Quantitative Models and Construction Methods 1. Model Name: Industry Mainline Model (Relative Strength Index, RSI) - **Model Construction Idea**: This model identifies leading industries by calculating their relative strength (RS) based on historical price performance. Industries with RS > 90% are considered potential market leaders [13] - **Model Construction Process**: 1. Use 31 first-level industry indices as the configuration targets [13] 2. Calculate the price change percentages over the past 20, 40, and 60 trading days for each industry [13] 3. Rank the industries based on their price changes for each period and normalize the rankings to obtain RS_20, RS_40, and RS_60 [13] 4. Compute the average of the three rankings to derive the final RS index: $ RS = (RS_{20} + RS_{40} + RS_{60}) / 3 $ [13] 5. Industries with RS > 90% before the end of April are identified as potential leaders for the year [13] - **Model Evaluation**: The model effectively identified leading industries in 2024, such as coal, utilities, home appliances, banks, oil and gas, telecommunications, non-ferrous metals, agriculture, and automobiles. These industries aligned with the market's main themes, including high dividends, resources, exports, and AI [13] 2. Model Name: Industry Sentiment-Trend-Crowding Framework - **Model Construction Idea**: This framework provides two right-side industry rotation strategies based on market sentiment, trend, and crowding levels [17] 1. High Sentiment + Strong Trend, avoiding high crowding (aggressive and synchronized with the market) [17] 2. Strong Trend + Low Crowding, avoiding low sentiment (trend-following and user-friendly) [17] - **Model Construction Process**: 1. Use sentiment as the core metric, combined with trend and crowding levels, to identify industries with strong potential [17] 2. Historical backtesting results show the model's annualized return and risk metrics [17] - **Model Evaluation**: The model demonstrates strong performance, with an annualized return of 22.0%, an annualized excess return of 13.4%, an IR of 1.5, and a maximum drawdown of -8.0%. The monthly win rate is 67% [17] 3. Model Name: Left-Side Inventory Reversal Model - **Model Construction Idea**: This model identifies industries in a recovery phase from distress or inventory pressure, aiming to capture turnaround opportunities during restocking cycles [27] - **Model Construction Process**: 1. Focus on industries with current or past distress but showing signs of recovery [27] 2. Evaluate long-term analyst sentiment and inventory pressure to identify industries with restocking potential [27] 3. Historical backtesting results show the model's performance metrics [27] - **Model Evaluation**: The model has shown strong historical performance, with absolute returns of 13.4% in 2023, 26.5% in 2024, and 28.7% in 2025. The excess returns relative to equal-weighted industry benchmarks were 17.0%, 15.4%, and 5.6%, respectively [27] --- Model Backtesting Results 1. Industry Mainline Model (RSI) - **2024**: Industries with RS > 90% included coal, utilities, home appliances, banks, oil and gas, telecommunications, non-ferrous metals, agriculture, and automobiles. These industries aligned with the year's main themes [13] - **2025**: 17 industries showed RS > 90%, including TMT, banks, manufacturing, and some consumer sectors [13] - **2026 (up to February 6)**: 7 industries showed RS > 90%, including media, building materials, oil and gas, non-ferrous metals, basic chemicals, defense, and telecommunications [14] 2. Industry Sentiment-Trend-Crowding Framework - **Annualized Return**: 22.0% [17] - **Annualized Excess Return**: 13.4% [17] - **IR**: 1.5 [17] - **Maximum Drawdown**: -8.0% [17] - **Monthly Win Rate**: 67% [17] - **January 2026 Performance**: Absolute return of 6.5%, excess return of 0.7% [17] 3. Left-Side Inventory Reversal Model - **2023**: Absolute return of 13.4%, excess return of 17.0% [27] - **2024**: Absolute return of 26.5%, excess return of 15.4% [27] - **2025**: Absolute return of 28.7%, excess return of 5.6% [27] - **January 2026**: Absolute return of 10.4%, excess return of 4.8% [27]