factor-research

What problem does it solve?

This Skill streamlines the process of conducting quantitative factor research, ensuring reproducible workflows, explicit controls, and deployable outputs for exposure decomposition and regime-dependent premia behavior.

Core Features & Use Cases

• Hypothesis to Production: Guides users through defining hypotheses, building features, estimating signal, stress-testing performance, and promoting factors only when robust.
• Reproducible Diagnostics: Utilizes a dedicated script to generate detailed diagnostics, including signal monotonicity, capacity stress, regime dependency, and cost-adjusted performance.
• Risk Controls: Implements essential risk controls such as exposure ceilings, concentration caps, and deactivation triggers.
• Use Case: A quantitative researcher needs to develop a new alpha factor. They can use this Skill to systematically define the factor, test its performance under various market conditions, and ensure it meets strict risk and cost criteria before deployment.

Quick Start

Run python scripts/factor_research_diagnostics.py input.csv --output diagnostics.json to generate factor research diagnostics.