How it works
Every earnings event is analyzed through six independent intelligence layers, each scoring 1-10. The weighted composite produces a final score out of 100 with a directional signal and conviction level.
BULLISH
65-100
NEUTRAL
45-64
BEARISH
30-44
AVOID
< 30
Each layer is scored independently on a 1-10 scale, then combined using proprietary weights that reflect the relative predictive power of each signal category. The framework includes automatic adjustments: a Known Headwind Discount reduces the total score when any single layer scores critically low, while a Near-52-Week-Low Snap-Back Amplifier adds points when a beaten-down stock shows strong estimate momentum.
For every ticker scored, we pull up to 3 years of past earnings and cross-reference with actual daily price bars. This reveals how the stock actually reacted in similar past scenarios \u2014 not just whether it beat or missed, but the exact gap at open and full-day move.
Scenario Matching
Finds past quarters with similar EPS estimates and shows how they played out
Price Reaction Data
Actual opening gap and full-day move after each historical earnings report
Pattern Badges
SERIAL BEATER, CONSISTENT, MISS STREAK, BIG MOVER — auto-detected from 12Q of data
AI-Weighted
Historical patterns directly influence the AI scoring model with explicit weighting instructions
Every score is generated from 100+ real-time data points aggregated from institutional-grade sources.
Massive-Benzinga
Earnings data, analyst ratings, news, fundamentals
Finnhub
Company profiles, real-time quotes, insider transactions
Polygon
Options flow, put/call ratios, implied volatility
FRED
GDP, inflation, yield curves, VIX, consumer sentiment
Alpha Vantage
AI sentiment analysis, economic indicators
Claude AI
Analysis engine, pattern recognition, natural language scoring