MESA Adaptive Moving Average (MAMA)
get_mama(quotes, fast_limit=0.5, slow_limit=0.05)
||Iterable[Quote]||Iterable(such as list or an object having
• Need help with pandas.DataFrame?
||float, default 0.5||Fast limit threshold. Must be greater than
||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.
- This method returns a time series of all available indicator values for the
MAMAResultsis just a list of
- 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
5periods will have
Mamasince there’s not enough data to calculate.
Convergence warning: The first
50periods will have decreasing magnitude, convergence-related precision errors that can be as high as ~5% deviation in indicator values for earlier periods.
||float, Optional||MESA adaptive moving average (MAMA)|
||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_history_from_feed("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]