商品整体震荡调整，市场情绪偏弱

Quantitative Models and Construction Methods 1. Model Name: Commodity Term Structure Simulation Portfolio - Model Construction Idea: The model is based on the roll yield factor to depict the contango and backwardation states of commodities, dynamically going long on commodities with high roll yields and shorting those with low roll yields[23][24] - Model Construction Process: - Identify the roll yield factor to determine the contango and backwardation states of commodities - Dynamically adjust the portfolio to go long on commodities with high roll yields and short on those with low roll yields - The portfolio's latest holdings are mainly long agricultural products and industrial metals, and short energy and chemical products[23][24][30] - Model Evaluation: The model has shown strong performance, achieving a new high since 2010[23][28] 2. Model Name: Commodity Time Series Momentum Simulation Portfolio - Model Construction Idea: The model uses multiple technical indicators to depict the medium and long-term trends of domestic commodities, dynamically going long on assets with upward trends and shorting those with downward trends[23][24] - Model Construction Process: - Use technical indicators to identify medium and long-term trends in commodities - Dynamically adjust the portfolio to go long on assets with upward trends and short on those with downward trends - The latest holdings are mainly long industrial metals and short energy and agricultural products[33][36] - Model Evaluation: The model has shown mixed performance, with some recent gains but an overall decline for the year[33][34] 3. Model Name: Commodity Cross-Sectional Inventory Simulation Portfolio - Model Construction Idea: The model is based on the inventory factor to depict changes in the fundamentals of domestic commodities, dynamically going long on assets with decreasing inventories and shorting those with increasing inventories[23][24] - Model Construction Process: - Identify the inventory factor to determine changes in commodity fundamentals - Dynamically adjust the portfolio to go long on assets with decreasing inventories and short on those with increasing inventories - The latest holdings are mainly long industrial metals and agricultural products, and short energy and chemical products[37][40][42] - Model Evaluation: The model has shown strong performance, achieving a new high since 2010[37][38] Model Backtesting Results 1. Commodity Term Structure Simulation Portfolio - Recent Two-Week Return: 0.90%[26] - Year-to-Date Return: 6.44%[28] - Top Contributors: Methanol (0.34%), Palm Oil (0.22%), Polypropylene (0.14%)[30] - Top Detractors: Copper (-0.09%), Rapeseed Oil (-0.10%), Soybean Meal (-0.20%)[30] 2. Commodity Time Series Momentum Simulation Portfolio - Recent Two-Week Return: 0.47%[26] - Year-to-Date Return: -2.66%[33] - Top Contributors: Methanol (0.29%), Aluminum (0.21%), Palm Oil (0.16%)[33] - Top Detractors: PTA (-0.06%), Copper (-0.08%), Hot Rolled Coil (-0.09%)[33] 3. Commodity Cross-Sectional Inventory Simulation Portfolio - Recent Two-Week Return: 0.34%[26] - Year-to-Date Return: 5.90%[37] - Top Contributors: Aluminum (0.30%), Polypropylene (0.29%), Polyethylene (0.28%)[40] - Top Detractors: Rubber (-0.18%), Zinc (-0.24%), Methanol (-0.35%)[40]