Investment Rating - The industry rating is "Neutral," indicating that the overall return is expected to be between -5% and 5% relative to the CSI 300 index over the next six months [12]. Core Insights - The model used for evaluating the defense and military industry assumes that price trends exhibit good local continuity, with reversals occurring less frequently than trend continuations. The model aims to identify trends based on price movements and volatility [4][5]. - The evaluation period for the model is from March 7, 2023, to March 18, 2025, with a focus on the Shenwan Level 1 Defense and Military Industry Index [4]. - The model's annualized return is -0.37%, with a volatility of 29.80% and a maximum drawdown of 29.79%. The total return during the evaluation period is -3.81% [4][5]. Summary by Sections Model Overview - The model is designed to track price movements and identify trends based on historical data, with specific algorithms to determine when a price has deviated from its previous range [4]. Results Assessment - The model experienced a decline in net value during specific periods, indicating a long-term drawdown and an inability to achieve favorable cumulative returns. The model is deemed unsuitable for direct application to the Shenwan Level 1 Defense and Military Industry Index due to negative returns [5]. Performance Metrics - The model's performance metrics include an annualized return of -0.37%, a volatility of 29.80%, a Sharpe ratio of -0.01, and a maximum drawdown of 29.79% [4].

金 金融工程点评 [Table_Message]2025-05-12 建筑材料指数趋势跟踪模型效果点评 [Table_Author] 证券分析师：刘晓锋 电话：13401163428 E-MAIL：liuxf@tpyzq.com 执业资格证书编码：S1190522090001 研究助理：孙弋轩 电话：18910596766 E-MAIL：sunyixuan@tpyzq.com 一般证券业务登记编码：S1190123080008 模型概述 结果评估： 区间年化收益：1.98% 波动率（年化）：24.36% 夏普率：0.08 最大回撤：25.11% 指数期间总回报率：-29.59% 太 平 洋 证 券 股 份 有 限 公 司 证 券 研 究 报 [Table_Title] [Table_Summary] 融 工 程 点 评 告 ◼ 设计原理：模型假定标的价格走势具有很好的局部延续性，标的价格永远处 于某一趋势中，出现反转行情的持续时间明显小于趋势延续的时间，若出现 窄幅盘整的情况，亦假设其延续之前的趋势。当处于大级别的趋势之中时， 给定较短时间的观察窗口，走势将延续观察窗口内的局部趋势。而当趋势发 生反转时，在观 ...

Quantitative Factors and Construction Methods Factor Name: Beta - Construction Idea: Measures the sensitivity of a stock's returns to market returns[14] - Construction Process: Calculated using the weighted regression of individual stock returns against market returns over the last 490 trading days[14] - Evaluation: Beta factor performed well in the recent week[8][10] Factor Name: Turnover Rate and Average Price Correlation (1 Month) - Construction Idea: Measures the correlation between turnover rate and average price over the past month[13] - Construction Process: Calculated as the correlation coefficient between turnover rate and average price over the past 20 trading days[13] - Evaluation: This factor showed good performance in the recent week and month[8][10] Factor Name: Turnover Rate Volatility (1 Month) - Construction Idea: Measures the volatility of turnover rate over the past month[13] - Construction Process: Calculated as the standard deviation of turnover rate over the past 20 trading days[13] - Evaluation: This factor performed well in the recent month and year[8][10] Factor Name: Reversal (1 Month) - Construction Idea: Measures the cumulative returns over the past month[13] - Construction Process: Calculated as the cumulative returns over the past 20 trading days[13] - Evaluation: This factor showed good performance in the recent week and month[8][10] Factor Name: Specificity (1 Month) - Construction Idea: Measures the specificity of stock returns relative to the Fama-French three-factor model[13] - Construction Process: Calculated as 1 minus the R-squared value from the regression of daily returns against the Fama-French three factors over the past 20 trading days[13] - Evaluation: This factor performed well in the recent year[8][10] Factor Name: Residual Volatility (Fama-French Three-Factor Model, 1 Month) - Construction Idea: Measures the residual volatility of stock returns relative to the Fama-French three-factor model[13] - Construction Process: Calculated as the standard deviation of residuals from the regression of daily returns against the Fama-French three factors over the past 20 trading days[13] - Evaluation: This factor showed good performance in the recent year[8][10] Factor Name: Excess Return Volatility (1 Month) - Construction Idea: Measures the volatility of excess returns over the past month[13] - Construction Process: Calculated as the standard deviation of excess returns over the past 20 trading days[13] - Evaluation: This factor performed well in the recent year[8][10] Factor Name: Small Market Capitalization - Construction Idea: Measures the logarithm of market capitalization[13] - Construction Process: Calculated as the logarithm of market capitalization[13] - Evaluation: This factor showed good performance in the recent week and year[8][10] Factor Backtesting Results Information Coefficient (IC) Performance - Beta: Recent week IC: 13.69%, Recent month IC: 0.85%, Recent year IC: 1.73%, Historical IC: 0.44%[9] - Turnover Rate and Average Price Correlation (1 Month): Recent week IC: 11.30%, Recent month IC: 7.07%, Recent year IC: 2.49%, Historical IC: 1.70%[9] - Turnover Rate Volatility (1 Month): Recent week IC: 6.15%, Recent month IC: 5.29%, Recent year IC: 2.99%, Historical IC: 2.51%[9] - Reversal (1 Month): Recent week IC: 11.08%, Recent month IC: 4.52%, Recent year IC: 2.87%, Historical IC: 2.15%[9] - Specificity (1 Month): Recent week IC: 11.05%, Recent month IC: 3.76%, Recent year IC: 3.63%, Historical IC: 2.41%[9] - Residual Volatility (Fama-French Three-Factor Model, 1 Month): Recent week IC: 5.42%, Recent month IC: 3.27%, Recent year IC: 3.62%, Historical IC: 2.48%[9] - Excess Return Volatility (1 Month): Recent week IC: -0.20%, Recent month IC: 1.88%, Recent year IC: 3.29%, Historical IC: 2.18%[9] - Small Market Capitalization: Recent week IC: 7.12%, Recent month IC: 2.70%, Recent year IC: 2.03%, Historical IC: 1.89%[9] Long Portfolio Performance - Beta: Recent week excess return: 1.08%, Recent month excess return: -0.75%, Recent year excess return: 6.46%, Historical cumulative excess return: -5.34%[11] - Turnover Rate and Average Price Correlation (1 Month): Recent week excess return: 1.08%, Recent month excess return: 2.92%, Recent year excess return: 2.72%, Historical cumulative excess return: 16.63%[11] - Turnover Rate Volatility (1 Month): Recent week excess return: 0.93%, Recent month excess return: 1.96%, Recent year excess return: 10.68%, Historical cumulative excess return: 32.01%[11] - Reversal (1 Month): Recent week excess return: 0.37%, Recent month excess return: 0.22%, Recent year excess return: 0.75%, Historical cumulative excess return: -1.18%[11] - Specificity (1 Month): Recent week excess return: 0.67%, Recent month excess return: 0.67%, Recent year excess return: 10.17%, Historical cumulative excess return: 16.91%[11] - Residual Volatility (Fama-French Three-Factor Model, 1 Month): Recent week excess return: 0.34%, Recent month excess return: 0.82%, Recent year excess return: 8.10%, Historical cumulative excess return: 18.57%[11] - Excess Return Volatility (1 Month): Recent week excess return: 0.02%, Recent month excess return: 0.09%, Recent year excess return: 7.20%, Historical cumulative excess return: 10.83%[11] - Small Market Capitalization: Recent week excess return: 0.95%, Recent month excess return: 0.12%, Recent year excess return: 10.84%, Historical cumulative excess return: 59.20%[11]

Group 1 - The core viewpoint of the report is that the model assumes a cyclical pattern of price deviation and regression relative to a reference index, with a defined limit on the degree of deviation, allowing for strategic buying when prices approach this limit [4][5]. - The model's design principle involves statistical analysis of historical data to identify reasonable thresholds for price deviations, which can signal buying opportunities when prices fall below these thresholds [4][5]. - The model tracks the performance of the Shenwan Level 1 Defense Industry Index relative to the CSI 300 Index over a defined period from January 4, 2010, to March 18, 2025 [4][5]. Group 2 - The total return of the interval strategy is reported at 159.57%, significantly outperforming the buy-and-hold return of 42.53%, resulting in an excess return of 117.05% [4]. - The maximum drawdown recorded is 50.87%, with the longest drawdown period lasting 2108 trading days, indicating substantial volatility in the strategy's performance [4]. - The model's effectiveness is questioned due to the observed price movements falling outside the historical sample range, suggesting that the strategy may not provide reliable guidance for future investments in the defense industry index [5].

Group 1: ETF Rotation Strategy Tracking - The ETF rotation strategy, constructed using GBDT+NN machine learning factors, has shown excellent performance in out-of-sample testing, with an IC value of 20.91% and a long position excess return of 0.61% last week [2][12][13] - The strategy's annualized excess return is 11.91%, with a maximum drawdown of 17.31% and an information ratio of 0.68, indicating strong recent performance [2][18][16] - The strategy has recorded an excess return of 0.88% last week, 1.44% for the month, and 0.15% year-to-date, reflecting its recent success [2][18] Group 2: High-Frequency Factor Overview - Various high-frequency factors have demonstrated strong performance, with the price range factor achieving a long position excess return of 1.01% last week and 5.84% year-to-date [3][22] - The volume-price divergence factor has shown a long position excess return of 10.13% this year, while the regret avoidance factor has underperformed with a return of -0.30% [3][22] - The overall performance of high-frequency factors has been commendable, with the price range factor and volume-price divergence factor leading in returns [3][22] Group 3: High-Frequency Factor Performance Tracking - The price range factor measures the activity level of stocks within different price ranges, indicating investor expectations for future price movements, and has shown stable performance this year [4][25] - The volume-price divergence factor assesses the correlation between stock price and trading volume, with lower correlation suggesting higher future price increases, although its performance has been inconsistent in recent years [4][25] - The regret avoidance factor reflects investor behavior, showing stable excess returns, indicating that regret avoidance sentiment significantly impacts expected stock returns [4][25] Group 4: Combined Strategies Performance - The high-frequency "gold" combination strategy has an annualized excess return of 10.68% and a maximum drawdown of 6.04%, with recent excess returns of 0.14% last week and 5.98% year-to-date [5][54] - The high-frequency and fundamental resonance combination strategy has shown an annualized excess return of 14.98% and a maximum drawdown of 4.52%, with recent excess returns of 0.28% last week and 4.99% year-to-date [5][60]

Quantitative Factors and Construction Methods - **Factor Name**: bp **Construction Idea**: Measures valuation by comparing net assets to market value **Construction Process**: Calculated as: $ bp = \frac{\text{Current Net Assets}}{\text{Current Total Market Value}} $ [13] **Evaluation**: Commonly used valuation factor, straightforward and widely applicable [13] - **Factor Name**: bp three-year percentile **Construction Idea**: Tracks the relative valuation of a stock over the past three years **Construction Process**: Represents the percentile rank of the current bp value within the last three years [13] **Evaluation**: Useful for identifying stocks with consistent valuation trends [13] - **Factor Name**: Quarterly ep **Construction Idea**: Measures profitability relative to net assets **Construction Process**: Calculated as: $ \text{Quarterly ep} = \frac{\text{Quarterly Net Profit}}{\text{Net Assets}} $ [13] **Evaluation**: Reflects short-term profitability, sensitive to quarterly fluctuations [13] - **Factor Name**: Quarterly ep one-year percentile **Construction Idea**: Tracks the relative profitability of a stock over the past year **Construction Process**: Represents the percentile rank of the current quarterly ep value within the last year [13] **Evaluation**: Helps identify stocks with improving or declining profitability trends [13] - **Factor Name**: Quarterly sp **Construction Idea**: Measures revenue generation relative to net assets **Construction Process**: Calculated as: $ \text{Quarterly sp} = \frac{\text{Quarterly Revenue}}{\text{Net Assets}} $ [13] **Evaluation**: Indicates operational efficiency, useful for growth-oriented analysis [13] - **Factor Name**: Quarterly sp one-year percentile **Construction Idea**: Tracks the relative operational efficiency of a stock over the past year **Construction Process**: Represents the percentile rank of the current quarterly sp value within the last year [13] **Evaluation**: Highlights trends in revenue generation efficiency [13] - **Factor Name**: Quarterly asset turnover **Construction Idea**: Measures revenue generation relative to total assets **Construction Process**: Calculated as: $ \text{Quarterly Asset Turnover} = \frac{\text{Quarterly Revenue}}{\text{Total Assets}} $ [13] **Evaluation**: Reflects operational efficiency, sensitive to asset-heavy industries [13] - **Factor Name**: Quarterly gross margin **Construction Idea**: Measures profitability relative to sales revenue **Construction Process**: Calculated as: $ \text{Quarterly Gross Margin} = \frac{\text{Quarterly Gross Profit}}{\text{Quarterly Sales Revenue}} $ [13] **Evaluation**: Indicates pricing power and cost control [13] - **Factor Name**: Quarterly roa **Construction Idea**: Measures profitability relative to total assets **Construction Process**: Calculated as: $ \text{Quarterly ROA} = \frac{\text{Quarterly Net Profit}}{\text{Total Assets}} $ [13] **Evaluation**: Reflects overall asset efficiency [13] - **Factor Name**: Quarterly roe **Construction Idea**: Measures profitability relative to net assets **Construction Process**: Calculated as: $ \text{Quarterly ROE} = \frac{\text{Quarterly Net Profit}}{\text{Net Assets}} $ [13] **Evaluation**: Commonly used profitability metric, sensitive to leverage [13] - **Factor Name**: Standardized unexpected earnings **Construction Idea**: Measures deviation of current earnings from historical growth trends **Construction Process**: Calculated as: $ \text{Standardized Unexpected Earnings} = \frac{\text{Current Quarterly Net Profit} - (\text{Last Year Same Quarter Net Profit} + \text{Average Growth of Last 8 Quarters})}{\text{Standard Deviation of Growth in Last 8 Quarters}} $ [13] **Evaluation**: Useful for identifying earnings surprises [13] - **Factor Name**: Standardized unexpected revenue **Construction Idea**: Measures deviation of current revenue from historical growth trends **Construction Process**: Calculated as: $ \text{Standardized Unexpected Revenue} = \frac{\text{Current Quarterly Revenue} - (\text{Last Year Same Quarter Revenue} + \text{Average Growth of Last 8 Quarters})}{\text{Standard Deviation of Growth in Last 8 Quarters}} $ [13] **Evaluation**: Highlights revenue surprises [13] - **Factor Name**: Dividend yield **Construction Idea**: Measures dividend payout relative to market value **Construction Process**: Calculated as: $ \text{Dividend Yield} = \frac{\text{Annual Dividend}}{\text{Current Market Value}} $ [13] **Evaluation**: Commonly used for income-focused strategies [13] - **Factor Name**: 1-month turnover rate volatility **Construction Idea**: Measures the variability of turnover rates over the past month **Construction Process**: Calculated as the standard deviation of daily turnover rates over the past 20 trading days [13] **Evaluation**: Reflects liquidity and trading activity [13] - **Factor Name**: Fama-French three-factor residual volatility **Construction Idea**: Measures the volatility of residuals from a Fama-French three-factor model regression **Construction Process**: Calculated as the standard deviation of residuals from daily returns regressed on the Fama-French three factors over the past 20 trading days [13] **Evaluation**: Indicates idiosyncratic risk [13] Factor Backtesting Results - **Factor Name**: bp **IC Values**: Weekly: -8.41%, Monthly: 3.48%, Yearly: 1.72% [8] **Excess Return**: Weekly: -0.18%, Monthly: 1.03%, Yearly: 3.10% [11] - **Factor Name**: bp three-year percentile **IC Values**: Weekly: 2.04%, Monthly: 7.90%, Yearly: 2.82% [8] **Excess Return**: Weekly: 0.67%, Monthly: 0.82%, Yearly: 2.55% [11] - **Factor Name**: Quarterly ep **IC Values**: Weekly: -5.19%, Monthly: 3.65%, Yearly: 0.24% [8] **Excess Return**: Weekly: -1.30%, Monthly: -0.08%, Yearly: 1.51% [11] - **Factor Name**: Quarterly ep one-year percentile **IC Values**: Weekly: 1.73%, Monthly: 4.68%, Yearly: 1.02% [8] **Excess Return**: Weekly: -0.35%, Monthly: 0.93%, Yearly: 4.35% [11] - **Factor Name**: Quarterly sp **IC Values**: Weekly: -5.87%, Monthly: -1.49%, Yearly: 0.18% [8] **Excess Return**: Weekly: -0.28%, Monthly: -1.23%, Yearly: 0.24% [11] - **Factor Name**: Quarterly sp one-year percentile **IC Values**: Weekly: 1.93%, Monthly: 7.04%, Yearly: 2.70% [8] **Excess Return**: Weekly: -0.66%, Monthly: 0.55%, Yearly: 3.80% [11] - **Factor Name**: Standardized unexpected earnings **IC Values**: Weekly: 0.24%, Monthly: 2.19%, Yearly: 0.64% [8] **Excess Return**: Weekly: -0.60%, Monthly: -0.75%, Yearly: 3.99% [11] - **Factor Name**: Standardized unexpected revenue **IC Values**: Weekly: -1.03%, Monthly: 0.72%, Yearly: 0.61% [8] **Excess Return**: Weekly: -0.41%, Monthly: -0.72%, Yearly: 1.55% [11] - **Factor Name**: Dividend yield **IC Values**: Weekly: -2.91%, Monthly: 1.85%, Yearly: -0.07% [8] **Excess Return**: Weekly: -0.37%, Monthly: 1.27%, Yearly: -4.85% [11]

Investment Rating - The industry investment rating is "Outperform the Market," indicating an expected industry index increase of over 5% in the next six months [18]. Core Insights - Recent factor performance shows that the average turnover rate, non-liquid shock, and quarterly gross margin factors have performed well, while factors like Beta and one-year momentum have underperformed [2][9]. - Over the past year, small-cap stocks, earnings forecast accuracy, and one-month turnover rate volatility have shown strong performance, while one-year momentum and expected adjustment averages have lagged [2][9]. Factor Tracking Summary Factor IC Performance - In the last week, the one-month average turnover rate, non-liquid shock, and turnover rate volatility factors performed well, while one-year momentum and quarterly asset turnover rate showed poor performance [7]. - Over the last month, the one-month average turnover rate and Fama-French three-factor one-month residual volatility factors performed well, while Beta and one-year momentum lagged [7]. - In the past year, the one-month specificity and Fama-French three-factor one-month residual volatility factors performed well, while one-year momentum and dividend yield factors underperformed [7][8]. Factor Long-Only Portfolio Performance - The long-only portfolio, constructed from the top 10% of factors, has shown cumulative excess returns, with quarterly gross margin and one-month average turnover rate factors performing well recently [9][10]. - Over the last year, small-cap stocks and earnings forecast accuracy have shown strong performance, while one-year momentum and expected adjustment averages have underperformed [9][10]. Factor Introduction - The factors used in the analysis are categorized into valuation, profitability, growth, dividends, reversal, turnover, volatility, and analyst factors, each with specific calculation methods [11][12].

Quantitative Factors and Construction Methods 1. Factor Name: Book-to-Price Ratio (BP) - **Construction Idea**: Measures the valuation of a stock by comparing its book value to its market value [12] - **Construction Process**: - Formula: $ BP = \frac{\text{Current Book Value}}{\text{Current Market Value}} $ [12] - **Evaluation**: BP is a widely used valuation factor, and its positive IC and excess return indicate its effectiveness in identifying undervalued stocks [8][10] 2. Factor Name: BP Three-Year Percentile - **Construction Idea**: Evaluates the relative valuation of a stock over the past three years [12] - **Construction Process**: - Formula: BP Three-Year Percentile = Percentile rank of the current BP within the last three years [12] - **Evaluation**: This factor provides a historical perspective on valuation, which can enhance its predictive power [8][10] 3. Factor Name: Quarterly Gross Profit Margin - **Construction Idea**: Measures profitability by comparing gross profit to sales revenue [12] - **Construction Process**: - Formula: $ \text{Quarterly Gross Profit Margin} = \frac{\text{Quarterly Gross Profit}}{\text{Quarterly Sales Revenue}} $ [12] - **Evaluation**: A positive IC and strong excess return suggest this factor is effective in identifying profitable companies [8][10] 4. Factor Name: 1-Month Average Daily Turnover - **Construction Idea**: Captures liquidity by analyzing the average daily turnover over the past month [12] - **Construction Process**: - Formula: 1-Month Average Daily Turnover = Mean of daily turnover over the last 20 trading days [12] - **Evaluation**: This factor demonstrates strong performance in short-term IC and excess return, indicating its utility in capturing liquidity-driven opportunities [8][10] 5. Factor Name: 1-Month Turnover Volatility - **Construction Idea**: Measures the variability of turnover over the past month to capture liquidity dynamics [12] - **Construction Process**: - Formula: 1-Month Turnover Volatility = Standard deviation of daily turnover over the last 20 trading days [12] - **Evaluation**: High IC and excess return suggest this factor effectively captures liquidity-related anomalies [8][10] 6. Factor Name: Fama-French Three-Factor 1-Month Residual Volatility - **Construction Idea**: Measures idiosyncratic risk by analyzing the residual volatility from the Fama-French three-factor model [12] - **Construction Process**: - Formula: Residual Volatility = Standard deviation of residuals from the regression of daily returns on the Fama-French three factors over the last 20 trading days [12] - **Evaluation**: This factor is effective in capturing risk-related anomalies, as evidenced by its strong IC and excess return [8][10] --- Factor Backtesting Results IC Performance - **BP**: Weekly IC = 5.32%, Monthly IC = 8.04%, Annual IC = 1.81% [8] - **BP Three-Year Percentile**: Weekly IC = 6.26%, Monthly IC = 10.63%, Annual IC = 3.10% [8] - **Quarterly Gross Profit Margin**: Weekly IC = 5.61%, Monthly IC = 3.29%, Annual IC = 0.64% [8] - **1-Month Average Daily Turnover**: Weekly IC = 12.54%, Monthly IC = 14.06%, Annual IC = 2.03% [8] - **1-Month Turnover Volatility**: Weekly IC = 10.49%, Monthly IC = 13.42%, Annual IC = 2.70% [8] - **Fama-French Three-Factor 1-Month Residual Volatility**: Weekly IC = 8.93%, Monthly IC = 13.16%, Annual IC = 3.32% [8] Excess Return Performance - **BP**: Weekly Excess Return = -0.04%, Monthly Excess Return = 1.27%, Annual Excess Return = 2.22% [10] - **BP Three-Year Percentile**: Weekly Excess Return = -0.25%, Monthly Excess Return = 2.07%, Annual Excess Return = 3.63% [10] - **Quarterly Gross Profit Margin**: Weekly Excess Return = 0.68%, Monthly Excess Return = 1.05%, Annual Excess Return = 4.64% [10] - **1-Month Average Daily Turnover**: Weekly Excess Return = 0.64%, Monthly Excess Return = 2.96%, Annual Excess Return = 7.46% [10] - **1-Month Turnover Volatility**: Weekly Excess Return = 0.55%, Monthly Excess Return = 2.95%, Annual Excess Return = 9.61% [10] - **Fama-French Three-Factor 1-Month Residual Volatility**: Weekly Excess Return = 0.29%, Monthly Excess Return = 2.75%, Annual Excess Return = 7.03% [10]

Quantitative Factors and Construction Methods - **Factor Name**: bp **Construction Idea**: Measures valuation by comparing net assets to market capitalization **Construction Process**: Calculated as: $ bp = \frac{\text{Net Assets}}{\text{Market Capitalization}} $ **Evaluation**: Provides a direct valuation metric for stocks[13] - **Factor Name**: bp three-year percentile **Construction Idea**: Evaluates the relative valuation of a stock over the past three years **Construction Process**: Represents the current bp value's percentile rank within the last three years[13] **Evaluation**: Useful for identifying stocks with consistent valuation trends[13] - **Factor Name**: Quarterly ep **Construction Idea**: Measures profitability relative to net assets **Construction Process**: Calculated as: $ \text{Quarterly ep} = \frac{\text{Quarterly Net Profit}}{\text{Net Assets}} $ **Evaluation**: Indicates profitability efficiency[13] - **Factor Name**: Quarterly ep one-year percentile **Construction Idea**: Tracks the relative profitability of a stock over the past year **Construction Process**: Represents the current quarterly ep value's percentile rank within the last year[13] **Evaluation**: Highlights short-term profitability trends[13] - **Factor Name**: Quarterly sp **Construction Idea**: Measures revenue generation relative to net assets **Construction Process**: Calculated as: $ \text{Quarterly sp} = \frac{\text{Quarterly Revenue}}{\text{Net Assets}} $ **Evaluation**: Reflects operational efficiency[13] - **Factor Name**: Quarterly sp one-year percentile **Construction Idea**: Tracks the relative revenue generation of a stock over the past year **Construction Process**: Represents the current quarterly sp value's percentile rank within the last year[13] **Evaluation**: Useful for identifying short-term revenue trends[13] - **Factor Name**: Quarterly ROA **Construction Idea**: Measures profitability relative to total assets **Construction Process**: Calculated as: $ \text{Quarterly ROA} = \frac{\text{Quarterly Net Profit}}{\text{Total Assets}} $ **Evaluation**: Indicates asset utilization efficiency[13] - **Factor Name**: Quarterly ROE **Construction Idea**: Measures profitability relative to shareholders' equity **Construction Process**: Calculated as: $ \text{Quarterly ROE} = \frac{\text{Quarterly Net Profit}}{\text{Net Assets}} $ **Evaluation**: Reflects return on equity for shareholders[13] - **Factor Name**: Quarterly net profit YoY growth **Construction Idea**: Tracks year-over-year growth in net profit **Construction Process**: Calculated as: $ \text{Net Profit YoY Growth} = \frac{\text{Current Net Profit} - \text{Previous Year Net Profit}}{\text{Previous Year Net Profit}} $ **Evaluation**: Highlights growth trends in profitability[13] - **Factor Name**: Quarterly revenue YoY growth **Construction Idea**: Tracks year-over-year growth in revenue **Construction Process**: Calculated as: $ \text{Revenue YoY Growth} = \frac{\text{Current Revenue} - \text{Previous Year Revenue}}{\text{Previous Year Revenue}} $ **Evaluation**: Reflects growth trends in operational performance[13] - **Factor Name**: Quarterly ROE YoY growth **Construction Idea**: Tracks year-over-year growth in ROE **Construction Process**: Calculated as: $ \text{ROE YoY Growth} = \frac{\text{Current ROE} - \text{Previous Year ROE}}{\text{Previous Year ROE}} $ **Evaluation**: Indicates improvement in equity returns[13] - **Factor Name**: Standardized unexpected earnings **Construction Idea**: Measures deviation of current earnings from historical growth trends **Construction Process**: $ \text{Standardized Unexpected Earnings} = \frac{\text{Current Earnings} - (\text{Last Year Earnings} + \text{8-Quarter Average Growth})}{\text{Standard Deviation of 8-Quarter Growth}} $ **Evaluation**: Useful for identifying earnings surprises[13] - **Factor Name**: Standardized unexpected revenue **Construction Idea**: Measures deviation of current revenue from historical growth trends **Construction Process**: $ \text{Standardized Unexpected Revenue} = \frac{\text{Current Revenue} - (\text{Last Year Revenue} + \text{8-Quarter Average Growth})}{\text{Standard Deviation of 8-Quarter Growth}} $ **Evaluation**: Highlights revenue surprises[13] - **Factor Name**: Dividend yield **Construction Idea**: Measures dividend payout relative to market capitalization **Construction Process**: Calculated as: $ \text{Dividend Yield} = \frac{\text{Annual Dividend}}{\text{Market Capitalization}} $ **Evaluation**: Indicates shareholder returns through dividends[13] - **Factor Name**: 1-month turnover rate volatility **Construction Idea**: Tracks the standard deviation of turnover rates over the past month **Construction Process**: $ \text{Turnover Rate Volatility} = \text{Standard Deviation of Daily Turnover Rates (Last 20 Days)} $ **Evaluation**: Reflects liquidity stability[13] Factor Backtesting Results - **bp**: Weekly IC 5.34%, Monthly IC 5.55%, Annual IC 1.76%, Historical IC 1.95%[8] Weekly excess return 0.20%, Monthly excess return 0.46%, Annual excess return 3.36%, Historical cumulative excess return 24.65%[10] - **bp three-year percentile**: Weekly IC 16.49%, Monthly IC 7.73%, Annual IC 2.81%, Historical IC 1.43%[8] Weekly excess return 1.02%, Monthly excess return 1.44%, Annual excess return 4.22%, Historical cumulative excess return -4.34%[10] - **Quarterly ep**: Weekly IC 14.19%, Monthly IC 7.50%, Annual IC 0.63%, Historical IC 1.32%[8] Weekly excess return 0.45%, Monthly excess return 2.65%, Annual excess return 3.46%, Historical cumulative excess return 30.85%[10] - **Quarterly ep one-year percentile**: Weekly IC 6.12%, Monthly IC 2.81%, Annual IC 1.13%, Historical IC 1.69%[8] Weekly excess return 0.40%, Monthly excess return 0.23%, Annual excess return 7.17%, Historical cumulative excess return 34.94%[10] - **Quarterly sp**: Weekly IC 4.90%, Monthly IC 1.26%, Annual IC 0.33%, Historical IC 0.74%[8] Weekly excess return 0.00%, Monthly excess return -0.55%, Annual excess return 1.08%, Historical cumulative excess return -2.52%[10] - **Quarterly sp one-year percentile**: Weekly IC 9.34%, Monthly IC 4.43%, Annual IC 2.73%, Historical IC 1.72%[8] Weekly excess return 0.27%, Monthly excess return 0.69%, Annual excess return 6.53%, Historical cumulative excess return 1.81%[10] - **Quarterly ROA**: Weekly IC 13.83%, Monthly IC 6.81%, Annual IC 0.59%, Historical IC 1.24%[8] Weekly excess return 0.38%, Monthly excess return 2.52%, Annual excess return 4.27%, Historical cumulative excess return 25.60%[10] - **Quarterly ROE**: Weekly IC 13.62%, Monthly IC 6.93%, Annual IC 0.58%, Historical IC 1.39%[8] Weekly excess return 0.24%, Monthly excess return 1.81%, Annual excess return 2.47%, Historical cumulative excess return 31.72%[10]

Quantitative Models and Factors Summary Quantitative Models and Construction Methods Model 1: Risk Premium Model - **Model Name**: Risk Premium Model - **Model Construction Idea**: The model measures the risk premium of various broad-based indices relative to the risk-free rate, using the yield of the 10-year government bond as a reference. - **Model Construction Process**: - Calculate the risk premium for each index as the difference between the index's return and the 10-year government bond yield. - Observe the mean reversion phenomenon of the risk premium. - Analyze the volatility of the risk premium over time. - Formula: $$ \text{Risk Premium} = \text{Index Return} - \text{10-year Government Bond Yield} $$ - **Model Evaluation**: The model effectively captures the relative investment value and deviation of the indices from the risk-free rate, showing clear mean reversion characteristics.[14][15][16] Model 2: PE-TTM Model - **Model Name**: PE-TTM Model - **Model Construction Idea**: The model uses the Price-to-Earnings ratio based on trailing twelve months (PE-TTM) as a valuation reference to assess the investment value of various indices. - **Model Construction Process**: - Calculate the PE-TTM for each index. - Compare the current PE-TTM with historical percentiles to determine the valuation level. - Observe the trend and volatility of the PE-TTM over time. - Formula: $$ \text{PE-TTM} = \frac{\text{Current Price}}{\text{Earnings per Share (TTM)}} $$ - **Model Evaluation**: The model provides a clear indication of the valuation level of the indices, helping to identify overvalued or undervalued conditions.[20][21][22] Model Backtesting Results Risk Premium Model - **Current Risk Premium**: - **Shanghai 50**: -0.17% - **CSI 300**: -0.41% - **CSI 500**: -0.78% - **CSI 1000**: -1.53% - **CSI 2000**: -1.85% - **CSI All Share**: -0.89% - **ChiNext**: -1.16% - **1-Year Percentile**: - **Shanghai 50**: 43.25% - **CSI 300**: 34.92% - **CSI 500**: 27.78% - **CSI 1000**: 15.48% - **CSI 2000**: 13.89% - **CSI All Share**: 19.44% - **ChiNext**: 24.21% - **5-Year Percentile**: - **Shanghai 50**: 44.37% - **CSI 300**: 35.08% - **CSI 500**: 22.70% - **CSI 1000**: 12.94% - **CSI 2000**: 9.76% - **CSI All Share**: 18.33% - **ChiNext**: 21.75%[16] PE-TTM Model - **Current PE-TTM**: - **Shanghai 50**: 10.86 - **CSI 300**: 12.60 - **CSI 500**: 28.92 - **CSI 1000**: 39.13 - **CSI 2000**: 96.99 - **CSI All Share**: 18.46 - **ChiNext**: 33.18 - **1-Year Historical Percentile**: - **Shanghai 50**: 76.45% - **CSI 300**: 69.83% - **CSI 500**: 96.28% - **CSI 1000**: 79.34% - **CSI 2000**: 97.93% - **CSI All Share**: 86.78% - **ChiNext**: 68.60% - **5-Year Historical Percentile**: - **Shanghai 50**: 64.96% - **CSI 300**: 58.43% - **CSI 500**: 86.28% - **CSI 1000**: 73.39% - **CSI 2000**: 51.82% - **CSI All Share**: 74.38% - **ChiNext**: 30.99%[22]