%garchex.m
clear all;

gmmdata;
size(rawdata)
pause
data = rawdata(:,2);  %use real, value-weighted return

%suppose we want to estimate an ARMA(1,1) model with no conditional mean
arp = 1;
maq = 1;
cflag = 0;
result = arma(data,arp,maq,cflag)

pause
%let's assume this data follows an AR(1) process with GARCH(1,1) volatility
spec = garchset('R', 1, 'P', 1, 'Q', 1);
garchfit(spec,data)
pause

%suppose now we think that lagged dividend yield predicts returns - we
%should include this in the conditional mean specification (ARMAX)
%we'll use an affine factor model where the factors correspond to
%Fama-French factors and the return corresponds to a portfolio of 
clear all;
garchff;
ret = rawdata(:,1);
factors = rawdata(:,2:4);
spec = garchset('P', 1, 'Q', 1);
garchfit(spec,ret,factors)