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A company uses a multiplicative time series model to forecast sales. The trend in sales is linear and is described by the following equation:
Trend = 400 + 10 T
Where T = 1 denotes the first quarter of 20X0
T = 2 denotes the second quarter of 20X0 etc.The average seasonal variations are as follows:
Quarter 1 2 3 4
% Variation -30 +40 +10 -20What is the sales forecast for Quarter 3 of 20X1?
480 units
423 units
517 units
3,157 units
Correct Answer
517 unitsT = 7 (4 quarters in 20X0 plus 3 quarters in 20X1)
Variation for quarter 3 = + 10%Sales forecast = 517 units ((400 + (10 x 7)) x 1.1)
Sir John,
I do not understand why they did (10 x 7)) x 1.1)
I thought it suppose to be (10 x 7) x 0.1
Sir you had told me using the additive model = 0
and multiplicative model = 4can you please clarify the multiplicative model . I am getting 0 when I add all seasonal variation up, I’m not getting 4
Where did you find this question? Because they way it is presented is very poor in that the seasonal variations they have given are more sensibly using the additive model rather than the multiplicative model (which is why they add up to zero).
With the multiplicative model, they should really be presented as 0.70 (a fall of 30% means it is 70% of the trend); 1.4 (an increase of 40% means it is 1.4 times the trend); 1.10 and 0.80.
Now the do add up to 4, and the rest of the answer should now make sense 🙂
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