Seasonality - Multiple Timeframes

📊 Seasonality - Multiple Timeframes

🎯 What This Indicator Does
This advanced seasonality indicator analyzes historical price patterns across multiple configurable timeframes and projects future seasonal behavior based on statistical averages. Unlike simple seasonal overlays, this indicator provides gap-resistant architecture specifically designed for commodity futures markets and other instruments with contract rolls.

🔧 Key Features
Multiple Timeframe Analysis

• Three Independent Timeframes: Configure separate historical periods (e.g., 5Y, 10Y, 15Y) for comprehensive analysis
  
• Individual Control: Enable/disable historical lines and projections independently for each timeframe
  
• Color Customization: Distinct colors for historical patterns and future projections
  

Advanced Architecture

• Gap-Resistant Design: Handles missing data and contract rolls in futures markets seamlessly
  
• Calendar-Day Normalization: Uses 365-day calendar system for accurate seasonal comparisons
  
• Outlier Filtering: Automatically excludes extreme price movements (>10% daily changes)
  
• Roll Detection: Identifies and excludes contract roll periods to maintain data integrity
  

Real-Time Projections

• Forward-Looking Analysis: Projects seasonal patterns into the future based on remaining calendar days
  
• Configurable Projection Length: Adjust forecast period from 10 to 150 bars
  
• Data Interpolation: Optional gap-filling for smoother seasonal curves
  

📈 How It Works
Data Collection Process
The indicator collects daily price returns for each calendar day (1-365) over your specified historical periods. For each timeframe, it:

1. Calculates daily returns while excluding roll periods and outliers
   
2. Accumulates these returns by calendar day across multiple years
   
3. Computes average seasonal performance from January 1st to current date
   
4. Projects remaining seasonal pattern based on historical averages
   

🎯 Designed For
Primary Use Cases

• Commodity Futures Trading: Corn, soybeans, coffee, sugar, cocoa, natural gas, crude oil
  
• Seasonal Strategy Development: Identify optimal entry/exit timing based on historical patterns
  
• Pattern Validation: Confirm seasonal tendencies across different time horizons
  
• Market Timing: Compare current performance against historical seasonal expectations
  

Trading Applications

• Trend Confirmation: Use multiple timeframes to validate seasonal direction
  
• Risk Assessment: Understand seasonal volatility patterns
  
• Position Sizing: Adjust exposure based on seasonal performance consistency
  
• Calendar Spread Analysis: Identify seasonal price relationships
  

⚙️ Configuration Guide
Timeframe Setup
Configure each timeframe independently:

• Years: Set historical lookback period (1-20 years)
  
• Historical Display: Show/hide the seasonal pattern line
  
• Projection Display: Enable/disable future seasonal projection
  
• Colors: Customize line colors for visual clarity
  

Display Options

• Current YTD: Compare actual year-to-date performance
  
• Info Table: Detailed performance comparison across timeframes
  
• Projection Bars: Control forward-looking projection length
  
• Fill Gaps: Interpolate missing data points for smoother curves
  

Debug Features
Enable debug mode to validate data quality:

• Data Point Counts: Verify sufficient historical data per calendar day
  
• Roll Detection Status: Monitor contract roll identification
  
• Empty Days Analysis: Identify potential data gaps
  
• Calculation Verification: Debug seasonal price computations
  

📊 Interpretation Guidelines
Strong Seasonal Signal

• All three timeframes align in the same direction
  
• Current price follows seasonal expectation
  
• Sufficient data points (>3 years minimum per timeframe)
  

Seasonal Divergence

• Different timeframes show conflicting patterns
  
• Recent years deviate from longer-term averages
  
• Current price significantly above/below seasonal expectation
  

Data Quality Indicators

• Green Status: Adequate data across all calendar days
  
• Red Warnings: Insufficient data or excessive gaps
  
• Roll Detection: Proper handling of futures contract changes
  

⚠️ Important Considerations
Data Requirements

• Minimum History: At least 3-5 years for reliable seasonal analysis
  
• Continuous Data: Best results with daily continuous contract data
  
• Market Hours: Designed for traditional market session data
  

Limitations

• Past Performance: Historical patterns don't guarantee future results
  
• Market Changes: Structural shifts can alter traditional seasonal patterns
  
• External Factors: Weather, geopolitics, and policy changes affect seasonal behavior
  
• Contract Rolls: Some data gaps may occur during futures roll periods
  

🔍 Technical Specifications
Performance Optimizations

• Array Management: Efficient data storage using Pine Script arrays
  
• Gap Handling: Robust price calculation with fallback mechanisms
  
• Memory Usage: Optimized for large historical datasets (max_bars_back = 4000)
  
• Real-Time Updates: Live calculation updates as new data arrives
  

Calculation Accuracy

• Outlier Filtering: Excludes daily moves >10% to prevent data distortion
  
• Roll Detection: 8% threshold for identifying contract changes
  
• Data Validation: Multiple checks for price continuity and data integrity
  

🚀 Getting Started

1. Add to Chart: Apply indicator to your desired futures contract or commodity
   
2. Configure Timeframes: Set historical periods (recommend 5Y, 10Y, 15Y)
   
3. Enable Projections: Turn on future seasonal projections for forward guidance
   
4. Validate Data: Use debug mode initially to ensure sufficient historical data
   
5. Interpret Patterns: Compare current price action against seasonal expectations
   

💡 Pro Tips

• Multiple Confirmations: Use all three timeframes for stronger signal validation
  
• Combine with Technicals: Integrate seasonal analysis with technical indicators
  
• Monitor Divergences: Pay attention when current price deviates from seasonal pattern
  
• Adjust for Volatility: Consider seasonal volatility patterns for position sizing
  
• Regular Updates: Recalibrate settings annually to maintain relevance
  

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This indicator represents years of development focused on commodity market seasonality. It provides institutional-grade seasonal analysis previously available only to professional trading firms.