PACIFIC SECURITIES(SH:601099) Tai Ping Yang Zheng Quan·2025-11-25 13:12Quantitative 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, focusing on the crowding degree of Shenwan Level-1 industry indices. It identifies industries with high or low crowding levels and tracks changes in crowding over time[3] Model Construction Process: The model calculates the crowding degree of each industry index based on specific metrics, such as main fund inflows and outflows. It then ranks industries by their crowding levels and highlights significant changes in crowding over recent trading days[3] Model Evaluation: The model provides a useful tool for identifying industry trends and potential investment opportunities by analyzing crowding dynamics[3] 2. Model Name: Premium Rate Z-Score Model Model Construction Idea: This model is used to screen ETF products for potential arbitrage opportunities by calculating the Z-score of their premium rates over a rolling window[4] Model Construction Process: - The premium rate of an ETF is calculated as the difference between its market price and its net asset value (NAV), divided by the NAV - The Z-score is then computed as: $ Z = \frac{(Premium\ Rate - \mu)}{\sigma} $ where $ \mu $ is the mean premium rate and $ \sigma $ is the standard deviation of the premium rate over a rolling window - ETFs with extreme Z-scores are flagged as potential arbitrage opportunities[4] Model Evaluation: The model effectively identifies ETFs with significant deviations from their historical premium rates, which may indicate arbitrage opportunities or risks of price corrections[4] --- Model Backtesting Results 1. Industry Crowding Monitoring Model: - Crowding levels for industries such as military, agriculture, and media were high, while automotive and non-bank financials showed low crowding levels[3] - Significant changes in crowding were observed in industries like computing and media over recent trading days[3] 2. Premium Rate Z-Score Model: - Specific ETFs with extreme Z-scores were identified, such as the Sci-Tech Innovation Board ETFs, which were flagged for potential arbitrage opportunities[4] --- Quantitative Factors and Construction Methods No specific quantitative factors were explicitly mentioned in the provided content --- Factor Backtesting Results No specific factor backtesting results were explicitly mentioned in the provided content