var mk mb ml;

run;

quit;

* compute statistic;

porc iml;

  * factor samplevariance-covariance matrilx;

  use omega;

  read all var {mk mb ml} intoomegah;

  * residual samplevariance-covariance matrix;

  * note; sigme comes from theOUTS= option of the FIT;

  *     statement in PROC MODEL;

  use sigma;

  read all var {s1b1 s1b2 s1b3s1b4 s1b5

s2b1 s2b2s2b3 s2be s2b5

s3b1 s3b2s3b3 s3b4 s3b5

s4b1 s4b2s4b3 s4b4 s4b5

s5b1 s5b2s5b3 s5b4 s5b5} into sigmah;

  * factor means;

  use stats;

  read all var {mean} intofbar;

  * intercept estimates andnumber of observations;

  use est1;

  read all var {a11 a12 a13a14 a15

a21 a22 a23a24 a25

a31 a32 a33a34 a35

a41 a42 a43a44 a45

a51 a52 a53a54 a55} into bo;

read all var{_NUSED_} into t;

* N = numberof assets (portfolios);

* K = numberof factors (e.g., 3 for MK, MB, and ML);

* T = numberof observations

N = 25;

K = 3;

iomega =inv(omegah);

isigma =inv(sigmah);

W = ((1 +fbar * iomega*fbar)**-1)*bo*isigma*bo;

F = (T/M)*((T-N-K)/(T-K-1)*W;

df1 = N;

df2 = T-N-K;

pvalue = 1 –probf (F, df1, df2);

print Fpvalue;

quit;