金工ETF点评：宽基ETF单日净流入51.19亿元，家电、环保拥挤变幅较大

• The industry crowding monitoring model was constructed to monitor the crowding level of Shenwan primary industry indices daily. The model identifies industries with high crowding levels, such as military, non-ferrous metals, and building materials, while industries like banking, computers, and media exhibit lower crowding levels. The model also tracks changes in crowding levels, highlighting significant variations in sectors like home appliances and environmental protection[3] - 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 investment opportunities while warning of possible risks of price corrections[4] - The Z-score premium rate model's construction process involves calculating the Z-score of the premium rate for each ETF product. The formula for Z-score is: $ Z = \frac{(P - \mu)}{\sigma} $ where $ P $ represents the premium rate, $ \mu $ is the mean premium rate, and $ \sigma $ is the standard deviation of the premium rate. This calculation helps identify ETFs with significant deviations from their average premium rate[4] - The Z-score premium rate model is evaluated as a useful tool for identifying arbitrage opportunities in ETF products, but it requires caution due to potential risks associated with price corrections[4] - The industry crowding monitoring model is considered effective for tracking daily crowding levels and identifying significant changes in industry crowding dynamics, aiding in investment decision-making[3] - The Z-score premium rate model's testing results are not explicitly provided in the report[4]