options crt;
name egarch 'egarch(1,1) example';
?  Uses ML PROC.
?  by Clint Cummins 2/1999

?--------------------------
?  generate artificial data
?--------------------------
?  Note: if 500 or 1000 observations are used for this particular
?  data generation process, the estimates are not very close to
?  the true parameter values.
smpl 1,2000;
trend obs;
random(seedin=308130) x e;
x = x*2;
param a0,1 a1,.3 b1,.3;
logh = a0/(1-a1-b1);
select obs>1;
logh = a0 + a1*abs(e(-1)) + b1*logh(-1);
select 1;
u = e*exp(logh/2);
param g0,1 g1,1;
y = g0 + g1*x + u;
?-----------------------------------
?  end of artificial data generation
?-----------------------------------

supres smpl;
ml egarch g0 g1 a0 a1 b1;

proc egarch;
  set lh = a0/(1-a1-b1);
  if (abs(lh) > 3 .or. a0<=0 .or. (a1+b1)>=1); then; do;
    set @logl = @miss;
    goto 900;
  enddo;
  u = y - (g0 + g1*x);
  h = exp(lh);
  select obs>1;
  genr(silent) h = exp(a0 + a1*abs(u(-1)/sqrt(h(-1))) + b1*log(h(-1)));
  select 1;
  logl = lnorm(u/sqrt(h)) - log(h)/2;
  mat @logl = sum(logl);
900 nodbug;
endproc;