[R-SIG-Finance] Passing optim.control arima arguments to ugarchfit in rugarch

[Andreas Keller Leth Laursen]

Ah, a misunderstanding on my part. Of course it makes perfect sense that
they are jointly estimated.

Thanks for the suggestions and the swift response.

Best regards,

Andreas

--
Andreas Keller
M.Sc. student in Economics and Management

On Wed, Jan 21, 2015 at 12:19 PM, alexios <alexios at 4dscape.com> wrote:

> Hi,
>
> arima is only used to obtain mean equation starting values for the joint
> recursion which is then ML based. Your best bet is to try using
> solver="gosolnp" which searches the parameter space for good starting
> values.
> Also, try setting variance.targeting=TRUE (in variance.model), and
> fit.control=list(scale=1).
>
> Ofcourse, this is all dependent on using a reasonable amount of data for
> the estimation (already discussed numerous times over the years).
>
> Regards,
>
> Alexios
>
>
> On 21/01/2015 10:38, Andreas Keller Leth Laursen wrote:
>
>> Dear all
>>
>> I am currently estimating a number of GARCH models using the excellent
>> rugarch package.
>>
>> I am however having a small problem, as the mean equation has convergence
>> problems. It is a simple ARMA(6,5) model, that is being used as mean
>> equation.
>>
>> When estimating the mean equation, I understand that ugarchfit() use the
>> standard arima() function. Is there a way to pass optim.control arguments
>> to the arima solver? A simple increase in the default maxit should solve
>> the problem, but I cannot figure out if there is a way to pass this
>> argument.
>>
>> As a small hack I have tried to simply give the arma(6,5) estimates as
>> stating values to ugarchspec() using arima() with a higher maxit.
>> However, ugarchfit() still reports convergence problems in the mean
>> equation, when I attempt this.
>>
>> Any help will be much appreciated.
>>
>> Current code:
>>
>> arima_start_val <- arima(input_series, order = c(6, 0, 5), optim.control =
>> list(maxit = 2000)) %>%
>>      coef %>%
>>      as.list
>>
>> names(arima_start_val) <- c("ar1", "ar2", "ar3", "ar4", "ar5", "ar6",
>> "ma1", "ma2", "ma3", "ma4",     "ma5", "mu")
>>
>> model <- ugarchspec(
>>      variance.model = list(model = "sGARCH",  garchOrder = c(1, 1)),
>>      mean.model = list(armaOrder = c(6, 5)),
>>      start.pars = arima_start_val,
>>      distribution = "norm")
>>
>> ugarchfit(spec = model, data = input_series)
>>
>> Best regards,
>> Andreas Keller
>>
>> --
>> Andreas Keller
>>
>>         [[alternative HTML version deleted]]
>>
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>>
>

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