一、资金流向

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 significant changes in crowding dynamics[4] - Model Construction Process: The model calculates crowding levels for each industry index based on specific metrics (not detailed in the report). It tracks daily changes and highlights industries with the highest and lowest crowding levels, as well as those with significant single-day changes[4] - Model Evaluation: The model provides actionable insights into industry crowding trends, 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 premium rates over a rolling window[5] - Model Construction Process: 1. Calculate the premium rate of each ETF product as the difference between its market price and its indicative net asset value (IOPV), divided by the IOPV 2. Compute the Z-score of the premium rate over a rolling window to standardize the deviation from the mean 3. Use the Z-score to filter ETFs with significant deviations, indicating potential arbitrage opportunities or risks of price corrections[5] - Model Evaluation: The model effectively identifies ETFs with potential mispricing, offering opportunities for arbitrage or caution against price reversals[5] --- Model Backtesting Results 1. Industry Crowding Monitoring Model - Top Crowded Industries (Previous Trading Day): Basic Chemicals, Machinery Equipment, Environmental Protection[4] - Least Crowded Industries (Previous Trading Day): Media, Real Estate[4] - Industries with Significant Single-Day Changes: Pharmaceuticals & Biotechnology, Agriculture, Forestry, Animal Husbandry, and Fishery[4] 2. Premium Rate Z-Score Model - Application: Used to screen ETF products for potential arbitrage opportunities and risks of price corrections[5] --- Quantitative Factors and Construction Methods No specific quantitative factors were detailed in the report --- Factor Backtesting Results No specific factor backtesting results were detailed in the report