I am trying to get a cross-correlogram between stock returns and trading volumes and run across PROC ARIMA. I wonder how does PROC ARIMA know which variable is the time variable? In PROC TIMESERIES or PROC EXPAND, we have to specify a time variable with an ID statement, and if there are many groups (in my case, stocks), we have to specify a BY statement.
Does PROC ARIMA assume there are only 1 group and the data is already sorted by time sequence?
Hi @somebody
PROC ARIMA assumes the data are equally-spaced and sorted sequentially over time, therefore, a time ID variable is not required to compute the cross-correlations. If you have gaps in the data, then these gaps should be filled in with missing values (or some other value of your choosing) prior to running the procedure in order to preserve the correct spacing between observations.
PROC ARIMA supports a BY statement so you can perform a separate analysis for each BY group. Within each BY group, PROC ARIMA assumes the data is equally-spaced and sorted sequentially over time.
I hope this helps!
DW
I moved this to the Forecasting community.
Hi @somebody
PROC ARIMA assumes the data are equally-spaced and sorted sequentially over time, therefore, a time ID variable is not required to compute the cross-correlations. If you have gaps in the data, then these gaps should be filled in with missing values (or some other value of your choosing) prior to running the procedure in order to preserve the correct spacing between observations.
PROC ARIMA supports a BY statement so you can perform a separate analysis for each BY group. Within each BY group, PROC ARIMA assumes the data is equally-spaced and sorted sequentially over time.
I hope this helps!
DW
Registration is open! SAS is returning to Vegas for an AI and analytics experience like no other! Whether you're an executive, manager, end user or SAS partner, SAS Innovate is designed for everyone on your team. Register for just $495 by 12/31/2023.
If you are interested in speaking, there is still time to submit a session idea. More details are posted on the website.
Learn how to run multiple linear regression models with and without interactions, presented by SAS user Alex Chaplin.
Find more tutorials on the SAS Users YouTube channel.