行业轮动周报：ETF资金净流入红利流出高位医药，指数与大金融回调有明显托底-20250721

Quantitative Models and Construction Methods - Model Name: Diffusion Index Model Construction Idea: The model is based on price momentum principles, aiming to capture upward trends in industry performance[25][37] Construction Process: 1. Calculate the diffusion index for each industry based on price momentum 2. Rank industries by their diffusion index values 3. Select industries with the highest diffusion index values for portfolio allocation Formula: Not explicitly provided in the report Evaluation: The model performs well during upward trends but struggles during reversals, as seen in historical performance[25][37] - Model Name: GRU Factor Model Construction Idea: The model leverages GRU (Gated Recurrent Unit) deep learning networks to analyze minute-level volume and price data for industry rotation[38][33] Construction Process: 1. Input minute-level volume and price data into the GRU network 2. Train the model using historical data to identify industry rotation signals 3. Generate GRU factor scores for each industry and rank them 4. Allocate portfolio weights based on GRU factor rankings Formula: Not explicitly provided in the report Evaluation: The model performs well in short cycles but faces challenges in long cycles and extreme market conditions[38][33] Model Backtesting Results - Diffusion Index Model: - Monthly average return: -0.81% - Excess return over equal-weighted industry benchmark: -1.61% (July 2025)[29] - Year-to-date excess return: 1.48%[24][29] - GRU Factor Model: - Weekly average return: -0.46% - Excess return over equal-weighted industry benchmark: -1.27% (July 2025)[36] - Year-to-date excess return: -5.75%[33][36] Quantitative Factors and Construction Methods - Factor Name: Diffusion Index Construction Idea: Measures industry momentum based on price trends[25][26] Construction Process: 1. Calculate the diffusion index for each industry using price data 2. Rank industries by diffusion index values 3. Select industries with the highest diffusion index values for portfolio allocation Formula: Not explicitly provided in the report Evaluation: Effective in capturing upward trends but vulnerable to reversals[25][26] - Factor Name: GRU Factor Construction Idea: Utilizes GRU deep learning networks to analyze minute-level volume and price data for industry rotation[38][33] Construction Process: 1. Input minute-level volume and price data into the GRU network 2. Train the model using historical data to identify industry rotation signals 3. Generate GRU factor scores for each industry and rank them 4. Allocate portfolio weights based on GRU factor rankings Formula: Not explicitly provided in the report Evaluation: Performs well in short cycles but struggles in long cycles and extreme market conditions[38][33] Factor Backtesting Results - Diffusion Index Factor: - Top-ranked industries (July 18, 2025): Comprehensive Finance (1.0), Comprehensive (0.998), Non-Banking Finance (0.996), Steel (0.995), Nonferrous Metals (0.994), Communication (0.993)[26][27] - Weekly changes in rankings: Consumer Services (+0.224), Food & Beverage (+0.208), National Defense (+0.091)[28] - GRU Factor: - Top-ranked industries (July 18, 2025): Banking (2.68), Transportation (2.42), Nonferrous Metals (-0.87), Steel (-1.92), Construction (-2.19), Coal (-2.36)[34] - Weekly changes in rankings: Building Materials (+), Banking (+), Comprehensive Finance (+)[34]