Adjusted Exponential Smoothing

Adjusted Exponential Smoothing

Adjusted exponential smoothing models have all the features of simple exponential smoothing models,

plus they project into the future (for example, to time period t + 1) by adding a trend correction

increment, Tt, to the current period smoothed average, Ft

Ft+1= FtTt

The components of a trend-adjusted forecast that utilizes a second smoothing coefficient β. The βvalue determines the extent to which the trend adjustment relies on the latest difference in forecast amounts (     F t -F t-1) versus the previous trend Tt–1

A low βgives more smoothing of the trend and may be useful if the trend is not well-established. A high βwill emphasize the latest trend and be more responsive to recent changes in trend. The initial trend adjustment Tt–1 is sometimes assumed to be zero.