# 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] 💬