2025年量化CTA年报：宏观驱动不止，CTA机险并存

Quantitative Models and Construction Methods - Model Name: CTA Trend Strategy Model Construction Idea: The model leverages market trends and volatility to capture trading opportunities, particularly in high-trend environments. It performs better in markets with strong directional movements. [21][22] Model Construction Process: The strategy is built on analyzing historical price movements and volatility metrics. It uses trend-following algorithms to identify upward or downward trends in commodity prices. Key metrics include annualized return, volatility, maximum drawdown, Sharpe ratio, and Calmar ratio. [21][22] Model Evaluation: The model demonstrates robust performance in high-trend markets but struggles in low-volatility or range-bound conditions. [21][22] - Model Name: CTA Cross-sectional Strategy Model Construction Idea: This strategy focuses on relative performance across different assets, aiming to exploit cross-sectional volatility and relative strength. [22][25] Model Construction Process: The strategy uses cross-sectional data to identify assets with stronger or weaker relative performance. It incorporates multi-factor analysis, including basic fundamental factors and price-based metrics. [22][25] Model Evaluation: The strategy underperformed in 2024 due to low cross-sectional volatility and synchronized market movements. [22][25] Model Backtesting Results - CTA Trend Strategy: - Annualized Return: 9.53% - Annualized Volatility: 4.56% - Maximum Drawdown: 2.83% - Sharpe Ratio: 1.62 - Calmar Ratio: 3.66 [21][22] - CTA Cross-sectional Strategy: - Annualized Return: -1.93% - Annualized Volatility: 3.82% - Maximum Drawdown: -4.49% - Sharpe Ratio: -0.96 - Calmar Ratio: -0.82 [29][30] Quantitative Factors and Construction Methods - Factor Name: Short-term Momentum Factor Construction Idea: Captures short-term price trends and reversals in commodity markets. [25][29] Factor Construction Process: The factor is calculated using rolling windows of short-term price changes. It identifies assets with strong recent performance for potential continuation. [25][29] Factor Evaluation: The factor struggled in 2024 due to frequent market reversals and low trend persistence. [25][29] - Factor Name: Long-term Momentum Factor Construction Idea: Focuses on sustained price trends over longer periods, aiming to capture structural market movements. [25][29] Factor Construction Process: The factor uses extended rolling windows to analyze price trends and volatility. It identifies assets with consistent upward or downward movements. [25][29] Factor Evaluation: The factor performed well in 2024, particularly in capturing trends in precious metals and base metals. [25][29] - Factor Name: Term Structure Factor Construction Idea: Exploits the pricing differences between near-term and long-term futures contracts. [25][29] Factor Construction Process: The factor is derived from the spread between front-month and back-month futures prices, adjusted for seasonal and macroeconomic influences. [25][29] Factor Evaluation: The factor underperformed in 2024 due to persistent backwardation in the black commodity sector. [25][29] Factor Backtesting Results - Short-term Momentum: - Annualized Return: -2.07% - Annualized Volatility: 4.21% - Maximum Drawdown: -4.08% - Sharpe Ratio: -0.9 - Calmar Ratio: -0.93 [29][30] - Long-term Momentum: - Annualized Return: 6.02% - Annualized Volatility: 2.51% - Maximum Drawdown: -1.31% - Sharpe Ratio: 1.64 - Calmar Ratio: 3.13 [29][30] - Term Structure: - Annualized Return: -3.85% - Annualized Volatility: 2.62% - Maximum Drawdown: -5.40% - Sharpe Ratio: -2.18 - Calmar Ratio: -1.06 [29][30]