First order exponential smoothing or simple exponential smoothing is suitable with constant variance and no seasonality. The approach is usually recommended to make short-term forecast. Chapter 2, Understanding Time Series data, has introduced the naïve method for the forecasting where prediction in horizon h is defined as value of t (or the last observation):
xt+h = xt
The approach is extended by simple moving average, which extends the naïve approach using the mean of multiple historical points:
The approach assumes equal weight to all historical observations, as shown in the following figure:
Figure 3.4: ...
