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Forecasting

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Exercise 9.1
Moving Expenses:
Fiscal Year Expenses
20X2 $5,500,000
20X3 $6,000,000
20X4 $6,750,000
20X2-4 $18,250,000
20X5 $18,250,000/3 = $6,083,333
Weighted Expenses:
Fiscal Year Expenses Weight Weighted Score
20X2 $5,500,000 x 1 = $5,500,000
20X3 $6,000,000 x 2 = $12,000,000
20X4 $6,750,000 x 3 = $20,250,000 6 $37,750,000
20X5 $37,750,000/6 = $6,291,667
Exponential Smoothing:
Given
The last forecasting (LF) = $6,300,000, the last data (LD) = $6,750,000, a = 0.95
I have used the 0.95 alpha because I believe the new forecast will be based on the last data.
NF = LF + a (LD – LF)
NF= $6,300,000 + 0.95 ($6,750,000 - $6,300,000)
NF = $6,300,000 + 0.95 ($450,000)
NF = $6,300,000 + $427,500
NF = $6,727,500
20X5 = $6,727,500
Time Series Regression:
Computer Output
Constant = 4625000
Variable = 500000
R-Square = 0.95
Y = A + BX
Y = $462,500 + $500,000X
Y = $462,500 + $500,000 (5)
Y = $462,500 + $2,500,000
Y = $7,125,000
20X5 = $7,125,000
I choose to use the time series regression because it reveals that the expenses will continue to grow on 20X5 and the years after 20X5.
Exercise 9.3
Moving Expenses:
Fiscal Year Expenses
20X2 $14,250,000
20X3 $14,000,000
20X4 $13,500,000
20X2-4 $41,750,000
20X5 $41,750,000/3 = $13,916,667
Weighted Averages:
Fiscal Year Expenses Weight Weighted Score
20X2 $14,250,000 x 1 = $14,250,000
20X3 $14,000,000 x 2 = $28,000,000
20X4 $13,500,000 x 3 = $40,500,000 6 $82,750,000
20X5 $82,750,000/6 = $13,791,667
Exponential Smoothing:
Given
The last forecasting (LF) = $13,000,000, the last data (LD) = $13,500,000, a = 0.95
I have used the 0.95 because I believe the new forecast will be based on the last data.
NF = LF + a (LD – LF)
NF = $13,000,000 + 0.95 ($13,500,000 - $13,000,000)
NF = $13,000,000 + 0.95 ($500,000)
NF = $13,000,000 + $475,000
NF = $13,475,000
20X5 = $13,475,000
Time Series Regression:
Computer Output
Constant = 15750000
Variable = 750000
R-Square = 0.95
Y = A + BX
Y = $15,750,000 + $750,000X
Y = $15,750,000 + $750,000 (5)
Y = $15,750,000 + $3,375,000
Y = $19,500,000
20X5 = $19,500,000
I choose to use the time series regression because it reveals that the expenses will continue to grow on 20X5 and the years after 20X5.

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