How to use the exponential smoothing forecast calculator
Forecast the next value of a series by weighting the latest actual value and the previous forecast. Enter latest actual value, previous forecast, smoothing factor α in the fields above; the next forecast, change from previous forecast are computed instantly and plotted on the chart so you can see how the answer changes.
Common searches this calculator answers include “exponential smoothing”, “simple forecast”, “smoothing forecast next value”, “calculate exponential smoothing forecast”, “find next forecast”.
Formula
Variables
- last — Latest actual value
- prev — Previous forecast
- alpha — Smoothing factor α
Worked example
With latest actual value = 120, previous forecast = 110, smoothing factor α = 0.3, the calculator gives next forecast ≈ 113; change from previous forecast ≈ 3.
Frequently asked questions
What is the exponential smoothing forecast calculator used for?
Forecast the next value of a series by weighting the latest actual value and the previous forecast. It helps with questions such as “exponential smoothing”, “simple forecast”, “smoothing forecast next value”.
What is the formula for the exponential smoothing forecast calculation?
Next forecast = alpha × last+(1-alpha) × prev. Change from previous forecast = [Next forecast]-prev. Here last is latest actual value, prev is previous forecast, alpha is smoothing factor α.
What inputs do I need for the exponential smoothing forecast calculator?
You need latest actual value, previous forecast, smoothing factor α. Each field is pre-filled with a typical example so you can see how the result responds as you edit the numbers.
How do I use the exponential smoothing forecast calculator?
Type values into the input fields. Results and the chart update instantly. Use Reset to restore the example values, Copy results to paste them elsewhere, or Share to copy a link that preserves your inputs.
Is the exponential smoothing forecast result exact?
Calculations use standard formulas and double-precision arithmetic, then display about seven significant figures. Real-world measurements carry uncertainty, so treat results as estimates unless your inputs are exact.