- The industry crowding monitoring model was constructed to monitor the daily crowding levels of Shenwan primary industry indices. The model identifies industries with high crowding levels, such as textiles, beauty care, and light manufacturing, while industries like media and electronics show lower crowding levels. It also tracks significant daily changes in crowding levels for industries like environmental protection, food & beverage, and real estate[4] - The Z-score premium rate model was developed to screen ETF products for potential arbitrage opportunities. This model uses rolling calculations to identify ETFs with significant deviations from their intrinsic value, providing signals for potential trades while warning of possible price corrections[5] - The industry crowding monitoring model highlights that defense, non-bank finance, and environmental protection sectors saw significant inflows of main funds, while sectors like automobiles, electrical equipment, and basic chemicals experienced outflows. Over the past three days, coal, beauty care, and banking sectors were favored, while computing, electronics, and electrical equipment were reduced[4] - The Z-score premium rate model provides ETF signals, including top inflows for ETFs like Sci-Tech 50 ETF (+5.77 billion yuan) and Sci-Tech 100 Index ETF (+2.27 billion yuan), while ETFs like Shanghai 50 ETF (-4.86 billion yuan) and ChiNext ETF (-3.46 billion yuan) saw significant outflows[6][7] - The industry crowding monitoring model's evaluation indicates its effectiveness in identifying crowded sectors and tracking fund flows, aiding investors in understanding market dynamics[4] - The Z-score premium rate model is evaluated as a useful tool for identifying arbitrage opportunities in ETFs, though it requires caution due to potential risks of price corrections[5] - The industry crowding monitoring model's testing results show significant fund flow changes in various sectors, such as coal (+4.28 billion yuan over three days) and computing (-129.02 billion yuan over three days)[14][15] - The Z-score premium rate model's testing results include ETF fund flow data, such as Sci-Tech 50 ETF (+5.77 billion yuan) and Shanghai 50 ETF (-4.86 billion yuan)[6][7]

[Table_Title] 金 金融工程点评 [Table_Message]2025-05-16 风险提示：本报告结论完全基于公开历史数据，建议关注的行业指数与 ETF 产品基于 构建的量化模型，仅供大家参考阅读，不构成任何投资建议。 金工 ETF 点评：宽基 ETF 单日净流出 52.58 亿元；标普油气、电池 ETF 可关注 [Table_Author] 证券分析师：刘晓锋 电话：13401163428 E-MAIL：liuxf@tpyzq.com 执业资格证书编码：S1190522090001 研究助理：孙弋轩 电话：18910596766 一、资金流向 二、行业拥挤度监测 ◼ 通过构建行业拥挤度监测模型，对申万一级行业指数的拥挤度进行每日监测， 前一交易日交通运输、纺织服饰、美容护理拥挤度靠前，相比较而言，传媒、 社会服务、房地产、电子、电力设备的拥挤度水平较低，建议关注。此外，农 林牧渔、汽车单日拥挤度变动较大。从主力资金流动来看，前一交易日主力 资金流入医药生物、美容护理、煤炭，流出计算机、电子、非银金融。近三个 交易日主力资金增配美容护理、医药生物、煤炭，减配电子、计算机、国防 军工。 三、ET ...

Investment Rating - The report indicates a neutral outlook for the industry, expecting returns to be within -5% to 5% compared to the CSI 300 index over the next six months [15]. Core Insights - The report highlights significant capital outflows from broad-based ETFs, totaling 9.22 billion yuan in a single day, with notable inflows into specific ETFs such as the ChiNext 50 ETF and the STAR Market Index ETFs [6][14]. - The industry crowding index shows that sectors like defense and military, textiles and apparel, and beauty care are currently crowded, while real estate and food and beverage sectors are less crowded, suggesting potential investment opportunities [4][12]. - The report emphasizes the importance of monitoring ETF products for potential arbitrage opportunities while being cautious of possible corrections in the underlying assets [5]. Summary by Sections Capital Flow - Broad-based ETFs experienced a net outflow of 9.22 billion yuan, with the top three inflows being ChiNext 50 ETF (+0.84 billion yuan), STAR Market Index ETF by Huitianfu (+0.48 billion yuan), and STAR Market Index ETF by Huatai-PB (+0.42 billion yuan) [6]. - The top three outflows were from CSI 300 ETF (-1.55 billion yuan), SSE 50 ETF (-0.93 billion yuan), and CSI 1000 ETF (-0.845 billion yuan) [6]. Industry Crowding Monitoring - The report constructed a crowding index model to monitor the crowding levels of various sectors, indicating that defense and military, textiles and apparel, and beauty care are currently crowded, while real estate and food and beverage sectors are less so [4]. - Recent capital flows show significant inflows into beauty care, pharmaceutical biology, and basic chemicals, while outflows were noted in defense and military, computer, and electronics sectors [4]. ETF Product Signals - The report suggests monitoring specific ETF products for potential arbitrage opportunities based on the Z-score model, while also advising caution regarding potential corrections in these products [5]. - The report lists several ETFs with significant capital movements, highlighting the need for investors to pay attention to these signals for potential investment strategies [14].

深圳证券交易所 SHENZHEN 深交所ETF投资问答(45) 901 FIFT PE (D) - 编者按 - 日内看涨行情 ▶ 投资者有两种操作方法: 一是在相对低位买入足够的ETF份额, 赎回获得一篮子股票组合,待市场反 弹后将赎回得到的股票卖出; 二是在相对低位买入一篮子股票,申 购ETF产品,获得基金份额,等到市场 反弹后场内卖出ETF基金份额。 日内看跌行情 投资者可以在相对高位融券,在二级 市场卖出ETF份额,待市场下跌后,在 二级市场买入ETF份额,其后进行还券。 由于当日不可还券,投资者可能需要 支付隔夜利息。 日内看涨 間内看跌 相对高 17 1) 2 保障要入ETF g x 股票 融券定HHETF 假网买入eTF 度回股票 ED网ETF 反弹起出股票 提号 STHETF 投资者进行日内波段趋势交易,需要 关注成份股以及ETF二级市场的流动性、 买入时点的折溢价情况。若标的指数 在日内频繁地上下波动,日内波段趋 势交易投资策略可以反复进行多次。 近年来我国指数型基金迅速发展,交易型开 放式指数基金(ETF) 备受关注。为帮助广 大投资者系统全面认识ETF,了解相关投资 方法,特摘编由深圳证券 ...