Average True Range (ATR)

get_atr(quotes, lookback_periods=14)

For raw True Range (TR) only, use:

get_tr(quotes) -> TrResults[TrResult]

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 14	Number of periods (`N`) to consider. Must be greater than 1.

Historical quotes requirements

You must have at least N+100 periods of quotes to cover the convergence periods. Since this uses a smoothing technique, we recommend you use at least N+250 data points prior to the intended usage date for better precision.

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

ATRResults[ATRResult]

This method returns a time series of all available indicator values for the quotes provided.
ATRResults is just a list of ATRResult.
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 for ATR since there’s not enough data to calculate.

⚞ Convergence warning: The first N+100 periods will have decreasing magnitude, convergence-related precision errors that can be as high as ~5% deviation in indicator values for earlier periods.

ATRResult

name	type	notes
`date`	datetime	Date
`tr`	float, Optional	True Range for current period
`atr`	float, Optional	Average True Range
`atrp`	float, Optional	Average True Range Percent is `(atr/Close Price)*100`. This normalizes so it can be compared to other stocks.

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 14-period ATR
results = indicators.get_atr(quotes, 14)

About Average True Range (ATR)

Created by J. Welles Wilder, Average True Range is a measure of volatility that captures gaps and limits between periods. [Discuss] 💬