Exponential Smoothing Forecast Calculator


Instructions: You can use this Exponential Smoothing Forecast Calculator for a given times series data set, by providing a set of data and smoothing constant. Also, you can indicate if the data periods are months or not, and you optionally can write your own custom names for the time periods in the form below:

Data (space or comma separated)
Smoothing Constant \(\alpha\) (between 0 and 1)
Initial Forecast (optional)
Monthly Time Periods?
Starting Month:
Custom Period Labels (optional)

Exponential Smoothing Calculator

More about the Exponential Smoothing Forecasts so you can get a better understanding of the outcome that will be provided by this solver. The idea behind Exponential Smoothing for making forecasts consists of estimating the data value of certain period based on the previous data value as well as the previous forecast, so that to attempt to correct for the deviation between the previous actual value and the prediction. The following formula is used to estimate the data value during period \(n\)

\[ \text{Forecast during period n} = F_n = F_{n-1} + \alpha (A_{n-1} - F_{n-1}) \]

The Exponential Smoothing method of forecasting is a commonly used method to make forecasts based on a times series data set. Other common methods are the naive forecast method, the weighted moving averages, the moving averages forecast method, and the linear trend forecasting method, just to mention a few.




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