- The industry crowding monitoring model was constructed to monitor the daily crowding levels of Shenwan primary industry indices. It identified utilities and building materials as having high crowding levels, while automotive, food & beverage, and home appliances showed low crowding levels. The model also tracked significant daily changes in crowding levels for industries like agriculture, coal, and environmental protection[4] - The Z-score premium rate model was developed to screen ETF products for potential arbitrage opportunities. This model uses rolling calculations to identify signals and warns of potential risks of price corrections for the identified ETFs[5] - Daily net inflows for broad-based ETFs amounted to 3.77 billion yuan, with top inflows observed in CSI 1000 ETF (+7.78 billion yuan), SSE 50 ETF (+6.96 billion yuan), and CSI 300 ETF (+5.38 billion yuan). Conversely, top outflows were recorded for ChiNext ETF (-6.73 billion yuan), CSI A500 ETF (-4.06 billion yuan), and STAR 50 ETF (-3.51 billion yuan)[6] - Industry-themed ETFs saw a daily net inflow of 1.82 billion yuan, with top inflows in Military ETF (+4.01 billion yuan), Securities ETF (+2.63 billion yuan), and Defense ETF (+2.31 billion yuan). Top outflows were noted for Robotics ETF (-1.39 billion yuan), Semiconductor ETF (-1.05 billion yuan), and AI ETF (-0.99 billion yuan)[6] - Style-strategy ETFs recorded a daily net inflow of 2.29 billion yuan, with top inflows in Low Volatility Dividend ETF (+1.62 billion yuan), Low Volatility Dividend 50 ETF (+0.53 billion yuan), and Dividend State-Owned Enterprise ETF (+0.28 billion yuan). Top outflows included CSI Dividend ETF (-0.19 billion yuan), Low Volatility Dividend ETF (-0.18 billion yuan), and Low Volatility Dividend 100 ETF (-0.15 billion yuan)[6] - Cross-border ETFs experienced a daily net outflow of 0.51 billion yuan, with top inflows in Hong Kong Non-Bank ETF (+3.84 billion yuan), Hang Seng Low Volatility Dividend ETF (+0.63 billion yuan), and S&P 500 ETF (+0.42 billion yuan). Top outflows were observed for Hang Seng Tech ETF (-1.19 billion yuan), Hong Kong Dividend ETF (-0.82 billion yuan), and Nasdaq 100 ETF (-0.69 billion yuan)[6]

[Table_Author] 证券分析师：刘晓锋 电话：13401163428 [Table_Title] 金 金融工程点评 [Table_Message]2025-05-21 金工 ETF 点评：宽基 ETF 单日净流出 16.79 亿元；传媒、医药拥挤度激增 电话：18910596766 E-MAIL：liuxf@tpyzq.com 执业资格证书编码：S1190522090001 研究助理：孙弋轩 E-MAIL：sunyixuan@tpyzq.com 一般证券业务登记编码：S1190123080008 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， 前一交易日纺织服饰、美容护理、轻工制造拥挤度靠前，相比较而言，电子、 石油石化的拥挤度水平较低，建议关注。此外，传媒、医药生物单日拥挤度 变动较大。从主力资金流动来看，前一交易日主力资金流入电子、传媒、医 药生物，流出国防军工、基础化工、计算机。近三个交易日主力资金增配汽 车、家用电器、银行，减配计算机、基础化工、国防军工。 三、ETF 产品关注信号 ◼ 根据溢价率 Z-score 模型搭建相关 ET ...

[Table_Title] 金 金融工程点评 [Table_Message]2025-05-20 金工 ETF 点评：宽基 ETF 单日净流出 26.91 亿元；美容护理拥挤度持续高位 [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 E-MAIL：sunyixuan@tpyzq.com 一般证券业务登记编码：S1190123080008 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， 前一交易日纺织服饰、美容护理、轻工制造拥挤度靠前，相比较而言，传媒、 电子的拥挤度水平较低，建议关注。此外，环保、食品饮料、房地产单日拥 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国防军工、 非银金融、环保，流出汽车、电力设备、基础化工。近三个交易日主力资金 增配煤炭、美容护理、银行，减配计算机、电子、电力设备。 三、ETF 产品关注信号 融 工 程 点 评 太 平 洋 证 券 股 份 ...

电话：13401163428 E-MAIL：liuxf@tpyzq.com 执业资格证书编码：S1190522090001 金 金融工程点评 [Table_Message]2025-05-14 金工 ETF 点评：宽基 ETF 单日净流出 92.20 亿元；食品饮料拥挤度持续下降 [Table_Author] 证券分析师：刘晓锋 研究助理：孙弋轩 电话：18910596766 E-MAIL：sunyixuan@tpyzq.com 一般证券业务登记编码：S1190123080008 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， 前一交易日国防军工、纺织服饰、美容护理拥挤度靠前，相比较而言，房地 产、食品饮料的拥挤度水平较低，建议关注。此外，交通运输、非银金融、电 力设备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 入美容护理、医药生物、基础化工，流出国防军工、计算机、电子。近三个交 易日主力资金增配非银金融、美容护理、家用电器，减配计算机、电子、国 防军工。 三、ETF 产品关注信号 ◼ 根据溢价率 Z-score 模型搭建相关 ET ...

金 金融工程点评 [Table_Title] 金工 ETF 点评：宽基 ETF 单日净流入 4.37 亿元；通信行业拥挤度激增 [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 E-MAIL：sunyixuan@tpyzq.com 一般证券业务登记编码：S1190123080008 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， 前一交易日国防军工、纺织服饰、机械设备拥挤度靠前，相比较而言，煤炭 的拥挤度水平较低，建议关注。此外，通信、非银金融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通信、电力设备、传媒，流 出基础化工、计算机、农林牧渔。近三个交易日主力资金增配国防军工、通 信、电力设备，减配计算机、基础化工、电子。 三、ETF 产品关注信号 太 平 洋 证 券 股 份 有 限 公 司 证 券 研 究 报 告 [Table_Summary] 数据截止日：20 ...

- 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]

金 金融工程点评 [Table_Title] 金工 ETF 点评：宽基 ETF 单日净流入 1032.10 亿元；农林牧渔拥挤度拉满 [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 E-MAIL：sunyixuan@tpyzq.com 一般证券业务登记编码：S1190123080008 一、资金流向 二、行业拥挤度监测 ◼ 根据溢价率 Z-score 模型搭建相关 ETF 产品筛选信号模型，通过滚动测算提 供存在潜在套利机会的标的，此外需警惕标的回调风险。 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。 ◼ 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， 前一交易日农林牧渔、食品饮料、基础化工靠前，相比较而言，传媒、房地 产的拥挤度水平较低，建议关注。此外，汽车、家用电器单日拥挤度变动较 大。从主力资金流动来看，前一交易日主力资 ...