Ultimate Oscillator

get_ultimate(quotes, short_periods=7, middle_periods=14, long_periods=28)

Parameters

name	type	notes
`quotes`	Iterable[Quote]	Iterable of the Quote class or its sub-class. • See here for usage with pandas.DataFrame
`short_periods`	int, default 7	Number of periods (`S`) in the short lookback. Must be greater than 0.
`middle_periods`	int, default 14	Number of periods (`M`) in the middle lookback. Must be greater than `S`.
`long_periods`	int, default 28	Number of periods (`L`) in the long lookback. Must be greater than `M`.

Historical quotes requirements

You must have at least L+1 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.

Return

UltimateResults[UltimateResult]

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

UltimateResult

name	type	notes
`date`	datetime	Date
`ultimate`	float, Optional	Simple moving average

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 20-period Ultimate
results = indicators.get_ultimate(quotes, 7, 14, 28)

About Ultimate Oscillator

Created by Larry Williams, the Ultimate Oscillator uses several lookback periods to weigh buying power against true range price to produce on oversold / overbought oscillator. [Discuss] 💬