本周估值风格显著，规模因子表现出色 ——因子周报 20250418 金融工程 1. 主要市场指数与风格表现回顾 本周主要宽基指数涨跌不一。北证 50 上涨 3.48%，上证指数上涨 1.19%，中证 2000 上涨 0.75%，沪深 300 上涨 0.59%，中证 800 上涨 0.34%；中证 500 下跌 0.37%，中证 1000 下跌 0.52%，深证成指下跌 0.54%，创业板指下跌 0.64%。 从行业来看，本周银行、房地产、煤炭、综合、石油石化等行业表现居 前；国防军工、农林牧渔、计算机、消费者服务、电子等行业表现居后。 从风格因子来看，最近一周估值因子、规模因子和非线性市值因子的表现 尤为突出，因子多空收益分别为 2.06%、-2.87%和-0.89%。 2. 选股因子表现跟踪 沪深 300 股票池中，本周 120 日成交比率、单季度 ROA 同比、BP 因子 表现较好。中证 500 股票池中，本周标准化预期外盈利、流动比率、单季度营 业收入同比增速因子表现较好。中证 800 股票池中，本周单季度 ROE 同比、 单季度净利润同比增速、单季度营业利润同比增速因子表现较好。中证 1000 股票池 ...

Quantitative Models and Construction Methods - **Model Name**: PB-ROE-50 **Model Construction Idea**: The model selects stocks based on a combination of Price-to-Book (PB) ratio and Return on Equity (ROE), aiming to capture value and profitability factors[23] **Model Construction Process**: The portfolio is constructed by ranking stocks based on PB and ROE metrics, selecting the top 50 stocks, and rebalancing periodically. Details of the construction process are referenced in earlier reports[23] **Model Evaluation**: The model underperformed this week, delivering negative excess returns across all stock pools, indicating potential challenges in the current market environment[23] - **Model Name**: Public and Private Institution Research Portfolios **Model Construction Idea**: These portfolios are based on stocks that receive significant attention from public and private institutional research, leveraging the informational advantage of institutional focus[25] **Model Construction Process**: Stocks are selected based on the frequency and intensity of institutional research coverage. The portfolios are rebalanced periodically to reflect updated research trends[25] **Model Evaluation**: The public research portfolio achieved positive excess returns this week, while the private research portfolio remained flat, suggesting varying effectiveness of institutional research strategies[25] - **Model Name**: Block Trade Portfolio **Model Construction Idea**: This model identifies stocks with high block trade activity and low volatility, hypothesizing that such stocks exhibit superior subsequent performance[29] **Model Construction Process**: Stocks are ranked based on "block trade transaction ratio" and "6-day transaction volatility." A portfolio is constructed by selecting stocks with high transaction ratios and low volatility, rebalanced monthly[29] **Model Evaluation**: The portfolio delivered strong positive excess returns this week, highlighting the effectiveness of the "high transaction, low volatility" principle[29] - **Model Name**: Private Placement Portfolio **Model Construction Idea**: This model focuses on stocks involved in private placement events, aiming to capture event-driven investment opportunities[34] **Model Construction Process**: Stocks are selected based on private placement announcements, considering factors such as market capitalization, rebalancing frequency, and position control. The portfolio is rebalanced periodically[34] **Model Evaluation**: The portfolio achieved modest positive excess returns this week, indicating the continued relevance of private placement events in generating alpha[34] Model Backtesting Results - **PB-ROE-50 Model**: - Excess return (CSI 500): -0.26% - Excess return (CSI 800): -0.83% - Excess return (All Market): -1.00%[24] - **Public Research Portfolio**: - Excess return (CSI 800): 0.81%[26] - **Private Research Portfolio**: - Excess return (CSI 800): 0.00%[26] - **Block Trade Portfolio**: - Excess return (CSI All Share): 1.55%[30] - **Private Placement Portfolio**: - Excess return (CSI All Share): 0.19%[35] Quantitative Factors and Construction Methods - **Factor Name**: Momentum Factor **Factor Construction Idea**: Captures the momentum effect by identifying stocks with strong recent performance[18] **Factor Construction Process**: Stocks are ranked based on their recent price performance, and the factor is constructed by taking long positions in high-momentum stocks and short positions in low-momentum stocks[18] **Factor Evaluation**: The factor delivered positive returns this week, indicating the presence of momentum effects in the market[18] - **Factor Name**: Nonlinear Market Cap Factor **Factor Construction Idea**: Measures the nonlinear relationship between market capitalization and stock returns[18] **Factor Construction Process**: The factor is derived by fitting a nonlinear regression model to market cap and return data, isolating the nonlinear component[18] **Factor Evaluation**: The factor underperformed this week, reflecting the dominance of small-cap stocks in the market[18] - **Factor Name**: Residual Volatility Factor **Factor Construction Idea**: Identifies stocks with low residual volatility, hypothesizing that such stocks exhibit superior risk-adjusted returns[18] **Factor Construction Process**: Residual volatility is calculated by regressing stock returns on market returns and measuring the standard deviation of residuals. Stocks with low residual volatility are favored[18] **Factor Evaluation**: The factor delivered negative returns this week, suggesting a challenging environment for low-volatility strategies[18] Factor Backtesting Results - **Momentum Factor**: Weekly return: 0.69%[18] - **Nonlinear Market Cap Factor**: Weekly return: -0.58%[18] - **Residual Volatility Factor**: Weekly return: -0.64%[18]