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 ofALMAResult
.- 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 haveNone
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] 💬