Awesome Oscillator (AO)

get_awesome(quotes, fast_periods=5, slow_periods=34)

Parameters

name	type	notes
`quotes`	Iterable[Quote]	Iterable of the Quote class or its sub-class. • See here for usage with pandas.DataFrame
`fast_periods`	int, default 5	Number of periods (`F`) for the faster moving average. Must be greater than 0.
`slow_periods`	int, default 34	Number of periods (`S`) for the slower moving average. Must be greater than `fast_periods`.

Historical quotes requirements

You must have at least S 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

AwesomeResults[AwesomeResult]

This method returns a time series of all available indicator values for the quotes provided.
AwesomeResults is just a list of AwesomeResult.
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 period S-1 periods will have None values since there’s not enough data to calculate.

AwesomeResult

name	type	notes
`date`	datetime	Date
`oscillator`	float, Optional	Awesome Oscillator
`normalized`	float, Optional	`100 × oscillator ÷ (median price)`

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
results = indicators.get_awesome(quotes, 5, 34)

About Awesome Oscillator (AO)

Created by Bill Williams, the Awesome Oscillator (aka Super AO) is a measure of the gap between a fast and slow period modified moving average. [Discuss] 💬