行业ETF配置模型2025年超额14.4%

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 leaders for the year [10] - Model Construction Process: 1. Use 29 first-level industry indices as the investment universe [10] 2. Calculate the price change over the past 20, 40, and 60 trading days for each industry index [10] 3. Rank the price changes for each period and normalize the rankings to obtain RS_20, RS_40, and RS_60 [10] 4. Compute the average of the three rankings to derive the final relative strength index: $ RS = (RS_{20} + RS_{40} + RS_{60}) / 3 $ where RS_20, RS_40, and RS_60 represent the normalized rankings of price changes over 20, 40, and 60 trading days, respectively [10] - Model Evaluation: The model successfully identified leading industries in 2024, such as coal, banking, and AI-related sectors, which showed strong performance during the year [10][12] 2. Model Name: Industry Rotation Model (Prosperity-Trend-Crowding Framework) - Model Construction Idea: This model combines three dimensions—prosperity, trend, and crowding—to recommend industry allocations. It includes two sub-strategies: "Strong Trend-Low Crowding" and "High Prosperity-Strong Trend" [7][15] - Model Construction Process: 1. Define prosperity as the core metric, supplemented by trend and crowding dimensions [15] 2. For the "High Prosperity-Strong Trend" strategy, focus on industries with high prosperity and strong trends while avoiding highly crowded industries [15] 3. For the "Strong Trend-Low Crowding" strategy, prioritize industries with strong trends and low crowding while avoiding low-prosperity industries [15] 4. Allocate weights to industries based on the framework, e.g., November 2025 allocation: Basic Chemicals (18%), Media (16%), Agriculture (12%), Light Manufacturing (12%), Computers (12%), Home Appliances (9%), Real Estate (9%), Retail (6%), New Energy (4%), Coal (3%) [7][15] - Model Evaluation: The model demonstrated strong performance, with an annualized excess return of 13.7% and an IR of 1.5. It also showed a high monthly win rate of 67% [15][22] 3. Model Name: Left-Side Inventory Reversal Model - Model Construction Idea: This model identifies industries in a recovery phase from distress by analyzing inventory levels and analyst expectations. It aims to capture reversal opportunities in industries with low inventory pressure and potential for restocking [29] - Model Construction Process: 1. Focus on industries experiencing current or past distress with signs of recovery [29] 2. Identify industries with low inventory pressure and restocking potential [29] 3. Incorporate analyst long-term positive outlooks for these industries [29] - Model Evaluation: The model achieved an absolute return of 27.9% and an excess return of 7.5% relative to equal-weighted industry benchmarks in 2025 (up to October) [29] --- Model Backtesting Results 1. Industry Mainline Model (RSI) - Annualized excess return: Not explicitly stated - IR: Not explicitly stated - Maximum drawdown: Not explicitly stated - Monthly win rate: Not explicitly stated - 2024 performance: Identified leading industries such as coal, banking, and AI, which showed strong performance during the year [10][12] 2. Industry Rotation Model (Prosperity-Trend-Crowding Framework) - Annualized excess return: 13.7% [15] - IR: 1.5 [15] - Maximum drawdown: -8.0% [15] - Monthly win rate: 67% [15] - 2023 excess return: 7.3% [15] - 2024 excess return: 5.7% [15] - 2025 excess return (up to October): 2.0% [15] 3. Left-Side Inventory Reversal Model - Annualized excess return: Not explicitly stated - IR: Not explicitly stated - Maximum drawdown: Not explicitly stated - Monthly win rate: Not explicitly stated - 2023 performance: Absolute return of 13.4%, excess return of 17.0% [29] - 2024 performance: Absolute return of 26.5%, excess return of 15.4% [29] - 2025 performance (up to October): Absolute return of 27.9%, excess return of 7.5% [29]