- The report introduces three quantitative models: Commodity Term Structure, Commodity Time-Series Momentum, and Commodity Cross-Sectional Inventory. These models are combined into a Composite Commodity Strategy using equal weighting of the three sub-strategies[25][26][28] - **Commodity Term Structure Model**: This model is constructed based on the roll yield factor to capture the contango and backwardation states of commodities. It dynamically goes long on commodities with high roll yields and short on those with low roll yields[26][30][33] - **Commodity Time-Series Momentum Model**: This model uses multiple technical indicators to capture medium- and long-term trends in domestic commodities. It dynamically goes long on assets with upward trends and short on assets with downward trends[26][35][36] - **Commodity Cross-Sectional Inventory Model**: This model is based on the inventory factor to reflect changes in the domestic commodity fundamentals. It dynamically goes long on assets with declining inventory and short on assets with increasing inventory[26][40][43] - **Evaluation of Models**: The Commodity Term Structure Model is noted for its strong performance, achieving a new high in net value during backtesting. The Time-Series Momentum Model has shown weaker performance recently, while the Cross-Sectional Inventory Model has demonstrated moderate gains[25][35][40] - **Backtesting Results**: - Commodity Term Structure Model: Two-week return of 2.31%, year-to-date return of 7.46%[30][33][34] - Commodity Time-Series Momentum Model: Two-week return of -0.38%, year-to-date return of -3.19%[35][36][39] - Commodity Cross-Sectional Inventory Model: Two-week return of 0.98%, year-to-date return of 5.43%[40][43][44]

Quantitative Models and Construction Methods Model 1: Commodity Term Structure Model - **Construction Idea**: This model captures the state of commodity contango and backwardation using the roll yield factor, dynamically going long on commodities with high roll yields and short on those with low roll yields[23][24] - **Construction Process**: - Identify the roll yield for each commodity - Rank commodities based on their roll yields - Go long on commodities with the highest roll yields and short on those with the lowest roll yields - **Evaluation**: The model has shown good performance recently, particularly in the industrial metals and agricultural products sectors[23][24] Model 2: Commodity Time Series Momentum Model - **Construction Idea**: This model captures medium to long-term trends in domestic commodities using multiple technical indicators, dynamically going long on assets with upward trends and short on those with downward trends[23][24] - **Construction Process**: - Use technical indicators to identify trends in commodity prices - Rank commodities based on their trend strength - Go long on commodities with the strongest upward trends and short on those with the strongest downward trends - **Evaluation**: The model has underperformed recently, with significant losses in the black and energy chemical sectors[33][35] Model 3: Commodity Cross-Sectional Inventory Model - **Construction Idea**: This model captures changes in the domestic commodity fundamentals using the inventory factor, dynamically going long on assets with decreasing inventories and short on those with increasing inventories[23][24] - **Construction Process**: - Identify inventory levels for each commodity - Rank commodities based on their inventory changes - Go long on commodities with the largest inventory decreases and short on those with the largest inventory increases - **Evaluation**: The model has shown mixed performance, with significant losses in the agricultural products sector[39][41] Model Backtesting Results Commodity Term Structure Model - **Recent Two-Week Return**: 1.69%[26] - **Year-to-Date Return**: 3.09%[28] - **Top Contributors**: Glass (1.27%), PVC (0.32%), Rubber (0.31%)[30] - **Top Detractors**: Sugar (-0.16%), PTA (-0.24%), Methanol (-0.25%)[30] Commodity Time Series Momentum Model - **Recent Two-Week Return**: -1.22%[26] - **Year-to-Date Return**: -3.17%[33] - **Top Contributors**: Soybean Oil (0.26%), LPG (0.16%), Soybean Meal (0.07%)[37] - **Top Detractors**: Rebar (-0.28%), Soda Ash (-0.30%), Cotton (-0.33%)[37] Commodity Cross-Sectional Inventory Model - **Recent Two-Week Return**: -0.56%[26] - **Year-to-Date Return**: 3.42%[39] - **Top Contributors**: Corn (0.54%), Polypropylene (0.27%), Nickel (0.22%)[43] - **Top Detractors**: PVC (-0.26%), Cotton (-0.39%), Soybean Oil (-0.46%)[43]