*
* Example from section 10.7 from pp 481-482
*
open data d-spcscointc.txt
data(format=free,org=columns) 1 2275 sp500 cisco intel
*
* Create the two mean equations, and group them into a model
*
equation eq1 cisco
# constant cisco{1 2 3}
equation eq2 intel
# constant
group bimodel eq1 eq2
*
* Do the univariate GARCH models and forecast the variances. (You need to do the
* variance forecasts immediately after the GARCH instruction)
*
garch(equation=eq1,p=1,q=1,resids=a1,hseries=h1)
@garchfore(steps=1) h1 a1
garch(equation=eq2,p=1,q=1,resids=a2,hseries=h2)
@garchfore(steps=1) h2 a2
*
* Forecast the means
*
forecast(model=bimodel,steps=1,results=rhat)
compute q1=rhat(1)(2276)+%invnormal(.05)*sqrt(h1(2276))
compute q2=rhat(2)(2276)+%invnormal(.05)*sqrt(h2(2276))
vcv(noprint)
# a1 a2
compute rho=%sigma(1,2)/sqrt(%sigma(1,1)*%sigma(2,2))
compute q12=sqrt(q1**2+q2**2+2*rho*q1*q2)
*
disp "Univariate Models"
disp "VaR on Cisco" @20 -10000*q1
disp "VaR on Intel" @20 -10000*q2
disp "VaR Overall" @20 10000*q12
*
garch(model=bimodel,p=1,q=1,mv=cc,hmatrices=h,rvectors=a)
*
@mvgarchfore(steps=1,mv=cc) h a
forecast(model=bimodel,steps=1,results=rhat)
*
compute q1=rhat(1)(2276)+%invnormal(.05)*sqrt(h(2276)(1,1))
compute q2=rhat(2)(2276)+%invnormal(.05)*sqrt(h(2276)(2,2))
compute rho=h(2276)(1,2)/sqrt(h(2276)(1,1)*h(2276)(2,2))
compute q12=sqrt(q1**2+q2**2+2*rho*q1*q2)
disp "Bivariate Model"
disp "VaR on Cisco" @20 -10000*q1
disp "VaR on Intel" @20 -10000*q2
disp "VaR Overall" @20 10000*q12