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Forecasting

Forecasting seasonal components

3.1 Two approaches to obtaining seasonal variations

The multiplicative model The additive model

S = Y/T S = Y – T

Example continued Example continued

Q1 Q 2 Q3 Q4 Q1 Q 2 Q3 Q4

20X1 – – 1.97 0.75 20X1 – – +29 –8

20X2 0.51 0.87 1.87 0.76 20X2 –16 –4 +28 –8

20X3 0.52 0.88 1.83 0.77 20X3 –16 –4 +28 –8

20X4 0.53 0.85 – – 20X4 –17 –5 – –

Average 0.52 0.87 1.89 0.76 Average –16 –4 28 –8

Adjusted 0.51 0.86 1.88 0.75 Adjusted –16 –4 28 –8

Note: Seasonal variations are adjusted Note: Seasonal variations are adjusted
so they add up to 4. so they add up to 0.

 usually considered the better  assumes that the seasonal
variations are a constant amount,
 ensures that seasonal variations are and thus would constitute a
assumed to be a constant diminishing part of, say, an
proportion of the sales. increasing sales trend.

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