Compare the error performance of these three forecasting techniques using MAD, MSE, and MAPE: a naive forecast, a two-period moving average, and exponential smoothing with α = .10 for periods 3 through 11, using the data shown in Figure 3.4B.

Question

Compare the error performance of these three forecasting techniques using MAD, MSE, and MAPE: a naive forecast, a two-period moving average, and exponential smoothing with [latex]α= .10[/latex] for periods 3 through 11, using the data shown in Figure 3.4B.

Accepted Answer

		Naive		Two-period MA		Exponential Smoothing
Period, t	Demand	Forecast	Error	Forecast	Error	Forecast	Error
1	42	—	—
2	40	42	-2			42	-2
3	43	40	3	41	2	41.8	1.2
4	40	43	-3	41.5	-1.5	41.92	-1.92
5	41	40	1	41.5	-0.5	41.73	-0.73
6	39	41	-2	40.5	-1.5	41.66	-2.66
7	46	39	7	40	6	41.39	4.61
8	44	46	-2	42.5	1.5	41.85	215
9	45	44	1	45	0	42.07	2.93
10	38	45	-7	44.5	-6.5	42.36	-4.36
11	40	38	2	41.5	-1.5	41.92	-1.92
	MAD		3.11		2.33		2.5
	MSE		16.25		11.44		8.73
	MAPE		7.49%		5.64%		5.98%

If lowest MAD is the criterion, the two-period moving average forecast has the greatest accuracy; if lowest MSE is the criterion, exponential smoothing works best; and if lowest MAPE is the criterion, the two o-period moving average method is again best. Of course, with other data, or with different values of [latex]α[/latex] for exponential smoothing, and different moving averages, the best performers could be different.

Question 3.4: Compare the error performance of these three forecasting tec...

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