Quantitative Models and Construction Methods 1. **Model Name**: CSI 300 Enhanced Portfolio - **Model Construction Idea**: The model aims to achieve excess returns over the CSI 300 Index by leveraging quantitative strategies and factor-based stock selection - **Model Construction Process**: The model is constructed by selecting stocks from the CSI 300 Index based on specific quantitative factors and optimizing the portfolio to maximize excess returns while managing risk. The exact factors and optimization techniques are not detailed in the report - **Model Evaluation**: The model has shown consistent performance in generating excess returns over the CSI 300 Index in the year-to-date period[5][9][15] 2. **Model Name**: CSI 500 Enhanced Portfolio - **Model Construction Idea**: The model seeks to outperform the CSI 500 Index by utilizing quantitative strategies and factor-based stock selection - **Model Construction Process**: Stocks are selected from the CSI 500 Index based on quantitative factors, and the portfolio is optimized to achieve excess returns while controlling risk. Specific details of the factors and optimization are not provided in the report - **Model Evaluation**: The model's performance has been mixed, with negative excess returns in the year-to-date period[5][9][15] 3. **Model Name**: CSI 1000 Enhanced Portfolio - **Model Construction Idea**: The model aims to generate excess returns over the CSI 1000 Index through quantitative strategies and factor-based stock selection - **Model Construction Process**: Stocks are selected from the CSI 1000 Index using quantitative factors, and the portfolio is optimized to maximize excess returns while managing risk. Specific details of the factors and optimization are not provided in the report - **Model Evaluation**: The model has demonstrated positive excess returns in the year-to-date period[5][9][15] 4. **Model Name**: PB-Profit Combination Portfolio - **Model Construction Idea**: The portfolio combines price-to-book (PB) ratio and profitability factors to identify undervalued stocks with strong earnings potential - **Model Construction Process**: The portfolio is constructed by selecting stocks with low PB ratios and high profitability metrics. The exact methodology for combining these factors is not detailed in the report - **Model Evaluation**: The portfolio has shown strong performance, with significant positive excess returns over the CSI 300 Index in the year-to-date period[5][31][33] 5. **Model Name**: GARP Portfolio - **Model Construction Idea**: The portfolio follows the Growth at a Reasonable Price (GARP) strategy, focusing on stocks with a balance of growth and valuation metrics - **Model Construction Process**: Stocks are selected based on a combination of growth and valuation factors. The specific factors and their weights are not detailed in the report - **Model Evaluation**: The portfolio has achieved significant positive excess returns over the CSI 300 Index in the year-to-date period[5][35] 6. **Model Name**: Small-Cap Value Portfolio 1 - **Model Construction Idea**: The portfolio targets small-cap stocks with value characteristics, aiming to outperform the micro-cap index - **Model Construction Process**: Stocks are selected based on small-cap and value factors. The exact methodology for combining these factors is not detailed in the report - **Model Evaluation**: The portfolio has underperformed the micro-cap index in the year-to-date period[5][37] 7. **Model Name**: Small-Cap Value Portfolio 2 - **Model Construction Idea**: Similar to Small-Cap Value Portfolio 1, this portfolio focuses on small-cap stocks with value characteristics - **Model Construction Process**: Stocks are selected based on small-cap and value factors. The exact methodology for combining these factors is not detailed in the report - **Model Evaluation**: The portfolio has outperformed the micro-cap index in the year-to-date period[5][39] 8. **Model Name**: Small-Cap Growth Portfolio - **Model Construction Idea**: The portfolio targets small-cap stocks with growth characteristics, aiming to outperform the micro-cap index - **Model Construction Process**: Stocks are selected based on small-cap and growth factors. The exact methodology for combining these factors is not detailed in the report - **Model Evaluation**: The portfolio has underperformed the micro-cap index in the year-to-date period[5][41] --- Model Backtesting Results 1. **CSI 300 Enhanced Portfolio** - Weekly return: -0.39% - Weekly excess return: -0.47% - Year-to-date return: 6.85% - Year-to-date excess return: 5.20%[9][15] 2. **CSI 500 Enhanced Portfolio** - Weekly return: -1.74% - Weekly excess return: 0.82% - Year-to-date return: 11.11% - Year-to-date excess return: -1.01%[9][15] 3. **CSI 1000 Enhanced Portfolio** - Weekly return: -0.97% - Weekly excess return: 1.58% - Year-to-date return: 11.99% - Year-to-date excess return: 3.31%[9][15] 4. **PB-Profit Combination Portfolio** - Weekly return: 0.92% - Weekly excess return: 0.84% - Year-to-date return: 6.17% - Year-to-date excess return: 4.52%[31][33] 5. **GARP Portfolio** - Weekly return: 0.95% - Weekly excess return: 0.87% - Year-to-date return: 11.43% - Year-to-date excess return: 9.78%[35] 6. **Small-Cap Value Portfolio 1** - Weekly return: -2.44% - Weekly excess return: -1.29% - Year-to-date return: 7.89% - Year-to-date excess return: -2.83%[37] 7. **Small-Cap Value Portfolio 2** - Weekly return: -1.64% - Weekly excess return: -0.48% - Year-to-date return: 12.37% - Year-to-date excess return: 1.66%[39] 8. **Small-Cap Growth Portfolio** - Weekly return: -2.07% - Weekly excess return: -0.92% - Year-to-date return: 9.13% - Year-to-date excess return: -1.59%[41] --- Quantitative Factors and Construction Methods 1. **Factor Name**: Market Capitalization (Size) Factor - **Construction Idea**: Small-cap stocks tend to outperform large-cap stocks over time - **Construction Process**: Stocks are ranked by market capitalization, and the top 10% (smallest) and bottom 10% (largest) are selected to form long and short portfolios, respectively. The difference in returns between these portfolios represents the factor's performance - **Evaluation**: The factor has shown mixed performance across different indices and time periods[43][44][45] 2. **Factor Name**: Price-to-Book (PB) Factor - **Construction Idea**: Low PB stocks are expected to outperform high PB stocks - **Construction Process**: Stocks are ranked by PB ratio, and the top 10% (lowest PB) and bottom 10% (highest PB) are selected to form long and short portfolios, respectively. The difference in returns between these portfolios represents the factor's performance - **Evaluation**: The factor has shown strong performance in the short term but mixed results in the year-to-date period[43][44][45] 3. **Factor Name**: Price-to-Earnings (PE_TTM) Factor - **Construction Idea**: Low PE stocks are expected to outperform high PE stocks - **Construction Process**: Stocks are ranked by PE ratio, and the top 10% (lowest PE) and bottom 10% (highest PE) are selected to form long and short portfolios, respectively. The difference in returns between these portfolios represents the factor's performance - **Evaluation**: The factor has shown positive short-term performance but mixed year-to-date results[43][44][45] 4. **Factor Name**: Reversal Factor - **Construction Idea**: Stocks with recent underperformance are expected to outperform in the short term - **Construction Process**: Stocks are ranked by recent performance, and the top 10% (worst performers) and bottom 10% (best performers) are selected to form long and short portfolios, respectively. The difference in returns between these portfolios represents the factor's performance - **Evaluation**: The factor has shown positive short-term performance but negative year-to-date results[49][50] 5. **Factor Name**: Turnover Factor - **Construction Idea**: Stocks with lower turnover rates are expected to outperform those with higher turnover rates - **Construction Process**: Stocks are ranked by turnover rate, and the top 10% (lowest turnover) and bottom 10% (highest turnover) are selected to form long and short portfolios, respectively. The difference in returns between these portfolios represents the factor's performance - **Evaluation**: The factor has shown strong short-term performance but negative year-to-date results[49][50] 6. **Factor Name**: Volatility Factor - **Construction Idea**

- The report highlights the performance of the quantitative stock portfolios, including the CSI 300 enhanced portfolio, which achieved a weekly excess return of 2.16% and a cumulative excess return of 5.70% in 2026[1][15][14] - The CSI 500 enhanced portfolio recorded a weekly excess return of 0.38% and a cumulative excess return of -1.98% in 2026[15][14][17] - The CSI 1000 enhanced portfolio achieved a weekly excess return of 0.96% and a cumulative excess return of 1.56% in 2026[15][14][24] - The PB-Earnings optimized portfolio delivered a weekly excess return of 4.05% and a cumulative excess return of 3.64% in 2026[30][31][32] - The GARP portfolio achieved a weekly excess return of 5.85% and a cumulative excess return of 8.81% in 2026[33][34] - The Small-cap Value Optimized Portfolio 1 recorded a weekly excess return of -0.75% and a cumulative excess return of -1.42% in 2026[35][36] - The Small-cap Value Optimized Portfolio 2 achieved a weekly excess return of 0.70% and a cumulative excess return of 2.23% in 2026[37][38] - The Small-cap Growth Portfolio delivered a weekly excess return of -0.24% and a cumulative excess return of -0.57% in 2026[39][40] - Style factors showed that small-cap stocks outperformed large-cap stocks, and low valuation stocks outperformed high valuation stocks. The market capitalization factor achieved a weekly multi-long-short return of 2.83%, while the PB factor and PE_TTM factor achieved 1.05% and 0.71%, respectively[42][43][45] - Technical factors indicated positive contributions from turnover rate factors, while reversal and volatility factors showed negative returns. The turnover rate factor achieved a weekly multi-long-short return of 0.48%, while reversal and volatility factors recorded -2.05% and -0.98%, respectively[46][48][49] - Fundamental factors demonstrated positive returns from SUE and adjusted net profit expectation factors. The SUE factor achieved a weekly multi-long-short return of 0.82%, while adjusted net profit expectation factors recorded 0.47%. ROE factors showed a negative return of -0.67%[50][51][52]

Quantitative Models and Construction Methods - **Model Name**: CSI 300 Enhanced Portfolio **Model Construction Idea**: The model aims to enhance the performance of the CSI 300 Index by leveraging quantitative strategies to generate excess returns over the benchmark index[5][9][15] **Model Construction Process**: The portfolio is constructed by applying quantitative stock selection and weighting methodologies to the CSI 300 Index constituents. The process involves identifying stocks with favorable factor exposures and optimizing the portfolio to maximize risk-adjusted returns while maintaining a low tracking error relative to the benchmark[9][15] **Model Evaluation**: The model demonstrated strong performance with positive excess returns over the benchmark index, indicating effective factor utilization and portfolio construction[15] - **Model Name**: CSI 500 Enhanced Portfolio **Model Construction Idea**: Similar to the CSI 300 Enhanced Portfolio, this model focuses on enhancing the performance of the CSI 500 Index by employing quantitative strategies[5][9][15] **Model Construction Process**: The portfolio is built by selecting stocks from the CSI 500 Index based on quantitative factors and optimizing the portfolio to achieve excess returns while controlling tracking error[9][15] **Model Evaluation**: The model underperformed the benchmark index during the observed period, suggesting potential challenges in factor effectiveness or market conditions[15] - **Model Name**: CSI 1000 Enhanced Portfolio **Model Construction Idea**: This model targets the CSI 1000 Index, aiming to generate excess returns through quantitative enhancements[5][9][15] **Model Construction Process**: The portfolio construction involves selecting stocks from the CSI 1000 Index using quantitative factors and optimizing the portfolio for risk-adjusted returns and low tracking error[9][15] **Model Evaluation**: The model showed a slight underperformance relative to the benchmark index, indicating room for improvement in factor application or portfolio optimization[15] - **Model Name**: GARP Portfolio **Model Construction Idea**: The GARP (Growth at a Reasonable Price) portfolio combines growth and valuation factors to identify stocks with strong growth potential at reasonable valuations[32] **Model Construction Process**: Stocks are selected based on a combination of growth metrics (e.g., earnings growth) and valuation metrics (e.g., price-to-earnings ratio). The portfolio is then optimized to balance growth and valuation exposures[32] **Model Evaluation**: The portfolio achieved positive excess returns over the CSI 300 Index, demonstrating the effectiveness of the GARP strategy in the observed period[32] - **Model Name**: Small-Cap Growth Portfolio **Model Construction Idea**: This portfolio focuses on small-cap stocks with strong growth characteristics, aiming to capture the growth premium in the small-cap segment[37] **Model Construction Process**: Stocks are selected from the small-cap universe based on growth factors such as earnings growth and revenue growth. The portfolio is optimized to maximize growth exposure while managing risk[37] **Model Evaluation**: The portfolio delivered positive excess returns over the micro-cap index, indicating the effectiveness of the growth factor in the small-cap segment[37] Model Backtesting Results - **CSI 300 Enhanced Portfolio**: Weekly return 4.69%, excess return 1.90%, tracking error 4.71%, maximum drawdown 1.68%[9][15][22] - **CSI 500 Enhanced Portfolio**: Weekly return 6.34%, excess return -1.58%, tracking error 4.07%, maximum drawdown 3.11%[9][15][16] - **CSI 1000 Enhanced Portfolio**: Weekly return 6.17%, excess return -0.86%, tracking error 5.31%, maximum drawdown 4.45%[9][15][18] - **GARP Portfolio**: Weekly return 3.62%, excess return 0.84%, tracking error 13.93%, maximum drawdown 4.04%[32][33] - **Small-Cap Growth Portfolio**: Weekly return 4.95%, excess return 0.49%, tracking error 11.60%, maximum drawdown 9.76%[37][40] Quantitative Factors and Construction Methods - **Factor Name**: Market Capitalization (Size) Factor **Factor Construction Idea**: This factor captures the size effect, where smaller companies tend to outperform larger companies over time[42] **Factor Construction Process**: Stocks are ranked by their market capitalization, and the top 10% (large-cap) and bottom 10% (small-cap) are selected to form long and short portfolios, respectively. The difference in returns between these portfolios represents the size factor's performance[41][42] **Factor Evaluation**: The factor showed mixed performance, with large-cap stocks outperforming small-cap stocks in the observed period[42] - **Factor Name**: Price-to-Book Ratio (PB) Factor **Factor Construction Idea**: This factor identifies undervalued stocks based on their price-to-book ratios[42] **Factor Construction Process**: Stocks are ranked by their PB ratios, and the top 10% (high PB) and bottom 10% (low PB) are selected to form long and short portfolios, respectively. The difference in returns between these portfolios represents the PB factor's performance[41][42] **Factor Evaluation**: The factor underperformed during the observed period, with high PB stocks outperforming low PB stocks[42] - **Factor Name**: Expected Net Profit Adjustment Factor **Factor Construction Idea**: This factor captures the impact of expected net profit adjustments on stock performance[53] **Factor Construction Process**: Stocks are ranked by their expected net profit adjustments, and the top 10% (high adjustment) and bottom 10% (low adjustment) are selected to form long and short portfolios, respectively. The difference in returns between these portfolios represents the factor's performance[41][53] **Factor Evaluation**: The factor delivered positive returns, indicating its effectiveness in identifying stocks with favorable profit adjustments[53] Factor Backtesting Results - **Market Capitalization (Size) Factor**: Multi-market excess returns: -0.79% (All Market), 4.83% (CSI 300), -5.59% (CSI 500), -2.47% (CSI 1000)[42][43][48] - **Price-to-Book Ratio (PB) Factor**: Multi-market excess returns: -4.01% (All Market), -5.52% (CSI 300), -6.06% (CSI 500), -5.68% (CSI 1000)[42][43][48] - **Expected Net Profit Adjustment Factor**: Multi-market excess returns: 0.57% (All Market), 0.86% (CSI 300), 1.89% (CSI 500), -0.58% (CSI 1000)[53][54][55]

Group 1 - The public fund investment strategy shows robust growth in both scale and number, with active equity funds achieving an average return of 29.69% in 2025, outperforming major indices [2][23][27] - The top three sectors for active equity fund holdings are technology, manufacturing, and cyclical industries, indicating a strong focus on growth-oriented sectors [2][28] - The market outlook for 2026 suggests continued structural opportunities in A-shares, with technology growth remaining a key theme, while Hong Kong stocks are seen as undervalued [2][3] Group 2 - The index fund market has reached a historical high in both scale and number, with total assets amounting to 6.14 trillion yuan, reflecting a significant increase of 32.27% from the previous year [2][37][40] - The ETF segment dominates the index fund market, accounting for 76.10% of total assets, with a notable increase in industry-themed ETFs [2][38][40] - The performance of thematic funds, particularly in technology, has been outstanding, with technology-themed funds achieving an average return of 44.06% in 2025 [2][27][28]

Core Insights - The report highlights that the market indices have shown positive performance, with the Shanghai Composite Index rising by 1.70% and the Shenzhen Component Index increasing by 4.55% as of August 15, 2025, marking a new high since 2022 [5][8] - The report emphasizes the construction of an AI-based low-frequency index enhancement strategy using deep learning frameworks, which has resulted in significant outperformance of enhanced index portfolios compared to their respective benchmarks [5][13] Market Index Performance - As of August 15, 2025, the Shanghai Composite Index increased by 1.70%, the Shenzhen Component Index by 4.55%, and the CSI 300 Index by 2.37%, with the Shanghai Composite Index reaching a new high since 2022 [5][9] - Year-to-date performance shows the CSI 300 Index up by 6.8%, while the CSI 300 enhanced portfolio has risen by 17.1%, yielding an excess return of 10.3% [5][17] - The CSI 500 Index has increased by 14.7% year-to-date, with its enhanced portfolio up by 21.6%, resulting in an excess return of 6.9% [5][22] - The CSI 1000 Index has seen a year-to-date increase of 19.5%, with its enhanced portfolio rising by 29.4%, leading to an excess return of 9.9% [5][29] Enhanced Portfolio Performance - The report details the performance of the CSI 300 enhanced portfolio, which has achieved a return of 17.1% year-to-date compared to the CSI 300's 6.8% [17][18] - The CSI 500 enhanced portfolio has delivered a year-to-date return of 21.6%, outperforming the CSI 500's 14.7% [22][23] - The CSI 1000 enhanced portfolio has recorded a year-to-date return of 29.4%, significantly higher than the CSI 1000's 19.5% [29][30] Sector Performance - The report notes that the telecommunications, electronics, and non-bank financial sectors performed well this week, with weekly returns of 7.66%, 7.02%, and 6.48% respectively [9][10] - Conversely, the banking, steel, and textile sectors underperformed, with weekly returns of -3.19%, -2.04%, and -1.37% respectively [9][10]

Group 1: Weekly Index Enhanced Portfolio Performance - The CSI 300 index enhanced portfolio achieved an excess return of 1.06% this week and 4.21% year-to-date [1][5] - The CSI 500 index enhanced portfolio recorded an excess return of -0.05% this week and 6.45% year-to-date [1][5] - The CSI 1000 index enhanced portfolio had an excess return of 0.72% this week and 9.41% year-to-date [1][5] - The CSI A500 index enhanced portfolio reported an excess return of 0.36% this week and 6.44% year-to-date [1][5] Group 2: Stock Selection Factor Performance Tracking - In the CSI 300 component stocks, factors such as three-month volatility, one-month volatility, and standardized unexpected earnings performed well [1][6] - In the CSI 500 component stocks, factors like quarterly revenue growth year-on-year, standardized unexpected revenue, and non-liquidity shocks showed strong performance [1][6] - For the CSI 1000 component stocks, factors such as EPTTM one-year percentile, SPTTM, and BP performed well [1][6] - In the CSI A500 index component stocks, factors like BP, quarterly EP, and three-month volatility showed good performance [1][6] - Among publicly offered fund heavy stocks, factors like quarterly unexpected magnitude, standardized unexpected earnings, and standardized unexpected revenue performed well [1][6] Group 3: Public Fund Index Enhanced Product Performance Tracking - The CSI 300 index enhanced products had a maximum excess return of 1.37%, a minimum of -0.21%, and a median of 0.32% this week [1][19] - The CSI 500 index enhanced products had a maximum excess return of 0.92%, a minimum of -0.09%, and a median of 0.35% this week [1][20] - The CSI 1000 index enhanced products had a maximum excess return of 0.98%, a minimum of -0.21%, and a median of 0.24% this week [1][22] - The CSI A500 index enhanced products had a maximum excess return of 0.70%, a minimum of -0.19%, and a median of 0.36% this week [1][24]

Group 1 - The core viewpoint of the article is to track the performance of index enhancement portfolios and the effectiveness of various stock selection factors across different indices [1][2][3] Group 2 - The performance of the HuShen 300 index enhancement portfolio showed an excess return of 0.37% for the week and 2.84% year-to-date [5] - The performance of the Zhongzheng 500 index enhancement portfolio showed an excess return of 1.06% for the week and 5.87% year-to-date [5] - The Zhongzheng 1000 index enhancement portfolio had an excess return of 1.73% for the week and 8.10% year-to-date [5] - The Zhongzheng A500 index enhancement portfolio reported an excess return of 0.53% for the week and 5.78% year-to-date [5] Group 3 - In the HuShen 300 component stocks, factors such as one-month reversal, expected PEG, and expected EPTTM performed well [6] - In the Zhongzheng 500 component stocks, one-month reversal, single-quarter SP, and SPTTM factors showed strong performance [6] - For Zhongzheng 1000 component stocks, factors like DELTAROA, executive compensation, and standardized expected external earnings performed well [6] - In the Zhongzheng A500 index component stocks, three-month reversal, single-quarter ROE, and one-month reversal factors were effective [6] - Among public fund heavy stocks, one-month reversal, three-month reversal, and single-quarter EP factors performed well [6] Group 4 - The HuShen 300 index enhancement products had a maximum excess return of 1.10%, a minimum of -0.76%, and a median of 0.06% for the week [19] - The Zhongzheng 500 index enhancement products had a maximum excess return of 0.99%, a minimum of -0.08%, and a median of 0.40% for the week [21] - The Zhongzheng 1000 index enhancement products had a maximum excess return of 0.81%, a minimum of -0.28%, and a median of 0.26% for the week [20] - The Zhongzheng A500 index enhancement products had a maximum excess return of 0.39%, a minimum of -0.52%, and a median of 0.23% for the week [22] Group 5 - The total number of public fund HuShen 300 index enhancement products is 67, with a total scale of 778 billion [16] - There are 70 Zhongzheng 500 index enhancement products with a total scale of 454 billion [16] - The Zhongzheng 1000 index enhancement products consist of 46 products with a total scale of 150 billion [16] - The Zhongzheng A500 index enhancement products have 35 products with a total scale of 223 billion [16]