金工ETF点评：宽基ETF单日净流入26.49亿元，医药、轻工拥挤度持续高位

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 industries on a daily basis, using the Shenwan First-Level Industry Index as the basis for analysis[4] - Model Construction Process: The model calculates the crowding levels of various industries by analyzing daily changes in key metrics such as capital inflows and outflows. Specific metrics or formulas are not detailed in the report[4] - Model Evaluation: The model provides actionable insights into which industries are experiencing high or low crowding levels, helping investors identify potential opportunities or risks[4] 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 their premium rates over a rolling window[5] - Model Construction Process: 1. Calculate the premium rate of an ETF as the percentage difference between its market price and net asset value (NAV) 2. Compute the Z-score of the premium rate over a specified rolling window to standardize deviations from the mean 3. Use the Z-score to signal potential arbitrage opportunities or risks of price corrections[5] - Model Evaluation: The model is effective in identifying ETFs with significant deviations from their fair value, providing a basis for arbitrage strategies[5] --- Model Backtesting Results 1. Industry Crowding Monitoring Model - Top Crowded Industries (Previous Trading Day): - Pharmaceuticals & Biotechnology, Light Manufacturing, Textiles & Apparel[4] - Least Crowded Industries (Previous Trading Day): - Real Estate, Electronics, Home Appliances[4] - Significant Daily Changes in Crowding Levels: - Building Materials, Social Services, Non-Banking Financials[4] 2. Premium Rate Z-Score Model - ETF Signals: - ETFs with potential arbitrage opportunities or risks are identified, but specific Z-score thresholds or ETF names are not detailed in the report[5] --- Quantitative Factors and Construction Methods No specific quantitative factors were explicitly mentioned in the report --- Factor Backtesting Results No specific factor backtesting results were explicitly mentioned in the report