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* This program performs a GARCH(1,1)-M model
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all 0 792:1
open data sp500.dat
data(org=obs) / rt 
set h = 0.0
nonlin a0 a1 b1 mu g0
frml at = rt(t) - mu - g0*h(t)
frml gvar = a0 + a1*at(t-1)**2+b1*h(t-1)
frml garchlog = -0.5*log(h(t)=gvar(t))-0.5*at(t)**2/h(t)
smpl 2 792
compute mu = 0.01, a0 = 0.01, a1 =0.1, b1=0.6, g0 =0.01
maximize(method=bhhh,recursive,iterations=150) garchlog
set resi = at(t)
set fv = gvar(t)                                                      
set resid = at(t)/sqrt(fv(t)) 
set residsq = resid(t)*resid(t) 
table / resid
*** 
*** Checking standardized residuals ***
cor(qstats,number=20,span=10) resid 
*** Checking squared standardized residuals ***
cor(qstats,number=20,span=10) residsq
*** print the last few data for forecasting
print 788 792 rt resi fv