Integrated OLS Residuals into Backtrader Strategies

• Day: 2024-01-18
• Time: 13:10 to 14:30
• Project: Dev
• Workspace: WP 2: Operational
• Status: In Progress
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Backtrader, OLS, Residuals, Python, Algorithmic Trading

Description

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.

Evidence

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• event_ids: []