Hi there,

1)      When specifying a model with external regressors in the mean equation and fixing the parameters, how do I pass the matrix of regressors to the rugarch filter method, or is it automatically passed via the specification? (please see excerpt below)
      ...
      external <- Data$LogReturnsStocks
      dim(external) = c(length(external),1)
      spec = ugarchspec(..., mean.model = list(..., external.regressors = external)...)
      cf = c(0.5,0.7,...)
      specf = spec
      setfixed(specf) <- as.list(cf)
      filt = ugarchfilter(specf, data = nrenditenWTI[1:(1001+i-1)], n.old = 1001)
      ...

2)      Is there a trick/way using rugarch to artificially set the first a standardized residuals of an ARMA(a,b) specification to zero as in the previous rgarch, i.e. reconstruct the rgarch package?  This would hopefully allow to get approximately the same filtering as before (please see excerpt below)

   rgarch:

   library(rgarch)
   data(sp500ret)
   spec = arfimaspec(mean.model = list(armaOrder = c(7,1), include.mean = FALSE, arfima = FALSE)
   fit = arfimafit(spec, sp500ret)

> residuals(fit)[1:8]
[1] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.006930002

The same in rugarch:

> residuals(fit)[1:8]
[1]  0.008840447 -0.001892734  0.003129678 -0.004577455 -0.005742768  0.014603325  0.001059376  0.005992187

Many thanks in advance.

Mit freundlichen Grüßen / Kind regards

Stefan Jäschke
RWE Supply & Trading GmbH
Risk Origination & Industrial Sales (MFM-R)
Altenessener Str. 27
45141 Essen
Germany
Phone           +49 201 5179-1674
Mobile                     +49 162-2596816
Email           stefan.jaeschke@rwe.com<mailto:stefan.jaeschke@rwe.com>
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