MESA Adaptive Moving Average (MAMA)

get_mama(quotes, fast_limit=0.5, slow_limit=0.05)

Parameters

name	type	notes
`quotes`	Iterable[Quote]	Iterable of the Quote class or its sub-class. • See here for usage with pandas.DataFrame
`fast_limit`	float, default 0.5	Fast limit threshold. Must be greater than `slowLimit` and less than 1.
`slow_limit`	float, default 0.05	Slow limit threshold. Must be greater than 0.

Historical quotes requirements

You must have at least 50 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

MAMAResults[MAMAResult]

This method returns a time series of all available indicator values for the quotes provided.
MAMAResults is just a list of MAMAResult.
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 5 periods will have None values for Mama since there’s not enough data to calculate.

⚞ Convergence warning: The first 50 periods will have decreasing magnitude, convergence-related precision errors that can be as high as ~5% deviation in indicator values for earlier periods.

MAMAResult

name	type	notes
`date`	datetime	Date
`mama`	float, Optional	MESA adaptive moving average (MAMA)
`fama`	float, Optional	Following adaptive moving average (FAMA)

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 Mama(0.5,0.05)
results = indicators.get_mama(quotes, 0.5,0.05)

About MESA Adaptive Moving Average (MAMA)

Created by John Ehlers, the MAMA indicator is a 5-period adaptive moving average of high/low price. [Discuss] 💬