This example shows how to use two Fame namelists to perform selection. Note that fame_namelist1 could be easily generated using the Fame WILDLIST
function. For more about the WILDLIST
function, see the section “The WILDLIST Function” in the Fame Command Reference, Volume 2, Functions. In the following statements, four tickers are selected in fame_namelist1, but when you use the KEEP statement, the resulting data set contains only the desired IBM ticker:
libname lib8 sasefame "%sysget(FAME_DATA)" convert=(frequency=business technique=constant) crosslist=( { IBM,SPALN,SUNW,XOM }, { adjust, close, high, low, open, volume, uclose, uhigh, ulow,uopen,uvolume } ); data trout; /* eleven companies, keep only the IBM ticker this time */ set lib8.training; where date between '01mar02'd and '20mar02'd; keep IBM: ; run; title1 'TRAINING DB, Pricing Timeseries for IBM Ticker in CROSSLIST='; proc contents data=trout; run; proc print data=trout; run;
Output 41.8.1 and Output 41.8.2 show the results.
Output 41.8.1: Contents of the IBM Time Series in the Fame TRAINING Data
TRAINING DB, Pricing Timeseries for IBM Ticker in CROSSLIST= |
Alphabetic List of Variables and Attributes | |||
---|---|---|---|
# | Variable | Type | Len |
1 | IBM.ADJUST | Num | 8 |
2 | IBM.CLOSE | Num | 8 |
3 | IBM.HIGH | Num | 8 |
4 | IBM.LOW | Num | 8 |
5 | IBM.OPEN | Num | 8 |
6 | IBM.UCLOSE | Num | 8 |
7 | IBM.UHIGH | Num | 8 |
8 | IBM.ULOW | Num | 8 |
9 | IBM.UOPEN | Num | 8 |
10 | IBM.UVOLUME | Num | 8 |
11 | IBM.VOLUME | Num | 8 |
Output 41.8.2: Listing of Ticker IBM Time Series in the Fame TRAINING Data
TRAINING DB, Pricing Timeseries for IBM Ticker in CROSSLIST= |
Obs | IBM.ADJUST | IBM.CLOSE | IBM.HIGH | IBM.LOW | IBM.OPEN | IBM.UCLOSE | IBM.UHIGH | IBM.ULOW | IBM.UOPEN | IBM.UVOLUME | IBM.VOLUME |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 1 | 103.020 | 103.100 | 98.500 | 98.600 | 103.020 | 103.100 | 98.500 | 98.600 | 104890 | 104890 |
2 | 1 | 105.900 | 106.540 | 103.130 | 103.350 | 105.900 | 106.540 | 103.130 | 103.350 | 107650 | 107650 |
3 | 1 | 105.670 | 106.500 | 104.160 | 104.250 | 105.670 | 106.500 | 104.160 | 104.250 | 75617 | 75617 |
4 | 1 | 106.300 | 107.090 | 104.750 | 105.150 | 106.300 | 107.090 | 104.750 | 105.150 | 76874 | 76874 |
5 | 1 | 103.710 | 107.500 | 103.240 | 107.300 | 103.710 | 107.500 | 103.240 | 107.300 | 109720 | 109720 |
6 | 1 | 105.090 | 107.340 | 104.820 | 104.820 | 105.090 | 107.340 | 104.820 | 104.820 | 107260 | 107260 |
7 | 1 | 105.240 | 105.970 | 103.600 | 104.350 | 105.240 | 105.970 | 103.600 | 104.350 | 86391 | 86391 |
8 | 1 | 108.500 | 108.850 | 105.510 | 105.520 | 108.500 | 108.850 | 105.510 | 105.520 | 110640 | 110640 |
9 | 1 | 107.180 | 108.650 | 106.700 | 108.300 | 107.180 | 108.650 | 106.700 | 108.300 | 64086 | 64086 |
10 | 1 | 106.600 | 107.950 | 106.590 | 107.020 | 106.600 | 107.950 | 106.590 | 107.020 | 53335 | 53335 |
11 | 1 | 106.790 | 107.450 | 105.590 | 106.550 | 106.790 | 107.450 | 105.590 | 106.550 | 108640 | 108640 |
12 | 1 | 106.350 | 108.640 | 106.230 | 107.100 | 106.350 | 108.640 | 106.230 | 107.100 | 53048 | 53048 |
13 | 1 | 107.490 | 108.050 | 106.490 | 106.850 | 107.490 | 108.050 | 106.490 | 106.850 | 46148 | 46148 |
14 | 1 | 105.500 | 106.900 | 105.490 | 106.900 | 105.500 | 106.900 | 105.490 | 106.900 | 48367 | 48367 |