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calculate_bollinger_bands

IndicatorsBBIndicator

INSTALLATION

$python -c "exec(open('calculate_bollinger_bands.py').read())"

#or paste directly into your Claude Code terminal

[ ABOUT ]

Computes upper band, middle band (SMA), and lower band for the most recent bar using a rolling window of configurable period (default 20) and standard deviation multiplier (default 2). Uses Python's built-in `statistics.stdev` to avoid external dependencies, returning a three-tuple `(upper, middle, lower)` rounded to 4 decimal places.

Bollinger Bands are a volatility measure as much as a momentum indicator — band width expands during high-volatility periods and contracts during low-volatility consolidations. A squeeze (narrow bands) often precedes a significant directional move. Combining band width tracking with `find_breakout_levels` can identify squeeze-and-breakout setups programmatically.

[ USAGE EXAMPLE ]

example.py

upper, mid, lower = bollinger_bands(close, period=20, mult=2)
if close[-1] < lower:
    print("Price below lower band — oversold zone")

[ FULL CODE ]

calculate_bollinger_bands.py

def bollinger_bands(close, period=20, mult=2): import statistics as s sma = [sum(close[i:i+period])/period for i in range(len(close)-period+1)] std = [s.stdev(close[i:i+period]) for i in range(len(close)-period+1)] return sma[-1]+mult*std[-1], sma[-1], sma[-1]-mult*std[-1]

[ METADATA ]

CategoryIndicators

ComplexityBeginner

LanguagePython 3.10+

TagsBB, Indicator

[ ASK CLAUDE ]

Ask AI about this skill before installing it.

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