Quantitative Models and Construction Methods - **Model Name**: Multi-granularity model (5-day label) **Construction Idea**: The model leverages deep learning techniques to capture multi-granularity features in stock data over a 5-day horizon[70][66] **Construction Process**: Based on bidirectional AGRU (Attention Gated Recurrent Unit) training, the model combines historical data and predictive features to optimize stock selection[68][66] **Evaluation**: Demonstrates consistent positive returns across multiple testing periods[70][66] - **Model Name**: Multi-granularity model (10-day label) **Construction Idea**: Similar to the 5-day label model, but extends the horizon to 10 days for broader feature extraction[70][68] **Construction Process**: Utilizes bidirectional AGRU training, integrating longer-term predictive signals for enhanced stock selection[68][70] **Evaluation**: Provides robust performance with slightly lower returns compared to the 5-day label model[70][68] - **Model Name**: AI-enhanced index optimization models **Construction Idea**: Combines deep learning factors (multi-granularity models) with risk control constraints to optimize portfolio returns[70][71] **Construction Process**: 1. **Objective Function**: $$ max\sum\mu_{i}w_{i} $$, where \( w_i \) represents stock weights and \( \mu_i \) represents expected excess returns[74][75] 2. **Constraints**: Includes stock-level, industry-level, market capitalization, PB, ROE, and turnover rate constraints[71][74] **Evaluation**: Effective in balancing risk and return, with varying performance across different constraint levels[70][71] Model Backtesting Results - **Multi-granularity model (5-day label)**: - IC: Historical 0.079, 2026 0.046 - RankMAE: Historical 0.343, 2026 0.337 - Multi-long-short returns: 8.05% (2026), 0.43% (March)[10][13][70] - **Multi-granularity model (10-day label)**: - IC: Historical 0.073, 2026 0.044 - RankMAE: Historical 0.342, 2026 0.340 - Multi-long-short returns: 6.25% (2026), 0.42% (March)[10][13][70] - **AI-enhanced index optimization models**: - **Air Quality Index Model**: - Weekly excess returns: 4.28% (2026), 0.55% (March) - Daily excess returns: 5.51% (2026), 0.61% (March)[79][76][70] - **CSI 500 Wide Constraint Model**: - Weekly excess returns: -0.93% (2026), 2.61% (March) - Daily excess returns: -4.25% (2026), 0.73% (March)[82][81][70] - **CSI 500 Strict Constraint Model**: - Weekly excess returns: 1.02% (2026), 2.09% (March) - Daily excess returns: 0.42% (2026), 1.29% (March)[84][83][70] - **CSI 1000 Wide Constraint Model**: - Weekly excess returns: 2.98% (2026), 2.43% (March) - Daily excess returns: 2.54% (2026), 2.36% (March)[88][87][70] - **CSI 1000 Strict Constraint Model**: - Weekly excess returns: 2.34% (2026), 1.33% (March) - Daily excess returns: 3.10% (2026), 1.25% (March)[93][91][70] Quantitative Factors and Construction Methods - **Factor Name**: Intraday skewness factor **Construction Idea**: Captures the asymmetry in intraday stock return distributions[15][17] **Construction Process**: Referenced from the report "Stock Selection Factor Series Research (19)"[15][17] **Evaluation**: Strong performance in capturing short-term market movements[15][17] - **Factor Name**: Downside volatility proportion factor **Construction Idea**: Measures the proportion of realized downside volatility in stock returns[20][22] **Construction Process**: Referenced from the report "Stock Selection Factor Series Research (25)"[20][22] **Evaluation**: Effective in identifying risk-averse stocks[20][22] - **Factor Name**: Opening buy intention proportion factor **Construction Idea**: Quantifies the proportion of buy orders during the opening period[23][27] **Construction Process**: Referenced from the report "Stock Selection Factor Series Research (64)"[23][27] **Evaluation**: Demonstrates strong predictive power for short-term returns[23][27] Factor Backtesting Results - **Intraday skewness factor**: - IC: Historical 0.026, 2026 0.036 - RankMAE: Historical 0.324, 2026 0.334 - Multi-long-short returns: 3.69% (2026), -0.62% (March)[10][11][15] - **Downside volatility proportion factor**: - IC: Historical 0.025, 2026 0.043 - RankMAE: Historical 0.324, 2026 0.333 - Multi-long-short returns: 5.65% (2026), -0.17% (March)[10][11][20] - **Opening buy intention proportion factor**: - IC: Historical 0.031, 2026 0.043 - RankMAE: Historical 0.322, 2026 0.326 - Multi-long-short returns: 4.27% (2026), 1.30% (March)[10][11][23]

Investment Rating - The report indicates a positive performance of large order factors and stable performance of multi-granularity factors, with AI-enhanced portfolios showing strong results [2][3]. Core Insights - The report highlights the differentiation in high-frequency factors, with large order factors performing well. The AI-enhanced portfolio continues to show strong performance [2][3]. - The multi-granularity factors have maintained stable performance, with significant returns reported for both 5-day and 10-day label models [6][9]. - The AI-enhanced portfolios have demonstrated substantial excess and absolute returns across various combinations, indicating effective investment strategies [14][73]. Summary by Sections High-Frequency Factors and Deep Learning Factors - High-frequency skewness factor reported a multi-directional return of -1.11% for the last week and 2.89% for February 2026 [6][10]. - The downward volatility proportion factor showed a return of -0.61% for the last week and 4.14% for February 2026 [6][10]. - The opening buy intention proportion factor had a return of -0.04% for the last week and 3.82% for February 2026 [6][10]. - The opening large order net buy proportion factor reported a return of 0.34% for the last week and 2.89% for February 2026 [6][10]. - The AI-enhanced portfolios, including the weekly rebalancing AI air value increase portfolio, reported excess returns of 3.63% and absolute returns of 3.29% for the last week [14][73]. Multi-Granularity Factors - The multi-granularity model (5-day label) reported a multi-directional return of 0.65% for the last week and 6.15% for February 2026 [6][10]. - The multi-granularity model (10-day label) reported a multi-directional return of 0.53% for the last week and 4.60% for February 2026 [6][10]. AI Enhanced Portfolios - The weekly rebalancing of the CSI 500 AI enhanced wide constraint portfolio reported an excess return of 2.25% and an absolute return of -0.42% for the last week [14][73]. - The daily rebalancing of the CSI 1000 AI enhanced strict constraint portfolio reported an excess return of 1.65% and an absolute return of -0.82% for the last week [14][73].