Ma13 - Q uantitative Forecasting Methods (Exponential S...

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Quantitative Forecasting Methods (Exponential Smoothing) We will talk about two kinds of exponential smoothing: simple exponential smoothing and exponential smoothing with trend adjustment. The forecast this time (Ft) is equal to the forecast last time (Ft-1) plus some weight (alpha) times the difference between what actually happened last time (At-1) and what we forecasted last time (Ft-1). It basically takes into account the deviation in our last forecast by applying some weight. Note that, by definition, this formula encompasses all past data, not just the data from the previous period. That is, all past data are incorporated into your current forecast. Exponential smoothing is really nothing more than an advanced form of the weighted moving average approach. The weights decline exponentially; with the most recent data being weighted the most. The weights sum up to one. Exponential smoothing incorporates all past data, but it really only requires two values to make a forecast: the last
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Ma13 - Q uantitative Forecasting Methods (Exponential S...

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