行业轮动周报：融资余额新高，创新药光通信调整，指数预期仍将震荡上行挑战前高-20250811

• Model Name: Diffusion Index Model; Model Construction Idea: The model is based on the principle of price momentum; Model Construction Process: The model tracks the weekly and monthly changes in the diffusion index of various industries, ranking them accordingly. The formula used is $ \text{Diffusion Index} = \frac{\text{Number of Upward Trends}}{\text{Total Number of Trends}} $; Model Evaluation: The model has shown varying performance over the years, with significant returns in some periods and notable drawdowns in others[27][28][31] - Model Name: GRU Factor Model; Model Construction Idea: The model utilizes GRU deep learning networks to analyze minute-level volume and price data; Model Construction Process: The model ranks industries based on GRU factors, which are derived from deep learning algorithms processing historical trading data. The formula used is $ \text{GRU Factor} = \text{GRU Network Output} $; Model Evaluation: The model performs well in short cycles but has mixed results in longer cycles[33][34][36] - Diffusion Index Model, Average Weekly Return: 2.06%, Excess Return: -0.00%, August Excess Return: -0.45%, Year-to-Date Excess Return: -0.41%[31] - GRU Factor Model, Average Weekly Return: 2.71%, Excess Return: 0.65%, August Excess Return: 0.32%, Year-to-Date Excess Return: -4.35%[36] - Factor Name: GRU Industry Factor; Factor Construction Idea: The factor is derived from GRU deep learning networks analyzing minute-level trading data; Factor Construction Process: The factor ranks industries based on GRU network outputs, which are calculated from historical volume and price data. The formula used is $ \text{GRU Factor} = \text{GRU Network Output} $; Factor Evaluation: The factor has shown significant changes in rankings, indicating its sensitivity to market conditions[6][14][34] - GRU Industry Factor, Steel: 2.82, Building Materials: 1.72, Transportation: 1.3, Oil & Petrochemicals: 0.27, Construction: -0.46, Comprehensive: -1.87[6][14][34]