Hello - This example might be useful: http://support.sas.com/documentation/cdl/en/etsug/66840/HTML/default/viewer.htm#etsug_ssm_examples03.htm Thanks, Udo ... View more

PS: I should have mentioned that the new TIMEDATA procedure provides you with capabilities you might be interested in as well:  http://support.sas.com/documentation/cdl/en/etsug/66840/HTML/default/viewer.htm#etsug_timedata_toc.htm - (aka Ken) has recorded a nice getting started video: Working with Time Series Data Using SAS/ETS - YouTube which you may want to check out. ... View more

Hello - You may have to consider writing a macro which loops through the rolling window you have in mind - TIMESERIES will use all data at hand. As an alternative you may want to check out the EXPAND procedure, which allows you to transform time series data at hand and which provides you access to many out-of-the-box transformations: http://support.sas.com/documentation/cdl/en/etsug/63939/HTML/default/viewer.htm#etsug_expand_sect026.htm including Moving Time Window Operators. Thanks, Udo ... View more

Hello - If you have access to SAS/ETS software you may want to explore the TIMESERIES procedure. Thanks, Udo Example: data have; input Comp date date9. time time8. returns; format date date9. time time9.; datalines; 1 12-Aug-97 10:23:38 0.919292648 1 12-Aug-97 10:59:43 0.204139521 1 13-Aug-97 11:03:12 0.31909242 1 14-Aug-97 11:10:02 0.989339371 1 14-Aug-97 11:19:27 0.08394389 1 15-Aug-97 11:56:17 0.481199854 1 16-Aug-97 13:53:45 0.140404929 1 17-Aug-97 10:09:03 0.538569786 2 14-Aug-97 11:43:49 0.427344962 2 14-Aug-97 11:48:32 0.154836294 2 15-Aug-97 14:03:47 0.445415114 2 15-Aug-97 9:38:59 0.696953041 2 15-Aug-97 13:59:23 0.577391987 2 15-Aug-97 9:10:12 0.750949097 2 15-Aug-97 10:22:38 0.077787596 2 15-Aug-97 11:07:57 0.515822161 2 16-Aug-97 11:37:26 0.862673945 2 17-Aug-97 11:42:33 0.400670247 2 19-Aug-97 11:59:34 0.109279307 run; proc timeseries data=have out=_null_ outcorr=outcorr; id date interval=day accumulate=total; var returns; by comp; run; ... View more

Hello - You will need to convert your JMP table to a SAS data set (when going from JMP to SAS Forecast Studio). Make sure that the data structure will fit requirements of SAS Forecast Studio: you will need a valid date (or datetime variable) in SAS format and at least one analysis variable in numeric format. You could potentially have additional BY variables (numeric or character type) if you have more than one time series, which is usually the case for SAS Forecast Studio.   All results of SAS Forecast Studio are stored as SAS data sets - you should be able to open them in JMP (JMP will take care of the conversion). Thanks, Udo ... View more

Saggi - A list of all supported intervals of the TIMESERIES procedure can be found here: http://support.sas.com/documentation/cdl/en/etsug/66840/HTML/default/viewer.htm#etsug_intervals_sect006.htm Thanks, Udo ... View more

Hello Saggi - As you mentioned earlier you may want to consider PROC TIMESERIES which analyzes time-stamped transactional data with respect to time and accumulates the data into a time series format as yet another option. An example can be found here: http://support.sas.com/documentation/cdl/en/etsug/66840/HTML/default/viewer.htm#etsug_timeseries_examples01.htm Thanks, Udo ... View more

Hello - If you have access to SAS Forecast Server - you may want to use the HPFDIAG procedure as a variable selection tool. Screening out weak predictors for time series models is a bit more tricky than for static regression models. Cross-correlation is an obvious way to assess predictors. Thanks, Udo ... View more