Hi Alexios,

thanks for your quick and extremely helpful response (and for your
beautiful package).

You were right, the nrow() of both objects weren't equal (if anybody has a
similar problem and finds this post in the mailing list while searching for
help, here is my mistake: nrow(ts.rtr.zoo) was the length of the time
series, while nrow(as.matrix(df.merged.**imputed[1,c(4, 9, 11)])) was the
number of time series itself).

Sorry for bothering you again, but i have some troubles fitting the model.
The estimates for my external regressors seem to be very close to zero (in
fact, all digits that are displayed are zero) and it happens quite often
that ugarchfit cannot invert hessian.
I have seen that it is possible and helpful to manipulate the solver using
solver.control in order to get a better fit of the models, but i wonder if
there are any rules of thumb for some cases? (I want to estimate parameters
for 225 different univariate time series which i believe to be quite
similar, so simply playing around with solver.control for every time series
until it fits the data will be quite painful.) I've noticed that adjusting
the tolerance parameter "tol" was helpful sometimes, but not in every
single case. Is there some information in the data itself which tells me
what kind of adjustments for the solver might be most helpful?

Best regards,
Max


2013/3/3 alexios ghalanos <alexios@4dscape.com>

> On 03/03/2013 17:58, Max Alletsee wrote:
>
>> Hi,
>>
>> i'm trying to fit some GARCH models with external regressors using the
>> package "rugarch", but it keeps on failing...
>>
>> This is how I create my zoo-object:
>>
>>  ts.rtr <- ts(data=as.numeric(df.merged.**imputed[1,32:5525]), start=1,
>>> end=5494, frequency=1)
>>> ts.rtr.zoo <- as.zoo(ts.rtr)
>>>
>>
>>
>> This is the specification of my model:
>>
>>    spec <- ugarchspec(variance.model = list(model="sGARCH", garchOrder =
>>> c(1,1), external.regressors=as.matrix(**df.merged.imputed[1,c(4, 9,
>>> 11)])))
>>>
>>
>>  Run:
> 'NROW(as.matrix(df.merged.**imputed[1,c(4, 9, 11)])))'.
>
> How many rows does that report? Are they the same as NROW(ts.rtr.zoo)?
>
>
>
>> This is my attempt to fit the model:
>>
>>  fit <- ugarchfit(spec = spec, data = ts.rtr.zoo, solver = "hybrid")
>>>
>>
>>
>> It always stops with the error message:
>>
>>  Error in .sgarchfit(spec = spec, data = data, out.sample = out.sample,  :
>>>
>>
>>    Subscript out of bounds
>>
>>
>>  -Alexios
>
> ______________________________**_________________
> R-SIG-Finance@r-project.org mailing list
> https://stat.ethz.ch/mailman/**listinfo/r-sig-finance<https://stat.ethz.ch/mailman/listinfo/r-sig-finance>
> -- Subscriber-posting only. If you want to post, subscribe first.
> -- Also note that this is not the r-help list where general R questions
> should go.
>

	[[alternative HTML version deleted]]

