Investment Rating - The report maintains an "Outperform" rating for the Hong Kong stock market [4] Core Insights - The Hong Kong stock market is currently under pressure due to global liquidity constraints, with all styles and sectors experiencing declines [1] - The overall market performance shows significant downturns, particularly in the automotive sector and various industrial categories [1][2] - Valuation levels have decreased across most industries, with only one sector, basic chemicals, showing an increase [2] - Earnings expectations have been adjusted, with a notable divergence among sectors, indicating a mixed outlook for future performance [3] Summary by Relevant Sections Market Performance - The Hang Seng Index fell by 5.1%, while the Hang Seng Composite Index decreased by 5.4% [1] - Large-cap stocks outperformed mid and small-cap stocks, with declines of 5.2%, 6.0%, and 6.1% respectively [1] - The automotive sector saw a significant drop of 9.6%, while other sectors like power equipment and new energy, steel, and non-ferrous metals also faced substantial declines [1] Valuation Levels - The valuation of the Hang Seng Index decreased by 4.8% to 11.6x, and the Hang Seng Composite Index fell by 5.0% to 11.5x [2] - The automotive sector's valuation dropped by 9.2% to 13.1x, while basic chemicals saw an increase of 8.3% [2] - Overall, 29 sectors experienced valuation declines, with steel and power equipment showing the largest decreases of 14.3% and 14.2% respectively [2] Earnings Expectations - The earnings per share (EPS) for the Hang Seng Index increased slightly by 0.1%, while the Hang Seng Composite Index remained stable [3] - There was a divergence in EPS adjustments among sectors, with consumer sectors seeing an increase of 0.5% and high dividend sectors experiencing a decrease of 0.3% [3] - A total of 20 sectors had upward EPS revisions, with steel and non-ferrous metals seeing increases of 5.0% and 3.4% respectively, while basic chemicals faced a significant downward revision of 11.8% [3]

Investment Rating - The report maintains a "Weaker than Market" investment rating for the U.S. stock market [4] Core Views - The report indicates that most industries are under pressure, but earnings forecasts are improving [4] - The S&P 500 index experienced a decline of 1.9%, while the Nasdaq fell by 2.7% [1] - There is a notable divergence in performance among sectors, with media and entertainment, pharmaceuticals, and consumer goods showing positive trends, while software and services, semiconductors, and retail sectors faced significant declines [1][2] Summary by Sections 2.1 Investment Returns - The energy sector saw a decline of 3.1% this week, while the healthcare sector increased by 1.9% [14] - The media and entertainment sector outperformed with a return of 3.7% [14] - The overall performance of the S&P 500 components was down by 1.7% [14] 2.2 Fund Flows - The estimated net fund flow for the S&P 500 was -15.403 billion USD this week, indicating significant outflows [16] - The media and entertainment sector had a net inflow of 0.896 billion USD, while the semiconductor sector faced a substantial outflow of -7.798 billion USD [16][2] 2.3 Earnings Forecasts - The earnings per share (EPS) forecast for the S&P 500 components was adjusted upward by 0.9% this week, following a 0.3% increase the previous week [3] - The semiconductor sector saw a notable EPS increase of 6.2%, while the retail sector's forecast was downgraded by 0.4% [3][17] 2.4 Valuation Levels - The report does not provide specific valuation levels but indicates a general trend of improving earnings forecasts across various sectors [19]

Economic Outlook - The goal for GDP per capita by 2035 is set at $29,000, necessitating a shift in China's economic logic from solely pursuing GDP growth to a new paradigm focusing on productivity enhancement, moderate inflation, and currency appreciation[1] - The new growth paradigm emphasizes the importance of nominal GDP growth and inflation levels, which directly impacts corporate profitability and capital returns[1] Market Dynamics - The equity market is positioned for a systematic revaluation, supported by three main factors: profit foundation, valuation environment, and relative returns[1] - The expectation of RMB appreciation is a significant driver for valuation improvements, enhancing the attractiveness of RMB assets and drawing global capital to Chinese assets[2] Asset Allocation Trends - There is a notable shift in asset preference from real estate and bonds to equities, driven by the changing yield characteristics of various asset classes in a moderate inflation environment[2] - Bonds, while still a stabilizing component, are expected to see diminishing capital gains potential, while real estate is facing downward pressure due to income and price expectations[2] Consumption and Production Insights - Recent data indicates a recovery in consumption, with metro passenger flow increasing by 5.9% year-on-year and logistics delivery volume rising by 5.8%[12] - Production shows structural improvement, particularly in real estate-related sectors, with a narrowing decline in rebar production and a continued decrease in inventory levels[14] Trade and External Factors - Port cargo throughput has decreased to 266 million tons, reflecting a structural adjustment in external demand, while the export container freight index has risen to 1094.03 points[25] - Geopolitical tensions, particularly with Japan, have introduced new uncertainties into the external trade environment, impacting market sentiment[25] Fiscal and Monetary Policy - The broad deficit for the week ending November 23 reached 204.3 billion, with a cumulative total of 11.2 trillion, indicating a slower pace compared to the previous year[35] - The monetary market remains in a loose state, with indicators suggesting continued low interest rates and a high willingness to leverage in the bond market[44]

Investment Rating - The report assigns an "Outperform" rating for the company [2][7]. Core Insights - The company is a leading enterprise in the wind power main gearbox sector, benefiting from industry prosperity and high growth in performance [4][6]. - The company has established strong partnerships with major wind turbine manufacturers, ensuring stable sales and operational stability [14][16]. - The wind power industry is expected to continue its growth, which will drive stable growth in the gearbox sector, with a projected global market size of $11.563 billion by 2030, growing at a CAGR of 5.10% from 2024 to 2030 [4][42]. Summary by Sections Company Overview - The company specializes in the research, production, and sales of high-speed heavy-duty precision gear transmission products, particularly wind power main gearboxes [3][6]. - The company was founded in 2017 and has rapidly grown to become one of the top three global suppliers of wind power main gearboxes [6][49]. Market Position - The company maintains a leading market share in the wind power main gearbox sector, with a global market share of 10.36% and a domestic market share of 16.22% as of 2024 [51]. - The company has established a diverse customer base, including major players like Goldwind Technology and Envision Energy, which helps mitigate risks associated with reliance on a few clients [5][16]. Financial Performance - The company expects significant growth in net profit from 2025 to 2027, with projected figures of 8.27 billion, 10.66 billion, and 13.28 billion yuan, representing year-on-year growth rates of 55.0%, 28.9%, and 24.5% respectively [5][76]. - The company has a robust order backlog, with nearly 2,800 units on hand by May 2025, valued at approximately 30.37 billion yuan, indicating strong future revenue potential [16][17]. Production Capacity and Expansion - The company is expanding its production capacity with projects aimed at producing 1,000 units of 8MW and above land-based wind power gearboxes and 800 units of offshore wind power gearboxes [3][18]. - The company’s production capacity reached 3,096 units by the end of 2024, with a utilization rate of 86% [17][18]. Product Range and Technology - The company offers a full range of wind power gearbox products, catering to both direct-drive and doubly-fed wind turbine technologies, with power ratings from 1.5MW to 22MW [18][19]. - The company’s gearboxes are designed with high safety factors and operational efficiency, exceeding industry standards [49][50]. Industry Outlook - The wind power industry is expected to experience robust growth driven by global carbon neutrality goals, with significant increases in installed capacity anticipated in both onshore and offshore segments [28][34]. - The domestic wind power gearbox market is projected to grow at a CAGR of 7.46% from 2024 to 2030, reaching a market size of 32.4 billion yuan by 2030 [42].

Content: --------- <doc id='1'>金融工程日报 A 股单边下行，AI 应用逆势走强、锂电池产业链全线下挫</doc> <doc id='2'>核心观点 金融工程日报 市场表现：20251121 市场全线下跌，规模指数中上证 50 指数表现较好，板 块指数中上证综指表现较好，风格指数中沪深 300 价值指数表现较好。行业 指数全线下跌，家电、传媒、食品饮料、银行、农林牧渔行业表现较好，综 合、有色金属、基础化工、通信、电子行业表现较差。中船系、水产、小红 书平台、拼多多合作商、短剧游戏等概念表现较好，锂矿、锂电正极、锂电 隔膜、盐湖提锂、锂电电解液等概念表现较差。 市场情绪：20251121 收盘时有 33 只股票涨停，有 107 只股票跌停。昨日涨 停股票今日表现低迷，赚钱效应较弱，高开低走，收盘收益为-0.55%，昨日 跌停股票今日收盘收益为-5.58%。今日封板率 61%，较前日提升 10%，连板 率 24%，较前日下降 0%。 市场资金流向：截至 20251120 两融余额为 24917 亿元，其中融资余额 24744 亿元，融券余额 173 亿元。两融余额占流通市值比重为 2.6%，两融交易占市 场成交额比重为 10.1%。</doc> <doc id='3'>折溢价：20251120 当日 ETF 溢价较多的是创科技 ETF，ETF 折价较多的是芯 片 ETF 景顺。近半年以来大宗交易日均成交金额达到 20 亿元，20251120 当 日大宗交易成交金额为 19 亿元，近半年以来平均折价率 6.36%，当日折价率 为 7.71%。近一年以来上证 50、沪深 300、中证 500、中证 1000 股指期货主 力合约的年化贴水率中位数分别为 0.48%、3.39%、10.86%、13.39%，当日上 证 50 股指期货主力合约年化贴水率为 4.00%，处于近一年来 29%分位点，当 日沪深 300 股指期货主力合约年化贴水率为 7.08%，处于近一年来 25%分位 点；当日中证 500 股指期货主力合约年化贴水率为 8.69%，处于近一年来 69% 分位点；当日中证 1000 股指期货主力合约年化贴水率为 8.76%，处于近一年 来 80%分位点。</doc> <doc id='4'>机构关注与龙虎榜：近一周内调研机构较多的股票是九号公司-WD、蓝思科 技、泰恩康、中航重机、沃尔德、超颖电子、宏昌科技、斯菱股份等，九号 公司-WD 被 179 家机构调研。20251121 披露龙虎榜数据中，机构专用席位净 流入前十的股票是天华新能、易点天下、安妮股份、久其软件、榕基软件、 古麒绒材、江龙船艇、荃银高科、华瓷股份、神农种业等，机构专用席位净 流出前十的股票是西藏城投、视觉中国、浪潮软件、德力佳、禾信仪器、中 水渔业、梦天家居、亚通精工、南侨食品、北方长龙等。陆股通净流入前十 的股票是天华新能、江龙船艇、英利汽车、国风新材、久其软件、久之洋、 荃银高科、西藏城投、南侨食品等，陆股通净流出前十的股票是华胜天成、 视觉中国、方大炭素、诺德股份、浪潮软件、易点天下、禾信仪器等。 风险提示：市场环境变动风险；本报告基于历史客观数据统计，不构成投资 建议。</doc> <doc id='5'> | 金融工程·数量化投资 | | | --- | --- | | 证券分析师：张欣慰 | 联系人：李子靖 | | 021-60933159 | 021-60875177 | 021-60933159 021-60875177 zhangxinwei1@guosen.com.cn lizijing1@guosen.com.cn S0980520060001 相关研究报告 《金融工程日报-A 股高开低走，封板率创近一个月新低》 —— 2025-11-20 《金融工程日报-沪指震荡收红，水产股集体大涨、黄金股午后 拉升》 ——2025-11-19 《金融工程日报-沪指震荡走低，锂电产业链回调、互联网电商 概念逆势走强》 ——2025-11-18 《金融工程日报-沪指震荡下跌，锂矿题材逆势爆发》 —— 2025-11-17 《金融工程日报-沪指冲高回落，算力、半导体产业链领跌》 — —2025-11-14</doc> <doc id='6'>市场表现 宽基与风格指数表现 今日(20251121，下同) 市场全线下跌，规模指数中，上证 50 指数表现较好，上 证 50 指数下跌 1.74%，沪深 300 指数下跌 2.44%，中证 500 指数下跌 3.46%，中 证 1000 指数下跌 3.72%，中证 2000 指数下跌 3.99%。 板块指数中，上证综指表现较好，上证综指下跌 2.45%，深证综指下跌 3.43%，中 小 100 指数下跌 3.25%，创业板指下跌 4.02%，科创 50 指数下跌 3.19%，科创 100 指数下跌 4.04%，北证 50 指数下跌 4.71%。 风格指数中，沪深 300 价值指数表现较好，沪深 300 价值指数下跌 1.70%，沪深 300 成长指数下跌 2.47%，中证 500 价值指数下跌 3.30%，中证 500 成长指数下跌 3.16%。主要宽基、板块及风格指数今日表现如下图所示。</doc> <doc id='7'>图1：今日宽基、板块与风格指数表现 行业指数表现 今日行业指数全线下跌，家电、传媒、食品饮料、银行、农林牧渔行业表现较好， 收益分别为-0.27%、-0.50%、-0.89%、-1.00%、-1.58%，综合、有色金属、基础 化工、通信、电子行业表现较差，收益分别为-5.41%、-5.30%、-5.26%、-4.59%、 -4.41%，中信一级行业指数今日表现如下图所示。</doc> <doc id='8'>资料来源：Wind，国信证券经济研究所整理</doc> <doc id='9'>图2：今日中信一级行业指数表现 概念主题表现 今日中船系、水产、小红书平台、拼多多合作商、短剧游戏等概念表现较好，收 益分别为 3.51%、0.65%、0.47%、0.42%、0.22%，锂矿、锂电正极、锂电隔膜、 盐湖提锂、锂电电解液等概念表现较差，收益分别为-9.67%、-8.66%、-8.18%、 -8.08%、-7.99%，今日收益较高与较低的前十个概念指数表现如下图所示。</doc> <doc id='10'>资料来源：Wind，国信证券经济研究所整理</doc> <doc id='11'>图3：今日收益较高与较低的前十个概念指数 资料来源：Wind，国信证券经济研究所整理</doc> <doc id='12'>市场情绪 日内涨跌停家数 我们统计上市满 3 个月以上的股票在今日盘中的实时涨跌停家数情况。今日盘中 最高有 33 只股票

Core Insights - The report highlights the performance tracking of Guosen Securities' active quantitative strategies, indicating a significant adjustment in small-cap growth stocks, with the Growth Steady Portfolio achieving a year-to-date return of 48.45% [1][2][3] Performance Overview - The Excellent Fund Performance Enhancement Portfolio recorded an absolute return of -5.06% this week and 18.71% year-to-date, ranking in the 59.18th percentile among active equity funds [1][24] - The Exceeding Expectations Selected Portfolio had an absolute return of -5.67% this week and 33.39% year-to-date, ranking in the 26.72nd percentile among active equity funds [1][32] - The Broker Golden Stock Performance Enhancement Portfolio achieved an absolute return of -4.15% this week and 27.25% year-to-date, ranking in the 38.69th percentile among active equity funds [1][39] - The Growth Steady Portfolio saw an absolute return of -7.33% this week and 43.06% year-to-date, ranking in the 13.84th percentile among active equity funds [2][44] Strategy Summaries - The Excellent Fund Performance Enhancement Portfolio is constructed by benchmarking against active equity funds rather than broad indices, utilizing quantitative methods to select superior holdings [3][19] - The Exceeding Expectations Selected Portfolio is built by screening stocks based on exceeding expectations and analyst profit upgrades, focusing on both fundamental and technical criteria [4][25] - The Broker Golden Stock Performance Enhancement Portfolio is based on a selection of stocks from the broker's golden stock pool, optimized to minimize deviation from the benchmark [5][61] - The Growth Steady Portfolio employs a two-dimensional evaluation system for growth stocks, prioritizing those closer to earnings report dates and using multi-factor scoring for selection [6][40]

Core Insights - The report tracks the performance of various active quantitative strategies, highlighting the significant adjustments in small-cap growth stocks and the robust performance of the growth steady combination, which has increased by 48.45% year-to-date [1][2][14]. Group 1: Performance Overview - The excellent fund performance enhancement combination recorded an absolute return of -5.06% this week and 18.71% year-to-date, ranking in the 59.18th percentile among active equity funds [1][23]. - The super expectation selection combination had an absolute return of -5.67% this week and 33.39% year-to-date, ranking in the 26.72nd percentile among active equity funds [1][31]. - The broker's golden stock performance enhancement combination achieved an absolute return of -4.15% this week and 27.25% year-to-date, ranking in the 38.69th percentile among active equity funds [1][38]. - The growth steady combination saw an absolute return of -7.33% this week and 43.06% year-to-date, ranking in the 13.84th percentile among active equity funds [2][43]. Group 2: Strategy Descriptions - The excellent fund performance enhancement combination aims to outperform the median return of active equity funds by utilizing a quantitative approach based on the holdings of top-performing funds [3][19]. - The super expectation selection combination focuses on stocks that have exceeded expectations, selecting based on both fundamental and technical criteria to build a portfolio of stocks with strong support [4][24]. - The broker's golden stock performance enhancement combination is constructed using a selection from the broker's golden stock pool, optimizing the combination to minimize deviation from the benchmark [5][32]. - The growth steady combination employs a two-dimensional evaluation system for growth stocks, prioritizing stocks close to their earnings report dates to capture excess returns effectively [6][39].

- The "Hong Kong Stock Selection Portfolio" model is constructed based on a dual-layer selection process, combining fundamental and technical analysis. It aims to identify stocks with both fundamental support and technical resonance, focusing on analyst-recommended stocks. The backtesting period for this portfolio spans from January 1, 2010, to June 30, 2025, with an annualized return of 19.11% and an excess return of 18.48% relative to the Hang Seng Index[15][16][20] - The "Stable New High Stock Screening" factor is designed to identify stocks that have recently reached a 250-day high and exhibit stable price paths. The calculation for the 250-day new high distance is as follows: $ 250 \text{ Day New High Distance} = 1 - \frac{\text{Close}_{t}}{\text{ts\_max(Close, 250)}} $ where $\text{Close}_{t}$ is the latest closing price, and $\text{ts\_max(Close, 250)}$ is the maximum closing price over the past 250 trading days. Stocks with a smaller distance are closer to their 250-day high. The screening process incorporates factors such as analyst attention, relative price strength, price path smoothness, and the persistence of new highs[21][23][24] - The backtesting results for the "Hong Kong Stock Selection Portfolio" show annualized returns of 19.11%, an IR of 1.22, and a tracking error of 14.55%. The maximum drawdown during the sample period was 23.73%[20] - The "Stable New High Stock Screening" factor identified stocks across various sectors, with the highest number of stocks in the cyclical sector (6 stocks), followed by consumer, manufacturing, healthcare, financials, and technology sectors. Specific stocks include China Eastern Airlines, BeiGene, and China Aluminum Corporation, among others[23][24][29]

- The provided content does not include any quantitative models or factors, nor their construction, evaluation, or backtesting results

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]