Group 1: Key Points on Investor-Centric Transformation - The China Securities Regulatory Commission (CSRC) released the "Action Plan for Promoting High-Quality Development of Public Funds" on May 7, 2025, emphasizing an investor-centric approach[3]. - The plan outlines four key focuses: strengthening the alignment of interests with investors, expanding equity funds, enhancing investor service capabilities, and increasing industry stability[9]. - The introduction of a floating management fee mechanism aims to align fund managers' compensation with investor returns, with a target for leading firms to issue at least 60% of new equity funds under this model[10]. Group 2: Focus on Equity Fund Development - The plan continues the emphasis on the growth of equity funds, which has been a consistent theme since the 2022 guidelines[13]. - Public funds will have expanded access to financial derivatives, allowing for better risk management and absolute return strategies[13]. - The registration process for equity funds will be expedited, with a commitment to complete registrations for ETFs within 5 working days and for actively managed equity funds within 10 working days[14]. Group 3: Enhancing Investor Services - Fund companies are required to improve their research and investment capabilities, moving towards a team-based investment approach to enhance performance stability[15]. - The establishment of a centralized data platform for institutional investors aims to streamline investment processes and improve service quality[16]. - The plan encourages the development of low-volatility and asset allocation products to cater to conservative investors, alongside the introduction of new fund types like "fixed income plus" products[16]. Group 4: Strengthening Industry Stability - The plan introduces measures for liquidity management and long-term investment strategies to enhance the stability of public funds[17]. - Regulatory frameworks will be established to ensure compliance and protect the reputation of fund companies, addressing issues like dual roles of fund managers and conflicts of interest[18]. - The overall goal is to shift the industry focus from scale-driven growth to prioritizing investor interests, fostering a sustainable investment environment[18].

| https://www.cninfo.com.cn/new/disclosure/detail?stockCode=600370&announcementId=122321 | 600370 | 三房巷 | 1239&orgId=gssh0600370&announcementTime=2025 | -04-23 | | | --- | --- | --- | --- | --- | --- | | https://www.cninfo.com.cn/new/disclosure/detail?stockCode=603697&announcementId=122321 | 603697 | 有友食品 | 2766&orgId=gfbj0831377&announcementTime=2025 | -04-23 | | | https://www.cninfo.com.cn/new/disclosure/detail?stockCode=605358&announcementId=122321 | 605358 | 立昂微 | 3378&orgId=9900038308&announcementTime= ...

证券研究报告——宏观策略月报 静观其变，谋而后动 ——2025年5月资产配置报告 ► 请仔细阅读报告结尾处风险提示及免责声明 HWABAO SECURITIES 2025年5月8日 分析师： 蔡梦苑（执业证书编号：S0890521120001） 分析师： 郝一凡（执业证书编号：S0890524080002） 分析师： 刘 芳（执业证书编号：S0890524100002） 宏观主线梳理 宏观主线梳理 关税缓和信号显现，但行业关税仍存变数： 内容目录 海外宏观 Ø 对等关税税率后续有望下调，行业关税仍存变数 关税对经济影响逐渐显现，既定政策加快落地 Ø 美国一季度GDP萎缩，后续走势取决于关税谈判及减税政策进展 u 今年第一季度美国实际国内生产总值(GDP)按年率计算萎缩至-0.3%，主要受到抢进口和政府投资减少的拖累。后续美国经济走势 取决于关税谈判的进展（商品消费），以及减税政策的支持（私人投资）。 u 基于财政收益最大化及后续行业关税实施空间的考量，对等关税存在下调预期。预计最终调整方向或与特朗普竞选大致匹配—— 即全球基准税率降至10%，中国维持约60%高位。 u 对华关税政策方面，特朗普表示"对中国达成 ...

Quantitative Factors and Construction Methods 1. Factor Name: Market Style Factors - **Construction Idea**: The market style factors track the balance and volatility between different market styles, such as large-cap vs. small-cap and value vs. growth[11][13] - **Construction Process**: - **Style Balance**: Measure the relative performance of large-cap vs. small-cap stocks and value vs. growth stocks to determine the market's style preference[11] - **Style Volatility**: Calculate the fluctuations in the relative performance of these styles over time to assess the stability of the market's style preference[11] - **Evaluation**: The market style factors showed a balanced preference between large-cap and small-cap stocks, as well as between value and growth stocks. Additionally, the volatility of these styles continued to decline, indicating a more stable market environment[11][13] 2. Factor Name: Market Structure Factors - **Construction Idea**: These factors analyze the dispersion of returns, sector rotation, and trading concentration to understand the structural dynamics of the market[11][13] - **Construction Process**: - **Return Dispersion**: Measure the excess return dispersion across industry indices to evaluate the variability in sector performance[11] - **Sector Rotation**: Assess the speed of sector rotation by tracking changes in sector leadership over time[11] - **Trading Concentration**: Calculate the proportion of trading volume concentrated in the top 100 stocks and the top 5 industries to gauge market concentration[11] - **Evaluation**: The market structure factors indicated a decline in return dispersion, slower sector rotation, and reduced trading concentration, suggesting a more evenly distributed market environment[11][13] 3. Factor Name: Market Activity Factors - **Construction Idea**: These factors measure the overall activity and liquidity of the market through volatility and turnover rates[12][13] - **Construction Process**: - **Volatility**: Calculate the index-level volatility to assess market stability[12] - **Turnover Rate**: Measure the turnover rate of the market to evaluate trading activity[12] - **Evaluation**: The market activity factors showed a decline in both volatility and turnover rates, reflecting reduced market activity, likely influenced by the holiday period[12][13] 4. Factor Name: Commodity Market Factors - **Construction Idea**: These factors analyze the performance, momentum, and liquidity of various commodity sectors[27][30] - **Construction Process**: - **Trend Strength**: Measure the strength of price trends in different commodity sectors, such as energy, metals, and agriculture[27] - **Basis Momentum**: Calculate the basis momentum, particularly for the metals sector, to assess the relative strength of futures prices compared to spot prices[27][30] - **Volatility**: Track the volatility levels across commodity sectors to evaluate risk[27][30] - **Liquidity**: Measure the liquidity of commodity sectors to assess trading ease[27][30] - **Evaluation**: The commodity market factors showed mixed performance, with strong trends in energy and metals, weaker trends in agriculture, and high volatility across sectors. Liquidity remained stable overall[27][30] 5. Factor Name: Options Market Factors - **Construction Idea**: These factors analyze the implied volatility and skewness of options to infer market sentiment and expectations[35] - **Construction Process**: - **Implied Volatility**: Measure the implied volatility levels of options on major indices, such as the SSE 50 and CSI 1000, to gauge market uncertainty[35] - **Skewness**: Analyze the skewness of call and put options to understand market expectations for upward or downward movements[35] - **Evaluation**: The options market factors indicated a divergence in sentiment, with increased optimism for small-cap stocks (CSI 1000) and reduced optimism for large-cap stocks (SSE 50). This suggests a potential shift in market preference post-holiday[35] 6. Factor Name: Convertible Bond Market Factors - **Construction Idea**: These factors evaluate the valuation and trading activity of the convertible bond market[38] - **Construction Process**: - **Valuation**: Measure the average conversion premium of convertible bonds to assess their relative attractiveness[38] - **Trading Activity**: Track the trading volume and turnover in the convertible bond market to evaluate market interest[38] - **Evaluation**: The convertible bond market factors showed a slight increase in valuation, with trading activity continuing to recover, indicating improving market sentiment[38] --- Factor Backtesting Results 1. Market Style Factors - **Style Balance**: Balanced between large-cap and small-cap, as well as value and growth[11][13] - **Style Volatility**: Continued decline in volatility, indicating stability[11][13] 2. Market Structure Factors - **Return Dispersion**: Declined, indicating less variability in sector performance[11][13] - **Sector Rotation**: Slowed down, suggesting reduced changes in sector leadership[11][13] - **Trading Concentration**: Decreased, reflecting a more evenly distributed market[11][13] 3. Market Activity Factors - **Volatility**: Declined, indicating reduced market risk[12][13] - **Turnover Rate**: Decreased, reflecting lower trading activity[12][13] 4. Commodity Market Factors - **Trend Strength**: Strong in energy and metals, weak in agriculture[27][30] - **Basis Momentum**: Highest in metals, declined in other sectors[27][30] - **Volatility**: High across all sectors[27][30] - **Liquidity**: Stable overall[27][30] 5. Options Market Factors - **Implied Volatility**: Increased for both SSE 50 and CSI 1000, indicating higher uncertainty[35] - **Skewness**: Positive for CSI 1000 (small-cap optimism), negative for SSE 50 (large-cap caution)[35] 6. Convertible Bond Market Factors - **Valuation**: Slight increase in average conversion premium[38] - **Trading Activity**: Continued recovery in trading volume[38]

Report Industry Investment Rating - No information provided in the report. Core Viewpoints - The report presents several ETF strategy indices constructed using ETFs, and tracks the performance and holdings of these indices on a weekly basis. These indices aim to obtain excess returns relative to the market through different strategies [11]. Summary by Relevant Catalogs 1. ETF Strategy Index Tracking - **Overall Performance**: The table shows the performance of various ETF strategy indices last week, including index returns, benchmark returns, and excess returns. For example, the Huabao Research Size Rotation ETF Strategy Index had a last - week index return of 0.61%, a benchmark (CSI 800) return of 0.29%, and an excess return of 0.32% [12]. 1.1. Huabao Research Size Rotation ETF Strategy Index - **Strategy**: Utilizes multi - dimensional technical indicator factors and a machine - learning model to predict the return difference between the Shenwan Large - Cap Index and the Shenwan Small - Cap Index. It outputs weekly signals to determine holdings and obtain excess returns [13]. - **Performance**: As of April 30, 2025, the excess return since 2024 was 16.87%, the recent one - month excess return was 1.04%, and the recent one - week excess return was 0.32%. The index's recent one - week return was 0.61%, recent one - month return was - 2.35%, and since 2024 was 25.11%, compared to the CSI 800's 0.29%, - 3.38%, and 8.24% respectively [13][14]. - **Holdings**: As of April 30, 2025, it held 50% of CSI 500ETF (159922.SZ) and 50% of CSI 1000ETF (512100.SH) [16]. 1.2. Huabao Research SmartBeta Enhanced ETF Strategy Index - **Strategy**: Uses price - volume indicators to time self - built Barra factors, and maps timing signals to ETFs based on their exposure to 9 major Barra factors to achieve market - outperforming returns. It selects mainstream broad - based index ETFs and some style and strategy ETFs [15]. - **Performance**: As of April 30, 2025, the excess return since 2024 was 16.49%, the recent one - month excess return was 1.48%, and the recent one - week excess return was - 1.51%. The index's recent one - week return was - 1.22%, recent one - month return was - 1.91%, and since 2024 was 24.73%, compared to the CSI 800's 0.29%, - 3.38%, and 8.24% respectively [16][17]. - **Holdings**: As of April 30, 2025, it held 100% of Dividend Low - Volatility ETF (512890.SH) [23]. 1.3. Huabao Research Quantitative Fire - Wheel ETF Strategy Index - **Strategy**: Adopts a multi - factor approach, including long - and medium - term fundamental analysis, short - term market trend tracking, and analysis of market participants' behaviors. It uses valuation and crowding signals to indicate industry risks and multi - dimensionally digs out potential sectors to obtain excess returns [20]. - **Performance**: As of April 30, 2025, the excess return since 2024 was 0.53%, the recent one - month excess return was 0.93%, and the recent one - week excess return was - 0.03%. The index's recent one - week return was 0.26%, recent one - month return was - 2.45%, and since 2024 was 8.78%, compared to the CSI 800's 0.29%, - 3.38%, and 8.24% respectively [20][23]. - **Holdings**: As of April 30, 2025, it held 20.93% of Bank ETF (512800.SH), 20.88% of Agriculture ETF (159825.SZ), 19.59% of Military Industry ETF (512660.SH), etc. [24]. 1.4. Huabao Research Quantitative Balancing Act ETF Strategy Index - **Strategy**: Employs a multi - factor system covering economic fundamentals, liquidity, technical aspects, and investor behavior. It constructs a quantitative timing system to judge the equity market trend, builds a prediction model for market large - and small - cap styles to adjust equity market position distribution, and comprehensively obtains excess returns through timing and rotation [24]. - **Performance**: As of April 30, 2025, the excess return since 2024 was 2.46%, the recent one - month excess return was 2.04%, and the recent one - week excess return was 0.32%. The index's recent one - week return was 0.27%, recent one - month return was - 0.97%, and since 2024 was 12.35%, compared to the SSE 300's - 0.05%, - 3.01%, and 9.89% respectively [24][26]. - **Holdings**: As of April 30, 2025, it held 5.09% of CSI 1000ETF (512100.SH), 4.98% of 500ETF Enhanced (159610.SZ), 29.13% of 300 Enhanced ETF (561300.SH), etc. [28]. 1.5. Huabao Research Hot - Spot Tracking ETF Strategy Index - **Strategy**: Based on strategies such as market sentiment analysis, industry event tracking, investor sentiment and professional opinions, policy and regulatory changes, and historical deduction, it tracks and mines hot - spot index target products in a timely manner to construct an ETF portfolio that can capture market hot - spots, providing short - term market trend references for investors [28]. - **Performance**: As of April 30, 2025, the recent one - month excess return was 2.06%, and the recent one - week excess return was 0.11%. The index's recent one - week return was 1.19%, compared to the CSI All - Share's 1.08% [28][31]. - **Holdings**: As of April 30, 2025, it held 4.15% of Real Estate ETF (515060.SH), 27.03% of Hong Kong Stock Consumption ETF (513230.SH), etc. [32]. 1.6. Huabao Research Bond ETF Duration Strategy Index - **Strategy**: Uses bond market liquidity and price - volume indicators to screen effective timing factors and predicts bond yields through machine - learning methods. When the expected yield is below a certain threshold, it reduces the long - duration position in the bond investment portfolio to improve long - term returns and drawdown control ability [32]. - **Performance**: As of April 30, 2025, the recent one - month excess return was 0.20%, and the recent one - week excess return was 0.02%. The index's recent one - week return was 0.19%, recent one - month return was 1.20%, since 2024 was 9.32%, and since inception was 14.47%, compared to the ChinaBond Aggregate Index's 0.17%, 1.00%, 4.97%, and 6.91% respectively [32][33]. - **Holdings**: As of April 30, 2025, it held 50.01% of 10 - Year Treasury Bond ETF (511260.SH), 25.00% of Policy Financial Bond ETF (511520.SH), etc. [36].

| 新股发行及今日交易提示 | 2025/5/7 | 星期三 | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | | 2025/5/7 | 新股发行 | 证券代码 | 证券简称 | 发行价格 | | | | | 787755 | 汉邦科技 | 22.77 | 2025/5/7 | 内地市场权益提示 | | | | | 类别 | 证券代码 | 证券简称 | 权益日期 | 最新公告链接 | https://www.cninfo.com.cn/new/disclosure/detail?stockCode=600777&announcementId=122337 | 要约申报期1：2025年4月8日至2025年5月7日 | | | 5830&orgId=gssh0600777&announcementTime=2025 | -04-29 | 要约收购 | 600777 | ST新潮 | https://www.cninfo.com.cn/new/disclosure/detail?stockCode=600777&announcementId= ...

Group 1 - The report highlights that the expectation for the Federal Reserve to cut interest rates has cooled, leading to market fluctuations and uncertainties [9][10][12] - The U.S. GDP contracted by 0.3% in Q1 2025, marking the first decline since Q1 2022, which may impact market sentiment [9] - The non-farm payroll data exceeded expectations with 177,000 new jobs added in April, while the unemployment rate remained at 4.2%, indicating a mixed economic outlook [9] Group 2 - In the bond market, there is an expectation for macroeconomic data to be released soon, with a focus on holding bonds as yields may decline further [10][12] - The stock market is expected to experience short-term disturbances, but sectors with strong earnings performance, particularly high-dividend defensive sectors like banks and utilities, are likely to be favored [3][12] - The report suggests monitoring sectors influenced by national subsidies, such as consumer electronics and home appliances, as well as non-energy cyclical sectors like steel and non-ferrous metals [3][12] Group 3 - The report indicates that the market is currently in a cautious state, with a preference for defensive positions in both the bond and stock markets [15] - The A-share market is experiencing a mixed performance, with a decline in average daily trading volume to 1,103.9 billion yuan, reflecting a low market sentiment [20] - The report emphasizes the importance of upcoming economic data releases, including the Federal Reserve's interest rate decision and China's CPI and PPI data [21]

| 新股发行及今日交易提示 | 2025/4/30 | 星期三 | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | | 2025/4/30 | 内地市场权益提示 | 类别 | 证券代码 | 证券简称 | 权益日期 | 最新公告链接 | | | https://www.cninfo.com.cn/new/disclosure/detail?stockCode=600777&announcementId=122337 | 要约申报期1：2025年4月8日至2025年5月7日 | 5830&orgId=gssh0600777&announcementTime=2025 | -04-29 | 要约收购 | 600777 | ST新潮 | | | https://www.cninfo.com.cn/new/disclosure/detail?stockCode=600777&announcementId=122337 | 要约申报期2：2025年4月23日至2025年5月22日 | 5831&orgId=gssh0600777&announceme ...

New Stock Offerings - ST Xinchao (600777) has two tender offer periods: April 8 to May 7, 2025, and April 23 to May 22, 2025[1] - Puli Tui (300630) is in the delisting arrangement period with 13 trading days remaining[1] - ST Yushun (002289) and ST Jingan (600190) are also highlighted for their recent announcements[1] Market Alerts - Jinlitai (300225) has been flagged for severe abnormal fluctuations[1] - Guoguang Chain (605188) and Dongfang Tong (300379) have recent announcements regarding their trading status[1] - Multiple stocks including Huadian Energy (600726) and Huadian Liaoning (600396) have recent updates as of April 29, 2025[1] Trading Periods - The last trading day for several stocks is approaching, with specific mention of ST Yushun and ST Jingan[1] - The report indicates that various stocks are under observation due to unusual trading activities[2]

Quantitative Factors and Models Summary Stock Market Factors and Construction - **Factor Name**: Market Style Factors **Construction Idea**: Analyze the dominant market style trends, including size and value-growth preferences [10][13] **Construction Process**: - **Size Style**: Evaluate the preference for large-cap stocks over small-cap stocks - **Value-Growth Style**: Assess the inclination towards value stocks compared to growth stocks - **Volatility Metrics**: Measure the volatility of size and value-growth styles to track stability trends [10][13] **Evaluation**: The market style factors indicate a stable preference for large-cap and value stocks, with declining volatility in both dimensions [10][13] - **Factor Name**: Market Structure Factors **Construction Idea**: Examine the structural dynamics of the market, including industry performance and trading concentration [10][13] **Construction Process**: - **Industry Excess Return Dispersion**: Calculate the dispersion of excess returns across industry indices - **Industry Rotation Speed**: Measure the rate of industry rotation - **Concentration Metrics**: Analyze the trading concentration by evaluating the proportion of trading volume in the top 100 stocks and top 5 industries [10][13] **Evaluation**: The market structure factors reveal increased industry rotation and reduced trading concentration, indicating a more dispersed market environment [10][13] - **Factor Name**: Market Activity Factors **Construction Idea**: Assess the overall activity level in the market through volatility and turnover metrics [10][13] **Construction Process**: - **Volatility**: Track the decline in market volatility from previous high levels - **Turnover Rate**: Measure the reduction in market turnover rates [10][13] **Evaluation**: The market activity factors suggest a calmer market environment with reduced trading intensity [10][13] Commodity Market Factors and Construction - **Factor Name**: Commodity Trend Strength **Construction Idea**: Evaluate the trend strength across different commodity sectors [25][28] **Construction Process**: - **Sector Analysis**: Identify strong trends in energy and black metal sectors, and weaker trends in non-ferrous metals and agricultural products [25][28] **Evaluation**: The factor highlights sector-specific trend strength variations, with energy and black metals showing robust trends [25][28] - **Factor Name**: Basis Momentum **Construction Idea**: Measure the momentum of basis changes across commodity sectors [25][28] **Construction Process**: - **Sector Basis Analysis**: Track the highest basis momentum in non-ferrous metals and rapid declines in black metals [25][28] **Evaluation**: The factor reflects significant basis momentum differences across sectors, indicating varied market dynamics [25][28] - **Factor Name**: Commodity Volatility **Construction Idea**: Monitor the volatility levels across commodity sectors [25][28] **Construction Process**: - **Sector Volatility Metrics**: Evaluate the consistently high volatility across all commodity sectors [25][28] **Evaluation**: The factor suggests persistent uncertainty in commodity markets [25][28] - **Factor Name**: Commodity Liquidity **Construction Idea**: Assess the liquidity conditions across commodity sectors [25][28] **Construction Process**: - **Sector Liquidity Metrics**: Measure stable liquidity levels across all sectors [25][28] **Evaluation**: The factor indicates steady liquidity conditions in commodity markets [25][28] Option Market Factors and Construction - **Factor Name**: Implied Volatility Factors **Construction Idea**: Analyze implied volatility trends in major indices [32] **Construction Process**: - **Indices Analysis**: Track slight increases in implied volatility for SSE 50 and CSI 1000 indices - **Volatility Curve**: Compare far-month and near-month implied volatility differences - **Skewness Metrics**: Evaluate skewness advantages of put options over call options [32] **Evaluation**: The factors reveal market concerns for small-cap stocks and neutral sentiment for large-cap stocks [32] Convertible Bond Market Factors and Construction - **Factor Name**: Convertible Bond Premium **Construction Idea**: Assess valuation levels and trading activity in the convertible bond market [36] **Construction Process**: - **Premium Metrics**: Measure the average premium levels, slightly above the historical median - **Low Premium Bond Count**: Track the rebound in the number of bonds with low premiums - **Market Turnover**: Evaluate the increase in overall market turnover [36] **Evaluation**: The factors indicate stable valuation levels and improved trading activity in the convertible bond market [36] Factor Backtesting Results - **Market Style Factors**: - Size preference: Large-cap dominant [10][13] - Value preference: Value stocks dominant [10][13] - Volatility: Declining [10][13] - **Market Structure Factors**: - Industry dispersion: Increased [10][13] - Industry rotation: Faster [10][13] - Trading concentration: Reduced [10][13] - **Market Activity Factors**: - Volatility: Declining [10][13] - Turnover: Reduced [10][13] - **Commodity Market Factors**: - Trend strength: Sector-specific variations [25][28] - Basis momentum: Sector-specific variations [25][28] - Volatility: High across sectors [25][28] - Liquidity: Stable across sectors [25][28] - **Option Market Factors**: - Implied volatility: Slight increase [32] - Skewness: Put options advantage [32] - **Convertible Bond Market Factors**: - Premium levels: Stable, slightly above median [36] - Low premium bond count: Rebound [36] - Turnover: Increased [36]