金工ETF点评：宽基ETF单日净流出71.31亿元，食饮、美护拥挤持续低位

• The report constructs an industry crowding monitoring model to monitor the crowding levels of Shenwan First-Level Industry Indexes on a daily basis[3] - The ETF product screening signal model is built using the premium rate Z-score model, which provides potential arbitrage opportunities through rolling calculations[4] - The industry crowding monitoring model indicates that the crowding levels of the power equipment and electronics industries were high on the previous trading day, while the food and beverage, beauty care, and petrochemical industries had lower crowding levels[3] - The ETF product screening signal model suggests caution regarding potential pullback risks of the identified targets[4] Model and Factor Construction Industry Crowding Monitoring Model - Model Name: Industry Crowding Monitoring Model - Construction Idea: Monitor the crowding levels of various industries on a daily basis to identify potential investment opportunities and risks[3] - Construction Process: The model calculates the crowding levels of Shenwan First-Level Industry Indexes daily, based on the flow of main funds and changes in allocation over recent trading days[3] - Evaluation: The model effectively identifies industries with significant changes in crowding levels, providing valuable insights for investment decisions[3] ETF Product Screening Signal Model - Model Name: ETF Product Screening Signal Model - Construction Idea: Identify potential arbitrage opportunities in ETF products using the premium rate Z-score model[4] - Construction Process: The model uses rolling calculations of the premium rate Z-score to screen for ETF products that may present arbitrage opportunities. It also highlights potential pullback risks for the identified targets[4] - Evaluation: The model provides a systematic approach to identifying arbitrage opportunities in ETF products, enhancing investment strategies[4] Model Backtesting Results Industry Crowding Monitoring Model - Power Equipment and Electronics: High crowding levels on the previous trading day[3] - Food and Beverage, Beauty Care, Petrochemical: Low crowding levels on the previous trading day[3] - Coal and Nonferrous Metals: Significant changes in crowding levels observed[3] ETF Product Screening Signal Model - Potential Arbitrage Opportunities: Identified through rolling calculations of the premium rate Z-score[4] - Pullback Risks: Highlighted for the identified ETF products[4]