# Triple Exponential Moving Average (TEMA)

##
**get_tema**(*quotes, lookback_periods*)

## Parameters

name | type | notes |
---|---|---|

`quotes` |
Iterable[Quote] | Iterable(such as list or an object having `__iter__()` ) of the Quote class or its sub-class. • Need help with pandas.DataFrame? |

`lookback_periods` |
int | Number of periods (`N` ) in the moving average. Must be greater than 0. |

### Historical quotes requirements

You must have at least `4×N`

or `3×N+100`

periods of `quotes`

, whichever is more, to cover the warmup periods. Since this uses a smoothing technique, we recommend you use at least `3×N+250`

data points prior to the intended usage date for better precision.

`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

```
TEMAResults[TEMAResult]
```

- This method returns a time series of all available indicator values for the
`quotes`

provided. -
`TEMAResults`

is just a list of`TEMAResult`

. - 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
`3×N-2`

periods will have`None`

values since there’s not enough data to calculate. Also note that we are using the proper weighted variant for TEMA. If you prefer the unweighted raw 3 EMAs value, please use the`Ema3`

output from the TRIX oscillator instead.

Convergence warning: The first`3×N+100`

periods will have decreasing magnitude, convergence-related precision errors that can be as high as ~5% deviation in indicator values for earlier periods.

### TEMAResult

name | type | notes |
---|---|---|

`date` |
datetime | Date |

`tema` |
float, Optional | Triple exponential 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_history_from_feed("SPY")
# calculate 20-period TEMA
results = indicators.get_tema(quotes, 20)
```

## About Triple Exponential Moving Average (TEMA)

Triple exponential moving average of the Close price over a lookback window. Note: TEMA is often confused with the alternative TRIX oscillator. [Discuss]

See related EMA and Double EMA.