OPEN-SOURCE SCRIPT

Bitcoin Monthly Seasonality [Alpha Extract]

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The Bitcoin Monthly Seasonality indicator analyzes historical Bitcoin price performance across different months of the year, enabling traders to identify seasonal patterns and potential trading opportunities. This tool helps traders:
  • Visualize which months historically perform best and worst for Bitcoin.
  • Track average returns and win rates for each month of the year.
  • Identify seasonal patterns to enhance trading strategies.
  • Compare cumulative or individual monthly performance.

🔶 CALCULATION

The indicator processes historical Bitcoin price data to calculate monthly performance metrics

Monthly Return Calculation

Inputs:
  • Monthly open and close prices.
  • User-defined lookback period (1-15 years).
  • Return Types:
  • Percentage: (monthEndPrice / monthStartPrice - 1) × 100
  • Price: monthEndPrice - monthStartPrice

Statistical Measures
  • Monthly Averages: ◦ Average return for each month calculated from historical data.
  • Win Rate: ◦ Percentage of positive returns for each month.
  • Best/Worst Detection: ◦ Identifies months with highest and lowest average returns.

Cumulative Option
  • Standard View: Shows discrete monthly performance.
  • Cumulative View: Shows compounding effect of consecutive months.

Example Calculation (Pine Script):

Pine Script®
monthReturn = returnType == "Percentage" ? (monthEndPrice / monthStartPrice - 1) * 100 : monthEndPrice - monthStartPrice calcWinRate(arr) => winCount = 0 totalCount = array.size(arr) if totalCount > 0 for i = 0 to totalCount - 1 if array.get(arr, i) > 0 winCount += 1 (winCount / totalCount) * 100 else 0.0


🔶 DETAILS

Visual Features
  • Monthly Performance Bars: ◦ Color-coded bars (teal for positive, red for negative returns). ◦ Special highlighting for best (yellow) and worst (fuchsia) months.
  • Optional Trend Line: ◦ Shows continuous performance across months.
  • Monthly Axis Labels: ◦ Clear month names for easy reference.
  • Statistics Table: ◦ Comprehensive view of monthly performance metrics. ◦ Color-coded rows based on performance.

Interpretation

  • Strong Positive Months: Historically bullish periods for Bitcoin.
  • Strong Negative Months: Historically bearish periods for Bitcoin.
  • Win Rate Analysis: Higher win rates indicate more consistently positive months.
  • Pattern Recognition: Identify recurring seasonal patterns across years.
  • Best/Worst Identification: Quickly spot the historically strongest and weakest months.

🔶 EXAMPLES

The indicator helps identify key seasonal patterns
  • Bullish Seasons: Visualize historically strong months where Bitcoin tends to perform well, allowing traders to align long positions with favorable seasonality.
  • Bearish Seasons: Identify historically weak months where Bitcoin tends to underperform, helping traders avoid unfavorable periods or consider short positions.
  • Seasonal Strategy Development: Create trading strategies that capitalize on recurring monthly patterns, such as entering positions in historically strong months and reducing exposure during weak months.
  • Year-to-Year Comparison: Assess how current year performance compares to historical seasonal patterns to identify anomalies or confirmation of trends.


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🔶 SETTINGS

Customization Options
  • Lookback Period: Adjust the number of years (1-15) used for historical analysis.
  • Return Type: Choose between percentage returns or absolute price changes.
  • Cumulative Option: Toggle between discrete monthly performance or cumulative effect.
  • Visual Style Options: Bar Display: Enable/disable and customize colors for positive/negative bars, Line Display: Enable/disable and customize colors for trend line, Axes Display: Show/hide reference axes.
  • Visual Enhancement: Best/Worst Month Highlighting: Toggle special highlighting of extreme months, Custom highlight colors for best and worst performing months.

The Bitcoin Monthly Seasonality indicator provides traders with valuable insights into Bitcoin's historical performance patterns throughout the year, helping to identify potentially favorable and unfavorable trading periods based on seasonal tendencies.

Penafian

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