How It Works
PatternRank uses proprietary quantitative models to analyze historical market behavior and generate ranked pattern outputs.
Models are validated across 10+ years of historical data to identify statistically significant momentum shifts.
Models are validated across 10+ years of historical data to identify statistically significant momentum shifts.
1. Data Collection
Historical market data is collected for liquid US equities traded on NYSE and NASDAQ. The pipeline ensures clean, consistent inputs spanning 10+ years of market history.
2. Pattern Recognition
Proprietary quantitative models analyze historical patterns to identify statistically significant relationships. Models are validated using rigorous 5-year out-of-sample backtesting.
3. Ranking Generation
Models produce ranked pattern outputs based on confidence scores and prevailing market conditions. Each ranking includes supporting metrics and contextual information for evaluation.
4. Daily Updates
Rankings are refreshed daily after market close. Filter by model type, confidence thresholds, and other criteria to surface rankings relevant to your research needs.
Pattern Types
7D Momentum Rankings
Short-term momentum behavior ranked over a 7-day horizon using proprietary quantitative pattern analysis. Validated across 5+ years of historical data.
- ✓7-day momentum ranking
- ✓Proprietary pattern matching
- ✓Daily ranking updates
- ✓Confidence-ranked results
ETB High-Quality Rankings
Liquidity-filtered rankings focused on easy-to-borrow US equities commonly tracked by professional desks. Designed to emphasize structural quality over volume.
- ✓Institutional-grade liquidity filtering
- ✓Easy-to-borrow universe
- ✓Quality-focused pattern rankings
- ✓Reduced structural noise
Important: Educational Purpose Only
PatternRank is an educational analytics platform. All outputs are provided for informational and research purposes only and do not constitute investment advice or recommendations. Past performance does not guarantee future results. Users are solely responsible for their own decisions. Please review the full disclaimer before using the platform.
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