========= - The "券商金股业绩增强组合" (Broker Gold Stock Performance Enhanced Portfolio) aims to outperform the median of public funds by optimizing the broker gold stock pool[39] - The portfolio uses the偏股混合型基金指数 (Equity-biased Hybrid Fund Index) as its benchmark, with a 90% position last month[39] - The absolute return of the portfolio for the month (2050901-20250930) was -0.55%, with an excess return of -3.50% relative to the偏股混合型基金指数[42] - The absolute return for the year (20250102-20250930) was 33.26%, with an excess return of 1.19% relative to the偏股混合型基金指数[42] - The portfolio ranked in the 43.07% percentile among active equity funds this year (1494/3469)[42] - The annualized return of the portfolio from 2018.1.2 to 2025.6.30 was 19.34%, with an annualized excess return of 14.38% relative to the偏股混合型基金指数[44] - The portfolio consistently ranked in the top 30% of active equity funds each year from 2018 to 2025[44] - The portfolio's performance statistics for each year from 2018 to 2025 are detailed in Table 6[47] - The portfolio's historical performance is illustrated in Figure 12[46] =========

Group 1 - In August, the A-share market strengthened, leading to positive returns for most of the recommended stocks by brokerages, with 244 out of 287 stocks recommended showing price increases [1][3] - The average gain of the recommended stocks in August was positive, with notable performances from brokerages such as Kaiyuan Securities and AVIC Securities [1][5] - The top three performing stocks in August were Huasheng Tiancai (600410.SH) with a gain of 115.11%, followed by Hanwujing (688256.SH) with a gain of 110.36%, and Siquan New Materials (301489.SZ) with a gain of 100.66% [3][4] Group 2 - As of September 4, over 40 brokerages had recommended 285 stocks for September, with Kaiying Network (002517.SZ) and Deepin Technology (300454.SZ) being the most frequently recommended [2][8] - Kaiying Network was recommended by multiple brokerages due to its upcoming product cycle and stable mid-year performance, reporting a revenue of 2.578 billion yuan, a year-on-year increase of 0.89%, and a net profit of 950 million yuan, a year-on-year increase of 17.41% [9][10] Group 3 - The technology sector performed exceptionally well in August, with 7 out of the top 10 recommended stocks belonging to this sector [5][6] - Conversely, the healthcare sector underperformed, with half of the stocks in the top 10 largest declines being from this industry, including Yifang Biotechnology (688382.SH) which fell by 19.62% [6][7] Group 4 - Among the stocks recommended for September, Deepin Technology had a high price-to-earnings ratio of 240.05, indicating a significant valuation compared to other recommended stocks [12] - Deepin Technology reported a revenue of 3.009 billion yuan for the first half of 2025, a year-on-year increase of 11.16%, but also reported a net loss of 228 million yuan, which was a 61.54% increase in loss compared to the previous year [12]

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 fund indices effectively, showcasing the analytical capabilities of brokerage firms [2][37]. - In August 2025, the top-performing stocks in the brokerage golden stock pool included Huasheng Tiancai, Hanwujing-U, and Siquan New Materials, with significant monthly increases [1][3]. - The top three brokerages by monthly returns were Kaiyuan Securities, AVIC Securities, and China Merchants Securities, with returns of 26.42%, 25.08%, and 24.07% respectively, outperforming the mixed equity fund index and the CSI 300 index [6][10]. Group 2 - The brokerage golden stock pool showed strong performance in factors such as quarterly net profit growth, quarterly ROE, and quarterly revenue growth, while factors like BP, intraday return, and expected dividend yield performed poorly [21][23]. - As of September 1, 2025, there were 39 brokerages publishing golden stocks, resulting in a total of 301 unique A-shares after deduplication, with significant allocations in the electronics, machinery, and basic chemical industries [23][27]. - The brokerage golden stock performance enhancement portfolio achieved an absolute return of 15.49% for the month and 34.01% year-to-date, outperforming the mixed equity fund index by 3.59% and 5.72% respectively [33][38]. Group 3 - The article highlights the interaction between brokerage analysts and public fund managers, indicating that the recommendations from brokerage analysts can significantly influence market attention towards certain stocks [13][27]. - The article also discusses the identification of stocks with relatively low market attention that have been recommended as golden stocks, suggesting potential investment opportunities [29][30]. - The performance of the brokerage golden stock industry portfolio showed excess returns in the electronics, electric new energy, and basic chemical industries for the month, while the year-to-date performance highlighted excess returns in electronics, automotive, and agriculture sectors [17][23].

Quantitative Models and Construction Methods Model Name: Broker Gold Stock Performance Enhancement Portfolio - **Model Construction Idea**: The model aims to optimize the selection of stocks from the broker gold stock pool to outperform the median of active equity funds[39][43]. - **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 distribution of all public funds is used as the industry allocation benchmark. - The model's detailed construction method can be found in the report "Broker Gold Stock Full Analysis - Data, Modeling, and Practice" published on February 18, 2022[39][43]. - **Model Evaluation**: The model has shown stable performance historically, consistently outperforming the active equity fund index from 2018 to 2022, ranking in the top 30% of active equity funds each year[12][39]. Model Backtesting Results Broker Gold Stock Performance Enhancement Portfolio - **Absolute Return (Monthly)**: 15.49%[5][42] - **Excess Return Relative to Active Equity Fund Index (Monthly)**: 3.59%[5][42] - **Absolute Return (Year-to-Date)**: 34.01%[5][42] - **Excess Return Relative to Active Equity Fund Index (Year-to-Date)**: 5.72%[5][42] - **Ranking in Active Equity Funds (Year-to-Date)**: 30.38% percentile (1054/3469)[5][42] Quantitative Factors and Construction Methods Factor Name: Single Quarter Net Profit Growth Rate - **Factor Construction Idea**: This factor measures the growth rate of net profit in a single quarter[3][28]. - **Factor Construction Process**: - Calculate the net profit for the current quarter. - Compare it to the net profit of the same quarter in the previous year. - The formula is: $ \text{Net Profit Growth Rate} = \frac{\text{Current Quarter Net Profit} - \text{Previous Year Same Quarter Net Profit}}{\text{Previous Year Same Quarter Net Profit}} \times 100\% $ - **Factor Evaluation**: This factor has performed well recently[3][28]. Factor Name: Single Quarter ROE - **Factor Construction Idea**: This factor measures the return on equity for a single quarter[3][28]. - **Factor Construction Process**: - Calculate the net income for the quarter. - Divide it by the average shareholders' equity for the quarter. - The formula is: $ \text{ROE} = \frac{\text{Net Income}}{\text{Average Shareholders' Equity}} \times 100\% $ - **Factor Evaluation**: This factor has performed well recently[3][28]. Factor Name: Single Quarter Revenue Growth Rate - **Factor Construction Idea**: This factor measures the growth rate of revenue in a single quarter[3][28]. - **Factor Construction Process**: - Calculate the revenue for the current quarter. - Compare it to the revenue of the same quarter in the previous year. - The formula is: $ \text{Revenue Growth Rate} = \frac{\text{Current Quarter Revenue} - \text{Previous Year Same Quarter Revenue}}{\text{Previous Year Same Quarter Revenue}} \times 100\% $ - **Factor Evaluation**: This factor has performed well recently[3][28]. Factor Backtesting Results Single Quarter Net Profit Growth Rate - **Performance**: This factor has shown good performance recently[3][28]. Single Quarter ROE - **Performance**: This factor has shown good performance recently[3][28]. Single Quarter Revenue Growth Rate - **Performance**: This factor has shown good performance recently[3][28].

Quantitative Models and Construction Methods 1. Model Name: "All Stocks Portfolio" - **Model Construction Idea**: This model aggregates all broker-recommended stocks ("golden stocks") and evaluates their performance as a portfolio[18][21] - **Model Construction Process**: 1. Collect all broker-recommended stocks for the month 2. Weight the stocks within the portfolio based on the number of recommendations by brokers 3. Exclude non-A-share stocks and Hong Kong-listed stocks to focus solely on A-shares[18] - **Model Evaluation**: The model demonstrates strong performance, significantly outperforming benchmark indices such as CSI 300 and CSI 500[18][21] 2. Model Name: "Newly Added Stocks Portfolio" - **Model Construction Idea**: Focuses on stocks newly added to the broker-recommended list, as they tend to exhibit better performance compared to repeated recommendations[18][23] - **Model Construction Process**: 1. Identify stocks newly added to the broker-recommended list for the month 2. Construct a portfolio weighted by the number of broker recommendations 3. Exclude non-A-share stocks and Hong Kong-listed stocks[18] - **Model Evaluation**: Newly added stocks outperform repeated recommendations, showcasing their superior return potential[18][23] 3. Model Name: "Repeated Stocks Portfolio" - **Model Construction Idea**: Focuses on stocks that have been repeatedly recommended by brokers across multiple months[18] - **Model Construction Process**: 1. Identify stocks that were recommended in the previous month and continue to be recommended in the current month 2. Construct a portfolio weighted by the number of broker recommendations 3. Exclude non-A-share stocks and Hong Kong-listed stocks[18] - **Model Evaluation**: While the performance is positive, it is generally weaker compared to newly added stocks[18] 4. Model Name: "Optimized Golden Stocks Portfolio" - **Model Construction Idea**: Selects the top 30 newly added stocks with the highest earnings surprise factor (SUE factor) to construct an optimized portfolio[23] - **Model Construction Process**: 1. Filter newly added stocks based on their earnings surprise factor (SUE factor) 2. Select the top 30 stocks with the highest SUE factor 3. Weight the portfolio based on the number of broker recommendations[23] - **Model Evaluation**: This optimized portfolio demonstrates superior performance compared to the "All Stocks Portfolio" and benchmark indices[23][25] --- Model Backtesting Results 1. All Stocks Portfolio - **August Return**: 13.6%[21] - **2025 YTD Return**: 33.5%[21] - **Annualized Return**: 13.7%[21] - **Annualized Volatility**: 23.6%[21] - **Sharpe Ratio**: 0.58[21] - **Maximum Drawdown**: 42.6%[21] 2. Newly Added Stocks Portfolio - **August Return**: 11.8%[21] - **2025 YTD Return**: 37.9%[21] - **Annualized Return**: 16.5%[21] - **Annualized Volatility**: 24.3%[21] - **Sharpe Ratio**: 0.68[21] - **Maximum Drawdown**: 38.5%[21] 3. Repeated Stocks Portfolio - **August Return**: 15.6%[21] - **2025 YTD Return**: 30.2%[21] - **Annualized Return**: 11.3%[21] - **Annualized Volatility**: 23.7%[21] - **Sharpe Ratio**: 0.48[21] - **Maximum Drawdown**: 45.0%[21] 4. Optimized Golden Stocks Portfolio - **August Return**: 19.6%[25] - **2025 YTD Return**: 37.6%[25] - **Annualized Return**: 22.3%[25] - **Annualized Volatility**: 25.5%[25] - **Sharpe Ratio**: 0.88[25] - **Maximum Drawdown**: 24.6%[25] --- Quantitative Factors and Construction Methods 1. Factor Name: Earnings Surprise Factor (SUE Factor) - **Factor Construction Idea**: Measures the degree to which a company's earnings exceed or fall short of market expectations, serving as a key indicator for stock selection[23] - **Factor Construction Process**: 1. Calculate the earnings surprise for each stock as the difference between reported earnings and consensus estimates 2. Normalize the earnings surprise to account for variations across stocks and industries 3. Rank stocks based on their normalized earnings surprise values[23] - **Factor Evaluation**: The SUE factor demonstrates strong predictive power, particularly in identifying high-performing newly added stocks[23] --- Factor Backtesting Results 1. SUE Factor - **Performance**: The SUE factor is highly effective in selecting top-performing stocks within the newly added category, contributing to the superior returns of the Optimized Golden Stocks Portfolio[23]

Core Viewpoint - On August 7, securities firms issued "buy" ratings for over 20 A-share listed companies, focusing on sectors such as medical services, agriculture, home appliances, semiconductors, construction materials, fertilizers, and specialized equipment [1]. Group 1: Key Stocks Recommended by Securities Firms - WuXi AppTec (603259) received a "buy" rating from Zhongyou Securities, with an upward revision of its annual performance guidance, expecting revenues of 43.29 billion, 49.02 billion, and 55.85 billion yuan for 2025, 2026, and 2027, respectively, with a net profit of 14.91 billion, 13.88 billion, and 16.16 billion yuan [2][3]. - Zhong'an Shares (002891) was highlighted by Kaiyuan Securities for significant revenue and profit growth, with a focus on domestic sales [2]. - Haida Group (002311) is noted for its overseas expansion potential, with a report from Guoxin Securities emphasizing its status as a quality asset in the agriculture sector [3][4]. - Junshi Network (688475) was rated "buy" by Yuanyin Galaxy, citing strong growth in its smart home business [2]. - Chipone Technology (688521) showed improved profitability in Q2, with a report from Xinda Securities [2]. - Dongfang Yuhong (002271) is expected to reach a profitability turning point in the second half of the year, according to Zhongyou Securities [2]. - Haiguang Information (688041) received attention for its performance in the semiconductor sector [2]. - Cangge Mining (000408) was noted for stable profitability in potassium chloride and strong performance from its copper mine [2]. - Jereh Group (002353) reported a 37% year-on-year increase in net profit, exceeding expectations [2]. - Zhuozhao Dispensing (873726) received initial coverage for its diverse expansion in dispensing equipment [2]. Group 2: Overall Market Insights - The focus of securities firms on various sectors indicates a strategic interest in industries with growth potential, particularly in medical services and agriculture [1][4]. - The reports suggest that while "buy" or "increase" ratings are provided, they do not guarantee stock price increases, and investors should consider these ratings as references rather than definitive investment advice [4].

数据显示，洛阳钼业8月5日主力资金净流入2271.80万元，但近五日主力资金净流出3.7亿元。 风险提示：市场有风险，投资需谨慎。 截至2025年8月5日15时，洛阳钼业股价报9.38元，较前一交易日上涨1.30%。当日成交额达15.93亿元， 振幅为2.59%。 洛阳钼业主要从事铜、钼、钨、钴等金属的采选、冶炼及深加工业务，是全球领先的钨钼生产商和重要 的铜生产商。公司业务覆盖亚洲、非洲、南美洲等多个国家和地区。 根据公开信息，洛阳钼业预计2025年上半年净利润为82亿元至91亿元，同比增长51.37%至67.98%。中 原证券、华源证券等五家券商将其列入8月金股推荐名单，主要基于铜价中枢上移的预期。 本文源自：金融界 作者：A股君 ...

Group 1 - In August, 42 brokerage firms released their "golden stocks" lists, recommending a total of 370 times across 286 A-shares, including 187 from the main board, 48 from the ChiNext, 50 from the Sci-Tech Innovation Board, and 1 from the Beijing Stock Exchange [1] - The most popular A-shares include Dongfang Zhiye, Luoyang Molybdenum, and Muyuan Foods, which were recommended 7 times, 5 times, and 5 times respectively [1] - A total of 182 A-shares saw an increase in recommendation counts compared to the previous month, with Wanhua Chemical, Dongfang Zhiye, and Luoyang Molybdenum experiencing the most significant increases of 4 times, 4 times, and 3 times respectively [1] Group 2 - Nineteen industries have been recommended more than 10 times, with the most favored sectors being electronic devices, instruments and components, metals, non-metals and mining, and chemicals, receiving 39, 38, and 34 recommendations respectively [1]

Group 1 - The article presents the number of "golden stocks" identified by securities firms across various industries, highlighting the sectors with the highest counts [1] - The electronics sector leads with 18 "golden stocks," followed by basic chemicals and machinery equipment, each with 18 and 16 respectively [1] - The pharmaceutical and biological industry has 15 "golden stocks," while non-ferrous metals and computer sectors have 13 and 12 respectively [1] Group 2 - The power equipment and non-bank financial sectors each have 10 "golden stocks," indicating a balanced interest in these industries [1] - The automotive sector also features 10 "golden stocks," reflecting its significance in the current market landscape [1] - The defense and military industry has 9 "golden stocks," suggesting a growing focus on this sector [1]

Quantitative Models and Construction - **Model Name**: "Kaiyuan JinGong Optimal Stock Portfolio" **Model Construction Idea**: This model is based on the observation that newly recommended stocks ("newly entered stocks") outperform repeatedly recommended stocks ("repeated stocks"). It incorporates the "Surprise in Earnings" (SUE) factor to select stocks with strong earnings surprises, aiming to enhance portfolio returns[23][25]. **Model Construction Process**: 1. Use newly recommended stocks as the sample universe. 2. Select the top 30 stocks with the highest SUE factor values. 3. Weight the portfolio based on the number of recommendations by brokers. **Model Evaluation**: The model demonstrates superior performance compared to the overall stock portfolio and benchmark indices, indicating its effectiveness in capturing excess returns[23][25]. Model Backtesting Results - **Kaiyuan JinGong Optimal Stock Portfolio**: - **July Return**: 5.8%[25] - **2025 YTD Return**: 18.0%[25] - **Annualized Return**: 20.8%[25] - **Annualized Volatility**: 25.2%[25] - **Sharpe Ratio (Return-to-Volatility)**: 0.82[25] - **Maximum Drawdown**: 24.6%[25] - **Overall Stock Portfolio**: - **July Return**: 7.7%[21] - **2025 YTD Return**: 18.5%[21] - **Annualized Return**: 12.2%[21] - **Annualized Volatility**: 23.4%[21] - **Sharpe Ratio (Return-to-Volatility)**: 0.52[21] - **Maximum Drawdown**: 42.6%[21] - **Benchmark Indices**: - **CSI 300**: - **July Return**: 3.5%[21] - **2025 YTD Return**: 3.6%[21] - **Annualized Return**: 2.4%[21] - **Annualized Volatility**: 21.2%[21] - **Sharpe Ratio (Return-to-Volatility)**: 0.11[21] - **Maximum Drawdown**: 40.6%[21] - **CSI 500**: - **July Return**: 5.3%[21] - **2025 YTD Return**: 8.7%[21] - **Annualized Return**: 0.1%[21] - **Annualized Volatility**: 23.7%[21] - **Sharpe Ratio (Return-to-Volatility)**: 0.01[21] - **Maximum Drawdown**: 37.5%[21] Quantitative Factors and Construction - **Factor Name**: Surprise in Earnings (SUE) Factor **Factor Construction Idea**: The SUE factor measures the degree of earnings surprise, which is a key indicator of stock performance. Stocks with higher earnings surprises are expected to outperform[23]. **Factor Construction Process**: 1. Calculate the earnings surprise for each stock based on the difference between actual and expected earnings. 2. Rank stocks by their SUE values. 3. Select the top stocks with the highest SUE values for portfolio inclusion[23]. **Factor Evaluation**: The SUE factor demonstrates strong stock selection ability, particularly within the newly recommended stock universe, contributing to the superior performance of the optimal stock portfolio[23]. Factor Backtesting Results - **SUE Factor**: - Integrated into the "Kaiyuan JinGong Optimal Stock Portfolio," contributing to its superior performance metrics as detailed above[23][25].