Estimating conditional variance using GARCH from daily returns

[kky6196]

Hello,

I have raw daily returns data for about 10 countries. For each country, I wish to compute conditional volatility using the model GARCH(1,1).

Would this be the right code?

Proc autoreg data=daily_return outest=est;

model daily_return= / garch=(q=1, p=1); by country;

output out=conditional_var cev=vhat; run; quit;

data conditional_vol; gc; conditional_vol=sqrt(vhat); run;

Thank you-

[SASCom1 · Accepted solution]

Hello @kky6196 

Your PROC AUTOREG code is fitting a GARCH(1,1) model for the  daily_return variable for each country, and saves the conditional error variance from the GARCH(1,1) model into the output data set. The subsequent data step is transforming the conditional error variance to the standard deviation by taking the square root. If this is what you intended to do, then it looks good.

I hope this helps.