A robust forecasting system, based on the combination of two simple moving averages

For series with negligible growth and seasonality, simple moving averages are frequently used to estimate the current level of a process, and the resultant value projected as a forecast for future observations. This paper shows that a linear combination of two simple moving averages can provide an improved estimate of the underlying level of the process. The proposition is demonstrated by simulation, and good combinations are listed. The theory underlying the improvement is developed. The general rules are then illustrated through an application in an inventory situation.