Implementation Guide

This section provides practical Python implementations of the concepts covered in other sections.

Key Topics

Code Examples

Working Python implementations of:

• Daily IC calculation
• Signal combination
• Covariance estimation
• Portfolio optimization
• Backtesting framework

Math Reference

LaTeX mathematical notation examples and common formulas used throughout the wiki.

Backtesting

Framework for testing strategies and evaluating performance.

Tools and Libraries

Recommended Python stack:

• numpy - Numerical computing
• pandas - Data manipulation
• scipy - Optimization
• cvxpy - Convex optimization (optional)
• matplotlib/plotly - Visualization

Code Philosophy

All examples prioritize:

1. Clarity over performance
2. Simplicity over completeness
3. Reproducibility - Clear assumptions and defaults
4. Modularity - Easy to adapt and extend