Calculating the CMA

The moving average of a value over a period of time helps to smooth the time-series lines and avoid the drastic peaks typical of this seasonal kind of data. The seasonal peaks that occur throughout are included in our analysis. They are part of the data behavior that will appear in the forecast, and they are not outliers. The moving average helps to direct the trend line of the forecast, including these peaks. We will use the distance of the data from the moving average line to determine the seasonal trend of the time series. This information helps to build the forecast curve of the data, taking the seasonal variations of the series into account.

The steps to produce a forecast from the moving average are as follows:

1. Calculating the moving average for the given period of time – for example, taking the moving average of all the quarters of the year.
2. Getting the CMA of your data. This is the middle of the calculating period. This CMA smooths...