Market Performance - In April, A-shares experienced significant volatility, with the Shanghai Composite Index down 1.7% to 3279.03 points, the Shenzhen Component Index down 5.75% to 9899.82 points, and the ChiNext Index down 7.4% to 1948.03 points [1][2]. Future Outlook - Analysts are optimistic about the A-share market in May, suggesting it is a good time for positioning, as historical data shows that the Shanghai Composite Index has risen in 7 out of the last 15 years during the 10 trading days following the May Day holiday [2][3]. Sector Performance - Historical analysis indicates that consumer and large financial sectors tend to perform well in the 10 trading days before and after the May Day holiday, driven by policy support and upward industry trends [3][4]. Investment Strategies - Analysts recommend focusing on three asset categories: stable assets (high dividends, gold), self-sufficient industrial chains, and domestic consumption [4][5]. - There is a consensus that the Chinese stock market's upward momentum is not over, with suggestions to increase allocations to Chinese assets due to improved economic policies and a decrease in risk premiums [4][5]. Structural Opportunities - May is expected to see a structural recovery in A-shares, with a focus on consumption, technology, and dividend stocks as key investment themes [5].

Investment Rating - The industry investment rating is "Neutral" with an expected industry index increase of -5% to 5% relative to the CSI 300 index over the next six months [22]. Core Insights - The market is currently in a downtrend, with a focus on when the profit effect will turn positive. The current profit effect is around -1% [2][10]. - The report suggests maintaining a neutral position until the 30-day moving average of the wind All A index is breached, considering the low valuation levels [4][10]. - The industry configuration model recommends focusing on "dilemma reversal" sectors, particularly in healthcare and consumer sectors related to export chains such as light industry and home appliances [3][10]. - The TWO BETA model continues to recommend the technology sector, emphasizing domestic substitution in the fields of information technology and AI chips [3][10]. - Despite a significant drop on Friday, the banking sector, which is still in an upward trend, remains worthy of attention [3][10]. Summary by Sections Market Overview - The wind All A index is currently in a downtrend, with the 20-day moving average at 4908 and the 120-day moving average at 5092.8, indicating a distance of -3.63% [2][9]. - The market's current environment is characterized by uncertainty due to upcoming Federal Reserve meetings and the release of April import and export data [4][10]. Valuation Metrics - The overall PE ratio of the wind All A index is around the 50th percentile, indicating a medium level, while the PB ratio is around the 20th percentile, indicating a relatively low level [3][10]. Positioning Recommendations - The report advises a 50% allocation in absolute return products based on the wind All A index as the main stock allocation [3][10].

金融工程 | 金工定期报告 2025 年 05 月 05 日 作者 吴先兴 分析师 SAC 执业证书编号：S1110516120001 wuxianxing@tfzq.com 相关报告 1 《金融工程：金融工程-因子跟踪周 报 ： Beta 、换手率因子表现较好 -20250504》 2025-05-04 2 《金融工程：金融工程-哪些行业进 入高估区域？——估值与基金重仓股配 置监控 2025-05-03》 2025-05-03 3 《金融工程：金融工程-净利润断层 本周超额基准 0.92%》 2025-05-03 金融工程 证券研究报告 量化择时周报：突破压力位前保持中性 突破压力位前保持中性 上周周报(20250427)认为：全 A 指数的 30 日均线构成压力位，但考虑到估 值不高，建议在压力位突破前维持中性仓位。最终 wind 全 A 维持原状。 市值维度上，上周代表小市值股票的中证 2000 上涨 0.84%，中盘股中证 500 上涨 0.08%，沪深 300 下跌 0.43%，上证 50 下跌 0.59%;上周中信一级行业中， 表现较强行业包括传媒、计算机，传媒上涨 2.86%，综合金融、房地产 ...

从近十年5月当月累计涨跌幅来看，沪指录得4年上涨、6年下跌；深成指则为5年上涨、5年下 跌。指数月涨跌幅与5月首个交易日行情无明显关联。 | 年份 | 沪指 | 深成指 | | --- | --- | --- | | 2015 | 3.83% | 8.65% | | 2016 | -0.74% | 0.18% | | 2017 | -1.19% | -3.61% | | 2018 | 0.43% | -0.28% | | 2019 | -5.84% | -7.77% | | 2020 | -0.27% | 0.23% | | 2021 | 4.89% | 3.86% | | 2022 | 4.57% | 4.59% | | 2023 | -3.57% | -4.80% | | 2024 | -0.58% | -2.32% | 作 者丨李彤欣 编 辑丨 陈思颖 今年"五一"假期，你持股过节了吗？作为财报季后的首个交易日，"五一"假期后A股能否实现 开门红，历来颇受投资者关注。 南财快讯记者统计近十年5月首个交易日涨跌情况发现，6个交易日沪深两市实现开门红，4个 交易日绿盘下跌，收红盘概率更高。可以看到2 0 2 ...

Group 1: Company Performance and Financials - In 2024, the company's net profit increased by 18.55%, primarily driven by the insurance business segment [2] - The net profit attributable to shareholders for 2024 was CNY 1.21 billion, with a weighted average return on equity of 5.68% and basic earnings per share of CNY 0.5251 [3] - In Q1 2025, the company achieved a net profit of CNY 392 million [3] Group 2: Business Strategy and Growth - The company focuses on value creation as the core of its market value management strategy while solidifying its main business [2] - Plans to enhance governance structure and improve internal control systems to protect minority shareholders' rights [2] - The company aims to deepen existing business operations and explore new growth areas to achieve high-quality development [3] Group 3: Investor Relations and Communication - The company held an annual performance briefing on April 30, 2024, to improve communication with investors [1] - It emphasizes transparency in information disclosure and actively engages with investors through various channels [2] - The company has implemented a structured approach to manage investor relations and respond to inquiries effectively [2] Group 4: Risk Management and Compliance - The company employs multiple control measures to identify, measure, and report credit risks amid economic uncertainties [2] - It adheres to accounting standards to ensure the reliability of financial data provided to investors [2] - The company is committed to enhancing its risk management framework to prevent systemic risks [3]

策略研究 | 证券研究报告 — 总量周报 2025 年 4 月 29 日 策略周报 AI 产业链有望重回主线 政治局会议延续基调，地产、消费政策进一步发力或仍需等待二季度经济数 据验证， "人工智能+"表述有所强化有机会重回主线。 中银国际证券股份有限公司 具备证券投资咨询业务资格 策略研究 证券分析师：王君 (8610)66229061 jun.wang@bocichina.com 证券投资咨询业务证书编号：S1300519060003 证券分析师：徐沛东 (8621)20328702 peidong.xu@bocichina.com 证券投资咨询业务证书编号：S1300518020001 证券分析师：郭晓希 (8610)66229019 xiaoxi.guo@bocichina.com 证券投资咨询业务证书编号：S1300521110001 证券分析师：徐亚 (8621)20328506 ya.xu@bocichina.com 证券投资咨询业务证书编号：S1300521070003 政策预期阶段性落地，短期震荡不改中期向好，科技产业具备长期趋 势。周五政治局会议召开，市场政策预期阶段性落地。总体来看，本次 ...

Market Performance - The domestic equity market continued a slight rebound last week, with an average daily trading volume around 1.1 trillion yuan, and the Wind All A index rose by 1.15% [1] - Among major domestic stock indices, small-cap indices performed well, with the CSI 1000 up by 1.8% and the CSI 2000 up by 2.7% [1] - The Shanghai Composite Index and CSI 300 increased by 0.6% and 0.4%, respectively, while the SSE 50 and STAR 50 declined by 0.3% and 0.4% [1] - Hong Kong stocks also saw gains, with the Hang Seng Technology Index and Hang Seng Index rising by 2.0% and 2.7%, respectively [1] Sector Performance - The financial sector (+5.1%), automotive sector (+5.0%), and power equipment & new energy sector (+3.1%) experienced significant increases [1] - Conversely, the real estate sector (-1.2%), consumer services sector (-1.3%), and food & beverage sector (-1.4%) faced notable declines [1] Future Outlook - The upcoming week is the last trading week before the May Day holiday, with annual and quarterly reports from listed companies expected to be fully disclosed [1] - According to Hongde Fund, the market will enter a performance vacuum period over the next three months, with potential external environmental changes impacting the domestic capital market [1] - The fund expresses confidence in China's economic stability and growth, emphasizing the importance of high-quality development in response to external uncertainties [1] Policy and Market Sentiment - Current policies are primarily focused on "preparation" and "accumulating flexibility," with structural adjustments and localized support being the main themes [2] - The market is closely watching the progress of US-China negotiations and potential tariff reduction expectations [2] - In the bond market, interest rates for government bonds generally rose last week, with credit bond yields also increasing [2] - The market remains cautious, awaiting potential reserve requirement ratio (RRR) cuts and interest rate reductions from the central bank [2]

Quantitative Models and Construction Methods 1. Model Name: Macro Timing Strategy - **Model Construction Idea**: The model aims to provide signals for equity allocation based on macroeconomic growth and monetary liquidity indicators[26] - **Model Construction Process**: The model uses dynamic macro event factors to construct a stock-bond rotation strategy. The signal strength for economic growth and monetary liquidity is calculated monthly. For April, the signal strength for economic growth is 0%, and for monetary liquidity is 50%[26][27] - **Model Evaluation**: The model has shown a return of 1.06% from the beginning of 2025 to the present, compared to a 1.90% return for the Wind All A index during the same period[26] 2. Model Name: Micro Cap Timing Model - **Model Construction Idea**: The model focuses on timing and rotation signals for micro-cap stocks based on volatility and interest rate indicators[30] - **Model Construction Process**: The model uses two mid-term risk warning indicators: 1) Ten-year government bond yield YoY indicator and 2) Volatility congestion YoY indicator. On October 15, 2024, the volatility congestion indicator fell below the threshold, lifting the risk warning signal. The interest rate YoY indicator was -20.45%, not triggering the risk control threshold of 0.3[30] - **Model Evaluation**: The model has not triggered risk control, suggesting investors continue holding micro-cap stocks[30] Model Backtest Results 1. Macro Timing Strategy - **Economic Growth Signal Strength**: 0%[27] - **Monetary Liquidity Signal Strength**: 50%[27] - **Equity Allocation Recommendation**: 25%[27] - **Return from 2025 to Present**: 1.06%[26] 2. Micro Cap Timing Model - **Ten-year Government Bond Yield YoY**: -28.69%[31] - **Volatility Congestion YoY**: -50.09%[31] Quantitative Factors and Construction Methods 1. Factor Name: Value Factor - **Factor Construction Idea**: The factor aims to capture the value characteristics of stocks based on fundamental metrics[37] - **Factor Construction Process**: The value factor includes metrics such as the latest annual report book value to market value (BP_LR), future 12-month consensus expected net profit to market value (EP_FTTM), and past 12-month operating income to market value (SP_TTM)[47] - **Factor Evaluation**: The value factor performed best in the CSI 300 stock pool last week[37] 2. Factor Name: Size Factor - **Factor Construction Idea**: The factor aims to capture the size characteristics of stocks based on market capitalization[37] - **Factor Construction Process**: The size factor includes metrics such as the logarithm of circulating market capitalization (LN_MktCap)[47] - **Factor Evaluation**: The size factor showed strong positive returns in the CSI 1000 stock pool last week[37] Factor Backtest Results 1. Value Factor - **IC Mean (CSI 300)**: 25.88%[38] - **IC Mean (CSI 500)**: 10.56%[38] - **IC Mean (CSI 1000)**: 6.32%[38] - **Multi-Long Return (CSI 300)**: 10.84%[38] - **Multi-Long Return (CSI 500)**: 10.56%[38] - **Multi-Long Return (CSI 1000)**: 6.32%[38] 2. Size Factor - **IC Mean (CSI 300)**: 3.33%[38] - **IC Mean (CSI 500)**: -3.23%[38] - **IC Mean (CSI 1000)**: -1.84%[38] - **Multi-Long Return (CSI 300)**: 3.33%[38] - **Multi-Long Return (CSI 500)**: -3.23%[38] - **Multi-Long Return (CSI 1000)**: -1.84%[38]

- The report discusses two main quantitative models: the Diffusion Index Model and the GRU Factor Model[6][7][14][33] Diffusion Index Model 1. **Model Name**: Diffusion Index Model 2. **Model Construction Idea**: The model is based on the principle of price momentum, capturing industry trends by observing the diffusion index of various sectors[6][27] 3. **Model Construction Process**: - Calculate the diffusion index for each industry - Rank industries based on their diffusion index values - Select top industries for investment based on their diffusion index rankings - Formula: $ \text{Diffusion Index} = \frac{\text{Number of advancing stocks}}{\text{Total number of stocks}} $ 4. **Model Evaluation**: The model has shown varying performance over the years, with significant returns in some periods and notable drawdowns in others[26][30] 5. **Model Test Results**: - 2025 YTD excess return: -3.16%[25] - April 2025 excess return: -1.08%[30] - Weekly excess return: 0.43%[30] GRU Factor Model 1. **Model Name**: GRU Factor Model 2. **Model Construction Idea**: The model leverages GRU (Gated Recurrent Unit) deep learning networks to analyze minute-level price and volume data, aiming to capture trading information and trends[7][33] 3. **Model Construction Process**: - Collect minute-level price and volume data - Train a GRU network on historical data to identify patterns - Rank industries based on GRU factor scores - Select top industries for investment based on their GRU factor rankings - Formula: $ \text{GRU Factor} = \text{GRU Network Output} $ 4. **Model Evaluation**: The model has shown strong performance in short cycles but may struggle in long cycles or extreme market conditions[33][36] 5. **Model Test Results**: - 2025 YTD excess return: -3.33%[33] - April 2025 excess return: 0.92%[36] - Weekly excess return: -0.31%[36] Factor Rankings and Performance 1. **Diffusion Index Rankings (as of April 25, 2025)**: - Top industries: Banking (0.986), Non-Banking Financials (0.948), Comprehensive Financials (0.926), Computers (0.873), Retail (0.847), Communication (0.841)[14][27] - Bottom industries: Coal (0.105), Oil & Petrochemicals (0.175), Food & Beverage (0.257), Agriculture (0.396), Steel (0.423), Utilities (0.491)[27][28] 2. **GRU Factor Rankings (as of April 25, 2025)**: - Top industries: Banking (3.81), Transportation (2.77), Non-Banking Financials (2.37), Textiles & Apparel (2.34), Media (1.98), Light Manufacturing (1.81)[7][34] - Bottom industries: Automobiles (-5.31), Agriculture (-4.05), Pharmaceuticals (-4.03), Home Appliances (-3), Coal (-2.67), Defense (-2.64)[34] Weekly and Monthly Performance 1. **Diffusion Index Weekly Performance**: - Top weekly gainers: Construction (0.189), Real Estate (0.187), Building Materials (0.136), Light Manufacturing (0.089), Textiles & Apparel (0.081), Communication (0.069)[29] - Top weekly losers: Steel (-0.111), Utilities (-0.038), Non-Ferrous Metals (-0.018), Coal (0.003), Transportation (0.007), Computers (0.009)[29] 2. **GRU Factor Weekly Performance**: - Top weekly gainers: Banking, Textiles & Apparel, Consumer Services[34] - Top weekly losers: Coal, Automobiles, Construction[34]

Market Performance - On April 14, 2025, the Shanghai Composite Index rose by 0.76%, the Shenzhen Component Index increased by 0.51%, and the ChiNext Index gained 0.34%[2] - The total market turnover was 12,772.80 billion yuan, a decrease of 712.00 billion yuan from the previous trading day[2] - A total of 4,614 stocks rose while 770 stocks fell across the market[2] Sector and Style Analysis - The top-performing sectors included Comprehensive Finance (3.87%), Textiles and Apparel (2.66%), and Retail Trade (2.58%)[20] - The sectors that underperformed were Home Appliances (-0.69%), Food and Beverage (-0.36%), and National Defense and Military Industry (0.25%)[20] - Market style performance ranked as follows: Cyclical > Growth > Stability > Financial > Consumption[20] Capital Flow - On April 14, 2025, the net inflow of main funds was 1.571 billion yuan, with large orders seeing a net inflow of 3.393 billion yuan and small orders continuing to see net inflows of 0.553 billion yuan[3] - Southbound funds recorded a net inflow of 57.80 billion HKD, with the Shanghai-Hong Kong Stock Connect contributing 55.20 billion HKD and the Shenzhen-Hong Kong Stock Connect contributing 2.60 billion HKD[4][27] ETF Trading Activity - Major ETFs such as the Huaxia Shanghai 50 ETF and the Huatai-PB CSI 300 ETF saw varying changes in trading volume, with the former decreasing by 1.716 billion yuan and the latter increasing by 0.329 billion yuan[3][30] - The trading volumes for various ETFs on April 14 included 12.35 billion yuan for the Huaxia Shanghai 50 ETF and 36.27 billion yuan for the Huatai-PB CSI 300 ETF[30] Global Market Overview - On April 14, 2025, major Asia-Pacific indices generally rose, with the Hang Seng Index up 2.40% and the Nikkei 225 Index up 1.18%[4][34] - In the U.S., major indices also saw gains, with the Dow Jones Industrial Average increasing by 1.56% and the S&P 500 rising by 1.81%[34]