商品量化CTA周度跟踪

Quantitative Models and Construction Methods 1. Model Name: Composite Signal Model - Model Construction Idea: The model integrates multiple factors to generate a comprehensive signal for trading decisions[3][7] - Model Construction Process: - Demand Factor: Influenced by the utilization rate of MTO capacity and the ex-factory price of acetic acid[3] - Supply Factor: Determined by methanol port arrivals and inland methanol plant operations[3] - Inventory Factor: Based on significant port destocking[3] - Price Spread Factor: Influenced by the price spread between different regions[6] - Profit Factor: Affected by the daily income of float glass production[7] - Model Evaluation: The model provides a comprehensive signal by balancing multiple factors, which helps in making informed trading decisions[3][7] Model Backtesting Results Composite Signal Model - Demand Factor: Last week's return: 0.31%, Monthly return: 1.82%[7] - Supply Factor: Last week's return: 0.00%, Monthly return: 1.01%[7] - Inventory Factor: Last week's return: 0.00%, Monthly return: -0.11%[7] - Price Spread Factor: Last week's return: 0.00%, Monthly return: 1.49%[7] - Profit Factor: Last week's return: -0.39%, Monthly return: -1.05%[7] Quantitative Factors and Construction Methods 1. Factor Name: Momentum Factor - Factor Construction Idea: The factor is based on the momentum of different commodity sectors[1][4] - Factor Construction Process: - Time-Series Momentum: Measures the momentum over a specific period[1][4] - Cross-Sectional Momentum: Compares the momentum across different commodities[1][4] - Formula: $\text{Momentum} = \frac{P_t - P_{t-n}}{P_{t-n}}$ where $P_t$ is the current price and $P_{t-n}$ is the price $n$ periods ago[1][4] - Factor Evaluation: The momentum factor helps in identifying the strength and direction of price movements, aiding in trend-following strategies[1][4] 2. Factor Name: Term Structure Factor - Factor Construction Idea: The factor is based on the term structure of futures contracts[1][4] - Factor Construction Process: - Near-Month vs. Far-Month Contracts: Compares the prices of near-month and far-month futures contracts[1][4] - Formula: $\text{Term Structure} = \frac{F_{near} - F_{far}}{F_{far}}$ where $F_{near}$ is the price of the near-month contract and $F_{far}$ is the price of the far-month contract[1][4] - Factor Evaluation: The term structure factor helps in understanding the market's expectations of future price movements and the cost of carry[1][4] 3. Factor Name: Open Interest Factor - Factor Construction Idea: The factor is based on the open interest of futures contracts[1][4] - Factor Construction Process: - Open Interest Analysis: Measures the total number of outstanding contracts[1][4] - Formula: $\text{Open Interest} = \sum_{i=1}^{N} OI_i$ where $OI_i$ is the open interest of the $i$-th contract[1][4] - Factor Evaluation: The open interest factor indicates the level of market participation and liquidity, which can signal the strength of a trend[1][4] Factor Backtesting Results Momentum Factor - Black Sector: Time-Series: 1.46, Cross-Sectional: 0.33[4] - Non-Ferrous Sector: Time-Series: 0.85, Cross-Sectional: 2.49[4] - Energy Sector: Time-Series: -0.38, Cross-Sectional: 0.00[4] - Agricultural Sector: Time-Series: -0.60, Cross-Sectional: 0.81[4] - Stock Index Sector: Time-Series: 0.06, Cross-Sectional: 0.78[4] - Precious Metals Sector: Time-Series: 1.01, Cross-Sectional: 2.56[4] Term Structure Factor - Black Sector: 1.10[4] - Non-Ferrous Sector: 0.83[4] - Energy Sector: 1.03[4] - Agricultural Sector: 1.83[4] - Stock Index Sector: -0.25[4] Open Interest Factor - Black Sector: 0.33[4] - Non-Ferrous Sector: 0.92[4] - Energy Sector: 1.46[4] - Agricultural Sector: -1.82[4] - Stock Index Sector: 1.37[4]