zlma
Calculate the zero lag exponential moving average (ZLEMA).
Created by John Ehlers and Ric Way. The idea is do a regular exponential moving average (EMA) calculation but on a de-lagged data instead of doing it on the regular data. Data is de-lagged by removing the data from "lag" days ago thus removing (or attempting to) the cumulative effect of the moving average.
Example
from openbb import obb
stock_data = obb.equity.price.historical(symbol='TSLA', start_date='2023-01-01', provider='fmp')
zlma_data = obb.technical.zlma(data=stock_data.results, target='close', length=50, offset=0)
Parameters
- standard
| Name | Type | Description | Default | Optional |
|---|---|---|---|---|
| data | List[Data] | List of data to be used for the calculation. | False | |
| target | str | Target column name. | close | False |
| index | str | Index column name to use with data, by default "date". | date | False |
| length | int | Number of periods to be used for the calculation, by default 50. | 50 | False |
| offset | int | Offset to be used for the calculation, by default 0. | 0 | False |
Returns
OBBject
results : List[Data]
The calculated data.