Core Insights - The significant transformation in the fund industry in 2025 is characterized by the remarkable growth of passive investment, particularly in enhanced index funds, which have seen a 319% increase in new fund establishments compared to 2024, reaching a total issuance of 96.17 billion units [1] - Tianhong Fund has strategically positioned itself in the enhanced index space, leveraging AI technology and a systematic research and investment capability to create a comprehensive and robust product matrix, achieving a place among the "billion-dollar club" in the industry [1][5] Group 1: Enhanced Index Fund Growth - As of December 25, 2025, 176 new equity-enhanced index funds were established, a significant increase from 42 in 2024, indicating a shift towards quality-focused asset management [1] - The total issuance of enhanced index funds reached 96.17 billion units, nearing the 100 billion mark, highlighting the growing acceptance and demand for these investment vehicles [1] Group 2: Tianhong Fund's Strategic Positioning - Tianhong Fund has been developing its enhanced index strategy since 2015, launching its first product in 2019 and expanding its offerings to five new products in 2025, indicating a robust growth trajectory [2] - The fund's product matrix includes a wide range of enhanced index funds covering major indices and sectors, catering to diverse asset allocation needs [2][3] Group 3: Performance and Risk Management - As of September 30, 2025, over 90% of investors holding Tianhong's enhanced index products for more than six months outperformed their respective benchmarks, demonstrating the effectiveness of the fund's strategies [5] - Tianhong's enhanced index products have shown strong performance, with the Tianhong CSI Technology 100 Enhanced A achieving a return of 56.51%, exceeding its benchmark by 5.42 percentage points over the past year [5] Group 4: Research and AI Integration - Tianhong Fund emphasizes a systematic approach to research and investment, utilizing a comprehensive quantitative research framework that integrates AI technology to enhance alpha generation and risk management [7][10] - The integration of AI allows for the identification of hidden excess factors and improves risk control, resulting in reduced volatility and better risk-adjusted returns for investors [10][12]

Group 1: Weekly Index Enhanced Portfolio Performance - The CSI 300 index enhanced portfolio achieved an excess return of 0.51% this week and 21.85% year-to-date [7] - The CSI 500 index enhanced portfolio recorded an excess return of -0.73% this week and 6.17% year-to-date [7] - The CSI 1000 index enhanced portfolio had an excess return of -1.12% this week and 15.93% year-to-date [7] - The CSI A500 index enhanced portfolio saw an excess return of -0.28% this week and 10.62% year-to-date [7] Group 2: Factor Performance Tracking - In the CSI 300 component stocks, factors such as one-year momentum, standardized unexpected earnings, and expected net profit quarter-on-quarter performed well [10] - In the CSI 500 component stocks, factors like expected net profit quarter-on-quarter, standardized unexpected earnings, and DELTAROE showed strong performance [10] - For the CSI 1000 component stocks, factors including one-month reversal, single-quarter revenue year-on-year growth, and standardized unexpected income performed well [10] - In the CSI A500 index component stocks, factors such as expected net profit quarter-on-quarter, one-year momentum, and standardized unexpected earnings performed well [10] Group 3: Public Fund Index Enhanced Product Performance Tracking - The CSI 300 index enhanced products had a maximum excess return of 1.61%, a minimum of -0.73%, and a median of 0.01% this week [23] - The CSI 500 index enhanced products had a maximum excess return of 0.79%, a minimum of -2.23%, and a median of -0.49% this week [25] - The CSI 1000 index enhanced products had a maximum excess return of 1.74%, a minimum of -1.55%, and a median of -0.15% this week [24] - The CSI A500 index enhanced products had a maximum excess return of 0.97%, a minimum of -1.15%, and a median of -0.12% this week [28] Group 4: Public Fund Index Enhanced Product Scale - There are currently 79 CSI 300 index enhanced products with a total scale of 79.9 billion [20] - There are 76 CSI 500 index enhanced products with a total scale of 51.4 billion [20] - There are 46 CSI 1000 index enhanced products with a total scale of 21.4 billion [20] - There are 71 CSI A500 index enhanced products with a total scale of 26.3 billion [20]

Quantitative Models and Factor Analysis Quantitative Models and Construction Methods Model Name: Guosen JinGong Index Enhanced Portfolio - **Model Construction Idea**: The model aims to outperform its respective benchmarks by constructing enhanced portfolios based on multiple factors[10]. - **Model Construction Process**: - **Return Prediction**: Predicting the returns of stocks within the benchmark index. - **Risk Control**: Implementing risk control measures to manage the portfolio's risk exposure. - **Portfolio Optimization**: Optimizing the portfolio to maximize returns while adhering to the risk constraints[11]. - **Model Evaluation**: The model is designed to consistently outperform its benchmarks by leveraging multiple factors and optimizing the portfolio accordingly[10][11]. Model Backtesting Results - **Guosen JinGong Index Enhanced Portfolio**: - **CSI 300 Index Enhanced Portfolio**: Weekly excess return 0.51%, annual excess return 21.85%[4][13]. - **CSI 500 Index Enhanced Portfolio**: Weekly excess return -0.73%, annual excess return 6.17%[4][13]. - **CSI 1000 Index Enhanced Portfolio**: Weekly excess return -1.12%, annual excess return 15.93%[4][13]. - **CSI A500 Index Enhanced Portfolio**: Weekly excess return -0.28%, annual excess return 10.62%[4][13]. Quantitative Factors and Construction Methods Factor Name: Momentum - **Factor Construction Idea**: The momentum factor captures the tendency of stocks that have performed well in the past to continue performing well in the future[15]. - **Factor Construction Process**: - **One-Year Momentum**: Calculated as the return of a stock over the past year, excluding the most recent month[15]. - **Formula**: $ \text{One-Year Momentum} = \text{Return}_{t-12} - \text{Return}_{t-1} $[15]. - **Factor Evaluation**: The momentum factor is effective in identifying stocks with strong past performance that are likely to continue performing well[15]. Factor Name: Standardized Unexpected Earnings (SUE) - **Factor Construction Idea**: The SUE factor measures the difference between actual and expected earnings, standardized by the standard deviation of expected earnings[15]. - **Factor Construction Process**: - **SUE Calculation**: $ \text{SUE} = \frac{\text{Actual Earnings} - \text{Expected Earnings}}{\text{Standard Deviation of Expected Earnings}} $[15]. - **Factor Evaluation**: The SUE factor is useful in identifying stocks with earnings surprises, which can lead to significant price movements[15]. Factor Name: Expected Net Profit QoQ - **Factor Construction Idea**: This factor measures the quarter-over-quarter change in expected net profit[15]. - **Factor Construction Process**: - **Calculation**: $ \text{Expected Net Profit QoQ} = \frac{\text{Expected Net Profit}_{t} - \text{Expected Net Profit}_{t-1}}{\text{Expected Net Profit}_{t-1}} $[15]. - **Factor Evaluation**: The factor is effective in identifying stocks with improving earnings expectations, which can lead to positive price movements[15]. Factor Backtesting Results - **CSI 300 Index**: - **One-Year Momentum**: Weekly excess return 1.09%, monthly excess return 2.08%, annual excess return 3.27%, historical annualized return 2.75%[18]. - **Standardized Unexpected Earnings**: Weekly excess return 0.87%, monthly excess return 2.24%, annual excess return 12.16%, historical annualized return 4.18%[18]. - **Expected Net Profit QoQ**: Weekly excess return 0.86%, monthly excess return 1.50%, annual excess return 6.56%, historical annualized return 1.72%[18]. - **CSI 500 Index**: - **Expected Net Profit QoQ**: Weekly excess return 0.73%, monthly excess return 1.98%, annual excess return 15.82%, historical annualized return 4.80%[20]. - **Standardized Unexpected Earnings**: Weekly excess return 0.72%, monthly excess return 2.48%, annual excess return 18.17%, historical annualized return 4.51%[20]. - **DELTAROE**: Weekly excess return 0.57%, monthly excess return 2.27%, annual excess return 11.09%, historical annualized return 5.36%[20]. - **CSI 1000 Index**: - **One-Month Reversal**: Weekly excess return 1.23%, monthly excess return 0.00%, annual excess return -2.94%, historical annualized return -3.76%[22]. - **Single-Quarter Revenue YoY Growth**: Weekly excess return 1.08%, monthly excess return 3.27%, annual excess return 23.01%, historical annualized return 5.16%[22]. - **Standardized Unexpected Revenue**: Weekly excess return 0.66%, monthly excess return 2.21%, annual excess return 21.47%, historical annualized return 6.55%[22]. - **CSI A500 Index**: - **Expected Net Profit QoQ**: Weekly excess return 1.89%, monthly excess return 1.49%, annual excess return 8.61%, historical annualized return 3.73%[24]. - **One-Year Momentum**: Weekly excess return 1.39%, monthly excess return 2.42%, annual excess return 2.76%, historical annualized return 1.81%[24]. - **Standardized Unexpected Earnings**: Weekly excess return 1.28%, monthly excess return 3.29%, annual excess return 14.02%, historical annualized return 5.92%[24]. - **Public Fund Heavyweight Index**: - **One-Year Momentum**: Weekly excess return 1.61%, monthly excess return 2.90%, annual excess return 4.13%, historical annualized return 15.48%[26]. - **Expected Net Profit QoQ**: Weekly excess return 0.70%, monthly excess return 2.31%, annual excess return 3.36%, historical annualized return 11.90%[26]. - **Single-Quarter Net Profit YoY Growth**: Weekly excess return 0.58%, monthly excess return 2.13%, annual excess return 2.95%, historical annualized return 9.10%[26].

Core Insights - The article emphasizes the importance of selecting the right index-enhanced funds, focusing on the dual benefits of "Beta base + Alpha excess" returns [3] - The stability and sustainability of excess returns are highlighted as the only hard standard for evaluating these funds [4] Performance Analysis - The China Securities 1000 Index Enhanced Fund has shown the strongest excess performance over the past three years [5] - The Guotai Haitong China Securities 1000 Index Enhanced A fund achieved a return of 57.67% over three years, significantly outperforming its benchmark of 14.46%, resulting in an excess return of over 43% [6] - The招商中证1000指数增强A fund recorded a three-year return of 40.39%, exceeding its benchmark by over 25%, and a five-year return of 58.75%, which is more than five times its benchmark of 11.73% [6] Fund Management Capabilities - The article outlines that the excess returns from quality index-enhanced funds are not due to luck but stem from the fund company's research and investment capabilities [7] - A comprehensive product line that covers various market segments is essential, avoiding reliance on a single sector [7] - The ability to customize strategies based on the characteristics of the index is crucial for identifying investment opportunities [7] - A strong research team with expertise in financial engineering, risk management, and information technology is necessary to adapt strategies dynamically [7]

Quantitative Models and Construction Methods Model Name: Maximized Factor Exposure Portfolio (MFE) - **Model Construction Idea**: The MFE portfolio is designed to maximize the exposure of a single factor while controlling for various constraints such as industry exposure, style exposure, stock weight deviation, and turnover rate. This approach ensures that the factor's predictive power is tested under realistic portfolio constraints, making it more applicable in practical investment scenarios [40][41]. - **Model Construction Process**: - The optimization model is formulated as follows: $$ \begin{array}{ll} \text{max} & f^{T}w \\ \text{s.t.} & s_{l} \leq X(w-w_{b}) \leq s_{h} \\ & h_{l} \leq H(w-w_{b}) \leq h_{h} \\ & w_{l} \leq w-w_{b} \leq w_{h} \\ & b_{l} \leq B_{b}w \leq b_{h} \\ & \mathbf{0} \leq w \leq l \\ & \mathbf{1}^{T}w = 1 \end{array} $$ - **Objective Function**: Maximize single-factor exposure, where \( f \) represents factor values, and \( f^{T}w \) is the weighted exposure of the portfolio to the factor. \( w \) is the weight vector of stocks in the portfolio [40][41]. - **Constraints**: 1. **Style Exposure**: \( X \) is the factor exposure matrix for stocks, \( w_b \) is the weight vector of the benchmark index, and \( s_l, s_h \) are the lower and upper bounds for style factor deviations [41]. 2. **Industry Exposure**: \( H \) is the industry exposure matrix, where \( H_{ij} = 1 \) if stock \( i \) belongs to industry \( j \). \( h_l, h_h \) are the lower and upper bounds for industry deviations [41]. 3. **Stock Weight Deviation**: \( w_l, w_h \) are the lower and upper bounds for individual stock weight deviations relative to the benchmark [41]. 4. **Component Stock Weight**: \( B_b \) is a 0-1 vector indicating whether a stock is a component of the benchmark. \( b_l, b_h \) are the lower and upper bounds for component stock weights [41]. 5. **No Short Selling**: Ensures non-negative weights and limits individual stock weights to a maximum \( l \) [41]. 6. **Full Investment**: Ensures the portfolio is fully invested, with the sum of weights equal to 1 [42]. - The MFE portfolio is constructed monthly, and historical returns are calculated after accounting for transaction costs (0.3% on both sides) [44]. - **Model Evaluation**: The MFE portfolio approach is effective in testing factor performance under realistic constraints, making it a robust method for practical applications [40][41]. --- Quantitative Factors and Construction Methods Factor Name: BP (Book-to-Price Ratio) - **Factor Construction Idea**: Measures the valuation of a stock by comparing its book value to its market price [16]. - **Factor Construction Process**: - Formula: \( \text{BP} = \frac{\text{Net Asset}}{\text{Market Value}} \) [16]. Factor Name: DELTAROE (Change in Return on Equity) - **Factor Construction Idea**: Captures the change in a company's profitability by comparing its return on equity (ROE) to the same period in the previous year [16]. - **Factor Construction Process**: - Formula: \( \text{DELTAROE} = \text{ROE}_{\text{current}} - \text{ROE}_{\text{previous year}} \) [16]. Factor Name: SPTTM (Sales-to-Price Ratio, Trailing Twelve Months) - **Factor Construction Idea**: Evaluates a company's valuation by comparing its trailing twelve-month sales to its market price [16]. - **Factor Construction Process**: - Formula: \( \text{SPTTM} = \frac{\text{Sales (TTM)}}{\text{Market Value}} \) [16]. Factor Name: One-Month Reversal - **Factor Construction Idea**: Measures the short-term reversal effect by calculating the stock's return over the past 20 trading days [16]. - **Factor Construction Process**: - Formula: \( \text{One-Month Reversal} = \text{Return over the past 20 trading days} \) [16]. Factor Name: Three-Month Turnover - **Factor Construction Idea**: Reflects the liquidity of a stock by calculating its average turnover rate over the past 60 trading days [16]. - **Factor Construction Process**: - Formula: \( \text{Three-Month Turnover} = \text{Average Turnover Rate over the past 60 trading days} \) [16]. --- Factor Backtesting Results Performance in the CSI 300 Universe - **DELTAROE**: Weekly excess return 0.74%, monthly 2.05%, YTD 16.88% [18]. - **BP**: Weekly excess return 0.34%, monthly -0.03%, YTD -1.23% [18]. - **SPTTM**: Weekly excess return 0.51%, monthly 0.36%, YTD -0.54% [18]. Performance in the CSI 500 Universe - **BP**: Weekly excess return 1.18%, monthly 1.34%, YTD -0.80% [20]. - **DELTAROE**: Weekly excess return -0.81%, monthly -0.60%, YTD 7.77% [20]. - **SPTTM**: Weekly excess return 0.79%, monthly -0.52%, YTD 2.01% [20]. Performance in the CSI 1000 Universe - **DELTAROE**: Weekly excess return 0.78%, monthly 2.46%, YTD 12.26% [22]. - **BP**: Weekly excess return 0.86%, monthly -0.19%, YTD -0.35% [22]. - **SPTTM**: Weekly excess return 1.05%, monthly 0.23%, YTD -2.52% [22]. Performance in the CSI A500 Universe - **DELTAROE**: Weekly excess return 0.60%, monthly 1.65%, YTD 18.37% [24]. - **BP**: Weekly excess return 0.51%, monthly 0.01%, YTD -4.35% [24]. - **SPTTM**: Weekly excess return 0.19%, monthly -0.31%, YTD -5.36% [24]. Performance in the Public Fund Heavyweight Index Universe - **BP**: Weekly excess return 1.18%, monthly -0.78%, YTD -8.84% [26]. - **DELTAROE**: Weekly excess return -0.11%, monthly -0.12%, YTD 8.42% [26]. - **SPTTM**: Weekly excess return 1.07%, monthly -1.21%, YTD -8.15% [26].

- The report tracks the performance of Guosen JinGong's index enhancement portfolios and public fund index enhancement products, and monitors the performance of common stock selection factors in different stock selection spaces[10] - Guosen JinGong's index enhancement portfolios are constructed using multi-factor stock selection, with benchmarks including CSI 300, CSI 500, CSI 1000, and CSI A500 indices[10][11] - The construction process of Guosen JinGong's index enhancement portfolios includes three main components: return prediction, risk control, and portfolio optimization[11] Factor Construction and Performance - The report monitors the performance of factors in different stock selection spaces, including CSI 300, CSI 500, CSI 1000, CSI A500, and public fund heavy positions index[14] - The factor library includes over 30 common factors from dimensions such as valuation, reversal, growth, profitability, liquidity, corporate governance, and analysts[15] - Factors are constructed using specific calculation methods, for example, BP (Book-to-Price) is calculated as net assets divided by total market value[16] Factor Performance in Different Stock Selection Spaces - **CSI 300 Index**: Factors like DELTAROE, dividend yield, and DELTAROA performed well recently, while factors like single-quarter revenue YoY growth, one-month reversal, and standardized unexpected income performed poorly[1][17] - **CSI 500 Index**: Factors like expected BP, BP, and three-month institutional coverage performed well recently, while factors like DELTAROA, single-quarter net profit YoY growth, and standardized unexpected earnings performed poorly[1][19] - **CSI 1000 Index**: Factors like expected PEG, single-quarter SP, and SPTTM performed well recently, while factors like one-year momentum, three-month reversal, and one-month reversal performed poorly[1][21] - **CSI A500 Index**: Factors like three-month turnover, dividend yield, and DELTAROE performed well recently, while factors like three-month reversal, single-quarter revenue YoY growth, and one-year momentum performed poorly[1][23] - **Public Fund Heavy Positions Index**: Factors like BP, SPTTM, and expected BP performed well recently, while factors like one-year momentum, single-quarter revenue YoY growth, and single-quarter net profit YoY growth performed poorly[1][25] Public Fund Index Enhancement Products Performance - **CSI 300 Index Enhancement Products**: Recently, the highest excess return was 1.38%, the lowest was -0.44%, and the median was 0.41%[2][31] - **CSI 500 Index Enhancement Products**: Recently, the highest excess return was 1.55%, the lowest was -0.51%, and the median was 0.46%[2][34] - **CSI 1000 Index Enhancement Products**: Recently, the highest excess return was 1.57%, the lowest was -0.32%, and the median was 0.57%[2][37] - **CSI A500 Index Enhancement Products**: Recently, the highest excess return was 1.29%, the lowest was -0.35%, and the median was 0.43%[3][39] Factor MFE Portfolio Construction - The MFE (Maximized Factor Exposure) portfolio is constructed using an optimization model to maximize single-factor exposure while controlling for various constraints such as style exposure, industry exposure, individual stock weight deviation, component stock weight ratio, and individual stock weight limits[40][41] - The optimization model's objective function is to maximize single-factor exposure, with constraints including style factor relative exposure limits, industry deviation limits, individual stock deviation limits, component stock weight ratio limits, and individual stock weight limits[41][42] - The MFE portfolio construction process involves setting constraints, constructing the MFE portfolio at the end of each month, and calculating historical returns and risk statistics for the MFE portfolio during the backtest period[44]

Group 1: Weekly Index Enhanced Portfolio Performance - The CSI 300 index enhanced portfolio achieved an excess return of 0.62% this week and 20.75% year-to-date [1][9] - The CSI 500 index enhanced portfolio recorded an excess return of -0.37% this week and 6.86% year-to-date [1][9] - The CSI 1000 index enhanced portfolio had an excess return of 0.97% this week and 16.87% year-to-date [1][9] - The CSI A500 index enhanced portfolio reported an excess return of 0.85% this week and 10.70% year-to-date [1][9] Group 2: Factor Performance Tracking - In the CSI 300 component stocks, factors such as DELTAROE, dividend yield, and DELTAROA performed well [1][10] - In the CSI 500 component stocks, factors like expected BP, BP, and three-month institutional coverage showed strong performance [1][12] - For the CSI 1000 component stocks, factors such as expected PEG, single-quarter SP, and SPTTM performed well [1][15] - In the CSI A500 index component stocks, factors like three-month turnover, dividend yield, and DELTAROE showed good performance [1][19] - In public fund heavy stocks, factors like BP, SPTTM, and expected BP performed well [1][23] Group 3: Public Fund Index Enhanced Product Performance Tracking - The CSI 300 index enhanced products had a maximum excess return of 1.38%, a minimum of -0.44%, and a median of 0.41% this week [1][28] - The CSI 500 index enhanced products achieved a maximum excess return of 1.55%, a minimum of -0.51%, and a median of 0.46% this week [1][30] - The CSI 1000 index enhanced products recorded a maximum excess return of 1.57%, a minimum of -0.32%, and a median of 0.57% this week [1][31] - The CSI A500 index enhanced products had a maximum excess return of 1.29%, a minimum of -0.35%, and a median of 0.43% this week [2][36]

Group 1 - The core viewpoint of the article emphasizes the growing interest in index-enhanced products, particularly the CSI 1000 Index, which combines high growth and high elasticity characteristics, making it suitable for investors with a certain risk tolerance seeking potential excess returns [3][4]. - The CSI 1000 Index represents small and mid-cap stocks, covering companies ranked approximately 801 to 1800 in market capitalization, with a significant proportion in high-growth sectors such as electronics, electrical equipment, pharmaceuticals, and computers [4]. - Since 2021, the Chinese government has implemented policies to support "specialized, refined, distinctive, and innovative" small and medium-sized enterprises, resulting in over 10 billion yuan in subsidies by 2025, which enhances the growth logic for the CSI 1000 Index in the medium to long term [6]. Group 2 - The performance of private equity CSI 1000 index-enhanced strategies has shown a significant advantage in "Beta + Alpha" returns, with a strategy index return exceeding 36% over the past year compared to a 16% increase in the CSI 1000 Index [6]. - The article introduces two new metrics for selecting CSI 1000 index-enhanced products: non-regular investment annualized return and regular investment annualized return, which provide a more accurate reflection of the investor's actual holding experience [9][10]. - The non-regular annualized return reflects the product's ability to generate returns from a single investment point, while the regular annualized return measures the stability of performance over time with fixed frequency investments [11][12]. Group 3 - The article discusses the compounding effect of index-enhanced strategies, highlighting that consistent small excess returns can accumulate significantly over time, making long-term holding a more effective strategy [14]. - A table illustrates the potential excess returns over one and three years based on daily outperformance against the benchmark, showing that even small daily outperformance can lead to substantial cumulative excess returns [15].

规模与业绩齐飞 Wind 数据显示，截至 12 月 12 日，今年以来新成立指增基金 168 只，合计募集规模达 924.76 亿元，数量和规模均超过过去三年的总和。业绩方面，近九成增强指数型 ETF 实现 正超额收益，年内最高超额收益达 22% 。 对于指数增强基金大发展的主要原因，永赢基金指数与量化投资部总经理蔡路平表示，首 先，市场环境提供沃土。 A 股市场今年呈现明显的结构性分化特征，这为通过量化策略获取 超额收益提供了有利环境。今年中小盘风格表现亮眼，以中证 500 指数、中证 1000 指数、 中证 2000 指数等中小盘宽基指数为基准的增强产品更容易取得超额收益。 其次，量化投资技术发展与新指数提供助力。随着量化模型和 AI 大模型的快速发展，基金公 司能够构建更综合全面的选股模型，提供不同类型的 Alpha 收益来源，捕捉多元的市场投资 机会。同时，稳健可靠的全流程风险控制也提升了超额收益的稳定性。 最后，投资者认知与渠道发力。随着市场教育和产品业绩的持续验证，投资者对指数增强产 品的认知从过去的 " 可选项 " 变成 " 必要项 " 。头部代销平台逐步将业务重点转向指数增 强基金，推出 " ...

Group 1: Weekly Index Enhanced Portfolio Performance - The CSI 300 index enhanced portfolio achieved an excess return of 0.73% this week and 19.95% year-to-date [1][7] - The CSI 500 index enhanced portfolio recorded an excess return of -0.02% this week and 7.36% year-to-date [1][7] - The CSI 1000 index enhanced portfolio had an excess return of -0.31% this week and 15.60% year-to-date [1][7] - The CSI A500 index enhanced portfolio saw an excess return of 0.09% this week and 9.62% year-to-date [1][7] Group 2: Factor Performance Tracking - In the CSI 300 component stocks, factors such as three-month earnings adjustments, standardized unexpected earnings, and quarterly net profit year-on-year growth performed well [1][8] - In the CSI 500 component stocks, factors like quarterly ROA, quarterly ROE, and non-liquidity shocks showed strong performance [1][8] - For the CSI 1000 component stocks, factors including quarterly ROA, quarterly revenue year-on-year growth, and quarterly ROE performed well [1][8] - In the CSI A500 index component stocks, factors such as three-month earnings adjustments, one-year momentum, and standardized unexpected earnings performed well [1][8] Group 3: Public Fund Index Enhanced Product Performance Tracking - The CSI 300 index enhanced products had a maximum excess return of 1.75%, a minimum of -0.80%, and a median of 0.21% this week [1][21] - The CSI 500 index enhanced products recorded a maximum excess return of 0.44%, a minimum of -1.50%, and a median of -0.29% this week [1][23] - The CSI 1000 index enhanced products had a maximum excess return of 0.83%, a minimum of -1.22%, and a median of -0.27% this week [1][27] - The CSI A500 index enhanced products achieved a maximum excess return of 1.02%, a minimum of -0.67%, and a median of 0.01% this week [1][28]