Bollinger Bands®

get_bollinger_bands(quotes, lookback_periods=20, standard_deviations=2)

Parameters

name	type	notes
`quotes`	Iterable[Quote]	Iterable of the Quote class or its sub-class. • See here for usage with pandas.DataFrame
`lookback_periods`	int, default 20	Number of periods (`N`) for the center line moving average. Must be greater than 1 to calculate; however we suggest a larger period for statistically appropriate sample size.
`standard_deviations`	int, default 2	Width of bands. Standard deviations (`D`) from the moving average. Must be greater than 0.

Historical quotes requirements

You must have at least N periods of quotes to cover the warmup periods.

quotes is an Iterable[Quote] collection of historical price quotes. It should have a consistent frequency (day, hour, minute, etc). See the Guide for more information.

Returns

BollingerBandsResults[BollingerBandsResult]

This method returns a time series of all available indicator values for the quotes provided.
BollingerBandsResults is just a list of BollingerBandsResult.
It always returns the same number of elements as there are in the historical quotes.
It does not return a single incremental indicator value.
The first N-1 periods will have None values since there’s not enough data to calculate.

BollingerBandsResult

name	type	notes
`date`	datetime	Date
`sma`	float, Optional	Simple moving average (SMA) of Close price (center line)
`upper_band`	float, Optional	Upper line is `D` standard deviations above the SMA
`lower_band`	float, Optional	Lower line is `D` standard deviations below the SMA
`percent_b`	float, Optional	`%B` is the location within the bands. `(Price-lower_band)/(upper_band-lower_band)`
`z_score`	float, Optional	Z-Score of current Close price (number of standard deviations from mean)
`width`	float, Optional	Width as percent of SMA price. `(upper_band-lower_band)/sma`

Utilities

See Utilities and Helpers for more information.

Example

from stock_indicators import indicators

# This method is NOT a part of the library.
quotes = get_historical_quotes("SPY")

# calculate BollingerBands(20, 2)
results = indicators.get_bollinger_bands(quotes, 20, 2)

About Bollinger Bands®

Created by John Bollinger, Bollinger Bands depict volatility as standard deviation boundary lines from a moving average of Close price. Bollinger Bands® is a registered trademark of John A. Bollinger. [Discuss] 💬