Question 1: The yield on a general obligation bond for the city of Davenport fluctuates withthe market.The monthly quotations for 2006 are given in Table shown below:

Month             Actual Value Y bar

January                9.29
February              9.99
March                  10.16
April                    10.25
May                     10.61
June                    11.07
July                     11.52
August                11.09
September          10.8
October               10.5
November           10.86
December             9.97

Use exponential smoothing with a smoothing constant of .2 and an initial value of 9.29 to forecast the yield for January 2007.

Is this forecast better than the forecast made using the better moving average model? Why? Explain your answer, support with numbers.

Question 2: The Hughes Supply Company uses an inventory management method to deter-mine the monthly demands for various products.The demand values for the last 12months of each product have been recorded and are available for future forecast-ing. The demand values for the 12 months of 2006 for one electrical fixture are presented in Table below. Use exponential smoothing with a smoothing constant of .5 and an initial value of 205 to forecast the demand for January 2007.

Month     Demand
Jan-06      205
Feb-06     251
Mar-06     304
Apr-06     284
May-06    352
Jun-06     300
Jul-06      241
Aug-06    284
Sep-06    312
Oct-06     289
Nov-06     385
Dec-06     256

Question 3: The Triton Energy Corporation explores for and produces oil and gas. Company president Gail Freeman wants to have her company's analyst forecast the company's sales per share for 2000. This will be an important forecast, since Triton's restructuring plans have hit a snag.The data are presented in Table shown below:

Year   Sales per Share   Year   Sales per Share
1974       0.93                1987         5.33
1975       1.35                1988         8.12
1976       1.48                1989        10.65
1977       2.36                1990        12.06
1978       2.45                1991        11.63
1979       2.52                1992         6.58
1980       2.81                1993         2.96
1981       3.82                1994         1.58
1982       5.54                1995         2.99
1983       7.16                1996         3.69
1984       1.93                1997         3.98
1985       5.17                1998         4.39
1986       7.72                1999         6.85

a) Calculate all forecasting smoothing methods that you know (naïve, exponential smoothing, 2PMA, 3PMA, and ???) and determine the best method. Rank all the methods starting from the best. Support each method with a graph.

b) forecast sales per share for 2000, compare the results for this year from all methods and rank the methods.

c) Compute MAD, MSE. RMSE, MAPE and MPE