[R-SIG-Finance] Question

[alexios ghalanos]

Please follow the guidelines and post a reproducible example next time.
1. What is data(Gold), where can we find it?
2. There is no model called "egarch" in the specification. It is "eGARCH"

You are starting the model with 100 data points using the eGARCH model 
and the normal distribution. It is quite likely, that the solution 
converges to one which is on the boundary of covariance stationarity. I 
have replicated this :
########################################
set.seed(10)
X = rnorm(1000)
spec =ugarchspec(variance.model=list(model="eGARCH"),distribution.model 
= "norm")
roll = ugarchroll(spec, data = X, n.start = 100,  refit.every = 500, 
refit.window = "moving", solver = "solnp", fit.control = list(),
calculate.VaR = TRUE, VaR.alpha = c(0.01, 0.025, 0.05), keep.coef = TRUE)
as.data.frame(roll)
########################################
See the NaNs in the sigma.

Solutions:
1. Use more more data for the estimation start (e.g. 200).
2. Use a different model (e.g. sGARCH, gjrGARCH etc).

Also, read some of the older posts in this forum on the amount of data 
to use and why it is a bad idea to use so little data.

-Alexios

On 08/02/2013 01:34, pantea hafezian wrote:
> Dear Sir/Ms
> Thank you for your valuable and very helpful package (rugarch). Actually
> I am going to compare different GARCH models (VaR) by using this package
> but unfortunately  I face a problem. The problem is related  to the back
> testing method. For instance, in Qupiec  test, the value of K (LRUC)  is
> amounting to 0 and consequently p-value is equal to 1 for all models. I
> performed this procedure several times with various data but the results
> is same as I mentioned even for your own example. It would be appreciate
> if let me know the result is supposed to be like this or the problem
> rises from my programming.
> My program is enclosed to this email.
> Thank you again and I look forward hearing from you about that.
> Sincerely Yours,
> Pantea Hafezian
> PhD candidate in Finance,
> University Technology Malaysia (UTM)
>
>
>
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