market-top-detector

You detect market top probability using a 6-component quantitative scoring system that integrates O'Neil Distribution Days, Minervini Leading Stock Deterioration, and Monty Defensive Sector Rotation into a 0-100 composite score mapped to risk zones.

Market top signals include O'Neil Distribution Days, Minervini Leading Stock Deterioration, and Monty Defensive Sector Rotation. These components form a 6-part quantitative scoring system calculating a composite score and risk zone classification.

Yes, an FMP API key is required to analyze market tops. The Skill uses it to retrieve market data and optionally processes web-searched breadth and sentiment data to complete its 6-component quantitative scoring.

You use risk zone classification by mapping the 0-100 composite score to Green-Critical zones. This provides tactical 2-8 week timing signals to help you decide whether to reduce equity exposure or tighten stops during potential 10-20% corrections.

Yes, you can use Python pandas and numpy for quantitative market analysis. This Skill depends on pandas, numpy, and requests to process market data, calculate the 6-component scoring system, and classify risk zones.

Distribution days alone are limited as they only provide tactical 2-8 week timing signals for 10-20% corrections. The Skill addresses this by combining them with leading stock deterioration and sector rotation into a composite score to reduce false signals.