MESA Adaptive Moving Average (MAMA)

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


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.



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.


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


See Utilities and Helpers for more information.


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] 💬