This function returns a confidence interval for the forecast value at the specified target date. Using confidence interval can help grasp the accuracy of the predicted model. A smaller interval would imply more confidence in the prediction for this specific point.
=FORECAST.ETS.CONFINT(target_date,values,timeline,[confidence_level],[seasonality],[data_completion],[aggregation])
The function has the following arguments:
Argument 
Description 


target_date 
[Required] is a date for which you want to predict a new value. Must be after the last date in the timeline.  
values  [Required] is a range of the historical values for which you want to predict a new point.  
timeline 
[Required] is a range of date/time values that correspond to the historical values. The timeline range must be of the same size as the values range. Date/time values must have a constant step between them. 

confidence_level 
[Optional] is a numeric value between 0 and 1 (exclusive) that specifies the confidence level for the calculated confidence interval. If it is omitted, the default value of 0.95 is used. 

seasonality 
[Optional] is a numeric value that specifies which method should be used to detect the seasonality. The possible values are listed in the table below.


data_completion 
[Optional] is a numeric value that specifies how to process the missing data points in the timeline data range. The possible values are listed below.


aggregation 
[Optional] is a numeric value that specifies which function should be used to aggregate identical time values in the timeline data range. The possible values are listed below.

A confidence interval of 95% means that 95% of future points are expected to fall within this radius from the result FORECAST.ETS forecasted (with normal distribution).
Returns a specified statistical value relating to a time series.
This function is available in product version 16.0 or later.