Dear all,

I'm a first time user of this list. Please let me know if I need to provide
more info,etc.
I have a question regarding dccforecast() and the number of external
regressors needed.

I'm using the dccforecast() function from the package "rmgarch" and use the
simple DCC model and a AR(1)-GARCH(1,1). The forecast works fine when I do
NOT include external regressors. However, I have an error message from the
dccforecast() function when I include the external regressors in the
external.forecasts=list(mregfor = ...) option.

"Error: dccforecast-->error: wrong number of external regressors!..."

>From the documentation, I understand that I need to have unconstraint
forecast of my ext. regr and these regressors must be the same as in the
ugarchspec(). I googled my problem, but nothing helpful came up. Anyone see
the mistake here ? I appreciate your help :) thanks!

Here are the main steps I took and my code is below.

step (1):  univariate GARCH specification with ARMA(1,0), GARCH(1,1) and a
842x17 matrix of external regressors. Then, I create a multispec object.
step (2):  varxfit( ... data matrix of 758x6,  and regressors of 758x17
dimensions)
step (3): dccspec( multispec, ext.regr of 842x17  dimensions)
              dccfit( dccspec, data of 842x6  and out.sample=84)
step (4) dccforecast ( dccfit,  n.ahead = 1 , n.roll = 5,  mregfor of
dimension 842.17 )
==>  and I get the embarrassing message with "wrong number of ext.
regressors!..."

My code:
###########################################################
uniGarchSpec <- ugarchspec(mean.model = list(armaOrder=c(1,0),
                                             external.regressors =
lag(extRegr)),

variance.model=list(model="sGARCH",
                                             garchOrder=c(1,1)))
multiGarchSpec <- multispec(replicate(6, uniGarchSpec))
# VAR
varFit <- varxfit(X=data.agriFact[-outSample.ind,c(5:9, 23)],
                                p=1, postpad='constant', robust=FALSE,
ns=200,
                                exogen=extRegr[-outSample.ind,])
# DCC
dccSpec <- dccspec(multiGarchSpec, VAR=TRUE, robust=FALSE,
                             lag=1, lag.max=NULL,
                             external.regressors=lag(extRegr),
                             robust.control = list("gamma" = 0.25,
                                                   "delta" = 0.01, "nc" =
10, "ns" = 250),
                             dccOrder=c(1,1), model=c("DCC"),
distribution=c("mvt"),
                             start.pars=list(dcca1=0.05, dccb1=0.816))
dccFit <- dccfit(dccSpec, data=lag(data.agriFact[,c(5:9, 23)]),
                                  VAR.fit = varFit, out.sample=84)
# Forecast
dccForecast <- dccforecast(dccFit, n.ahead=1,n.roll=5,
                           external.forecasts=list(mregfor=lag(extRegr)))
###########################################################

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