Workflow
反转因子
icon
Search documents
反转因子表现相对较优,GARP组合周收益率
- The reversal factor performed relatively well, with the GARP portfolio achieving a weekly return of 3.28% from August 1, 2025, to August 8, 2025[1] - The cumulative return of the GARP portfolio in 2025 was 28.2%[1] - The PB-profit combination had a weekly return of 2.86%, with a cumulative return of 20.53% in 2025[5][9] - The small-cap growth portfolio had a weekly return of 4.87%, with a cumulative return of 56.37% in 2025[5][9] - The small-cap value preferred portfolio 1 had a weekly return of 3.67%, with a cumulative return of 48.10% in 2025[5][9] - The small-cap value preferred portfolio 2 had a weekly return of 5.00%, with a cumulative return of 56.61% in 2025[5][9] - The performance of the multi-factor portfolios showed that the aggressive portfolio and the balanced portfolio had weekly returns of 3.37% and 3.19%, respectively[10][11] - The aggressive portfolio and the balanced portfolio had cumulative returns of 61.10% and 49.08% in 2025, respectively[11] - The enhanced CSI 300 portfolio had a weekly return of 1.43%, with a cumulative return of 11.18% in 2025[14][15] - The enhanced CSI 500 portfolio had a weekly return of 2.17%, with a cumulative return of 14.96% in 2025[14][15] - The enhanced CSI 1000 portfolio had a weekly return of 2.01%, with a cumulative return of 22.07% in 2025[14][15] - The performance of the style factors showed that small-cap stocks outperformed large-cap stocks, and high-valuation stocks outperformed low-valuation stocks[5][43] - The performance of the technical factors showed that the reversal factor contributed positive returns, with a weekly long-short return of 0.98%[5][46][48] - The performance of the fundamental factors showed that the SUE factor and the expected net profit adjustment factor contributed positive returns, with weekly long-short returns of 0.51% and 0.34%, respectively[5][50][52]
量化资产配置月报:持续配置反转因子-20250701
2025 年 07 月 01 日 持续配置反转因子 —— 量化资产配置月报 202507 - 相关研究 证券分析师 沈思逸 A0230521070001 shensy@swsresearch.com 邓虎 A0230520070003 denghu@swsresearch.com 联系人 沈思逸 (8621)23297818× shensy@swsresearch.com 权 益 量 化 研 究 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 证 券 研 究 报 告 ⚫ 持续配置反转因子。按照定量指标的结果,目前经济回落、流动性略偏松,信用指标转好, 微观映射中经济(盈利预期)好转回到中等,信用转好,微观流动性偏紧,因此仅流动性 触发修正,修正后的方向为经济下行、流动性偏紧而信用转好,修正后的方向与上期维持 一致;由于流动性与信用产生明显背离,我们主要按照对经济不敏感、对信用敏感来选择 得分前三的因子,各股票池配置风格仍偏向成长,300、500 的因子选择与上期保持一致, 无共振因子,中证 1000 的因子选择中增加了短期反转因子,低波动率、短期反转 ...
因子跟踪周报:波动率、bp分位数因子表现较好-20250621
Tianfeng Securities· 2025-06-21 07:11
Quantitative Factors and Construction Methods 1. Factor Name: **bp** - **Factor Construction Idea**: Measures the valuation level of a stock based on its book-to-price ratio [13] - **Factor Construction Process**: Calculated as the current net asset divided by the current total market value $ bp = \frac{\text{Current Net Asset}}{\text{Current Total Market Value}} $ [13] 2. Factor Name: **bp Three-Year Percentile** - **Factor Construction Idea**: Evaluates the relative valuation of a stock over the past three years [13] - **Factor Construction Process**: Represents the percentile rank of the current bp value within the stock's bp distribution over the last three years [13] 3. Factor Name: **Quarterly EP** - **Factor Construction Idea**: Reflects the profitability of a stock relative to its equity [13] - **Factor Construction Process**: Calculated as the quarterly net profit divided by the net asset $ \text{Quarterly EP} = \frac{\text{Quarterly Net Profit}}{\text{Net Asset}} $ [13] 4. Factor Name: **Quarterly EP One-Year Percentile** - **Factor Construction Idea**: Measures the relative profitability of a stock over the past year [13] - **Factor Construction Process**: Represents the percentile rank of the current quarterly EP value within the stock's EP distribution over the last year [13] 5. Factor Name: **Quarterly SP** - **Factor Construction Idea**: Indicates the revenue generation efficiency of a stock relative to its equity [13] - **Factor Construction Process**: Calculated as the quarterly operating revenue divided by the net asset $ \text{Quarterly SP} = \frac{\text{Quarterly Operating Revenue}}{\text{Net Asset}} $ [13] 6. Factor Name: **Quarterly SP One-Year Percentile** - **Factor Construction Idea**: Evaluates the relative revenue efficiency of a stock over the past year [13] - **Factor Construction Process**: Represents the percentile rank of the current quarterly SP value within the stock's SP distribution over the last year [13] 7. Factor Name: **Fama-French Three-Factor One-Month Residual Volatility** - **Factor Construction Idea**: Measures the idiosyncratic risk of a stock based on its residual volatility after regressing against the Fama-French three-factor model [13] - **Factor Construction Process**: Calculated as the standard deviation of the residuals from the regression of daily returns over the past 20 trading days on the Fama-French three factors $ \text{Residual Volatility} = \sqrt{\frac{\sum (\text{Actual Return} - \text{Predicted Return})^2}{n}} $ where "Predicted Return" is derived from the Fama-French three-factor model [13] 8. Factor Name: **One-Month Excess Return Volatility** - **Factor Construction Idea**: Captures the volatility of a stock's excess return over the past month [13] - **Factor Construction Process**: Calculated as the standard deviation of the excess returns over the past 20 trading days $ \text{Excess Return Volatility} = \sqrt{\frac{\sum (\text{Excess Return} - \text{Mean Excess Return})^2}{n}} $ [13] --- Factor Backtesting Results IC Performance - **bp**: Weekly IC = 9.73%, Monthly IC = 2.21%, Yearly IC = 1.64%, Historical IC = 2.27% [9] - **bp Three-Year Percentile**: Weekly IC = 14.75%, Monthly IC = 3.36%, Yearly IC = 2.85%, Historical IC = 1.69% [9] - **Quarterly EP**: Weekly IC = -4.31%, Monthly IC = 0.38%, Yearly IC = -0.58%, Historical IC = 1.13% [9] - **Quarterly EP One-Year Percentile**: Weekly IC = 7.25%, Monthly IC = 3.57%, Yearly IC = 0.94%, Historical IC = 1.73% [9] - **Quarterly SP**: Weekly IC = -0.92%, Monthly IC = 0.38%, Yearly IC = 0.23%, Historical IC = 0.71% [9] - **Quarterly SP One-Year Percentile**: Weekly IC = 11.79%, Monthly IC = 4.40%, Yearly IC = 3.08%, Historical IC = 1.86% [9] - **Fama-French Three-Factor One-Month Residual Volatility**: Weekly IC = 14.50%, Monthly IC = 5.11%, Yearly IC = 3.29%, Historical IC = 2.54% [9] - **One-Month Excess Return Volatility**: Weekly IC = 14.87%, Monthly IC = 5.14%, Yearly IC = 3.26%, Historical IC = 2.22% [9] Long-Only Portfolio Excess Returns - **bp**: Weekly Excess Return = 0.52%, Monthly Excess Return = -0.36%, Yearly Excess Return = 1.57%, Historical Cumulative Excess Return = 30.39% [11] - **bp Three-Year Percentile**: Weekly Excess Return = 0.75%, Monthly Excess Return = -0.59%, Yearly Excess Return = 3.19%, Historical Cumulative Excess Return = -1.63% [11] - **Quarterly EP**: Weekly Excess Return = 0.13%, Monthly Excess Return = 1.56%, Yearly Excess Return = 1.05%, Historical Cumulative Excess Return = 30.66% [11] - **Quarterly EP One-Year Percentile**: Weekly Excess Return = 0.81%, Monthly Excess Return = 0.32%, Yearly Excess Return = 3.53%, Historical Cumulative Excess Return = 33.78% [11] - **Quarterly SP**: Weekly Excess Return = -0.30%, Monthly Excess Return = 0.33%, Yearly Excess Return = 0.34%, Historical Cumulative Excess Return = -2.98% [11] - **Quarterly SP One-Year Percentile**: Weekly Excess Return = 0.56%, Monthly Excess Return = 1.09%, Yearly Excess Return = 9.91%, Historical Cumulative Excess Return = 1.99% [11] - **Fama-French Three-Factor One-Month Residual Volatility**: Weekly Excess Return = 1.33%, Monthly Excess Return = 1.68%, Yearly Excess Return = 8.97%, Historical Cumulative Excess Return = 19.84% [11] - **One-Month Excess Return Volatility**: Weekly Excess Return = 1.34%, Monthly Excess Return = 1.55%, Yearly Excess Return = 10.29%, Historical Cumulative Excess Return = 11.42% [11]
因子跟踪周报:小市值、成长因子表现较好20250607-20250607
Tianfeng Securities· 2025-06-07 07:54
Quantitative Factors and Construction Methods Factor Name: BP (Book-to-Price Ratio) - **Construction Idea**: Measures the valuation of a stock by comparing its book value to its market value [13] - **Construction Process**: - Formula: $ BP = \frac{\text{Current Book Value}}{\text{Current Market Value}} $ [13] Factor Name: BP Three-Year Percentile - **Construction Idea**: Evaluates the relative valuation of a stock over the past three years [13] - **Construction Process**: - Formula: BP Three-Year Percentile = Percentile rank of the current BP within the last three years [13] Factor Name: Quarterly EP (Earnings-to-Price Ratio) - **Construction Idea**: Measures the profitability of a stock relative to its market price [13] - **Construction Process**: - Formula: $ \text{Quarterly EP} = \frac{\text{Quarterly Net Profit}}{\text{Net Assets}} $ [13] Factor Name: Quarterly EP One-Year Percentile - **Construction Idea**: Tracks the relative profitability of a stock over the past year [13] - **Construction Process**: - Formula: Quarterly EP One-Year Percentile = Percentile rank of the current Quarterly EP within the last year [13] Factor Name: Quarterly SP (Sales-to-Price Ratio) - **Construction Idea**: Measures the revenue generation capability of a stock relative to its market price [13] - **Construction Process**: - Formula: $ \text{Quarterly SP} = \frac{\text{Quarterly Revenue}}{\text{Net Assets}} $ [13] Factor Name: Quarterly SP One-Year Percentile - **Construction Idea**: Tracks the relative revenue generation capability of a stock over the past year [13] - **Construction Process**: - Formula: Quarterly SP One-Year Percentile = Percentile rank of the current Quarterly SP within the last year [13] Factor Name: Small Market Cap - **Construction Idea**: Captures the size effect by focusing on smaller companies [13] - **Construction Process**: - Formula: $ \text{Small Market Cap} = \log(\text{Market Capitalization}) $ [13] Factor Name: 1-Month Reversal - **Construction Idea**: Captures the short-term reversal effect in stock prices [13] - **Construction Process**: - Formula: $ \text{1-Month Reversal} = \text{Cumulative Return over the Last 20 Trading Days} $ [13] Factor Name: Fama-French Three-Factor 1-Month Residual Volatility - **Construction Idea**: Measures the idiosyncratic risk of a stock based on the Fama-French three-factor model [13] - **Construction Process**: - Formula: $ \text{Residual Volatility} = \text{Standard Deviation of Residuals from Fama-French Three-Factor Regression over the Last 20 Trading Days} $ [13] --- Factor Backtesting Results IC Performance - **BP**: Weekly IC = -4.17%, Monthly IC = 0.88%, Yearly IC = 1.86%, Historical IC = 2.19% [9] - **BP Three-Year Percentile**: Weekly IC = -1.08%, Monthly IC = -0.99%, Yearly IC = 2.58%, Historical IC = 1.58% [9] - **Quarterly EP**: Weekly IC = 2.10%, Monthly IC = -0.48%, Yearly IC = -0.46%, Historical IC = 1.18% [9] - **Quarterly EP One-Year Percentile**: Weekly IC = 4.23%, Monthly IC = 3.81%, Yearly IC = 0.98%, Historical IC = 1.73% [9] - **Quarterly SP**: Weekly IC = 0.79%, Monthly IC = 0.93%, Yearly IC = 0.53%, Historical IC = 0.74% [9] - **Quarterly SP One-Year Percentile**: Weekly IC = 4.80%, Monthly IC = 2.82%, Yearly IC = 2.87%, Historical IC = 1.83% [9] - **Small Market Cap**: Weekly IC = 10.49%, Monthly IC = 8.17%, Yearly IC = 3.61%, Historical IC = 2.05% [9] - **1-Month Reversal**: Weekly IC = 7.22%, Monthly IC = 1.22%, Yearly IC = 3.40%, Historical IC = 2.22% [9] - **Fama-French Three-Factor 1-Month Residual Volatility**: Weekly IC = 3.60%, Monthly IC = 1.11%, Yearly IC = 3.49%, Historical IC = 2.48% [9] Excess Return Performance (Long-Only Portfolio) - **BP**: Weekly Excess Return = -0.83%, Monthly Excess Return = -1.04%, Yearly Excess Return = 3.02%, Historical Cumulative Excess Return = 28.90% [11] - **BP Three-Year Percentile**: Weekly Excess Return = -0.58%, Monthly Excess Return = -1.51%, Yearly Excess Return = 0.97%, Historical Cumulative Excess Return = -3.21% [11] - **Quarterly EP**: Weekly Excess Return = 0.57%, Monthly Excess Return = 1.10%, Yearly Excess Return = 1.44%, Historical Cumulative Excess Return = 30.83% [11] - **Quarterly EP One-Year Percentile**: Weekly Excess Return = -0.01%, Monthly Excess Return = 0.51%, Yearly Excess Return = 3.23%, Historical Cumulative Excess Return = 34.69% [11] - **Quarterly SP**: Weekly Excess Return = -0.01%, Monthly Excess Return = 0.49%, Yearly Excess Return = 0.70%, Historical Cumulative Excess Return = -2.69% [11] - **Quarterly SP One-Year Percentile**: Weekly Excess Return = 0.09%, Monthly Excess Return = 1.25%, Yearly Excess Return = 7.91%, Historical Cumulative Excess Return = 2.23% [11] - **Small Market Cap**: Weekly Excess Return = 0.96%, Monthly Excess Return = 2.76%, Yearly Excess Return = 18.31%, Historical Cumulative Excess Return = 62.57% [11] - **1-Month Reversal**: Weekly Excess Return = 0.83%, Monthly Excess Return = 0.76%, Yearly Excess Return = 3.54%, Historical Cumulative Excess Return = 1.57% [11] - **Fama-French Three-Factor 1-Month Residual Volatility**: Weekly Excess Return = 0.28%, Monthly Excess Return = 0.75%, Yearly Excess Return = 8.69%, Historical Cumulative Excess Return = 18.67% [11]
反转因子表现出色,中证 1000 增强组合年内超额6.24%【国信金工】
量化藏经阁· 2025-05-11 00:55
Group 1 - The core viewpoint of the article is to track and analyze the performance of various index enhancement portfolios and the factors influencing stock selection across different indices [1][2][3]. Group 2 - The performance of the HuShen 300 index enhancement portfolio showed an excess return of 0.54% for the week and 2.44% year-to-date [5][19]. - The performance of the Zhongzheng 500 index enhancement portfolio indicated an excess return of 1.29% for the week and 4.77% year-to-date [5][21]. - The Zhongzheng 1000 index enhancement portfolio achieved an excess return of 1.67% for the week and 6.24% year-to-date [5][21]. - The Zhongzheng A500 index enhancement portfolio reported an excess return of 0.21% for the week and 5.19% year-to-date [5][25]. Group 3 - In the HuShen 300 component stocks, factors such as expected PEG, quarterly ROE, and quarterly EP performed well [6][4]. - In the Zhongzheng 500 component stocks, factors like three-month reversal, one-month reversal, and three-month turnover showed strong performance [6][8]. - For the Zhongzheng 1000 component stocks, one-month reversal, specificity, and three-month reversal were notable factors [6][10]. - In the Zhongzheng A500 index component stocks, three-month reversal, expected PEG, and expected EPTTM were effective factors [6][12]. - Among public fund heavy stocks, one-month reversal, three-month reversal, and expected PEG were the best-performing factors [6][14]. Group 4 - The public fund index enhancement products for HuShen 300 had a maximum excess return of 0.57%, a minimum of -0.34%, and a median of 0.05% for the week [19]. - The Zhongzheng 500 index enhancement products had a maximum excess return of 1.06%, a minimum of -0.28%, and a median of 0.25% for the week [21]. - The Zhongzheng 1000 index enhancement products reported a maximum excess return of 0.97%, a minimum of -0.55%, and a median of 0.23% for the week [21]. - The Zhongzheng A500 index enhancement products had a maximum excess return of 0.58%, a minimum of -0.49%, and a median of 0.02% for the week [25].
盘点SmartBeta指数(策略指数)常用的八大策略因子
雪球· 2025-03-04 09:08
Core Viewpoint - The article emphasizes the importance of investment factors in selecting stocks and constructing investment strategies, highlighting that understanding these factors can lead to better investment decisions and potential returns [2][20]. Investment Factors Overview - The article introduces eight commonly used investment factors, each with distinct principles, applicable market conditions, and associated risks, which can help investors optimize their investment strategies [4][16]. Factor Summaries 1. Market Capitalization Factor - Focuses on the impact of stock size on returns, with large-cap stocks generally being more stable but less elastic, while small-cap stocks offer higher growth potential but come with increased risk [5][6]. 2. Value Factor - Concentrates on the discrepancy between a company's intrinsic value and market price, aiming to identify undervalued stocks for potential gains when market sentiment improves [8]. 3. Growth Factor - Evaluates a company's earnings growth and future potential, typically performing well in favorable economic conditions but facing higher risks during downturns [9]. 4. Low Volatility Factor - Selects stocks with stable prices and low volatility, providing better risk-adjusted returns, especially during market downturns [11]. 5. Dividend Factor - Targets stocks with stable dividends and high yield, offering defensive characteristics in volatile markets but may lag in strong bull markets [12]. 6. Quality Factor - Based on financial and operational metrics to identify high-quality companies, which may face valuation risks during periods of high market risk appetite [13]. 7. Momentum Factor - Utilizes the trend-following theory, capitalizing on stocks that have shown strong past performance, though it may struggle in volatile markets [14]. 8. Reversal Factor - Exploits price reversal opportunities, performing well in choppy or bearish markets but underperforming in strong trends [15]. Factor Usage Considerations - Investors should choose factors that align with their risk tolerance and investment goals, combining multiple factors to enhance returns while being mindful of market conditions [17][18][19].
多因子ALPHA系列报告之三十:个股配对思想在因子策略中的应用
GF SECURITIES· 2017-03-29 16:00
- The report discusses the application of stock pair trading ideas in factor strategies, specifically focusing on reversal factors which have historically shown strong performance[1] - Traditional reversal factors include "N-month price reversal," "highest price length," and "volume ratio," which capture the trend that stocks with low past returns tend to perform better in the future and vice versa[1][2] - The report introduces a pair reversal factor that captures reversal opportunities between individual stocks within the same industry, differing from traditional pair trading by using periodic closing instead of stop-loss conditions[2][3] - The pair reversal factor is tested using a hedging strategy with a monthly rebalancing frequency, using the CSI 800 index constituents as the stock pool, and achieving an annualized excess return of 8% from 2007 to 2016[3][4] - The pair reversal factor is also applied to enhance multi-factor portfolios with weekly rebalancing, showing improved returns even after considering transaction costs, with a benchmark multi-factor portfolio return of 424.40% and a pair rebalancing portfolio return of 501.59% during the sample period from 2007 to 2016[4][5] Quantitative Models and Construction Methods 1. **Model Name**: Pair Reversal Factor - **Construction Idea**: Capture reversal opportunities between individual stocks within the same industry, similar to pair trading but with periodic closing instead of stop-loss conditions[2][3] - **Construction Process**: 1. Perform cointegration regression on the log prices of two assets to check for cointegration relationship[43][44] 2. Calculate the spread and standard deviation of the spread during the learning period[45][46] 3. Use the spread and standard deviation to determine the opening threshold and execute trades accordingly[46][49] 4. Rebalance the portfolio monthly by closing all positions and reopening new ones based on the updated spread and standard deviation[51][53] - **Evaluation**: The pair reversal factor effectively captures stock price reversals and mean reversion of price spreads, providing significant excess returns at the individual stock level[69] Model Backtest Results 1. **Pair Reversal Factor**: - **Annualized Return**: 31.17% (2007), 50.85% (2008), 51.19% (2009), 21.39% (2010), 14.26% (2011), 14.75% (2012), 25.75% (2013), 9.10% (2014), 59.01% (2015), 17.05% (2016), 1246.06% (full sample)[63] - **Maximum Drawdown**: 4.44% (2007), 4.62% (2008), 4.61% (2009), 2.97% (2010), 2.64% (2011), 2.23% (2012), 2.57% (2013), 4.99% (2014), 5.48% (2015), 4.07% (2016), 5.48% (full sample)[63] - **Win Rate**: 58.38% (2007), 60.57% (2008), 59.02% (2009), 58.26% (2010), 58.20% (2011), 59.66% (2012), 59.66% (2013), 51.02% (2014), 59.84% (2015), 59.43% (2016), 58.27% (full sample)[63] Quantitative Factors and Construction Methods 1. **Factor Name**: N-month Price Reversal - **Construction Idea**: Measure the price change over a fixed time window to capture the reversal effect[30][33] - **Construction Process**: 1. Calculate the price change over the past N months: $(\text{Current Price} - \text{Price N months ago}) / \text{Price N months ago}$[33] - **Evaluation**: Reversal factors have shown strong performance in historical studies, with high IC values and good performance in various metrics such as LS return, LS win rate, LS IR, IC IR, and IC P[33][35] Factor Backtest Results 1. **N-month Price Reversal**: - **IC**: -5.72% (1-month), -4.75% (3-month), -4.10% (6-month), -3.55% (12-month)[35] - **LS Return**: 21.84% (1-month), 20.33% (3-month), 18.13% (6-month), 17.66% (12-month)[35] - **LS Win Rate**: 64.41% (1-month), 59.32% (3-month), 56.78% (6-month), 61.02% (12-month)[35] - **LS IR**: 0.99 (1-month), 0.81 (3-month), 0.77 (6-month), 0.83 (12-month)[35] - **IC IR**: 0.72 (1-month), 0.92 (3-month), 0.78 (6-month), 0.83 (12-month)[35] - **IC P**: 0.0% (1-month), 0.2% (3-month), 0.5% (6-month), 1.1% (12-month)[35]