金工ETF点评：宽基ETF单日净流出57.97亿元，有色金属、美护拥挤度激增

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 and tracking changes in crowding over time[3] - Model Construction Process: The report does not provide specific details on the mathematical or algorithmic process used to construct the crowding monitoring model. However, it is implied that the model uses historical data and metrics to assess crowding levels across industries[3] - Model Evaluation: The model effectively highlights industries with significant crowding changes, such as the notable increases in crowding for the non-ferrous metals and beauty care sectors, providing actionable insights for investors[3] 2. Model Name: Premium Rate Z-Score Model - Model Construction Idea: This model is used to identify 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 as: $ Z = \frac{(X - \mu)}{\sigma} $ - Where $ X $ is the current premium rate, $ \mu $ is the mean premium rate over the rolling window, and $ \sigma $ is the standard deviation of the premium rate over the same period - The model identifies ETFs with extreme Z-scores, signaling potential arbitrage opportunities or risks of price corrections[4] - Model Evaluation: The model provides a systematic approach to ETF selection, helping investors identify mispriced ETFs while cautioning against potential downside risks[4] --- Model Backtesting Results 1. Industry Crowding Monitoring Model - No specific numerical backtesting results or metrics are provided for this model in the report[3] 2. Premium Rate Z-Score Model - No specific numerical backtesting results or metrics are provided for this model in the report[4] --- Quantitative Factors and Construction Methods The report does not explicitly mention any standalone quantitative factors or their construction processes. It focuses on the models described above. --- Factor Backtesting Results No standalone factor backtesting results are provided in the report. The focus remains on the models and their applications.