金工ETF点评：跨境ETF单日净流入55.62亿元，煤炭、汽车拥挤变动幅度较大

• The report introduces an industry crowding monitoring model to monitor the crowding levels of Shenwan first-level industry indices on a daily basis. The model identifies industries with high crowding levels, such as electric equipment, steel, and non-ferrous metals, while industries like media and social services exhibit lower crowding levels. The model also tracks changes in crowding levels, highlighting significant shifts in coal and automotive industries. [3] - The report mentions the premium rate Z-score model for screening ETF products with potential arbitrage opportunities. The model uses rolling calculations to identify ETFs with significant deviations from their fair value, which may indicate potential trading opportunities. [4] - The report provides a detailed analysis of ETF fund flows, categorizing them into broad-based ETFs, industry-themed ETFs, style strategy ETFs, and cross-border ETFs. It highlights the top three ETFs with the highest and lowest net inflows for each category. [5] - The report includes a heatmap of industry crowding levels over the past 30 trading days, providing a visual representation of crowding trends across various industries. [9] - The report provides a summary of main fund inflows and outflows across different industries over the past three trading days, highlighting significant changes in sectors such as electronics, electric equipment, and non-ferrous metals. [12] - The report identifies specific ETF products with trading signals based on the constructed models, suggesting potential opportunities for investment or caution. Examples include the Infrastructure ETF, Red Dividend State-Owned Enterprise ETF, Online Consumption ETF, and Shanghai Gold ETF. [13]