东方因子周报：Beta风格领衔，一个月UMR因子表现出色，建议关注市场敏感度高的资产-20250810

Quantitative Models and Construction Methods Model Name: DFQ-FactorGCL - Model Construction Idea: Based on hypergraph convolutional neural networks and temporal residual contrastive learning for stock return prediction[6] - Model Construction Process: The model uses hypergraph convolutional neural networks to capture complex relationships between stocks and temporal residual contrastive learning to enhance prediction accuracy[6] - Model Evaluation: The model is effective in capturing stock trends and improving prediction accuracy[6] Model Name: Neural ODE - Model Construction Idea: Reconstructing time series dynamic systems for deep learning factor mining[6] - Model Construction Process: The model uses ordinary differential equations to model the continuous dynamics of stock prices, allowing for more accurate factor extraction[6] - Model Evaluation: The model provides a novel approach to factor mining, improving the robustness and accuracy of predictions[6] Model Name: DFQ-FactorVAE-pro - Model Construction Idea: Incorporating feature selection and environmental variable modules into the FactorVAE model[6] - Model Construction Process: The model uses variational autoencoders with additional modules for feature selection and environmental variables to enhance stock selection[6] - Model Evaluation: The model improves stock selection by considering more comprehensive factors and environmental variables[6] Quantitative Factors and Construction Methods Factor Name: Beta - Factor Construction Idea: Bayesian compressed market Beta[16] - Factor Construction Process: The factor is constructed by compressing the market Beta using Bayesian methods to capture market sensitivity[16] - Factor Evaluation: The factor is effective in identifying stocks with high market sensitivity[12] Factor Name: Volatility - Factor Construction Idea: Average logarithmic turnover rate over the past 243 days[16] - Factor Construction Process: The factor is calculated using the average logarithmic turnover rate and its regression with the market turnover rate over the past 243 days[16] - Factor Evaluation: The factor captures the demand for high volatility assets[12] Factor Name: Liquidity - Factor Construction Idea: Average logarithmic turnover rate over the past 243 days[16] - Factor Construction Process: The factor is calculated using the average logarithmic turnover rate and its regression with the market turnover rate over the past 243 days[16] - Factor Evaluation: The factor indicates the demand for high liquidity assets[12] Factor Name: Value - Factor Construction Idea: Book-to-market ratio (BP) and earnings yield (EP)[16] - Factor Construction Process: The factor is calculated using the book-to-market ratio and earnings yield[16] - Factor Evaluation: The factor shows limited recognition of value investment strategies[12] Factor Name: Growth - Factor Construction Idea: State-owned enterprise stock proportion[16] - Factor Construction Process: The factor is calculated using the proportion of state-owned enterprise stocks[16] - Factor Evaluation: The factor indicates the market's attention to state-owned enterprise stocks[12] Factor Name: Cubic Size - Factor Construction Idea: Market capitalization power term[16] - Factor Construction Process: The factor is calculated using the market capitalization power term[16] - Factor Evaluation: The factor shows the market's reduced attention to micro-cap stocks[12] Factor Name: Trend - Factor Construction Idea: EWMA with different half-lives[18] - Factor Construction Process: The factor is calculated using EWMA with half-lives of 20, 120, and 240 days, standard volatility, FF3 specific volatility, range, and maximum and minimum returns over the past 243 days[18] - Factor Evaluation: The factor indicates the market's reduced preference for trend investment strategies[12] Factor Name: Certainty - Factor Construction Idea: Sales growth, institutional holding percentage, net asset growth, analyst coverage, and listing days[18] - Factor Construction Process: The factor is calculated using sales growth, institutional holding percentage, net asset growth, analyst coverage, and listing days[18] - Factor Evaluation: The factor shows the market's reduced confidence in certainty investment strategies[12] Factor Performance Monitoring Performance in Different Index Spaces - CSI 300 Index: Factors like expected PEG, DELTAROE, and single-quarter EP performed well, while three-month reversal and one-month volatility performed poorly[7][24][26] - CSI 500 Index: Factors like one-year momentum and expected ROE change performed well, while three-month reversal and three-month institutional coverage performed poorly[7][28][30] - CSI 800 Index: Factors like expected ROE change and DELTAROE performed well, while one-month volatility and three-month reversal performed poorly[7][32][34] - CSI 1000 Index: Factors like DELTAROA and single-quarter net profit growth performed well, while public holding market value and standardized unexpected revenue performed poorly[7][36][37] - CNI 2000 Index: Factors like non-liquidity impact and expected PEG performed well, while public holding market value and one-month volatility performed poorly[7][39][41] - ChiNext Index: Factors like three-month earnings adjustment and single-quarter EP performed well, while expected net profit change and expected ROE change performed poorly[7][43][45] - CSI All Index: Factors like one-month UMR and one-month reversal performed well, while one-month volatility and three-month volatility performed poorly[7][47][50] Factor Backtesting Results CSI 300 Index - Expected PEG: 0.75% (recent week), 2.07% (recent month), 7.23% (year-to-date), 5.96% (annualized)[24] - DELTAROE: 0.73% (recent week), 2.19% (recent month), 7.91% (year-to-date), 5.07% (annualized)[24] - Single-quarter EP: 0.71% (recent week), 0.96% (recent month), 5.93% (year-to-date), 7.58% (annualized)[24] CSI 500 Index - One-year momentum: 0.84% (recent week), 2.33% (recent month), 3.83% (year-to-date), 3.00% (annualized)[28] - Expected ROE change: 0.76% (recent week), 0.28% (recent month), 6.15% (year-to-date), 7.67% (annualized)[28] - Three-month UMR: 0.74% (recent week), -0.38% (recent month), 0.29% (year-to-date), -1.06% (annualized)[28] CSI 800 Index - Expected ROE change: 0.93% (recent week), 1.76% (recent month), 2.27% (year-to-date), -3.20% (annualized)[32] - Expected PEG: 0.83% (recent week), 2.60% (recent month), 10.99% (year-to-date), 10.96% (annualized)[32] - DELTAROE: 0.79% (recent week), 2.64% (recent month), 11.60% (year-to-date), 8.99% (annualized)[32] CSI 1000 Index - DELTAROA: 0.63% (recent week), 1.57% (recent month), 8.06% (year-to-date), 15.10% (annualized)[36] - Single-quarter net profit growth: 0.57% (recent week), 1.03% (recent month), 8.04% (year-to-date), 10.77% (annualized)[36] - One-month UMR: 0.47% (recent week), -0.92% (recent month), 1.13% (year-to-date), -3.13% (annualized)[36] CNI 2000 Index - Non-liquidity impact: 1.26% (recent week), 1.99% (recent month), 12.11% (year-to-date), 21.51% (annualized)[39] - Expected PEG: 0.54% (recent week), 0.32% (recent month), 10.32% (year-to-date), 36.23% (annualized)[39] - Three-month institutional coverage: 0.54% (recent week), 4.56% (recent month), 5.41% (year-to-date), -1.19% (annualized)[39] ChiNext Index - Three-month earnings adjustment: 0.66% (recent week), 0.53% (recent month), -12.72% (year-to-date), -28.10% (annualized)[43] - Single-quarter EP: 0.66% (recent week), 0.69% (recent month), 2.90% (year-to-date), 24.70% (annualized)[43] - PB_ROE rank difference: 0.61% (recent week), -0.26% (