Trading Selection Diversity Validation

소개

This skill provides a robust validation framework for algorithmic trading portfolios to ensure that diversity constraints, such as maximum asset correlation and minimum crypto positions, are strictly enforced rather than silently ignored. By implementing the 'Fail Loudly' pattern, it catches selection logic bugs during development or optimization phases, preventing the deployment of over-correlated or unbalanced portfolios. It is particularly useful for quantitative developers working with trading environments where statistical selection integrity is critical for risk management.

주요 기능

• Automated multi-asset correlation checking for portfolio symbols
• Fail Loudly constraint enforcement using explicit error raising
• Minimum asset class position validation for guaranteed exposure
• Optimization for full-universe scanning by removing arbitrary limits
• Post-selection validation to detect logic overrides or re-sorting bugs
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사용 사례

• Debugging selection pipelines where notebook re-sorting accidentally defeats diversity logic
• Ensuring mandatory crypto or sector-specific exposure in multi-asset strategies
• Preventing over-concentration in highly correlated assets within a quantitative portfolio