# 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] 💬