Using exponential smoothing with a 6 then trend analysis


Boulanger Savings and Loan is proud of its long tradition in Winter Park, Florida. Begun by Michelle Boulanger 22 years after World War II, the S&L has bucked the trend of financial and liquidity problems that has repeatedly plagued the industry. Deposits have increased slowly but surely over the years, despite recessions in 1983, 1988, 1991, 2001, and 2010. Ms. Boulanger believes it is necessary to have a long-range strategic plan for her firm, including a 1-year forecast and preferably even a 5-year forecast of deposits. She examines the past deposit data and also peruses Florida's gross state product (GSP) over the same 44 years. (GSP is analogous to gross national product [GNP] but on the state level.) The resulting data are in the following table.

YEAR

DEPOSITS

GSP

Year

DEPOSITS

GSP

1

.25

.4

23

6.2

2.5

2

.24

.4

24

4.1

2.8

3

.24

.5

25

4.5

2.9

4

.26

.7

26

6.1

3.4

5

.25

.9

27

7.7

3.8

6

.30

1.0

28

10.1

4.1

7

.31

1.4

29

15.2

4.0

8

.32

1.7

30

18.1

4.0

9

.24

1.3

31

24.1

3.9

10

.26

1.2

32

25.6

3.8

11

.25

1.1

33

30.3

3.8

12

.33

.9

34

36.0

3.7

13

.50

1.2

35

31.1

4.1

14

.95

1.2

36

31.7

4.1

15

1.70

1.2

37

38.5

4.0

16

2.3

1.6

38

47.9

4.5

17

2.8

1.5

39

49.1

4.6

18

2.8

1.6

40

55.8

4.5

19

2.7

1.7

41

70.1

4.6

20

3.9

1.9

42

70.9

4.6

21

4.9

1.9

43

79.1

4.7

22

5.3

2.3

44

94.0

5.0

a) Using exponential smoothing, with a = .6, then trend analysis, and finally linear regression, discuss which forecasting model fits best for Boulanger's strategic plan. Justify the selection of one model over another.

b) Carefully examine the data. Can you make a case for excluding a portion of the information? Why? Would that change your choice of model?

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