The Holt‐Winters Forecasting Procedure

Summary The Holt‐Winters forecasting procedure is a simple widely used projection method which can cope with trend and seasonal variation. However, empirical studies have tended to show that the method is not as accurate on average as the more complicated Box‐Jenkins procedure. This paper points out that these empirical studies have used the automatic version of the method, whereas a non‐automatic version is also possible in which subjective judgement is employed, for example, to choose the correct model for seasonality. The paper re‐analyses seven series from the Newbold‐Granger study for which Box‐Jenkins forecasts were reported to be much superior to the (automatic) Holt‐Winters forecasts. The series do not appear to have any common properties, but it is shown that the automatic Holt‐Winters forecasts can often be improved by subjective modifications. It is argued that a fairer comparison would be that between Box‐Jenkins and a non‐automatic version of Holt‐Winters. Some general recommendations are made concerning the choice of a univariate forecasting procedure. The paper also makes suggestions regarding the implementation of the Holt‐Winters procedure, including a choice of starting values.