📅 2024-01-18 — Session: Integrated OLS Residuals into Backtrader Strategies
🕒 13:10–14:30
🏷️ Labels: Backtrader, OLS, Residuals, Python, Algorithmic Trading
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to integrate Ordinary Least Squares (OLS) residuals into Backtrader strategies, enhancing algorithmic trading models with data-driven insights.
Key Activities
- Data Preparation: Calculated rolling OLS residuals for stock prices using Python, Pandas, and Statsmodels, providing a foundation for strategy integration.
- Optimization: Developed a Python function to optimize residual calculation by selecting every nth data point, improving computational efficiency.
- Strategy Implementation: Modified a Backtrader strategy to incorporate residual data feeds, detailing class structure and methods for decision-making based on residuals.
Achievements
- Successfully integrated OLS residuals into Backtrader strategies, enhancing decision-making processes with refined data analysis.
- Optimized residual calculation for better performance and efficiency.
Pending Tasks
- Further test and validate the modified trading strategies using historical data to ensure robustness and reliability.
- Explore additional optimization techniques for residual calculation and strategy performance.