Seasonality Scanner

Seasonality analysis detects recurring calendar-driven price behaviors by computing win rates and pattern strength across 5, 10, or 20 years of history. It compares monthly, weekly, and hourly intervals to highlight best and worst periods with statistical confidence scoring.

Intraday seasonality analysis applies to forex sessions by evaluating hourly price tendencies across multiple years. It computes historical win rates for specific sessions and generates confidence-scored directions to optimize entry and exit timing.

Seasonal trading signals are generated by computing multi-year win rates to produce entry directions with confidence scores. Risk and position sizing are then adjusted based on the confidence level, and optimal seasonal exit timing is suggested.

Pattern detection estimates typical seasonal ranges and flags anomalies when the current year deviates from historical averages. It surfaces strong versus weak seasonal periods to help identify when calendar effects may not hold.

Monthly seasonality analysis compares multi-year SPY history to identify the strongest buy and sell months. It computes win rates and pattern strength across the specified lookback period, returning results with confidence scores.

Calendar effects rely on historical averages and may not predict future price action during anomalous years. Confidence scoring helps gauge pattern strength, but seasonal signals should supplement, not replace, broader risk management strategies.