Group 1 - The core viewpoint of the article emphasizes the performance of the "brokerage golden stocks" and their ability to track the performance of mixed equity funds, showcasing the analytical capabilities of brokerage firms [2][9]. - In November 2025, the top-performing stocks in the brokerage golden stock pool included Blue Cursor, Yanjiang Co., and Suzhou Tianmai, with significant monthly increases [1][4]. - The top three brokerages in terms of monthly returns were Guolian Minsheng Securities, Guoyuan Securities, and Huaxin Securities, with returns of 4.48%, 3.40%, and 0.64% respectively, while the mixed equity fund index and the CSI 300 index both saw negative returns [6][8]. Group 2 - As of December 1, 2025, a total of 41 brokerages released their golden stocks for the month, resulting in 264 unique A-shares after deduplication [21][28]. - The current allocation of brokerage golden stocks is heavily weighted in the electronics (15.38%), basic chemicals (7.96%), and machinery (7.43%) sectors, with notable increases in food and beverage, media, and consumer services sectors [28][21]. - The performance of the brokerage golden stock performance enhancement portfolio showed an absolute return of -1.06% for the month and a return of 33.65% year-to-date, outperforming the mixed equity fund index by 1.39% and 4.42% respectively [36][32]. Group 3 - The article highlights the performance of various selection factors within the brokerage golden stock pool, noting that total market capitalization and quarterly revenue growth rates performed well recently, while analyst net adjustment ratios showed weaker performance [20][16]. - The brokerage golden stock index has been able to track the mixed equity fund index effectively, indicating a strong correlation between the two [9][14]. - The article also discusses the importance of analyst recommendations in increasing market attention for lesser-known stocks within the brokerage golden stock pool [24][22].

Quantitative Models and Construction Methods - **Model Name**: Securities Firm Golden Stock Performance Enhancement Portfolio **Model Construction Idea**: The model aims to optimize the selection of stocks from the securities firm's golden stock pool to outperform the benchmark index, specifically the actively managed equity fund index. It leverages a multi-factor approach and portfolio optimization techniques to control deviations in individual stocks and styles while aligning with the industry distribution of public funds[37][42]. **Model Construction Process**: 1. Use the securities firm's golden stock pool as the stock selection space and constraint benchmark. 2. Apply a multi-factor model to further refine the stock selection within the pool. 3. Optimize the portfolio to control deviations in individual stocks and styles relative to the golden stock pool. 4. Use the industry distribution of all public funds as the industry allocation benchmark. 5. Adjust the portfolio at the beginning of each month based on the latest recommendations and market data[37][42]. **Model Evaluation**: The model demonstrates strong alpha generation potential and consistently outperforms the benchmark index, reflecting the research strength of securities firms[42]. Model Backtesting Results - **Securities Firm Golden Stock Performance Enhancement Portfolio**: - **Absolute Return (Monthly)**: -1.06% (20251103-20251128)[41] - **Excess Return (Monthly)**: +1.39% relative to the actively managed equity fund index[41] - **Absolute Return (Year-to-Date)**: +33.65% (20250102-20251128)[41] - **Excess Return (Year-to-Date)**: +4.42% relative to the actively managed equity fund index[41] - **Ranking in Actively Managed Equity Funds (Year-to-Date)**: 35.37th percentile (1227/3469)[41] - **Annualized Return (2018-2025)**: +19.34%[43] - **Annualized Excess Return (2018-2025)**: +14.38% relative to the actively managed equity fund index[43] - **Performance Ranking (2018-2025)**: Top 30% of actively managed equity funds every year[43] Quantitative Factors and Construction Methods - **Factor Name**: Total Market Capitalization **Factor Construction Idea**: Reflects the size of a company, often used to capture the size effect in stock returns[26][27]. **Factor Construction Process**: Calculate the total market capitalization of each stock in the golden stock pool. Group stocks into quintiles based on their market capitalization and calculate the long-short portfolio returns for each group[26][27]. **Factor Evaluation**: Demonstrates strong performance in both the recent month and year-to-date periods[26][27]. - **Factor Name**: Single-Quarter Revenue Growth **Factor Construction Idea**: Measures the growth in revenue over a single quarter, capturing the growth potential of a company[26][27]. **Factor Construction Process**: Compute the quarter-over-quarter revenue growth for each stock. Group stocks into quintiles based on their growth rates and calculate the long-short portfolio returns for each group[26][27]. **Factor Evaluation**: Exhibits strong performance year-to-date[26][27]. - **Factor Name**: SUR (Surprise) **Factor Construction Idea**: Captures the degree to which a company's earnings or revenue exceed market expectations[26][27]. **Factor Construction Process**: Calculate the difference between actual and expected earnings or revenue for each stock. Group stocks into quintiles based on their surprise levels and calculate the long-short portfolio returns for each group[26][27]. **Factor Evaluation**: Performs well in both the recent month and year-to-date periods[26][27]. - **Factor Name**: EPTTM (Earnings to Price Trailing Twelve Months) **Factor Construction Idea**: A valuation factor that measures the earnings yield of a stock[26][27]. **Factor Construction Process**: Compute the ratio of trailing twelve-month earnings to the current stock price for each stock. Group stocks into quintiles based on their EPTTM values and calculate the long-short portfolio returns for each group[26][27]. **Factor Evaluation**: Underperforms year-to-date[26][27]. - **Factor Name**: Expected Dividend Yield **Factor Construction Idea**: Reflects the expected return from dividends, often used as a value factor[26][27]. **Factor Construction Process**: Calculate the expected dividend yield for each stock. Group stocks into quintiles based on their yields and calculate the long-short portfolio returns for each group[26][27]. **Factor Evaluation**: Underperforms year-to-date[26][27]. - **Factor Name**: BP (Book-to-Price Ratio) **Factor Construction Idea**: A valuation factor that measures the book value relative to the stock price[26][27]. **Factor Construction Process**: Compute the ratio of book value to stock price for each stock. Group stocks into quintiles based on their BP values and calculate the long-short portfolio returns for each group[26][27]. **Factor Evaluation**: Underperforms year-to-date[26][27]. Factor Backtesting Results - **Total Market Capitalization**: Strong performance in the recent month and year-to-date[26][27] - **Single-Quarter Revenue Growth**: Strong performance year-to-date[26][27] - **SUR (Surprise)**: Strong performance in the recent month and year-to-date[26][27] - **EPTTM (Earnings to Price Trailing Twelve Months)**: Weak performance year-to-date[26][27] - **Expected Dividend Yield**: Weak performance year-to-date[26][27] - **BP (Book-to-Price Ratio)**: Weak performance year-to-date[26][27]

Quantitative Models and Construction Methods - **Model Name**: Securities Firm Golden Stock Performance Enhancement Portfolio **Model Construction Idea**: The model aims to optimize the selection of stocks from the securities firm golden stock pool, using a multi-factor approach to achieve stable outperformance relative to the benchmark index (Active Equity Hybrid Fund Index) [37][42] **Model Construction Process**: 1. The securities firm golden stock pool is used as the stock selection space and constraint benchmark [42] 2. The portfolio optimization method is applied to control deviations in individual stocks and styles between the portfolio and the golden stock pool [42] 3. The industry allocation is based on the distribution of all public funds [42] 4. The portfolio's benchmark is the Active Equity Hybrid Fund Index, and the portfolio's position last month was 90.48% [37] **Model Evaluation**: The model demonstrates strong alpha generation potential and stable performance, consistently outperforming the benchmark index over multiple years [42][43] Model Backtesting Results - **Securities Firm Golden Stock Performance Enhancement Portfolio**: - **Absolute Return (Monthly)**: -1.06% [41] - **Excess Return (Monthly)**: 1.39% relative to the Active Equity Hybrid Fund Index [41] - **Absolute Return (Year-to-Date)**: 33.65% [41] - **Excess Return (Year-to-Date)**: 4.42% relative to the Active Equity Hybrid Fund Index [41] - **Ranking in Active Equity Funds (Year-to-Date)**: 35.37% percentile (1227/3469) [41] - **Annualized Return (2018-2025)**: 19.34% [43] - **Annualized Excess Return (2018-2025)**: 14.38% relative to the Active Equity Hybrid Fund Index [43] - **Performance Ranking (2018-2025)**: Top 30% of active equity funds every year [43] Quantitative Factors and Construction Methods - **Factor Name**: Total Market Capitalization **Factor Construction Idea**: Reflects the size of a company, often used to capture size-related effects in stock returns [26][27] **Factor Evaluation**: Demonstrated strong performance both in the past month and year-to-date [26][27] - **Factor Name**: Single-Quarter Surprise (SUR) **Factor Construction Idea**: Measures the degree of earnings surprise in a single quarter, capturing the market's reaction to unexpected earnings [26][27] **Factor Evaluation**: Performed well in both the past month and year-to-date [26][27] - **Factor Name**: Single-Quarter Revenue Growth **Factor Construction Idea**: Tracks the growth rate of revenue in a single quarter, reflecting a company's operational growth [26][27] **Factor Evaluation**: Strong performance year-to-date [26][27] - **Factor Name**: EPTTM (Earnings to Price Trailing Twelve Months) **Factor Construction Idea**: A valuation factor that measures earnings relative to price over the trailing twelve months [26][27] **Factor Evaluation**: Underperformed year-to-date [26][27] - **Factor Name**: Expected Dividend Yield **Factor Construction Idea**: Captures the expected dividend income relative to the stock price, often used as an income-focused valuation metric [26][27] **Factor Evaluation**: Underperformed year-to-date [26][27] - **Factor Name**: BP (Book-to-Price Ratio) **Factor Construction Idea**: A valuation factor that measures the book value of equity relative to the stock price [26][27] **Factor Evaluation**: Underperformed year-to-date [26][27] Factor Backtesting Results - **Total Market Capitalization**: Strong performance in both the past month and year-to-date [26][27] - **Single-Quarter Surprise (SUR)**: Strong performance in both the past month and year-to-date [26][27] - **Single-Quarter Revenue Growth**: Strong performance year-to-date [26][27] - **EPTTM**: Weak performance year-to-date [26][27] - **Expected Dividend Yield**: Weak performance year-to-date [26][27] - **BP (Book-to-Price Ratio)**: Weak performance year-to-date [26][27]

Quantitative Models and Construction Methods - **Model Name**: "Kaiyuan Quantitative Engineering Preferred Gold Stock Portfolio" **Model Construction Idea**: The model is based on the observation that newly introduced stocks outperform repeated stocks. It incorporates the "SUE factor" (Surprise Earnings Factor), which demonstrates superior stock selection ability within newly introduced stocks[25] **Model Construction Process**: 1. Select the top 30 newly introduced stocks with the highest earnings surprise (SUE factor) 2. Weight the portfolio based on the number of recommendations by brokers 3. Construct the portfolio using these weighted stocks[25] **Model Evaluation**: The model demonstrates better performance compared to the overall gold stock portfolio, with higher annualized returns and lower maximum drawdowns[25][27] Model Backtesting Results - **Kaiyuan Quantitative Engineering Preferred Gold Stock Portfolio**: - November return: -0.2% - 2025 YTD return: 45.1% - Annualized return: 22.5% - Annualized volatility: 25.3% - Return-to-volatility ratio: 0.89 - Maximum drawdown: 24.6%[27][28] - **Overall Gold Stock Portfolio**: - November return: -3.4% - 2025 YTD return: 32.2% - Annualized return: 13.2% - Annualized volatility: 23.5% - Return-to-volatility ratio: 0.56 - Maximum drawdown: 42.6%[23][27] - **CSI 300 Index**: - November return: -2.5% - 2025 YTD return: 15.0% - Annualized return: 3.3% - Annualized volatility: 21.1% - Return-to-volatility ratio: 0.16 - Maximum drawdown: 40.6%[23][27] - **CSI 500 Index**: - November return: -4.1% - 2025 YTD return: 22.8% - Annualized return: 1.2% - Annualized volatility: 23.8% - Return-to-volatility ratio: 0.05 - Maximum drawdown: 37.5%[23][27] Quantitative Factors and Construction Methods - **Factor Name**: Surprise Earnings Factor (SUE Factor) **Factor Construction Idea**: The factor captures stocks with earnings that significantly exceed market expectations, which are likely to outperform in the short term[25] **Factor Construction Process**: 1. Calculate the earnings surprise for each stock as the difference between reported earnings and consensus estimates 2. Rank stocks based on their earnings surprise values 3. Select the top-ranked stocks for portfolio inclusion[25] **Factor Evaluation**: The SUE factor demonstrates strong stock selection ability, particularly within newly introduced stocks, and contributes to the superior performance of the preferred gold stock portfolio[25] Factor Backtesting Results - **SUE Factor**: - Incorporated into the preferred gold stock portfolio, contributing to its annualized return of 22.5% and return-to-volatility ratio of 0.89[25][27]

- The report highlights that in November 2025, the top-performing factors in the broker's gold stock pool were total market capitalization, single-quarter revenue surprise, and SUR, while factors like intraday return, analyst net upgrade magnitude, and analyst net upgrade ratio performed poorly[3][26] - For the year 2025, the best-performing factors were total market capitalization, single-quarter revenue growth, and SUR, whereas EPTTM, expected dividend yield, and BP underperformed[3][26] - The broker's gold stock performance enhancement portfolio achieved an absolute return of -1.06% for the month (20251103-20251128) and an excess return of 1.39% relative to the mixed equity fund index[5][41] - For the year (20250102-20251128), the portfolio achieved an absolute return of 33.65% and an excess return of 4.42% relative to the mixed equity fund index, ranking in the 35.37% percentile among active equity funds[5][41] - The broker's gold stock performance enhancement portfolio has consistently outperformed the mixed equity fund index from 2018 to 2022, ranking in the top 30% of active equity funds each year[12][37][43]

Core Viewpoint - The performance of listed companies in the A-share market has stabilized as the third-quarter reports are disclosed, leading to a focus on certain sectors and stocks by brokerages for November's "golden stocks" list [1] Group 1: Sector Recommendations - Over 180 stocks have been included in brokerages' November "golden stocks" list, with notable recommendations in the automotive and parts sector, as well as in the new energy and home appliance sectors [1] - Top Group has been recommended by five brokerages in the automotive and parts sector, while CATL has also received five recommendations in the new energy sector [1] - Haier Smart Home stands out in the home appliance sector with four recommendations, making it the most recommended company in its industry [1] Group 2: Home Appliance Sector Insights - The home appliance sector is benefiting from policies like trade-in programs and increasing export demand, which favor leading companies with stable performance and global presence [1] - Haier Smart Home is highlighted for its improving operational performance in the European and American markets and its ability to capture market share in emerging markets, supported by strong product innovation capabilities [1] - Despite challenges from real estate and related factors, leading companies in the home appliance sector are expected to experience structural growth driven by consumer recovery and industrial upgrades [1]

Industry Overview - In November, the electronic sector remains the most favored industry among brokerages, accounting for 15.1% of the recommended stocks [2][3] - Coal is the industry with the most significant increase in allocation, with a rise of 2.2% compared to October [3] - The media and machinery sectors have seen a notable decrease in weight, with reductions of 2.0% and 1.7% respectively [4] Stock Recommendations - Kingsoft Office (688111) is the most recommended stock, appearing in the top recommendations six times [6][7] - Other highly recommended stocks include Zijin Mining (601899), Zhongji Xuchuang (300308), and Top Group (601689), each recommended five times [6][7] - New entries in the recommended stocks include Haier Smart Home (600690) and Ping An Insurance (601318), both recommended four times [9] Sector-Specific Insights - The top recommended stocks in the electronic sector include Industrial Fulian, recommended five times [11] - In the power equipment sector, both Ningde Times and Tianci Materials were recommended three times [11] - The automotive sector's leading stock is Top Group, also recommended five times [10][11] Market Trends - The overall market trend indicates a shift towards value style, as evidenced by the declining market capitalization and valuation levels of the recommended stocks [4] - The increase in coal, home appliances, and banking sectors suggests a potential pivot in investment strategies [3][4]

Quantitative Models and Factor Construction Quantitative Models and Construction Methods 1. Model Name: Broker Gold Stock Performance Enhancement Portfolio - **Model Construction Idea**: The model aims to optimize the selection from the broker gold stock pool to outperform the benchmark index of equity-biased hybrid funds[12][39] - **Model Construction Process**: - The model uses the broker gold stock pool as the stock selection space and constraint benchmark - It employs portfolio optimization to control deviations in individual stocks and styles from the broker gold stock pool - The industry allocation is based on the industry distribution of all public funds - The portfolio is adjusted at the closing price on the first day of each month[12][39][42] - **Model Evaluation**: The model has shown stable performance historically, consistently outperforming the equity-biased hybrid fund index annually from 2018 to 2022[12][39][42] Model Backtest Results Broker Gold Stock Performance Enhancement Portfolio - **Absolute Return (Monthly)**: -0.77% (20251009-20251031)[41] - **Excess Return Relative to Equity-biased Hybrid Fund Index (Monthly)**: 1.37% (20251009-20251031)[41] - **Absolute Return (Year-to-date)**: 35.08% (20250102-20251031)[41] - **Excess Return Relative to Equity-biased Hybrid Fund Index (Year-to-date)**: 2.61% (20250102-20251031)[41] - **Ranking in Active Equity Funds (Year-to-date)**: 40.13% percentile (412/3469)[41] Quantitative Factors and Construction Methods 1. Factor Name: Total Market Value - **Factor Construction Idea**: This factor measures the total market capitalization of a stock, which is often used to capture the size effect in stock returns[3][28] - **Factor Construction Process**: - The total market value is calculated as the product of the stock's current price and the total number of outstanding shares[3][28] - **Factor Evaluation**: The total market value factor has shown good performance in the recent month and year-to-date periods[3][28] 2. Factor Name: Single Quarter Revenue Growth Rate - **Factor Construction Idea**: This factor measures the growth rate of a company's revenue in a single quarter, indicating its short-term growth potential[3][28] - **Factor Construction Process**: - The single quarter revenue growth rate is calculated as the percentage change in revenue from the previous quarter to the current quarter[3][28] - **Factor Evaluation**: The single quarter revenue growth rate factor has shown good performance year-to-date[3][28] 3. Factor Name: Analyst Net Upward Revision - **Factor Construction Idea**: This factor measures the net number of upward revisions by analysts, reflecting positive changes in analyst sentiment[3][28] - **Factor Construction Process**: - The analyst net upward revision is calculated as the difference between the number of upward revisions and the number of downward revisions over a specific period[3][28] - **Factor Evaluation**: The analyst net upward revision factor has shown good performance year-to-date[3][28] Factor Backtest Results Total Market Value Factor - **Recent Month Performance**: Good[3][28] - **Year-to-date Performance**: Good[3][28] Single Quarter Revenue Growth Rate Factor - **Recent Month Performance**: Not specified - **Year-to-date Performance**: Good[3][28] Analyst Net Upward Revision Factor - **Recent Month Performance**: Not specified - **Year-to-date Performance**: Good[3][28]

Group 1 - The core viewpoint of the article emphasizes the performance of the "brokerage golden stocks" and their ability to track the performance of mixed equity funds, showcasing the analytical capabilities of brokerage firms [2][10][31] - In October 2025, the top-performing stocks in the brokerage golden stock pool included GuoDun Quantum, Rongxin Culture, and JiangBolong, with significant monthly increases [1][3][4] - The top three brokerages in terms of monthly returns were Western Securities, Great Wall Securities, and Guoyuan Securities, with returns of 5.84%, 5.43%, and 4.03% respectively, while the mixed equity fund index returned -2.14% [6][8] Group 2 - As of November 3, 2025, a total of 42 brokerages released their golden stocks for the month, resulting in 275 unique A-shares after deduplication [21][27] - The sectors with the highest allocation in the current golden stock pool were electronics (15.26%), non-ferrous metals (8.68%), and basic chemicals (6.84%) [27] - The brokerage golden stock performance enhancement portfolio had an absolute return of -0.77% for the month and a relative excess return of 1.37% compared to the mixed equity fund index [35] Group 3 - The article highlights the performance of various selection factors within the brokerage golden stock pool, noting that total market capitalization and quarterly revenue growth rates performed well recently [18][16] - The article also discusses the stocks that received multiple recommendations from analysts, indicating higher market attention, with stocks like Industrial Fulian and Kingsoft receiving recommendations from five or more analysts [22][23] - The brokerage golden stock index showed a year-to-date return of 28.59%, compared to the mixed equity fund index's return of 32.47% [14][35]

- 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]