Exponential smoothing

Refers to a class of method in which the value of a time series at some point in time ese determined by past values of the time series. The importance of the past values declines exponentially as they age. These methods is similar to moving averages except that, with exponential smoothing, past values have different weights and all past values contribute in some way to the forecast. Exponential smoothing methods are useful in short-term forecasting. They can often produce food forecasts for one or two periods into the future. The advantage of exponential smoothing is in its relatively simple application for quickly producing forecasts of a large number of variables. Exponential smoothing should not be used for medium or long term forecasts. Such forecasts depend heavily on the most recent data point and they tend to perform well in the very short term and very poorly in the long term.