Scanner Outputs
Automated data observation across market instruments. The scanner system processes structured data feeds and produces quantitative observations for research purposes.
What the Scanner Does
The scanner is an automated data observation system that continuously monitors a defined universe of instruments. It applies statistical filters, anomaly detection models, and pattern recognition algorithms to produce structured research outputs. The system operates on a rules-based framework with no discretionary intervention.
Filtered Data Sets
Instrument-level data filtered through configurable quantitative criteria. Outputs include statistical summaries and structured observations across multiple timeframes.
Statistical Anomalies
Automated detection of statistically significant deviations from baseline models. Each anomaly record includes confidence intervals, z-scores, and contextual data points.
Pattern Observations
Systematic identification of recurring structural patterns in time series data. Observations are categorized by pattern type, duration, and statistical reliability.
Output Frequency
DAILY Published after market close. Includes instrument-level observations, anomaly flags, and updated statistical summaries for the trading session.
WEEKLY Aggregated reports covering cross-instrument patterns, statistical distribution changes, and model performance metrics over the trailing five-session window.
Sample Output Format
Scanner outputs are delivered as structured data records. Each record contains the following fields:
| Instrument | Observation Type | Timestamp | Data Points |
|---|---|---|---|
| AAPL | Statistical Anomaly | 2026-02-14 16:00 UTC | z=2.31, vol_ratio=1.47, n=252 |
| TSLA | Pattern Observation | 2026-02-14 16:00 UTC | pattern=mean_rev, duration=5d, p=0.03 |
| SPY | Filtered Data Set | 2026-02-14 16:00 UTC | rank=3, score=0.82, sector=broad |