证券研究报告 | 公司点评报告 2025 年 04 月 13 日 圣农发展（002299.SZ） 24 年业绩逐季度改善，25Q1 逆势再突破 消费品/农林牧渔 综合造肉成本持续下行&食品端发力共同驱动公司 2024 年业绩逐季度改善；成 本优化及 C 端高增助力公司 25Q1 逆势再突破，看好公司发展前景。 ❑ 风险提示：鸡价上涨不达预期；自然灾害风险；原料成本上涨风险；动物疫 病风险；食品安全风险。 财务数据与估值 | 会计年度 | 2023 | 2024 | 2025E | 2026E | 2027E | | --- | --- | --- | --- | --- | --- | | 营业总收入(百万元) | 18487 | 18586 | 21524 | 24926 | 28867 | | 同比增长 | 10% | 1% | 16% | 16% | 16% | | 营业利润(百万元) | 759 | 802 | 1213 | 1516 | 1815 | | 同比增长 | 56% | 6% | 51% | 25% | 20% | | 归母净利润(百万元) | 664 | 724 | 1104 | 138 ...

Core Insights - The report indicates that after the tariff impact, there is a need for policies to stimulate domestic demand, with expectations for more incremental policies to be introduced in the upcoming Politburo meeting, particularly in consumption, real estate, and livelihood areas [2][5][10] - The report highlights that the recent tariff adjustments have led to a marginal improvement in the negative impacts of tariffs, with the market expected to recover and enter an upward cycle [2][9] - The report emphasizes that the focus for the year will be on domestic demand policies and the application of AI technologies [9][10] Policy Directions - Consumption policies are expected to be strengthened, with historical precedents showing that direct cash subsidies and supply-side optimization are effective during severe external shocks [11][12] - The real estate sector may see increased efforts in city-specific policies and urban village renovations, aiming to stabilize the housing market [13] - Livelihood policies may include nationwide childbirth subsidies and measures to stabilize employment, reflecting a broader commitment to social welfare [14] Market Dynamics - The report notes that the recent fluctuations in the A-share market were primarily due to external shocks, including trade tensions and global market volatility [5][6] - The report indicates that the sales of excavators and new energy vehicles have shown significant year-on-year growth, suggesting a recovery in certain sectors [5] - The report mentions that the ETF market has seen record inflows, indicating strong institutional support for the A-share market [44][46] Tariff Exemptions - The report details that the U.S. has granted significant tariff exemptions on electronic products, which could positively impact China's exports to the U.S., with an estimated export value of $100.2 billion affected by these exemptions [49]

基金大幅拉久期——债市晴雨表 【债市情绪】上周债市情绪指数为 114.9，较前值回升 0.3；债市情绪扩散指数 52.3%，较前值回升 2.4 个百分点。 【机构久期】上周五基金久期为 2.28 年，较前一周五回升 0.11 年；农商行久 期为 2.56 年，较前一周五回落 0.14 年；保险久期为 6.78 年，较前一周五回落 0.11 年。 证券研究报告 | 债券点评报告 2025 年 04 月 13 日 【杠杆率】上周质押式回购余额为 10.7 万亿元，较前值回落 0.3 万亿元；大行 净融出余额为 2.9 万亿元，较前值回落 0.3 万亿元；债市杠杆率为 103.5%，较 前值持平。 【二级成交】上周从换手率来看，30Y 国债换手率为 2.7%，较前值回升 1.0 个 百分点。10Y 国债换手率为 2.0%，较前值回升 0.8 个百分点；10Y 国开债换手 率为 28.9%，较前值回升 5.1 个百分点；超长期信用债换手率为 0.46%，较前 值回落 0.03 个百分点。 【配置力量】债市配置力量来看，上周债基新发行份额为 23 亿元，较前值回升 23 亿元；风险偏好来看，股市风险溢价为 1.83%， ...

Report Industry Investment Rating No relevant content provided. Core Viewpoints of the Report - This week, the equity market declined overall, with the BeiZheng 50 slightly rising and the Hong Kong stock market experiencing a significant correction. The bond market rose, while the convertible bond market fell. Among funds, consumer and TMT funds performed relatively well [1][2]. - The average return of active equity funds in the whole market was -3.85%. Short - term bond funds had an average return of 0.10%, and medium - and long - term bond funds had an average return of 0.17%. Both equity - containing bond funds and convertible bond funds had negative average returns [1][2]. - There were 3 new stocks listed this week, with no break - even on the first day of listing. The average return of sample new - stock subscription funds this week was -0.86%, and the new - stock subscription yield for an 800 - million - yuan account was 0.030% [2]. - As of April 9, 2025, the average returns of low, medium, and high - risk FOF funds in the sample in the past week were -1.28%, -4.09%, and -6.64% respectively. During the statistical period, equity - oriented, index - type, alternative, and bond - type QDII funds declined by 7.81%, 8.37%, 5.94%, and 0.94% on average, and REITs declined by 0.57% on average [2]. Summary by Directory Market Review - Equity Market: The equity market declined overall, with the BeiZheng 50 slightly rising and the Hong Kong stock market correcting significantly. As of the close this week, the CSI 300 Index closed at 3,751 points, down 2.87%; the Shanghai Composite Index closed at 3,238 points, down 3.11%; the Shenzhen Component Index closed at 9,834 points, down 5.13%; the ChiNext Index closed at 1,926 points, down 6.73%. The Hang Seng Index in Hong Kong fell 8.47%, and the Hang Seng Tech Index fell 7.77% [6]. - Industry Performance: Agriculture, forestry, animal husbandry, and fishery led, with a gain of over 3%. Commerce and retail, national defense and military industry, and consumer services also performed well. Power equipment and new energy, communication, and media declined significantly, with a drop of over 6.5% [8]. - Number of Rising Stocks: As of April 11, 2025, there were 5,409 stocks in the A - share market, of which 796 rose this week. The number of rising stocks in the BeiZheng, ChiNext, Science and Technology Innovation Board, and Main Board was 117, 134, 97, and 448 respectively. Industries such as basic chemicals, machinery, agriculture, forestry, animal husbandry, and fishery, and electronics had a relatively large number of rising stocks, while the banking, coal, and steel industries had no rising stocks [11][15]. Key Fund Tracking Active Equity - Fund Performance: There were 3,949 active equity funds in the sample. The average return of the whole - market funds in the sample this week was -3.85%. Funds with better performance were mostly heavily invested in industries such as electronics, machinery, and medicine. Among industry funds, consumer funds had relatively better average returns, and top - performing funds in the TMT sector were leading [17][19]. - Position Estimation: The positions of ordinary stock - type and partial - stock hybrid funds increased this week. Compared with the previous week, the position of ordinary stock - type funds increased by 0.53 percentage points, and that of partial - stock hybrid funds increased by 0.26 percentage points. Actively managed partial - stock funds increased their allocation to stable and growth sectors and reduced their allocation to consumption, cyclical, and financial sectors. In terms of sub - industries, the allocation to industries such as computers, power equipment, and household appliances increased, while the allocation to industries such as banking, electronics, and non - banking finance decreased [22]. Bond - Type Funds - Bond Market Performance: The bond market rose overall this week. The ChinaBond Total Wealth Index closed at 245.84, up 0.38% from last week; the ChinaBond Treasury Bond Index closed at 246.84, up 0.5%; the ChinaBond Credit Bond Index closed at 222.13, up 0.16%. The CSI Non - Pure Bond Fund Index closed at 2,170.4 on Thursday, down 0.33% from last Thursday. The CSI Convertible Bond Index closed at 420.91, with a weekly decline of 1.7%, and the trading volume was 465.5 billion yuan, a change of 224.248 billion yuan from last week [30][32]. - Fund Performance Overview: The average return of short - term bond funds this week was 0.10%, and the median was 0.09%. The average return of medium - and long - term bond funds was 0.17%, and the median was 0.15%. The average return of first - tier bond funds was -0.03%, and the median was 0.07%. The average return of second - tier bond funds was -0.52%, and the median was -0.42%. The average return of partial - bond hybrid funds was -0.74%, and the median was -0.62%. The average return of low - position flexible allocation funds was -0.54%, and the median was -0.35%. The average return of convertible bond funds was -1.98%, and the median was -2.01% [34][36][37][39]. New - Stock Subscription Funds - New - Stock Overview: Three new stocks were listed this week, all with inquiry and offline placement details, raising a total of 1.81 billion yuan. There was no break - even on the first day of listing, and the total expected income from successful subscription was 241,100 yuan [40]. - New - Stock Subscription Income Calculation: Assuming weekly participation in offline new - stock subscriptions and successful subscription, based on the successful subscription rate of Class A investors, the number of allocated shares was calculated. Using the closing price on the first day of listing or the opening - board day as the selling price, the weekly new - stock subscription yield sequence for an 800 - million - yuan account was calculated. The weekly new - stock subscription yield for an 800 - million - yuan account this week was 0.030%. The optimal weekly and annual new - stock subscription scales were 200 million yuan and 400 million yuan respectively [41][43]. - Fund Company New - Stock Subscription Overview: Eight fund companies with two or more new - stock subscription funds were selected. All of them had a 100% successful subscription rate for the three new stocks this week, except for Southern Fund, which had a 50% successful subscription rate [44]. - New - Stock Subscription Fund Performance: There were 36 new - stock subscription funds in the sample. The average return of new - stock subscription funds in the sample this week was -0.86% [45]. FOF Funds - FOF funds were divided into low - risk, medium - risk, and high - risk categories. The average returns of low - risk, medium - risk, and high - risk FOF funds in the sample in the past week were -1.28%, -4.09%, and -6.64% respectively [46]. QDII Funds - During the statistical period, the average decline of equity - oriented and index - type QDII funds was 7.81% and 8.37% respectively, and the average decline of alternative and bond - type QDII funds was 5.94% and 0.94% respectively [47][48]. REITs Funds - The average decline of REITs this week was 0.57%. The Huaxia Beijing Affordable Housing REIT had a relatively high increase, rising 3.67% in the past week. The Huaxia China Communications Construction Expressway REIT had the strongest liquidity, with a trading volume of 200.4172 million yuan in the past week [49][50].

Quantitative Models and Construction Methods 1. Model Name: Short-term Quantitative Timing Model - **Model Construction Idea**: This model integrates signals from valuation, liquidity, fundamentals, and sentiment to generate short-term market timing signals[17][18] - **Model Construction Process**: - **Valuation Signal**: Based on PE and PB percentile rankings over the past 5 years. A higher percentile indicates optimism, while a lower percentile indicates caution[17][21] - **Liquidity Signal**: Derived from indicators such as money market rates, exchange rate expectations, and net financing. Favorable liquidity conditions generate optimistic signals[18][21] - **Fundamental Signal**: Includes metrics like manufacturing PMI, long-term loan growth, and M1 growth. Stronger fundamentals lead to optimistic signals[17][21] - **Sentiment Signal**: Combines metrics like trading volume, turnover rate, and market volatility. Higher sentiment scores indicate optimism[18][21] - **Signal Aggregation**: Signals from the four dimensions are aggregated to determine the overall market timing signal (optimistic, neutral, or cautious)[17][18] - **Model Evaluation**: The model demonstrates strong predictive power for short-term market movements, with significant outperformance over the benchmark strategy[19][22] 2. Model Name: Growth-Value Style Rotation Model - **Model Construction Idea**: This model identifies the relative attractiveness of growth versus value styles based on fundamentals, valuation, and sentiment[27][28] - **Model Construction Process**: - **Fundamental Signal**: Factors include profit cycle slope, interest rate cycle level, and credit cycle changes. Favorable conditions for growth or value are identified based on these metrics[27][29] - **Valuation Signal**: PE and PB valuation spreads between growth and value are analyzed. A narrowing spread favors growth, while a widening spread favors value[27][29] - **Sentiment Signal**: Metrics like turnover and volatility differences between growth and value are used. Lower turnover favors value, while higher volatility favors balance[28][29] - **Signal Aggregation**: Signals from the three dimensions are combined to determine the allocation between growth and value styles[27][28] - **Model Evaluation**: The strategy has historically outperformed a balanced allocation, though it underperformed in certain years like 2014 and 2020[28][31] 3. Model Name: Small-Cap vs. Large-Cap Style Rotation Model - **Model Construction Idea**: This model evaluates the relative attractiveness of small-cap versus large-cap styles based on fundamentals, valuation, and sentiment[32][33] - **Model Construction Process**: - **Fundamental Signal**: Similar to the growth-value model, factors include profit cycle slope, interest rate cycle level, and credit cycle changes. Favorable conditions for small-cap or large-cap are identified[32][34] - **Valuation Signal**: PE and PB valuation spreads between small-cap and large-cap are analyzed. A narrowing spread favors large-cap, while a widening spread favors small-cap[33][34] - **Sentiment Signal**: Metrics like turnover and volatility differences between small-cap and large-cap are used. Higher turnover favors small-cap, while lower volatility favors large-cap[33][34] - **Signal Aggregation**: Signals from the three dimensions are combined to determine the allocation between small-cap and large-cap styles[32][33] - **Model Evaluation**: The strategy has historically delivered significant outperformance over a balanced allocation, though it underperformed in certain years like 2020[33][35] 4. Model Name: Four-Style Rotation Model - **Model Construction Idea**: This model combines the conclusions of the growth-value and small-cap-large-cap models to allocate across four styles: small-cap growth, small-cap value, large-cap growth, and large-cap value[38][39] - **Model Construction Process**: - **Signal Aggregation**: The allocation is determined by combining the signals from the growth-value and small-cap-large-cap models. For example, the current allocation is 37.5% small-cap growth, 12.5% small-cap value, 37.5% large-cap growth, and 12.5% large-cap value[38][39] - **Model Evaluation**: The strategy has consistently outperformed a balanced allocation, with significant annualized excess returns. However, it underperformed in years like 2014 and 2020[38][39] --- Model Backtesting Results 1. Short-term Quantitative Timing Model - **Annualized Return**: 16.16% - **Annualized Volatility**: 14.80% - **Maximum Drawdown**: 27.70% - **Sharpe Ratio**: 0.9509 - **Monthly Win Rate**: 67.79%[19][22][24] 2. Growth-Value Style Rotation Model - **Annualized Return**: 11.06% - **Annualized Volatility**: 21.01% - **Maximum Drawdown**: 43.07% - **Sharpe Ratio**: 0.5101 - **Monthly Win Rate**: 57.43%[28][31] 3. Small-Cap vs. Large-Cap Style Rotation Model - **Annualized Return**: 11.84% - **Annualized Volatility**: 22.91% - **Maximum Drawdown**: 50.65% - **Sharpe Ratio**: 0.5168 - **Monthly Win Rate**: 60.14%[33][35] 4. Four-Style Rotation Model - **Annualized Return**: 12.65% - **Annualized Volatility**: 21.75% - **Maximum Drawdown**: 47.91% - **Sharpe Ratio**: 0.5656 - **Monthly Win Rate**: 58.78%[38][39]

证券研究报告 | 基金研究（公募） 2025 年 4 月 12 日 A 股收跌，量化基金表现偏弱 量化基金周度跟踪（20250407-20250411） 本报告重点聚焦量化基金市场表现，总结近一周主要指数和量化基金业绩表现、 不同类型公募量化基金整体表现和业绩分布，以及本周收益表现较优的量化基 金，供投资者参考。 市场整体表现： 本周（4 月 7 日-4 月 11 日）A 股整体收跌，量化基金收益表现偏弱。 主要指数表现： 主要股指普遍下跌，其中沪深 300、中证 500、中证 1000 分别跌 2.87%、 4.52%、5.50%。 各类基金表现： 本周量化基金收益表现偏弱，主动量化跌 4.26%；市场中性跌 0.11%。指 数增强型基金普遍录得负超额，其中中证 1000 指增收益表现基本与基准持 平，仅 47%的产品跑赢基准，平均超额收益为 0.01%；沪深 300 指增和中 证 500 指增分别平均跑输基准 0.39%、0.38%。 风险提示：图表中列示的数据结果仅为对市场及个基历史表现的客观描述，并 不预示其未来表现，亦不构成投资收益的保证或投资建议。 徐燕红 S1090524120003 xuyan ...

本周流动性风格显著，招商量化中证 1000 指增组合近一周 超额 1.38% ——因子周报 20250411 金融工程 1. 主要市场指数与风格表现回顾 本周主要宽基指数大多下跌。北证 50 上涨 0.92%，沪深 300 下跌 2.87%， 上证指数下跌 3.11%，中证 800 下跌 3.30%，中证 500 下跌 4.52%，深证成指 下跌 5.13%，中证 1000 下跌 5.50%，创业板指下跌 6.73%，中证 2000 下跌 7.01%。 从行业来看，本周农林牧渔，商贸零售，国防军工，消费者服务，食品饮 料等行业表现居前；电力设备及新能源，通信，传媒，机械，钢铁等行业表现 居后。 从风格因子来看，最近一周非线性市值因子、流动性因子和 Beta 因子的表 现尤为突出，因子多空收益分别为 2.00%、-2.51%和-1.47%。 2. 选股因子表现跟踪 沪深 300 股票池中，本周 60 日成交额、单季度营业利润率、20 日换手率 因子表现较好。中证 500 股票池中，本周对数市值、60 日成交额、20 日非流 动性冲击因子表现较好。中证 800 股票池中，本周 60 日成交额、20 日成交额、 单 ...

1. Report Industry Investment Rating No relevant content provided. 2. Core Viewpoints of the Report - The report focuses on the performance of the ETF fund market in the week from April 7th to April 11th, including the market performance and capital flow of different types of ETF funds, to provide reference for investors [1]. - Most A - share - focused ETFs declined this week. Defense and military industry ETFs rose with an average increase of 0.67% for funds above a certain scale, while mid - stream manufacturing ETFs had a deeper decline with an average drop of 6.15% for funds above a certain scale. Commodity ETFs had the largest increase, with an average rise of 1.47% for funds above a certain scale [2][6]. - There was a significant inflow of funds into large - cap index ETFs, with a net inflow of 96.189 billion yuan throughout the week. On the contrary, there was a slight outflow of funds from financial real estate, TMT, cyclical, and Shanghai - Hong Kong - Shenzhen index ETFs [3][10]. 3. Summary by Related Catalogs 3.1 ETF Market Overall Performance Market Performance - Defense and military industry ETFs recorded an increase, with an average increase of 0.67% for funds above a certain scale; mid - stream manufacturing ETFs had a deep decline, with an average decrease of 6.15% for funds above a certain scale. Commodity ETFs had the largest increase, with an average increase of 1.47% for funds above a certain scale [2][6]. Capital Flow - There was a significant inflow of funds into large - cap index ETFs, with a net inflow of 96.189 billion yuan throughout the week. Financial real estate, TMT, cyclical, and Shanghai - Hong Kong - Shenzhen index ETFs had a slight outflow of funds [3][10]. - Tables 1 - 3 show the top - performing funds in terms of returns, the top ten funds with the largest capital inflows, and the top ten funds with the largest capital outflows in the past week [12][13][14]. 3.2 Different Popular Sub - type ETF Fund Market Performance - The report lists the market performance of different popular sub - type ETF funds, including various types such as broad - based index, industry - themed, SmartBeta, bond, QDII, and commodity ETFs, showing their latest scale, weekly capital flow, weekly return, and other data [16 - 32]. 3.3 Innovation Theme and Sub - industry ETF Fund Market Performance - The report presents the market performance of innovation theme and sub - industry ETF funds, including TMT innovation themes, consumer sub - industries, pharmaceutical sub - industries, new energy themes, central and state - owned enterprise themes, stable - growth themes, Shanghai - Hong Kong - Shenzhen/Hong Kong Stock Connect sub - industries, dividend/dividend low - volatility index families, and ChiNext index families, providing information such as weekly returns, year - to - date returns, and latest scales [34 - 43].

证券研究报告 | 金融工程 2025 年 4 月 12 日 利率择时信号偏多，机构久期微升 ——利率市场趋势定量跟踪 20250411 利率市场结构变化 - 10 年期国债到期收益率录得 1.66%，相对上周下降 6.12BP。当前 利率水平、期限和凸性结构读数分别为 1.53%、0.26%、-0.08%， 从均值回归视角看，目前处于水平结构点位较低、期限结构点位 较低、凸性结构点位较低的状态。 利率价量周期择时信号：偏多 - 利率数据的多周期择时信号为：长周期无信号、中周期向下突破、 短周期向上突破。综合来看，当前合计下行突破 1 票、上行突破 1 票，由于 3 种周期下的同向突破总得票数未达 2/3，最终信号的综 合评分结果为中性震荡。同时，由于价量择时的最新趋势未出现变 脸信号，近期我们对利率的走势判断为由看多转中性，整体而言为 中性偏多观点。 公募债基行为跟踪：久期微升、分歧微降 任瞳 S1090519080004 rentong@cmschina.com.cn 王武蕾 S1090519080001 wangwulei@cmschina.com.cn 梁雨辰 S1090523070008 liangy ...

- The DTW timing model is based on the principle of similarity and the DTW (Dynamic Time Warping) algorithm, which is a volume-price timing model[1][4][14] - The foreign capital timing model is constructed based on the divergence between foreign and domestic related assets, using four indicators reflecting foreign capital movements to generate timing signals for the A-share market[1][4][14] - The DTW timing model has shown an absolute return of 17.39% and an excess return of 17.83% relative to the CSI 300 since November 2022, with a maximum drawdown of 21.32% and a weekly win rate of over 60%[4][16] - The foreign capital timing model's long strategy has achieved an absolute return of 28.83% since 2024, with a maximum drawdown of 8.32%[4][23] - The DTW timing model uses the DTW distance algorithm instead of the Euclidean distance to measure similarity, as the DTW distance can better handle the misalignment of time series[29][30] - The DTW timing model has been improved by incorporating boundary constraints proposed by Sakoe-Chiba and Itakura to address the "pathological matching" problem of the traditional DTW algorithm[31][32][37] - The foreign capital timing strategy is based on two overseas listed assets related to A-shares: FTSE China A50 Index Futures (Singapore market) and Southern A50ETF (Hong Kong market), constructing timing signals through price divergence and premium/discount indicators[36][12] - The DTW timing model's performance in 2024 includes an absolute return of 15.68%, an excess return of 4.93%, a maximum drawdown of 21.36%, a trading win rate of 63.64%, and a profit-loss ratio of 2.64[18][19][20] - The foreign capital timing model's performance from December 30, 2014, to December 31, 2024, shows an annualized return of 18.96% (long-short) and 14.19% (long-only), with maximum drawdowns of 25.69% and 17.27%, respectively, and a daily win rate of nearly 55%[20][22][24]