一、本周指数增强组合表现 沪深300指数增强组合本周超额收益-0.71%，本年超额收益16.74%。 中证500指数增强组合本周超额收益0.12%，本年超额收益6.85%。 中证1000指数增强组合本周超额收益-0.94%，本年超额收益14.08%。 中证A500指数增强组合本周超额收益-1.37%，本年超额收益7.55%。 二、本周选股因子表现跟踪 沪深300成分股中一个月波动、一个月换手、三个月波动等因子表现较好。 中证500成分股中三个月机构覆盖、一个月反转、三个月反转等因子表现较 好。 中证1000成分股中一个月换手、三个月机构覆盖、单季ROA等因子表现较 好。 中证A500指数成分股中一个月换手、三个月换手、一个月波动等因子表现较 好。 公募基金重仓股中一个月波动、一个月换手、三个月换手等因子表现较好。 三、本周公募基金指数增强产品表现跟踪 沪深300指数增强产品本周超额收益最高0.70%，最低-1.26%，中位数 0.09%。 中证500指数增强产品本周超额收益最高1.17%，最低-1.13%，中位数 0.11%。 中证1000指数增强产品本周超额收益最高0.89%，最低-1.38%，中位 数-0 ...

Quantitative Models and Construction Methods 1. Model Name: Guosen Quantitative Index Enhanced Portfolio - **Model Construction Idea**: The model aims to construct enhanced portfolios benchmarked against indices such as CSI 300, CSI 500, CSI 1000, and CSI A500, with the goal of consistently outperforming their respective benchmarks [10][11]. - **Model Construction Process**: 1. **Revenue Prediction**: Predict stock returns using multiple factors. 2. **Risk Control**: Apply constraints on industry exposure, style exposure, stock weight deviation, and turnover rate. 3. **Portfolio Optimization**: Optimize the portfolio to maximize single-factor exposure while adhering to constraints. The optimization model is as follows: $ \begin{array}{ll} max & f^{T} w \\ 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, \( w \) is the stock weight vector, and \( f^{T}w \) is the weighted exposure to the factor. - **Constraints**: - **Style Exposure**: \( X \) is the factor exposure matrix, \( w_b \) is the benchmark weight vector, and \( s_l, s_h \) are the lower and upper bounds for style exposure. - **Industry Exposure**: \( H \) is the industry exposure matrix, and \( h_l, h_h \) are the lower and upper bounds for industry deviation. - **Stock Weight Deviation**: \( w_l, w_h \) are the lower and upper bounds for stock weight deviation. - **Component Stock Weight**: \( B_b \) is a 0-1 vector indicating whether a stock is a benchmark component, and \( b_l, b_h \) are the lower and upper bounds for component stock weight. - **No Short Selling**: Ensure non-negative weights and limit individual stock weights. - **Full Investment**: Ensure the portfolio is fully invested with weights summing to 1 [40][41][42]. 4. **Backtesting**: Rebalance the portfolio monthly, calculate historical returns, and evaluate performance metrics such as excess returns and risk statistics [44]. 2. Model Name: Public Fund Heavyweight Index - **Model Construction Idea**: Construct an index based on the holdings of public funds to evaluate factor performance under "institutional style" [42][43]. - **Model Construction Process**: 1. **Sample Selection**: Include ordinary equity funds and partial equity hybrid funds with a minimum size of 50 million RMB and at least six months of listing history. Exclude recently transformed funds or those with insufficient data. 2. **Data Collection**: Use fund periodic reports (annual, semi-annual, or quarterly) to gather holding information. 3. **Weight Calculation**: Average the stock weights across eligible funds. 4. **Index Construction**: Sort stocks by weight in descending order and select those accounting for 90% of cumulative weight to form the index [43]. --- Model Backtesting Results 1. Guosen Quantitative Index Enhanced Portfolio - **CSI 300 Enhanced Portfolio**: - Weekly excess return: -0.71% - Year-to-date excess return: 16.74% [13] - **CSI 500 Enhanced Portfolio**: - Weekly excess return: 0.12% - Year-to-date excess return: 6.85% [13] - **CSI 1000 Enhanced Portfolio**: - Weekly excess return: -0.94% - Year-to-date excess return: 14.08% [13] - **CSI A500 Enhanced Portfolio**: - Weekly excess return: -1.37% - Year-to-date excess return: 7.55% [13] 2. Public Fund Heavyweight Index - **CSI 300 Index Enhanced Products**: - Weekly excess return: Max 0.70%, Min -1.26%, Median 0.09% - Year-to-date excess return: Max 9.92%, Min -4.53%, Median 2.58% [31] - **CSI 500 Index Enhanced Products**: - Weekly excess return: Max 1.17%, Min -1.13%, Median 0.11% - Year-to-date excess return: Max 13.14%, Min -9.17%, Median 3.94% [33] - **CSI 1000 Index Enhanced Products**: - Weekly excess return: Max 0.89%, Min -1.38%, Median -0.05% - Year-to-date excess return: Max 19.12%, Min -1.84%, Median 8.24% [36] - **CSI A500 Index Enhanced Products**: - Weekly excess return: Max 0.71%, Min -0.86%, Median -0.04% - Year-to-date excess return: Max 2.67%, Min -4.14%, Median -0.76% [39] --- Quantitative Factors and Construction Methods 1. Factor Name: Maximized Factor Exposure (MFE) - **Factor Construction Idea**: Evaluate factor effectiveness under real-world constraints by maximizing single-factor exposure in a portfolio [40][41]. - **Factor Construction Process**: 1. Define constraints for style exposure, industry exposure, stock weight deviation, and component stock weight. 2. Optimize the portfolio to maximize single-factor exposure while adhering to constraints. 3. Rebalance monthly and calculate historical returns [40][41][44]. 2. Factor Name: Public Fund Heavyweight Factors - **Factor Construction Idea**: Test factor performance in the public fund heavyweight index to reflect institutional preferences [42][43]. - **Factor Construction Process**: 1. Use public fund holdings to construct the index. 2. Evaluate factor performance within this index using metrics such as excess returns and risk-adjusted returns [42][43]. --- Factor Backtesting Results 1. Maximized Factor Exposure (MFE) - **CSI 300 Sample Space**: - Best-performing factors (weekly): One-month volatility (0.83%), one-month turnover (0.68%), three-month volatility (0.65%) - Worst-performing factors (weekly): Single-quarter profit growth (-0.26%), three-month institutional coverage (-0.24%), one-year momentum (-0.24%) [18] - **CSI 500 Sample Space**: - Best-performing factors (weekly): Three-month institutional coverage (1.09%), one-month reversal (1.01%), three-month reversal (0.99%) - Worst-performing factors (weekly): Standardized unexpected earnings (-1.00%), DELTAROA (-0.81%), DELTAROE (-0.81%) [20] - **CSI 1000 Sample Space**: - Best-performing factors (weekly): One-month turnover (1.08%), three-month institutional coverage (1.06%), single-quarter ROA (1.04%) - Worst-performing factors (weekly): Single-quarter SP (-1.29%), expected PEG (-1.25%), SPTTM (-1.22%) [22] - **CSI A500 Sample Space**: - Best-performing factors (weekly): One-month turnover (0.82%), three-month turnover (0.75%), one-month volatility (0.74%) - Worst-performing factors (weekly): Expected net profit QoQ (-0.91%), single-quarter net profit growth (-0.61%), expected PEG (-0.41%) [24] - **Public Fund Heavyweight Index**: - Best-performing factors (weekly): One-month volatility (1.32%), one-month turnover (1.23%), three-month turnover (0.89%) - Worst-performing factors (weekly): Single-quarter revenue growth (-0.89%), single-quarter profit growth (-0.88%), single-quarter ROE (-0.81%) [26]

Performance of Index Enhancement Portfolios - The CSI 300 index enhancement portfolio recorded an excess return of -0.22% for the week and 18.41% year-to-date [1][6] - The CSI 500 index enhancement portfolio had an excess return of -0.52% for the week and 7.09% year-to-date [1][6] - The CSI 1000 index enhancement portfolio showed an excess return of -0.12% for the week and 16.38% year-to-date [1][6] - The CSI A500 index enhancement portfolio achieved an excess return of 0.01% for the week and 9.75% year-to-date [1][6] Stock Selection Factor Performance Tracking - In the CSI 300 component stocks, factors such as three-month volatility, one-month volatility, and three-month reversal performed well [1][9] - In the CSI 500 component stocks, factors like one-month turnover, BP, and illiquidity shock showed strong performance [1][9] - For the CSI 1000 component stocks, factors such as illiquidity shock, expected net profit month-on-month, and EPTTM one-year percentile performed well [1][9] - In the CSI A500 index component stocks, factors like three-month volatility, one-month volatility, and one-month turnover performed well [1][9] Public Fund Index Enhancement Products Performance Tracking - The CSI 300 index enhancement products had a maximum excess return of 1.15%, a minimum of -2.04%, and a median of 0.19% for the week [1][20] - The CSI 500 index enhancement products recorded a maximum excess return of 2.03%, a minimum of -0.65%, and a median of 0.27% for the week [1][21] - The CSI 1000 index enhancement products had a maximum excess return of 1.84%, a minimum of -0.95%, and a median of 0.00% for the week [1][23] - The CSI A500 index enhancement products achieved a maximum excess return of 0.94%, a minimum of -0.47%, and a median of 0.16% for the week [1][25] Public Fund Index Enhancement Product Quantity and Scale - There are currently 76 CSI 300 index enhancement products with a total scale of 77.9 billion [1][19] - There are 74 CSI 500 index enhancement products with a total scale of 50.5 billion [1][19] - There are 46 CSI 1000 index enhancement products with a total scale of 21.4 billion [1][19] - There are 68 CSI A500 index enhancement products with a total scale of 25.3 billion [1][19]

- The report tracks the performance of Guosen Financial Engineering's index enhancement portfolios, which are constructed based on multi-factor stock selection models targeting benchmarks such as CSI 300, CSI 500, CSI 1000, and CSI A500 indices[10][11][13] - The construction process of the index enhancement portfolios includes three main components: return prediction, risk control, and portfolio optimization[11] - The report monitors the performance of single-factor Maximized Factor Exposure (MFE) portfolios across different stock selection spaces, including CSI 300, CSI 500, CSI 1000, CSI A500 indices, and public fund heavy positions index[10][14][39] - The MFE portfolio construction process involves optimizing the portfolio to maximize single-factor exposure while controlling for constraints such as style exposure, industry exposure, individual stock weight deviation, and turnover rate[39][40][41] - The optimization model for MFE portfolios is defined as follows: $\begin{array}{ll}max&f^{T}\ w\\ s.t.&s_{l}\leq X(w-w_{b})\leq s_{h}\\ &h_{l}\leq H(w-w_{b})\leq h_{h}\\ &w_{l}\leq w-w_{b}\leq w_{h}\\ &b_{l}\leq B_{b}w\leq b_{h}\\ &\mathbf{0}\leq w\leq l\\ &\mathbf{1}^{T}\ w=1\end{array}$ where `f` represents factor values, `w` is the stock weight vector, and constraints include style factor deviation, industry deviation, individual stock weight deviation, and component stock weight limits[39][40] - The report highlights the weekly, monthly, and yearly performance of various factors in different stock selection spaces, such as CSI 300, CSI 500, CSI 1000, CSI A500 indices, and public fund heavy positions index[17][19][21][23][25] - Factors such as three-month volatility, one-month volatility, and three-month turnover performed well in the CSI 300 space recently, while factors like one-year momentum and single-quarter profit growth rate performed poorly[17][18] - In the CSI 500 space, factors like one-month turnover and BP showed strong performance recently, while one-year momentum and standardized unexpected earnings performed poorly[19][20] - In the CSI 1000 space, factors such as illiquidity shock and expected net profit growth performed well recently, while standardized unexpected revenue and one-year momentum showed weak performance[21][22] - In the CSI A500 space, factors like three-month volatility and one-month turnover performed well recently, while one-year momentum and standardized unexpected earnings performed poorly[23][24] - In the public fund heavy positions index space, factors such as one-month volatility and three-month turnover performed well recently, while standardized unexpected revenue and one-year momentum showed weak performance[25][26] - The report tracks the performance of public fund index enhancement products, including CSI 300, CSI 500, CSI 1000, and CSI A500 index enhancement funds, with detailed statistics on excess returns across different time periods[27][28][31][33][35][38]

Group 1: Weekly Index Enhanced Portfolio Performance - The CSI 300 index enhanced portfolio achieved an excess return of 0.01% this week and 18.92% year-to-date [6][18] - The CSI 500 index enhanced portfolio recorded an excess return of -0.26% this week and 7.89% year-to-date [6][18] - The CSI 1000 index enhanced portfolio had an excess return of -0.63% this week and 16.63% year-to-date [6][18] - The CSI A500 index enhanced portfolio posted an excess return of 0.20% this week and 9.84% year-to-date [6][18] Group 2: Stock Selection Factor Performance Tracking - In the CSI 300 component stocks, factors such as EPTTM, expected BP, and BP performed well [9][10] - In the CSI 500 component stocks, three-month volatility, expected EPTTM, and expected BP showed strong performance [9][10] - For the CSI 1000 component stocks, EPTTM, three-month volatility, and expected EPTTM were the top-performing factors [9][10] - In the CSI A500 index component stocks, expected EPTTM, EPTTM, and BP were the best-performing factors [9][10] Group 3: Public Fund Index Enhanced Product Performance Tracking - The CSI 300 index enhanced products had a maximum excess return of 0.89%, a minimum of -1.44%, and a median of -0.18% this week [22][24] - The CSI 500 index enhanced products achieved a maximum excess return of 1.65%, a minimum of -1.05%, and a median of 0.05% this week [24][28] - The CSI 1000 index enhanced products recorded a maximum excess return of 0.94%, a minimum of -1.66%, and a median of -0.30% this week [24][28] - The CSI A500 index enhanced products had a maximum excess return of 0.59%, a minimum of -1.02%, and a median of -0.16% this week [24][29]

Quantitative Models and Construction Methods 1. Model Name: Maximized Factor Exposure Portfolio (MFE) - **Model Construction Idea**: The MFE portfolio is designed to test the effectiveness of single factors under real-world constraints, such as industry exposure, style exposure, stock weight limits, and turnover rate. This approach ensures that the factors deemed "effective" can genuinely contribute to return prediction in the final portfolio[38][39]. - **Model Construction Process**: - The objective function is to maximize single-factor exposure, represented as $f^{T}w$, where $f$ is the factor value, and $w$ is the stock weight vector. - The optimization model includes the following constraints: 1. **Style Exposure Constraint**: Limits the portfolio's deviation from the benchmark in terms of style factors. $X$ is the factor exposure matrix, $w_b$ is the benchmark weight vector, and $s_l, s_h$ are the lower and upper bounds for style factor exposure[39]. 2. **Industry Exposure Constraint**: Limits the portfolio's deviation from the benchmark in terms of industry exposure. $H$ is the industry exposure matrix, and $h_l, h_h$ are the lower and upper bounds for industry exposure[39]. 3. **Stock Weight Deviation Constraint**: Limits individual stock weight deviations from the benchmark. $w_l, w_h$ are the lower and upper bounds for stock weight deviations[39]. 4. **Constituent Stock Weight Constraint**: Limits the weight of constituent stocks within the portfolio. $B_b$ is a binary vector indicating whether a stock is a benchmark constituent, and $b_l, b_h$ are the lower and upper bounds for constituent stock weights[39]. 5. **No Short Selling Constraint**: Ensures no short positions and limits individual stock weights to a maximum value $l$[39]. 6. **Full Investment Constraint**: Ensures the portfolio is fully invested, with the sum of weights equal to 1[40]. - The optimization model is expressed as: $$ \begin{array}{ll} max & f^{T}w \\ s.t. & s_{l} \leq X(w-w_{b}) \leq s_{h} \\ & h_{l} \leq H(w-w_{b}) \leq h_{h} \\ & w_{l} \leq w-w_{b} \leq w_{h} \\ & b_{l} \leq B_{b}w \leq b_{h} \\ & \mathbf{0} \leq w \leq l \\ & \mathbf{1}^{T}w = 1 \end{array} $$ - The MFE portfolio is constructed monthly, and historical returns are backtested with a 0.3% transaction cost applied on both sides[42]. - **Model Evaluation**: The MFE portfolio effectively tests factor performance under realistic constraints, making it a robust tool for evaluating factor predictability in practical scenarios[38][39]. --- Factor Construction and Methods 1. Factor Name: EPTTM (Earnings to Price Trailing Twelve Months) - **Factor Construction Idea**: Measures the profitability of a company relative to its market value, using trailing twelve months' earnings[15]. - **Factor Construction Process**: - Formula: $EPTTM = \frac{\text{Net Income (TTM)}}{\text{Market Value}}$ - The numerator represents the trailing twelve months' net income, while the denominator is the company's total market value[15]. 2. Factor Name: BP (Book-to-Price Ratio) - **Factor Construction Idea**: Evaluates the valuation of a company by comparing its book value to its market value[15]. - **Factor Construction Process**: - Formula: $BP = \frac{\text{Book Value}}{\text{Market Value}}$ - The numerator is the company's book value, and the denominator is its total market value[15]. 3. Factor Name: Three-Month Volatility - **Factor Construction Idea**: Captures the stock's price fluctuation over the past three months, reflecting its risk level[15]. - **Factor Construction Process**: - Formula: $Volatility = \text{Average True Range (ATR)}$ over the past 60 trading days. - The ATR is calculated as the average of the daily high-low range over the specified period[15]. 4. Factor Name: One-Month Reversal - **Factor Construction Idea**: Measures the short-term reversal effect by analyzing the stock's return over the past month[15]. - **Factor Construction Process**: - Formula: $Reversal = \text{Return over the past 20 trading days}$ - Positive values indicate a reversal effect, while negative values suggest momentum continuation[15]. --- Factor Backtesting Results 1. EPTTM - **HS300**: Weekly return 1.35%, monthly return 4.28%, YTD return 5.95%, historical annualized return 4.60%[18]. - **CSI500**: Weekly return 1.54%, monthly return 3.55%, YTD return -3.61%, historical annualized return 4.78%[20]. - **CSI1000**: Weekly return 1.44%, monthly return 2.78%, YTD return 0.15%, historical annualized return 6.84%[22]. - **CSIA500**: Weekly return 1.72%, monthly return 3.92%, YTD return 2.62%, historical annualized return 3.71%[24]. - **Public Fund Index**: Weekly return 1.82%, monthly return 5.32%, YTD return 4.75%, historical annualized return 1.42%[26]. 2. BP - **HS300**: Weekly return 1.25%, monthly return 2.83%, YTD return -1.86%, historical annualized return 2.72%[18]. - **CSI500**: Weekly return 1.36%, monthly return 2.23%, YTD return 3.09%, historical annualized return 3.47%[20]. - **CSI1000**: Weekly return 0.99%, monthly return 1.56%, YTD return -0.45%, historical annualized return 3.07%[22]. - **CSIA500**: Weekly return 1.50%, monthly return 3.44%, YTD return -4.52%, historical annualized return 2.89%[24]. - **Public Fund Index**: Weekly return 1.45%, monthly return 3.20%, YTD return -8.75%, historical annualized return 0.74%[26]. 3. Three-Month Volatility - **HS300**: Weekly return 0.52%, monthly return 1.75%, YTD return -3.56%, historical annualized return 1.84%[18]. - **CSI500**: Weekly return 1.76%, monthly return 3.07%, YTD return -7.17%, historical annualized return 3.50%[20]. - **CSI1000**: Weekly return 1.40%, monthly return 2.54%, YTD return -8.22%, historical annualized return 4.33%[22]. - **CSIA500**: Weekly return 0.79%, monthly return 2.15%, YTD return -9.34%, historical annualized return 2.77%[24]. - **Public Fund Index**: Weekly return 0.97%, monthly return 2.04%, YTD return -15.34%, historical annualized return 1.54%[26]. 4. One-Month Reversal - **HS300**: Weekly return -0.93%, monthly return 0.98%, YTD return -0.57%, historical annualized return -0.33%[18]. - **CSI500**: Weekly return -1.83%, monthly return -0.84%, YTD return 2.56%, historical annualized return -0.84%[20]. - **CSI1000**: Weekly return -1.49%, monthly return -0.55%, YTD return -4.63%, historical annualized return -3.84%[22]. - **CSIA500**: Weekly return -1.28%, monthly return 0.51%, YTD return -1.07%, historical annualized return -2.34%[24]. - **Public Fund Index**: Weekly return -1.11%, monthly return 0.95%, YTD return 4.67%, historical annualized return -1.80%[26].

- The report highlights the performance of selection factors in the "broker gold stock pool," including factors such as total market capitalization, single-quarter revenue growth, and analyst net upward revisions, which performed well this year. Conversely, factors like EPTTM, expected dividend yield, and volatility showed weaker performance this year[3][28][29] - The "broker gold stock performance enhancement portfolio" is constructed using a multi-factor approach to optimize stock selection within the broker gold stock pool. The portfolio aims to outperform the benchmark, the actively managed equity fund index, by controlling deviations in individual stocks and styles while aligning industry allocation with the overall distribution of public funds[12][39][42] - The historical performance of the "broker gold stock performance enhancement portfolio" demonstrates robust results, with annualized returns of 19.34% and an annualized excess return of 14.38% relative to the actively managed equity fund index during the period from 2018 to 2025. The portfolio consistently ranked in the top 30% of actively managed equity funds each year[43][46] - The monthly performance of the "broker gold stock performance enhancement portfolio" (20251009-20251031) showed an absolute return of -0.77% and an excess return of 1.37% relative to the actively managed equity fund index. Year-to-date (20250102-20251031), the portfolio achieved an absolute return of 35.08% and an excess return of 2.61%, ranking in the 40.13% percentile among actively managed equity funds[5][41][46]

Group 1: Weekly Index Enhanced Portfolio Performance - The CSI 300 index enhanced portfolio recorded a weekly excess return of -0.02% and a year-to-date excess return of 18.75% [6][18] - The CSI 500 index enhanced portfolio had a weekly excess return of -0.64% and a year-to-date excess return of 8.25% [6][18] - The CSI 1000 index enhanced portfolio experienced a weekly excess return of -1.24% and a year-to-date excess return of 17.45% [6][18] - The CSI A500 index enhanced portfolio achieved a weekly excess return of 1.03% and a year-to-date excess return of 9.51% [6][18] Group 2: Stock Selection Factor Performance Tracking - In the CSI 300 component stocks, factors such as EPTTM, expected BP, and expected EPTTM performed well [9][10] - In the CSI 500 component stocks, factors like single-season SP, SPTTM, and expected PEG showed strong performance [10][11] - In the CSI 1000 component stocks, factors such as specificity, three-month turnover, and expected net profit month-on-month performed well [10][12] - In the CSI A500 index component stocks, single-season SP, SPTTM, and BP factors performed well [10][14] - Among publicly offered fund heavy stocks, factors like SPTTM, one-month reversal, and single-season SP performed well [10][16] Group 3: Public Fund Index Enhanced Product Performance Tracking - The CSI 300 index enhanced products had a maximum excess return of 1.06%, a minimum of -0.51%, and a median of 0.13% for the week [20][22] - The CSI 500 index enhanced products recorded a maximum excess return of 0.79%, a minimum of -1.26%, and a median of -0.13% for the week [23][25] - The CSI 1000 index enhanced products had a maximum excess return of 0.75%, a minimum of -1.44%, and a median of -0.34% for the week [24][25] - The CSI A500 index enhanced products achieved a maximum excess return of 0.91%, a minimum of -0.59%, and a median of 0.07% for the week [24][25]

Core Insights - The Galaxy CSI 800 Index Enhanced Securities Investment Fund will be launched on November 10, aiming to provide investors with a pathway to participate in China's long-term economic development while pursuing excess returns [1][2] - The CSI 800 Index is a representative index in the A-share market, established as a "pillar" since its release at the end of 2004, reflecting the achievements of economic structural adjustments [1] Fund Strategy - The fund manager, Luo Bo, employs a "multi-factor stock selection + event-driven strategy" combined with a rigorous risk model for comprehensive management [2] - The multi-factor model evaluates constituent stocks based on growth, valuation, and profitability, dynamically adjusting factor weights to adapt to changing market conditions [2] - The event-driven strategy focuses on identifying assets that may yield excess returns for individual stocks, aiming to enhance overall portfolio performance [2] Risk Management - The fund aims to maintain an annualized tracking error within 7.75% and an average absolute tracking deviation of no more than 0.5%, closely aligning with the CSI 800 Index to prevent style drift [1]

Group 1: Weekly Index Enhanced Portfolio Performance - The CSI 300 index enhanced portfolio achieved an excess return of 0.53% this week and 18.86% year-to-date [1][7] - The CSI 500 index enhanced portfolio recorded an excess return of 0.45% this week and 9.03% year-to-date [1][7] - The CSI 1000 index enhanced portfolio had an excess return of 0.34% this week and 19.00% year-to-date [1][7] - The CSI A500 index enhanced portfolio experienced an excess return of -0.46% this week and 8.18% year-to-date [1][7] Group 2: Stock Selection Factor Performance Tracking - In the CSI 300 component stocks, factors such as quarterly ROA, quarterly ROE, and one-year momentum performed well [1][10] - In the CSI 500 component stocks, factors like SPTTM, executive compensation, and three-month institutional coverage showed strong performance [1][10] - For the CSI 1000 component stocks, factors such as three-month earnings revisions, standardized unexpected revenue, and standardized unexpected earnings performed well [1][10] - In the CSI A500 index component stocks, factors like one-year momentum, quarterly revenue year-on-year growth, and DELTAROA showed good performance [1][10] - Among publicly offered fund heavy stocks, factors like one-year momentum, standardized unexpected revenue, and three-month earnings revisions performed well [1][10] Group 3: Public Fund Index Enhanced Product Performance Tracking - The CSI 300 index enhanced products had a maximum excess return of 2.02%, a minimum of -1.13%, and a median of 0.06% this week [1][23] - The CSI 500 index enhanced products recorded a maximum excess return of 1.24%, a minimum of -1.61%, and a median of 0.19% this week [1][25] - The CSI 1000 index enhanced products achieved a maximum excess return of 1.52%, a minimum of -1.23%, and a median of 0.45% this week [1][29] - The CSI A500 index enhanced products had a maximum excess return of 0.84%, a minimum of -0.53%, and a median of 0.03% this week [1][30]