If a time series X_t is described by an additive model with constant level and no seasonality, 1-step ahead forecasts may be obtained by simple exponential smoothing using the formula
\(\hat{x}_{n+1}\)= αx_n + (1 − α)\(\hat{x}_n\)
where:

• x_n is the observed value at time n,
• \(\hat{x}_n\)​and \(\hat{x}_{n+1}\)are the 1-step ahead forecasts of X_n and X_n+1,
• and α is a smoothing parameter, 0 ≤ α ≤ 1.

The method requires an initial value \(\hat{x}_1\), which is often chosen to be x₁ : \(\hat{x}_1\) = x₁.