topic Re: Rolling regression with conditions in SAS Programming

Rolling regression with conditions

trungcva112 — Thu, 04 Jun 2020 00:49:24 GMT

Re: Rolling regression with conditions

trungcva112 — Wed, 13 Dec 2017 13:59:23 GMT

Please. Anything could help

Re: Rolling regression with conditions

mkeintz — Wed, 13 Dec 2017 14:28:19 GMT

If you drop quarters with greater than a 75% change in cogsq or sale, then how do you define lag(cogsq) and lag(sale) for the subsequent quarter.

If Q3 has 80% change vs Q2, then what values will you use as lag of coqsq and sale in Q4?

Re: Rolling regression with conditions

trungcva112 — Wed, 13 Dec 2017 14:46:22 GMT

Good question. For example, If cogs in Q3 has 80% change vs Q2, then the lag of cogs in Q4 would be cogs in Q2 (or equivalently the nearest quarter that has cogs growth rate within (-75%, +75%).

Re: Rolling regression with conditions

mkeintz — Wed, 13 Dec 2017 15:38:26 GMT

So does this mean that the concept of lagged values of cogsq and sale can represent varying time spans? Let's say you have successive changes in sales of +80%, -%78%, and +90%, for a highly seasonal company. Then your lagged value of cogsq and sale will represent one-year old values.

And more generally, I don't get this notion of dropping dramatic changes anyway, since it is likely to introduce even more dramatic changes in your analysis data. Let's say a company is in a growth spurt, with successive changes in sales of 78% (for Q2) and 20% (for Q3). By dropping Q2 and inserting Q1 sales as the lagged value for Q3, you will have introduced a "change" of 96% between current and "preceding" value of the variable. That would increase the beta coefficient for lagged sale.

What you MIGHT want to do instead is insert a dummy variable indicating records with large absolute proportional changes, and keep those records.

Re: Rolling regression with conditions

trungcva112 — Wed, 13 Dec 2017 23:12:23 GMT

Thanks for your advice. But how can I insert this dummy variable and other conditions in the rolling regression?

Re: Rolling regression with conditions

trungcva112 — Thu, 14 Dec 2017 14:17:18 GMT

Anyone has any idea?

Re: Rolling regression with conditions

mkeintz — Thu, 14 Dec 2017 15:43:08 GMT

This program should give you then needed infrastructure:

data need1 (keep=window data cogsq sale lag_: outlier_:) /view=need1;

  do n=1 by 1 until (last.gvkey);
   set have;
   by gvkey;
   lag_cogsq=lag(cogsq);
   lag_sale=lag(sale);
   if n=1 then call missing(of lag_:);
   else do;
     outlier_cogsq=1-(0.25<cogsq/lag_cogsq<1.75);
     outlier_sale=1-(0.25<sale/lag_sale<1.75);
   end;

   array var {*} data cogsq sale lag_cogsq lag_sale outlier_cogsq outlier_sale;
   array data {100,7}; /*Up to 100 historic records for 7 vars*/

   do v=1 to 7; data{n,v}=var{v};end
  end;

  if n>10 then do end=11 to n;
    beg=max(2,n-59);
    window=end-11;
    do row=beg to end;
      do v=1 to 7; var{v}=data{row,v};end;
      output;
    end;
  end;
run;

proc reg data=need;
 ......
 run;
quit;

Remember data set NEED will be roughly 20 times the size of HAVE (you want 5-year rolling quarterly data). So I made NEED a data set VIEW instead of a data set FILE. It's only activated when a subsequent PROC calls for NEED, and the data is streamed directly to the proc instead of a disk file.

Re: Rolling regression with conditions

trungcva112 — Mon, 08 Jan 2018 08:55:23 GMT

Hi everyone.

I have describe the data in more detail. Could anyone has an idea? Because previous codes do not work

Re: Rolling regression with conditions

mkeintz — Mon, 08 Jan 2018 15:53:48 GMT

The phrase "do not work" is not a usefull description of the problem. What results did you get vs what you expected? Please show those results.
Test this with a sample data set with two gvkeys and just a couple years of data. And if you are testing my suggestion, change the dataset view VNEED to a data set file. Then you can examine the intermediate data set to confirm it is constructed as intended.