proc optmodel

Amalik — Thu, 26 Jul 2018 01:23:37 GMT

Hi, I am using the following code to minimize the variance of the following optimization problem;

min VAR(R.f - SUM[w_i * R.s_i]) = min VAR(F - w*S)
  s.t. SUM(w_i) = 1; w_i > 0

where:
R.f   Fund returns
R.s   Style returns
w_i   Style weights

I am using the following code for this. This code works perfectly fine, but I want to run this using a by variable (by permno). When I add permno to my data, it tends to calculate treat it as a dependent variable but rather I want to use it as a by variable only.

Any suggestions on how to modify this and run my optimization using by variables?

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;

Re: proc optmodel

RobPratt — Thu, 26 Jul 2018 02:09:40 GMT

This Usage Note illustrates how to implement BY-group processing in PROC OPTMODEL:

http://support.sas.com/kb/42/332.html

topic proc optmodel in Mathematical Optimization, Discrete-Event Simulation, and OR

proc optmodel

Re: proc optmodel