- The report introduces an industry crowding monitoring model to track daily crowding levels of Shenwan primary industry indices. The model identifies high crowding levels in industries such as beauty care, basic chemicals, and utilities, while industries like media and electrical equipment exhibit lower crowding levels[3] - A Z-score model is constructed to monitor ETF product signals. This model calculates rolling measurements to identify potential arbitrage opportunities in ETFs while also warning of potential risks of price corrections[4] - The Z-score model is applied to ETF products, providing signals for potential arbitrage opportunities and highlighting risks associated with price adjustments[4] - The report provides detailed data on ETF fund flows, categorizing them into broad-based ETFs, industry-themed ETFs, style-strategy ETFs, and cross-border ETFs. It highlights the top three funds with the highest inflows and outflows for each category[6] - The industry crowding monitoring model tracks the movement of main funds across industries over the past three trading days, showing significant inflows into industries like automobiles and utilities, while outflows are observed in industries such as electronics and retail[3][11]

Market Overview - The Shanghai Composite Index is expected to have short-term entry opportunities tomorrow, but no medium-term opportunities until after the May Day holiday [1] - The index closed at 3288, with a support level at 3262, indicating potential upward movement despite a recent top formation [1][2] Technical Analysis - The market is currently in a downward oscillation from the peak of 360074, without completing a reversal [2] - Key resistance is at 3319, while support remains at 3262, with a focus on the 30-minute chart for potential buying opportunities [2] - The 5-minute chart indicates a need for a pullback before any upward movement can be confirmed [2] Sector Performance - The ChiNext Index is showing a different trend, with a continued pullback and a need for confirmation of upward movement [3] - Most sectors are experiencing declines, with notable drops in cross-border payments, communication equipment, and general equipment [3][4] - The software development sector saw a significant outflow of capital, indicating bearish sentiment [4] Market Sentiment - The market sentiment is negative, with 48 stocks hitting the daily limit up and 77 hitting the limit down, suggesting a lack of strong buying interest [4] - The number of stocks with declines exceeding 7% is concerning, with nearly 200 stocks affected, indicating a cautious approach for investors [4]

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Group 1 - As of April 28, a total of 495 stocks in the Shanghai and Shenzhen markets have experienced net outflows of main funds for five consecutive days or more [1] - The stock with the longest consecutive net outflow is Gao Meng New Materials, with 17 days, followed by *ST Jiu You with 16 days [1] - The largest total net outflow amount is from Light Media, with a cumulative net outflow of 2.024 billion yuan over five days [1] Group 2 - China Duty Free has seen a cumulative net outflow of 1.803 billion yuan over 13 days, ranking second in total outflow [1] - The stock with the highest net outflow ratio relative to trading volume is *ST Longyu, which has seen a 26.28% decline over the past six days [1] - The table lists various stocks with their respective net outflow days, amounts, ratios, and cumulative price changes, indicating a trend of declining stock prices among those with significant net outflows [1][2] Group 3 - The gold stock ETF (product code: 159562) tracks the CSI Hong Kong and Shanghai Gold Industry Stock Index and has seen a 1.39% decline over the past five days [4] - The ETF has a price-to-earnings ratio of 19.23 times and has experienced a net inflow of 3.337 million yuan, with the latest share count increasing by 1 million to 430 million [4]

主力资金净流出的行业有29个，电子行业主力资金净流出规模居首，今日下跌0.44%，全天净流出资金 31.04亿元，其次是汽车行业，今日跌幅为1.59%，净流出资金为25.16亿元，净流出资金较多的还有机 械设备、医药生物、非银金融等行业。 今日各行业资金流向 | 行业 | 日涨跌幅（%） | 资金流向（亿元） | 行业 | 日涨跌幅（%） | 资金流向（亿元） | | --- | --- | --- | --- | --- | --- | | 钢铁 | 0.53 | 2.00 | 商贸零售 | -1.49 | -8.02 | | 石油石化 | -0.03 | 0.67 | 农林牧渔 | -1.20 | -8.02 | | 轻工制造 | -1.25 | -0.22 | 有色金属 | -0.46 | -9.32 | | 建筑材料 | -1.57 | -1.69 | 通信 | -0.75 | -10.19 | | 传媒 | 0.02 | -1.79 | 国防军工 | -1.06 | -10.38 | | 纺织服饰 | -0.90 | -1.90 | 食品饮料 | -0.38 | -10.45 | | 美容护理 | ...

| 属 | | | | | | | --- | --- | --- | --- | --- | --- | | 通信 | 23.27 | -10.64 | 1.33 | -0.75 | -10.19 | | 国防军 | 13.44 | -14.05 | 1.25 | -1.06 | -10.38 | | 工 | | | | | | | 食品饮 | 20.45 | -4.78 | 2.28 | -0.38 | -10.45 | | 料 | | | | | | | 房地产 | 51.63 | -18.02 | 2.37 | -3.66 | -15.54 | | 公用事 | 70.72 | 13.03 | 1.79 | 0.39 | -18.36 | | 业 | | | | | | | 电力设 | 47.36 | 5.45 | 1.93 | -0.59 | -18.40 | | 备 | | | | | | | 计算机 | 56.99 | -0.84 | 3.22 | -0.54 | -20.01 | | 非银金 | 33.17 | -11.39 | 0.79 | -0.67 | -21.94 | | 融 | | | ...

| 排名 | 板块名称 | 主力资金净流出(亿元) | 主力资金净流出率(%) | | --- | --- | --- | --- | | 1 | 电新行业 | -23.66 | -3.81 | | 2 | 电子 | -23.14 | -3.57 | | 3 | 机械设备 | -19.43 | -3.88 | | ব | 矢药 | -18.30 | -4.27 | | 5 | 交运设备 | -16.96 | -4.76 | 星矿主力资金监控：早盘买入前十榜（截止时间： 10 时 50 分) | 排名 | 股票名称 | 主力资金净流入(亿元) | 主力资金净流入率(%) | | --- | --- | --- | --- | | 1 | 大位科技 | 4.08 | 34.89 | | 2 | 杭钢股份 | 3.15 | 14.07 | | 3 | 格力电器 | 2.17 | 8.36 | | র | 跨境通 | 2.07 | 14.72 | | 5 | 章阅科技 | 2.00 | 34.41 | | 6 | 美财互联 | 1.74 | 54.00 | | 1 | 天沃科技 | 1.63 | 30.59 | | ...

Quantitative Models and Factors Summary Quantitative Models and Construction Methods Model Name: Liquidity Factor - **Construction Idea**: The liquidity factor is based on the market's liquidity conditions and the effectiveness of the main fund factor[12] - **Construction Process**: The model selects industries such as computers, electronics, machinery, electrical equipment and new energy, communications, and automobiles based on the liquidity factor. The recommended weight for the main fund factor is 5%[12] - **Evaluation**: The effectiveness of the main fund factor has stopped declining and is beginning to recover as market liquidity becomes abundant again[11][12] Model Name: Long-term Prosperity Expectation - **Construction Idea**: This factor serves as a proxy variable for prosperity investment[16] - **Construction Process**: The model selects industries such as non-bank finance, non-ferrous metals, electric power and utilities, steel, home appliances, and electronics. The recommended weight is 10%[16] - **Evaluation**: The effectiveness of this factor has recently declined, and the clustering effect has not formed[16] Model Name: Short-term Prosperity Expectation - **Construction Idea**: This factor focuses on short-term prosperity expectations, particularly in domestic demand[20] - **Construction Process**: The model selects industries such as home appliances, basic chemicals, agriculture, forestry, animal husbandry, and fishery, automobiles, machinery, and national defense. The recommended weight is 30%[20] - **Evaluation**: The short-term prosperity expectation factor shows significant upward movement in excess returns[20] Model Name: Momentum Reversal - **Construction Idea**: This factor focuses on long-term low and short-term strong defensive sectors[23] - **Construction Process**: The model tracks one-month momentum and selects industries such as electric power and utilities, agriculture, forestry, animal husbandry, and fishery, retail, banking, real estate, and transportation. The recommended weight is 10%[23] - **Evaluation**: The model suggests tracking defensive sectors with long-term low and short-term strong performance[23] Model Backtesting Results - **Liquidity Factor**: Excess return of the long position is shown in the chart[14] - **Long-term Prosperity Expectation**: Excess return of the long position is shown in the chart[18] - **Short-term Prosperity Expectation**: Excess return of the long position is shown in the chart[22] - **Momentum Reversal**: Excess return of the long position is shown in the chart[25] Quantitative Factors and Construction Methods Factor Name: Financial Report Quality Factor - **Construction Idea**: This factor focuses on the quality of financial reports[11] - **Construction Process**: The factor is used to select industries such as banking, non-bank finance, transportation, and construction[11] - **Evaluation**: The financial report quality factor has shown concentrated absolute returns recently[11] Factor Name: Correlation Factor - **Construction Idea**: This factor focuses on the correlation between industries[11] - **Construction Process**: The factor is used to analyze industry rotation and select industries based on their correlation[11] - **Evaluation**: The correlation factor has shown concentrated absolute returns recently[11] Factor Name: Momentum Factor - **Construction Idea**: This factor focuses on the momentum of industries[11] - **Construction Process**: The factor is used to analyze industry momentum and select industries based on their momentum[11] - **Evaluation**: The momentum factor has shown concentrated absolute returns recently[11] Factor Name: Main Fund Factor - **Construction Idea**: This factor focuses on the main fund flows in the market[11] - **Construction Process**: The factor is used to analyze the effectiveness of main fund flows and select industries based on their fund flows[11] - **Evaluation**: The effectiveness of the main fund factor has stopped declining and is beginning to recover[11] Factor Backtesting Results - **Financial Report Quality Factor**: Excess return of the long position is shown in the chart[14] - **Correlation Factor**: Excess return of the long position is shown in the chart[14] - **Momentum Factor**: Excess return of the long position is shown in the chart[14] - **Main Fund Factor**: Excess return of the long position is shown in the chart[14]

Market Overview - The Shanghai Composite Index fell by 0.07% on April 25, with 21 out of the 28 sectors experiencing gains, led by utilities and telecommunications, which rose by 1.36% and 1.15% respectively [1] - The real estate and coal sectors had the largest declines, with decreases of 0.60% and 0.59% respectively [1] Capital Flow - The net inflow of capital in the two markets was 4.975 billion yuan, with 14 sectors seeing net inflows [1] - The computer sector had the highest net inflow, totaling 3.368 billion yuan, while the utilities sector followed with a net inflow of 1.581 billion yuan [1] Coal Industry Analysis - The coal sector experienced a decline of 0.59% with a net outflow of 19.4741 million yuan [2] - Among the 37 stocks in the coal sector, 16 stocks rose while 20 stocks fell [2] - The top five stocks with net inflows exceeding 10 million yuan included Yongtai Energy (1.23 billion yuan), Zhengzhou Coal Electricity (417.494 million yuan), and China Shenhua (338.088 million yuan) [2][3] - The stocks with the highest net outflows included Huaibei Mining (-43.6057 million yuan), Hengyuan Coal Electricity (-39.3828 million yuan), and Shaanxi Coal and Chemical Industry (-34.1931 million yuan) [2][3] Individual Stock Performance - The top three stocks with the largest net outflows were: - Huaibei Mining: -43.6057 million yuan - Hengyuan Coal Electricity: -39.3828 million yuan - Shaanxi Coal and Chemical Industry: -34.1931 million yuan [2][3] - The stock with the highest net inflow was Yongtai Energy, with a net inflow of 1.2254 billion yuan [3]

行业来看，申万所属的一级行业中，本周上涨的有23个，涨幅居前的行业为银行、房地产，涨幅为 4.04%、3.40%。跌幅居前的行业为国防军工、农林牧渔，跌幅为2.55%、2.15%。 行业资金流向方面，本周有7个行业主力资金净流入，房地产行业主力资金净流入规模居首，该行业本 周上涨3.40%，合计净流入资金17.14亿元，其次是银行行业，一周涨幅为4.04%，净流入资金为4.67亿 元。 沪指本周上涨1.19%，深成指下跌0.54%，创业板指下跌0.64%，沪深300指数上涨0.59%。可交易A股 中，上涨的有3047只，占比56.43%，下跌的2247只。 资金面上，本周主力资金合计净流出632.90亿元。其中，创业板主力资金净流出173.21亿元；科创板主 力资金净流出29.85亿元；沪深300成份股主力资金净流出190.69亿元。 | 公用事业 | | | 机械设备 | | | | --- | --- | --- | --- | --- | --- | | 社会服务 | 0.14 | -6.94 | 电力设备 | -0.37 | -53.39 | | 纺织服饰 | 1.57 | -8.20 | 计算机 | ...