Machine learning-powered earnings prediction simulation analyzing 200+ fundamental factors, sentiment data, and historical patterns to predict earnings surprises with an 82% simulated accuracy. Features real-time-style earnings calendar, surprise magnitude prediction, and automated trade signal prototypes.
Reuse the scenario engine, synthetic data seeds, and hooks that power this experience.
Inference gradients over 200+ factors with surprise probability curves and trade signals.
SEC EDGAR: Quarterly reports filtered through the feature engineering pipeline.
useRealTimeData: Hydrates earnings calendar widgets with live ticker metadata.
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