📅 2024-01-18 — Session: Integrated OLS Residuals into Backtrader Strategies
🕒 13:10–14:20
🏷️ Labels: Backtrader, OLS, Residuals, Python, Algorithmic Trading
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal:
The session aimed to integrate residuals from Ordinary Least Squares (OLS) regression into Backtrader strategies for enhanced decision-making in algorithmic trading.
Key Activities:
- Data Preparation: Calculated rolling OLS residuals using Python, Pandas, and Statsmodels for stock price data.
- Optimization: Implemented performance optimization by calculating residuals with selected data points to speed up computation.
- Strategy Implementation: Modified Backtrader strategies to incorporate residual data feeds, adjusting parameters for trading decisions based on calculated residuals.
Achievements:
- Successfully calculated and integrated OLS residuals into Backtrader strategies.
- Optimized the residual calculation process for efficiency.
- Enhanced trading strategy by incorporating residuals into buy/sell decision processes.
Pending Tasks:
- Further testing and validation of the strategy in live trading environments to ensure robustness and accuracy of decision-making.
- Explore additional optimization techniques for residual calculation.