Parabolic SAR

get_parabolic_sar(quotes, acceleration_step=0.02, max_acceleration_factor=0.2)

More overloaded interfaces

get_parabolic_sar(quotes, acceleration_step, max_acceleration_factor, initial_factor)

Parameters

name	type	notes
`quotes`	Iterable[Quote]	Iterable of the Quote class or its sub-class. • See here for usage with pandas.DataFrame
`acceleration_step`	float, default 0.02	Incremental step size for the Acceleration Factor. Must be greater than 0.
`max_acceleration_factor`	float, default 0.2	Maximum factor limit. Must be greater than `acceleration_step`.
`initial_factor`	float	Initial Acceleration Factor. Must be greater than 0 and not larger than `max_acceleration_factor`. Default is `acceleration_step`.

Historical quotes requirements

You must have at least two historical quotes to cover the warmup periods; however, we recommend at least 100 data points. Initial Parabolic SAR values prior to the first reversal are not accurate and are excluded from the results. Therefore, provide sufficient quotes to capture prior trend reversals, before your intended usage period.

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.

Return

ParabolicSARResults[ParabolicSARResult]

This method returns a time series of all available indicator values for the quotes provided.
ParabolicSARResults is just a list of ParabolicSARResult.
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 trend will have None values since it is not accurate and based on an initial guess.

ParabolicSARResult

name	type	notes
`date`	datetime	Date
`sar`	float, Optional	Stop and Reverse value
`is_reversal`	bool, Optional	Indicates a trend reversal

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 ParabolicSar(0.02,0.2)
results = indicators.get_parabolic_sar(quotes, 0.02, 0.2)

About Parabolic SAR

Created by J. Welles Wilder, Parabolic SAR (stop and reverse) is a price-time based indicator used to determine trend direction and reversals. [Discuss] 💬