proc optmodel

[Amalik]

Hi,

I have the following type of dataset and have as many as 4000 permnos.

 I am trying to do the following ,

min VAR(R.dr - SUM[w_i * R.s_i]) = min VAR(Dr - w*S)
  s.t. SUM(w_i) = 1; w_i > 0
(R.s_i include rmrf hml smb)

I am using the following code for this. The code works perfectly fine,when I run it for one permno only but I want to run this using a by variable (by permno and month). I am not sure how to incorporate this, I have read this document (http://support.sas.com/kb/42/332.html) but I am not getting how to apply this on my data.

Any help would be much appreciated.

proc corr data=return1 (drop=date)
   out=corrout(where=(_type_ ne 'CORR')) cov noprint;
  
run;

data stats(drop=_name_);
   set corrout;
   if _type_ = 'COV' then delete;
run;
proc transpose data=stats out=stats;
   id _type_;
run;


proc optmodel;
   /* declare parameters and read data */
   set <str> ASSETS;
   str target = 'f';
   set BENCH = ASSETS diff {target};
   num cov {ASSETS, ASSETS};
   read data stats into ASSETS=[_name_];
   read data corrout(where=(_type_='COV')) into [_name_]
      {i in ASSETS} <cov[_name_,i]=col(i)>;
/* let w1, w2, w3, w4 be the amount invested in each asset */
   var x{1..4} >= 0;
   /* declare optimization model */
   var W {BENCH} >= 0 <= 1;
   /* Var(X - Y) = Var(X) + Var(Y) - 2 Cov(X,Y) */
   min Variance = 
      sum {i in BENCH, j in BENCH} cov[i,j] * W[i] * W[j]
    + cov[target,target] 
    - 2 * sum {i in BENCH} cov[i,target] * W[i];
	/* subject to the following constraints */
    con weights:  sum {i in BENCH} W[i] = 1;

   /* call solver and print optimal solution */
   solve;
   print W;
quit;

[RobPratt]

The linked example illustrates a single BY variable.  One approach for your pair of BY variables is to introduce a new variable that concatenates the two and then use that new variable as your BY variable.