v0.1.9 - Intraday Cache Updates and Transformation Module

Added

• Intraday cache update feature for Bloomberg data with selective field updates
  • update_cached_data() function for efficient cache refresh
  • Configurable refresh intervals and field subsets
  • Comprehensive integration tests validating update workflow
• Centralized time series transformation module (data/transforms.py)
  • Reusable functions for z-score normalization, returns calculation, rolling statistics
  • Separation of data processing logic from signal computation
  • Enhanced code modularity and testability

Changed

• Refined evaluation layer positioning and scope in documentation
  • Clarified relationship between suitability and performance evaluation
  • Updated governance design with evaluation registry patterns
  • Enhanced documentation structure guide

Fixed

• P&L calculation now correctly computes incremental returns instead of cumulative from entry
  • Prevents compounding errors in multi-period backtests
  • Aligns with standard financial performance metrics
• Resolved test suite failures and improved code quality
  • Fixed suitability evaluation test configuration patterns
  • Enhanced error handling in transformation functions
  • Updated type hints to modern Python syntax

Documentation

• Added CONTRIBUTING.md with project scope disclaimers and contribution guidelines
• Added SECURITY.md with security policy and research framework limitations
• Updated evaluation layer documentation for clarity and accuracy