Simple Exponential Smoothing

Simple exponential smoothing assumes the data fluctuates around a stationary mean, with no trend or seasonal pattern.

In a simple Exponential Smoothing model, each forecast (smoothed value) is computed as the weighted average of the previous observations, where the weights decrease exponentially depending on the value of smoothing constant α. Values of the smoothing constant, α, near one, put almost all weight on the most recent observations. Values of α near zero allows the distant past observations to have a large influence.