中邮因子周报：小市值持续，高波风格占优-20250519

Quantitative Models and Construction Methods 1. Model Name: GRU (Generalized Recurrent Unit) - Model Construction Idea: GRU models are used to capture temporal dependencies and patterns in financial data, leveraging recurrent neural network structures to predict stock performance or factor returns[3][4][5] - Model Construction Process: The GRU model is trained on historical stock data, incorporating features such as price movements, volume, and other technical indicators. Specific GRU-based models mentioned include: - open1d: Focuses on daily opening prices - close1d: Focuses on daily closing prices - barra1d: Integrates Barra-style risk factors for daily predictions - barra5d: Extends Barra-style risk factors to a 5-day horizon[5][6][25] - Model Evaluation: GRU models show mixed performance, with some models like open1d performing well, while others like barra1d and barra5d experience significant drawdowns in certain market conditions[5][6][25] --- Model Backtesting Results GRU Model Performance - open1d: - Weekly excess return: 1.22% - Monthly excess return: 2.58% - Year-to-date excess return: 6.08%[29][30] - close1d: - Weekly excess return: 1.89% - Monthly excess return: 2.91% - Year-to-date excess return: 4.14%[29][30] - barra1d: - Weekly excess return: 0.85% - Monthly excess return: 1.50% - Year-to-date excess return: 3.48%[29][30] - barra5d: - Weekly excess return: 0.84% - Monthly excess return: 2.25% - Year-to-date excess return: 5.59%[29][30] --- Quantitative Factors and Construction Methods 1. Factor Name: Barra Style Factors - Factor Construction Idea: Barra factors are designed to capture systematic risk exposures across various dimensions such as size, value, momentum, and volatility[13][14] - Factor Construction Process: - Beta: Historical beta of the stock - Size: Natural logarithm of total market capitalization - Momentum: Weighted average of historical excess returns, combining volatility, cumulative deviation, and residual volatility $ Momentum = 0.74 \cdot \text{Volatility} + 0.16 \cdot \text{Cumulative Deviation} + 0.1 \cdot \text{Residual Volatility} $ - Volatility: Weighted average of historical residual return volatilities - Valuation: Inverse of price-to-book ratio - Liquidity: Weighted average of turnover ratios (monthly, quarterly, yearly) - Profitability: Weighted average of analyst forecasted earnings yield, cash flow yield, and other profitability metrics - Growth: Weighted average of earnings and revenue growth rates - Leverage: Weighted average of market leverage, book leverage, and debt-to-asset ratio[14][15] - Factor Evaluation: Barra factors demonstrate varying performance across different market conditions, with some factors like volatility and liquidity showing strong returns, while others like size and growth exhibit weaker performance[15][16] 2. Factor Name: Technical Factors - Factor Construction Idea: Technical factors aim to capture price and volume-based patterns, focusing on momentum and volatility metrics[17][20][24] - Factor Construction Process: - Momentum: Calculated over different time horizons (e.g., 20-day, 60-day, 120-day) - Volatility: Measured as the standard deviation of returns over specific periods (e.g., 20-day, 60-day, 120-day) - Median Deviation: Captures the median absolute deviation of returns[27] - Factor Evaluation: High-momentum and high-volatility stocks generally outperform, but certain periods show negative returns for these factors, especially in the 120-day horizon[17][27] 3. Factor Name: Fundamental Factors - Factor Construction Idea: Fundamental factors are derived from financial statements, focusing on profitability, growth, and valuation metrics[17][20][24] - Factor Construction Process: - Static Financial Metrics: Return on equity (ROE), return on assets (ROA), and profit margins - Growth Metrics: Earnings growth, revenue growth, and cash flow growth - Surprise Metrics: Earnings and revenue surprises relative to analyst expectations[19][21][23] - Factor Evaluation: Growth and surprise factors perform well, while static financial metrics like ROA and ROE show weaker performance in certain periods[19][21][23] --- Factor Backtesting Results Barra Factors - Volatility: Weekly return: 0.75%, Monthly return: 2.73% - Liquidity: Weekly return: 0.68%, Monthly return: 1.37% - Size: Weekly return: -1.45%, Monthly return: -3.60%[15][16] Technical Factors - 20-day Momentum: Weekly return: -1.81%, Monthly return: -6.16% - 60-day Volatility: Weekly return: -1.79%, Monthly return: -0.74% - 120-day Momentum: Weekly return: -1.68%, Monthly return: -0.80%[27] Fundamental Factors - ROA Growth: Weekly return: 0.23%, Monthly return: 1.31% - Earnings Surprise: Weekly return: 0.20%, Monthly return: 1.11% - Revenue Growth: Weekly return: 0.17%, Monthly return: 0.77%[19][21][23]