金工ETF点评：行业主题ETF单日净流入92.01亿元，商贸零售、煤炭拥挤大幅收窄

Quantitative Models and Construction Methods 1. Model Name: Industry Crowding Monitoring Model - Model Construction Idea: This model is designed to monitor the crowding levels of Shenwan First-Level Industry Indices on a daily basis, identifying industries with high or low crowding levels to provide actionable insights for investors[3] - Model Construction Process: The model calculates the crowding levels of various industries based on specific metrics (not detailed in the report) and tracks daily changes. For example, on the previous trading day, the crowding levels of "Electric Power Equipment" and "Electronics" were high, while "Food & Beverage," "Beauty Care," and "Petrochemical" had lower crowding levels. Significant changes in crowding levels were observed in "Retail" and "Coal"[3] - Model Evaluation: The model provides a useful tool for identifying industry crowding trends and potential investment opportunities or risks[3] 2. Model Name: Premium Rate Z-Score Model - Model Construction Idea: This model identifies potential arbitrage opportunities in ETF products by calculating the Z-score of premium rates over a rolling window[4] - Model Construction Process: The Z-score is calculated based on the rolling premium rates of ETF products. The model flags ETFs with significant deviations from their historical averages, indicating potential arbitrage opportunities or risks of price corrections[4] - Model Evaluation: The model is effective in screening ETFs for arbitrage opportunities while also highlighting potential risks of price pullbacks[4] --- Backtesting Results of Models 1. Industry Crowding Monitoring Model - No specific numerical backtesting results were provided for this model in the report 2. Premium Rate Z-Score Model - No specific numerical backtesting results were provided for this model in the report