Forecasting Wal-mart Stock:

Date	Close		These data are also used in "Data Analysis for Managers" by Albright, Winston & Zappe
5-Feb-01	53.84
6-Feb-01	53.20
7-Feb-01	54.66
8-Feb-01	52.30
9-Feb-01	50.40
12-Feb-01	53.45
13-Feb-01	54.10
14-Feb-01	53.00
15-Feb-01	52.00
16-Feb-01	52.36
20-Feb-01	53.40
21-Feb-01	50.21
22-Feb-01	49.70
23-Feb-01	50.28
26-Feb-01	51.07
27-Feb-01	50.99
28-Feb-01	50.09
1-Mar-01	48.34
2-Mar-01	48.92
5-Mar-01	48.37
6-Mar-01	49.55
7-Mar-01	50.70
8-Mar-01	51.65
9-Mar-01	50.78
12-Mar-01	48.31
13-Mar-01	48.80
14-Mar-01	47.20
15-Mar-01	47.85
16-Mar-01	46.93
19-Mar-01	47.38
20-Mar-01	47.88
21-Mar-01	48.31
22-Mar-01	46.91
23-Mar-01	47.57
26-Mar-01	49.60
27-Mar-01	50.29
28-Mar-01	49.66
29-Mar-01	50.62
30-Mar-01	50.50
2-Apr-01	50.64
3-Apr-01	49.19
4-Apr-01	49.87
5-Apr-01	50.54
6-Apr-01	51.24
9-Apr-01	50.30
10-Apr-01	50.84
11-Apr-01	50.23
12-Apr-01	49.70
16-Apr-01	49.05
17-Apr-01	49.24
18-Apr-01	52.73
19-Apr-01	52.50
20-Apr-01	51.71
23-Apr-01	52.04
24-Apr-01	50.10
25-Apr-01	50.67
26-Apr-01	51.24
27-Apr-01	52.83
30-Apr-01	51.74
1-May-01	53.50
2-May-01	53.08
3-May-01	53.10
4-May-01	53.02
7-May-01	52.05
8-May-01	51.98
9-May-01	51.59
10-May-01	53.42
11-May-01	54.10
14-May-01	54.35
15-May-01	52.00
16-May-01	51.65
17-May-01	51.76
18-May-01	52.04
21-May-01	53.20
22-May-01	53.52
23-May-01	52.52
24-May-01	52.89
25-May-01	51.20
29-May-01	51.21
30-May-01	51.47
31-May-01	51.75
1-Jun-01	51.72
4-Jun-01	50.99
5-Jun-01	51.30
6-Jun-01	50.75
7-Jun-01	51.10
8-Jun-01	51.02
11-Jun-01	50.23
12-Jun-01	50.57
13-Jun-01	50.15
14-Jun-01	49.50
15-Jun-01	48.15
18-Jun-01	48.52
19-Jun-01	48.86
20-Jun-01	49.80
21-Jun-01	50.45
22-Jun-01	49.98
25-Jun-01	49.00
26-Jun-01	49.10
27-Jun-01	48.50
28-Jun-01	49.37
29-Jun-01	48.80
2-Jul-01	49.75
3-Jul-01	49.22
5-Jul-01	48.60
6-Jul-01	47.34
9-Jul-01	48.25
10-Jul-01	47.50
11-Jul-01	48.85
12-Jul-01	51.85
13-Jul-01	52.90
16-Jul-01	53.48
17-Jul-01	53.35
18-Jul-01	53.98
19-Jul-01	54.23
20-Jul-01	54.28
23-Jul-01	53.03
24-Jul-01	53.10
25-Jul-01	55.10
26-Jul-01	55.50
27-Jul-01	55.41
30-Jul-01	55.88
31-Jul-01	55.90
1-Aug-01	55.01
2-Aug-01	55.99
3-Aug-01	55.39
6-Aug-01	54.50
7-Aug-01	55.08
8-Aug-01	54.53
9-Aug-01	54.17
10-Aug-01	53.60
13-Aug-01	52.20
14-Aug-01	52.36
15-Aug-01	52.00
16-Aug-01	51.69
17-Aug-01	50.80
20-Aug-01	51.59
21-Aug-01	49.94
22-Aug-01	50.24
23-Aug-01	49.74
24-Aug-01	50.95
27-Aug-01	50.39
28-Aug-01	50.10
29-Aug-01	49.15
30-Aug-01	47.60
31-Aug-01	48.05
4-Sep-01	48.45
5-Sep-01	49.15
6-Sep-01	47.37
7-Sep-01	46.22
10-Sep-01	46.23
17-Sep-01	44.00
18-Sep-01	45.35
19-Sep-01	45.45
20-Sep-01	45.31
21-Sep-01	44.66
24-Sep-01	47.28
25-Sep-01	48.40
26-Sep-01	49.48
27-Sep-01	49.39
28-Sep-01	49.50
1-Oct-01	49.76
2-Oct-01	51.60
3-Oct-01	52.73
4-Oct-01	51.50
5-Oct-01	52.40
8-Oct-01	51.11
9-Oct-01	52.08
10-Oct-01	53.63
11-Oct-01	53.49
12-Oct-01	52.90
15-Oct-01	53.48
16-Oct-01	53.14
17-Oct-01	52.22
18-Oct-01	51.90
19-Oct-01	53.01
22-Oct-01	53.04
23-Oct-01	52.61
24-Oct-01	52.48
25-Oct-01	53.30
26-Oct-01	53.42
29-Oct-01	51.90
30-Oct-01	50.60
31-Oct-01	51.40
1-Nov-01	52.24
2-Nov-01	52.97
5-Nov-01	53.90
6-Nov-01	54.94
7-Nov-01	53.82
8-Nov-01	54.50
9-Nov-01	55.10
12-Nov-01	55.58
13-Nov-01	54.26
14-Nov-01	55.28
15-Nov-01	56.00
16-Nov-01	55.10
19-Nov-01	55.75
20-Nov-01	55.70
21-Nov-01	55.12
23-Nov-01	55.80
26-Nov-01	55.75
27-Nov-01	55.08
28-Nov-01	55.00
29-Nov-01	54.65
30-Nov-01	55.15
3-Dec-01	54.58
4-Dec-01	55.17
5-Dec-01	56.57
6-Dec-01	55.62
7-Dec-01	55.34
10-Dec-01	54.27
11-Dec-01	54.08
12-Dec-01	54.33
13-Dec-01	53.36
14-Dec-01	54.06
17-Dec-01	55.85
18-Dec-01	55.78
19-Dec-01	56.28
20-Dec-01	56.26
21-Dec-01	57.57
24-Dec-01	57.13
26-Dec-01	58.15
27-Dec-01	58.37
28-Dec-01	58.35
31-Dec-01	57.55
2-Jan-02	58.05
3-Jan-02	57.98
4-Jan-02	57.60
7-Jan-02	57.39
8-Jan-02	57.84
9-Jan-02	56.40
10-Jan-02	57.00
11-Jan-02	55.80
14-Jan-02	55.76
15-Jan-02	56.87
16-Jan-02	55.99
17-Jan-02	56.76
18-Jan-02	56.35
22-Jan-02	58.01
23-Jan-02	59.86
24-Jan-02	59.67
25-Jan-02	58.40
28-Jan-02	58.63
29-Jan-02	57.91
30-Jan-02	59.75
31-Jan-02	59.98
1-Feb-02	59.26
4-Feb-02	58.90

(a) create a timeplot of the differenced series.

(b) which of the following is/are relevant for testing whether this stock is a random walk?

- the autocorelations of the closing price series

-the AR(1) slope coefficient for the closing price series

- the AR(1) constant coefficient for the closing price series

- the autocorrelations of the differenced series

- the AR(1) slope coefficient for the differenced series

- The AR(1) constant coefficient for the differenced series

(c) Recreate the AR(1) model output for the Close price series shown in the left of Table 7.4. Does the AR model indicate that this is a random walk? Explain how you reached your conclusion.

(d) what are the iplications of finding that a time series is a random walk? choose the correct statement below.

-it is impossible to obtain useful forecasts of the series.

- the series is random

- the changes in the series from one period to the other are random.