55] - **Sharpe Ratio**: 0.5438[55] - **Return-to-Drawdown Ratio**: 0.2731[55] 3. Small-Cap vs. Large-Cap Style Rotation Model - **Annualized Return**: 12.45%[60] - **Annualized Volatility**: 22.65%[60] - **Maximum Drawdown**: 50.65%[60] - **Sharpe Ratio**: 0.5441[60] - **Return-to-Drawdown Ratio**: 0.2459[60] 4. Four-Style Rotation Model - **Annualized Return**: 13.37%[63] - **Annualized Volatility**: 21.51%[63] - **Maximum Drawdown**: 47.91%[63] - **Sharpe Ratio**: 0.5988[63] - **Return-to-Drawdown Ratio**: 0.2790[63]

证券研究报告·金融工程·金工定期报告 金工定期报告 20250801 从微观出发的风格轮动月度跟踪 202508 2025 年 08 月 01 日 [Table_Tag] [Table_Summary] 报告要点 证券分析师 高子剑 执业证书：S0600518010001 021-60199793 gaozj@dwzq.com.cn 证券分析师 凌志杰 执业证书：S0600525040007 lingzhj@dwzq.com.cn 相关研究 《从微观出发的风格轮动月度 跟踪 202507》 2025-07-01 ◼ 2025 年 7 月风格轮动模型收益率为 2.52%。 ◼ 2025 年 8 月最新风格择时方向为：低估值、大市值、反转、低波。 ◼ 2025 年 8 月风格择时最新持仓为： 表1：2025 年 8 月风格择时最新持仓 | 指数代码 | 指数名称 | ETF 代码 | ETF 名称 | | --- | --- | --- | --- | | 399378.SZ | ESG 300 | 159653.SZ | ESG300ETF | | 930839.CSI | 港股通高息精选 | 159691.S ...

Quantitative Models and Construction Methods 1. Model Name: Short-term Timing Model - **Model Construction Idea**: The model aims to provide short-term market timing signals based on various market indicators. - **Model Construction Process**: - **Fundamental Indicators**: - Manufacturing PMI: Current value is 49.70, at the 44.92% percentile over the past 5 years, giving a neutral signal[17] - RMB medium and long-term loan balance growth rate: Current value is 6.78%, at the 0.00% percentile over the past 5 years, giving a cautious signal[17] - M1 growth rate: Current value is 2.30%, at the 77.97% percentile over the past 5 years, giving an optimistic signal[17] - **Valuation Indicators**: - PE median: Current value is 40.16, at the 92.80% percentile over the past 5 years, giving a neutral signal[18] - PB median: Current value is 2.68, at the 71.05% percentile over the past 5 years, giving a neutral signal[18] - **Sentiment Indicators**: - Beta dispersion: Current value is -0.59%, at the 40.68% percentile over the past 5 years, giving a neutral signal[20] - Volume sentiment score: Current value is 0.30, at the 72.70% percentile over the past 5 years, giving an optimistic signal[20] - Volatility: Current value is 11.57% (annualized), at the 12.99% percentile over the past 5 years, giving a neutral signal[20] - **Liquidity Indicators**: - Monetary rate indicator: Current value is -0.10, at the 33.90% percentile over the past 5 years, giving an optimistic signal[20] - Exchange rate expectation indicator: Current value is -0.09%, at the 40.68% percentile over the past 5 years, giving a neutral signal[20] - Average new financing amount over 5 days: Current value is 23.20 billion, at the 80.81% percentile over the past 5 years, giving a neutral signal[20] - **Model Evaluation**: The model provides a comprehensive view of short-term market conditions by integrating fundamental, valuation, sentiment, and liquidity indicators. 2. Model Name: Growth-Value Style Rotation Model - **Model Construction Idea**: The model aims to rotate between growth and value styles based on economic cycles and market conditions. - **Model Construction Process**: - **Fundamental Indicators**: - Profit cycle slope: High, favoring growth[32] - Interest rate cycle level: High, favoring value[32] - Credit cycle trend: Weak, favoring value[32] - **Valuation Indicators**: - PE valuation difference: 5-year percentile is 15.19%, favoring growth[32] - PB valuation difference: 5-year percentile is 34.08%, favoring growth[32] - **Sentiment Indicators**: - Turnover difference: 5-year percentile is 21.01%, favoring value[32] - Volatility difference: 5-year percentile is 20.58%, favoring balanced allocation[32] - **Model Evaluation**: The model effectively captures the rotation between growth and value styles by considering fundamental, valuation, and sentiment factors. 3. Model Name: Small-Cap vs. Large-Cap Style Rotation Model - **Model Construction Idea**: The model aims to rotate between small-cap and large-cap styles based on economic cycles and market conditions. - **Model Construction Process**: - **Fundamental Indicators**: - Profit cycle slope: High, favoring small-cap[36] - Interest rate cycle level: High, favoring large-cap[36] - Credit cycle trend: Weak, favoring large-cap[36] - **Valuation Indicators**: - PE valuation difference: 5-year percentile is 80.60%, favoring large-cap[36] - PB valuation difference: 5-year percentile is 99.59%, favoring large-cap[36] - **Sentiment Indicators**: - Turnover difference: 5-year percentile is 54.26%, neutral[36] - Volatility difference: 5-year percentile is 83.71%, favoring large-cap[36] - **Model Evaluation**: The model provides a balanced approach to rotating between small-cap and large-cap styles by integrating fundamental, valuation, and sentiment indicators. 4. Model Name: Four-Style Rotation Model - **Model Construction Idea**: The model combines the growth-value and small-cap vs. large-cap rotation models to provide a comprehensive allocation across four styles. - **Model Construction Process**: - **Allocation Recommendation**: - Small-cap growth: 12.5%[41] - Small-cap value: 37.5%[41] - Large-cap growth: 12.5%[41] - Large-cap value: 37.5%[41] - **Model Evaluation**: The model offers a diversified approach to style rotation, leveraging insights from both growth-value and small-cap vs. large-cap models. Model Backtest Results Short-term Timing Model - Annualized Return: 16.58%[26] - Annualized Volatility: 14.57%[26] - Maximum Drawdown: 27.70%[26] - Sharpe Ratio: 0.9889[26] - Monthly Win Rate: 69.74%[26] - Quarterly Win Rate: 69.23%[26] - Annual Win Rate: 85.71%[26] Growth-Value Style Rotation Model - Annualized Return: 11.67%[35] - Annualized Volatility: 20.84%[35] - Maximum Drawdown: 43.07%[35] - Sharpe Ratio: 0.5387[35] - Monthly Win Rate: 58.28%[35] - Quarterly Win Rate: 60.78%[35] Small-Cap vs. Large-Cap Style Rotation Model - Annualized Return: 12.21%[40] - Annualized Volatility: 22.73%[40] - Maximum Drawdown: 50.65%[40] - Sharpe Ratio: 0.5336[40] - Monthly Win Rate: 60.93%[40] - Quarterly Win Rate: 58.82%[40] Four-Style Rotation Model - Annualized Return: 13.17%[43] - Annualized Volatility: 21.58%[43] - Maximum Drawdown: 47.91%[43] - Sharpe Ratio: 0.5895[43] - Monthly Win Rate: 59.60%[43] - Quarterly Win Rate: 62.75%[43] - Annual Win Rate: 69.23%[43]

- Model Name: Style Rotation Model; Model Construction Idea: The model is built from basic style factors such as valuation, market capitalization, volatility, and momentum, gradually constructing a style timing and scoring system[1][6] - Model Construction Process: 1. Construct 640 micro features based on 80 underlying micro indicators[1][6] 2. Use common indices as style stock pools instead of absolute proportion division of style factors to construct new style returns as labels[1][6] 3. Use a rolling training random forest model to avoid overfitting risks, select features, and obtain style recommendations[1][6] 4. Construct a style rotation framework from style timing to style scoring and from style scoring to actual investment[1][6] - Model Evaluation: The model effectively avoids overfitting risks and provides a comprehensive framework for style rotation from timing to scoring and actual investment[1][6] Model Backtest Results - Style Rotation Model, Annualized Return: 21.63%, Annualized Volatility: 24.09%, IR: 0.90, Monthly Win Rate: 59.12%, Maximum Drawdown: 28.33%[7][8] - Market Benchmark, Annualized Return: 7.21%, Annualized Volatility: 21.56%, IR: 0.33, Monthly Win Rate: 56.20%, Maximum Drawdown: 43.34%[8] - Excess Return, Annualized Return: 13.35%, Annualized Volatility: 11.43%, IR: 1.17, Monthly Win Rate: 66.42%, Maximum Drawdown: 10.28%[7][8] Monthly Performance - June 2025, Style Rotation Model Return: 1.28%, Excess Return: -2.51%[13] - July 2025, Latest Style Timing Directions: Low Valuation, Small Market Cap, Reversal, Low Volatility[13] - July 2025, Latest Holding Index: CSI Dividend Index[13]

行业轮动 6 月观点。 单 因子多策略推荐配置的多头行业为非银行金融、电子、银行。复合因子策略推荐 的多头行业为非银行金融、医药、建材、基础化工、钢铁。 风险提示： 模型失效风险、因子失效风险、海外市场波动风险。 报告导读： 风格轮动模型层面， 2025Q2 ，宏观量价双驱大小盘、价值成长模型分别发 出大盘、价值信号。 5 月，风格轮动模型预判获得持续印证。行业轮动模型层面， 5 月， 单因子多策略模型表现较优，月收益率为 3.31% ，相对基准的超额为 0.33% 。 风格层面， 2025Q2 ，大小盘双驱轮动策略发出大盘信号 ,5 月，大盘占优，相对小盘的月超额为 0.56% 。 2025Q2 ，价值成长轮动策略发出价值信号 ;5 月，价值占优，相对成长的月超额为 3.40% 。 风格轮动模型预判获得持续印证，市场偏向大盘、价值风格。 行业轮动模型层面， 5 月单因子多策略模 型表现较优，月收益率为 3.31% ，相对基准的超额为 0.33% 。 6 月，单因子策略、复合因子策略推荐 配置的多头行业均涵盖非银金融行业。 大小盘风格轮动 Q2 配置信号。 根据 2025 年 03 月 31 日的最新数据， ...

金融工程/[Table_Date] 2025.06.05 | 风格及行业观点月报（2025.06） | [Table_Authors] | 郑雅斌(分析师) | | --- | --- | --- | | | | 021-38676666 | | 风格轮动模型持续得到验证，行业轮动两模型均推荐配置非银 | 登记编号 | S0880525040105 | | 本报告导读： | | 卓洢萱(分析师) | | 风格轮动模型层面，2025Q2，宏观量价双驱大小盘、价值成长模型分别发出大盘、 | | 021-38676666 | | 价值信号。5 月，风格轮动模型预判获得持续印证。行业轮动模型层面，5 月，单因 子多策略模型表现较优，月收益率为 3.31%，相对基准的超额为 0.33%。 | 登记编号 | S0880525040128 | 投资要点： 基 本 面 量 化 月 报 证 券 研 究 报 告 请务必阅读正文之后的免责条款部分 金 融 工 程 6947146 [Table_Summary] 风格层面，2025Q2，大小盘双驱轮动策略发出大盘信号,5 月，大盘 占优，相对小盘的月超额为 0.56%。2025Q2， ...

Quantitative Models and Construction Methods - **Model Name**: Style Rotation Model **Model Construction Idea**: The model is built from micro-level stock factors, focusing on valuation, market capitalization, volatility, and momentum. It integrates a style timing and scoring system to construct a monthly frequency style rotation framework[1][6] **Model Construction Process**: 1. Start with 80 base micro-level factors selected based on the Dongwu multi-factor system[6] 2. Generate 640 micro-level features from these base factors[6] 3. Replace the absolute proportion division of style factors with commonly used indices as style stock pools to create new style returns as labels[6] 4. Use a rolling training random forest model to avoid overfitting risks, optimize feature selection, and derive style recommendations[6] 5. Construct a framework that transitions from style timing to style scoring and finally to actual investment decisions[6] **Model Evaluation**: The model effectively avoids overfitting risks and provides a comprehensive framework for style rotation[6] Model Backtesting Results - **Style Rotation Model**: - Annualized Return: 21.56% - Annualized Volatility: 24.17% - IR: 0.89 - Monthly Win Rate: 58.82% - Maximum Drawdown: 28.33%[7][8] - Excess Performance (Hedged Against Benchmark): - Annualized Return: 13.45% - Annualized Volatility: 11.47% - IR: 1.17 - Monthly Win Rate: 66.18% - Maximum Drawdown: 10.28%[7][8] Quantitative Factors and Construction Methods - **Factor Name**: Valuation, Market Capitalization, Volatility, Momentum **Factor Construction Idea**: These are foundational style factors used to construct the style rotation model. They are further refined into micro-level features and integrated into the model's scoring and timing system[1][6] **Factor Construction Process**: 1. Valuation: Derived from traditional valuation metrics such as P/E, P/B, and dividend yield[6] 2. Market Capitalization: Categorized into large-cap and small-cap stocks based on market size[6] 3. Volatility: Measured using historical price fluctuations[6] 4. Momentum: Calculated based on past price trends and returns[6] Factor Backtesting Results - **Factor Performance (2025, Multi-Factor Timing Results)**: - Valuation: -2.00% - Market Capitalization: 4.00% - Volatility: -6.00% - Momentum: -8.00%[10][17] - **Factor Performance (2025, Actual Factor Returns)**: - Valuation: 2.00% - Market Capitalization: 6.00% - Volatility: -4.00% - Momentum: -8.00%[10][11] Additional Notes - **Latest Style Timing Directions (May 2025)**: Value, Large-Cap, Reversal, Low Volatility[14] - **Latest Holding Index (May 2025)**: CSI Dividend Index[15]