Should VAR(1) and VAR(1)-GARCH(1, 1) give equal point forecasts out of sample?
I have a VAR(1) with heteroscedastic errors, so I used the rmgarch package
for R to estimate a VAR(1)-GARCH(1,1). After that I performed an out-sample
forecast for the mean equation with both models. They give me the exact same
result with GARCH or without. Is that suppose to happen?
I will provide the code that I'm using:
## VAR(1) ##
Data <- betas[-c(163,164), ]
var1 <- VAR(Data, p = 1, type = "const",
season = NULL, exogen = NULL, lag.max = NULL,
ic = c("AIC", "HQ", "SC", "FPE"))
var.predict <- predict(var1, n.ahead = 2, ci = 0.95)