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Quantitative Models and Construction Methods 1. Model Name: Commodity Term Structure Strategy - Model Construction Idea: This strategy utilizes the roll yield factor to capture the contango or backwardation state of commodities, dynamically going long on commodities with high roll yields and shorting those with low roll yields[51] - Model Construction Process: - The roll yield factor is calculated based on the term structure of commodity futures prices - The strategy dynamically adjusts positions to go long on commodities with high roll yields and short on those with low roll yields[51] - Model Evaluation: The strategy is designed to exploit the carry factor in commodity markets, providing a systematic approach to capturing term structure-related returns[51] 2. Model Name: Commodity Time-Series Momentum Strategy - Model Construction Idea: This strategy uses multiple technical indicators to capture medium- to long-term trends in domestic commodities, dynamically going long on assets with upward trends and shorting those with downward trends[51] - Model Construction Process: - Technical indicators such as moving averages and momentum signals are used to identify trends - Positions are dynamically adjusted based on the identified trends, with long positions in upward-trending assets and short positions in downward-trending assets[51] - Model Evaluation: The strategy systematically captures momentum effects in commodity markets, leveraging trend-following behavior[51] 3. Model Name: Commodity Cross-Sectional Inventory Strategy - Model Construction Idea: This strategy uses inventory factors to capture changes in the fundamentals of domestic commodities, dynamically going long on assets with declining inventories and shorting those with increasing inventories[51] - Model Construction Process: - Inventory data is used to construct factors reflecting supply-demand dynamics - Positions are dynamically adjusted to go long on commodities with declining inventories and short on those with increasing inventories[51] - Model Evaluation: The strategy effectively captures fundamental changes in commodity markets, providing a systematic approach to exploiting inventory-related signals[51] 4. Model Name: Commodity Fusion Strategy - Model Construction Idea: This strategy combines the above three sub-strategies (term structure, time-series momentum, and cross-sectional inventory) using equal weighting to create a diversified commodity investment approach[49] - Model Construction Process: - The three sub-strategies are equally weighted to form a composite strategy - The combined strategy dynamically adjusts positions based on the signals from the sub-strategies[49] - Model Evaluation: The fusion strategy aims to diversify risk and enhance returns by integrating multiple sources of alpha in commodity markets[49] --- Model Backtesting Results 1. Commodity Term Structure Strategy - Two-Week Return: -1.39%[54] - Year-to-Date Return: 1.38%[56] 2. Commodity Time-Series Momentum Strategy - Two-Week Return: 1.99%[54] - Year-to-Date Return: -1.97%[61] 3. Commodity Cross-Sectional Inventory Strategy - Two-Week Return: -0.26%[54] - Year-to-Date Return: 4.00%[68] 4. Commodity Fusion Strategy - Two-Week Return: 0.12%[49] - Year-to-Date Return: 1.14%[49] --- Quantitative Factors and Construction Methods 1. Factor Name: Roll Yield Factor - Factor Construction Idea: Measures the contango or backwardation state of commodity futures markets[51] - Factor Construction Process: - Calculated based on the difference between near-month and far-month futures prices - Positive roll yield indicates backwardation, while negative roll yield indicates contango[51] 2. Factor Name: Momentum Factor - Factor Construction Idea: Captures the trend-following behavior in commodity prices[51] - Factor Construction Process: - Derived from technical indicators such as moving averages and momentum signals - Positive momentum indicates an upward trend, while negative momentum indicates a downward trend[51] 3. Factor Name: Inventory Factor - Factor Construction Idea: Reflects supply-demand dynamics in commodity markets[51] - Factor Construction Process: - Based on changes in inventory levels - Declining inventories indicate tightening supply, while increasing inventories indicate loosening supply[51] --- Factor Backtesting Results 1. Roll Yield Factor - Performance: Contributed positively to the term structure strategy, with key contributors being iron ore, ethylene glycol, and methanol[58] 2. Momentum Factor - Performance: Contributed positively to the time-series momentum strategy, with key contributors being hot-rolled coil, rebar, and zinc[67] 3. Inventory Factor - Performance: Contributed positively to the cross-sectional inventory strategy, with key contributors being PVC, zinc, and rubber[73]