Arnaud Legoux Moving Average (ALMA)

get_alma(quotes, lookback_periods=9, offset=0.85, sigma=6)

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 9	Number of periods (`N`) in the moving average. Must be greater than 1, but is typically in the 5-20 range.
`offset`	float, default 0.85	Adjusts smoothness versus responsiveness on a scale from 0 to 1; where 1 is max responsiveness.
`sigma`	float, default 6	Defines the width of the Gaussian normal distribution. 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

ALMAResults[ALMAResult]

This method returns a time series of all available indicator values for the quotes provided.
ALMAResults is just a list of ALMAResult.
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.

ALMAResult

name	type	notes
`date`	datetime	Date
`alma`	float, Optional	Arnaud Legoux 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 Alma
results = indicators.get_alma(quotes, 10, 0.5, 6)

About Arnaud Legoux Moving Average (ALMA)

Created by Arnaud Legoux and Dimitrios Kouzis-Loukas, ALMA is a Gaussian distribution weighted moving average of Close price over a lookback window. [Discuss] 💬