[R-SIG-Finance] modeling VARMA-Garch in R

[Alexios Galanos]

1. rmgarch does not support varma, only VAR
2. The model you estimated is univariate ARMA(1,1)
3. The NAs are because you set fit.control = list(eval.se = FALSE)
i.e. you are telling the routine to not evaluate the standard errors.

Alexios


> On Jul 25, 2018, at 16:08, Marcio Bernardo <marciobernardo1 using gmail.com> wrote:
> 
> Hi,
> 
> I was wondering if the current rmgarch version allows for a VARMA-GARCH modeling. 
> 
> 
> I tried forcing the issue, changing the rmgarch example:
> 
> 
> uspec.n = multispec(replicate(30, ugarchspec(mean.model = list(armaOrder = c(1,1)))))
> spec.dccn = dccspec(uspec.n, dccOrder = c(1, 1), distribution = 'mvnorm')
> fit.1 = dccfit(spec.dccn, data = X, solver = 'solnp', cluster = cl, fit.control = list(eval.se = FALSE))
> 
> but the results were a bit off:
> 
> 
>> fit.1
> 
> *---------------------------------*
> *          DCC GARCH Fit          *
> *---------------------------------*
> 
> Distribution         :  mvnorm
> Model                :  DCC(1,1)
> No. Parameters       :  617
> [VAR GARCH DCC UncQ] : [0+180+2+435]
> No. Series           :  30
> No. Obs.             :  1141
> Log-Likelihood       :  70882.93
> Av.Log-Likelihood    :  62.12 
> 
> Optimal Parameters
> -----------------------------------
>               Estimate  Std. Error  t value Pr(>|t|)
> [AA].mu        0.002643          NA       NA       NA
> [AA].ar1      -0.693738          NA       NA       NA
> [AA].ma1       0.664589          NA       NA       NA
> [AA].omega     0.000065          NA       NA       NA
> [AA].alpha1    0.115044          NA       NA       NA
> [AA].beta1     0.869706          NA       NA       NA
> [AXP].mu       0.002737          NA       NA       NA
> [AXP].ar1      0.072418          NA       NA       NA
> [AXP].ma1     -0.150777          NA       NA       NA
> [AXP].omega    0.000011          NA       NA       NA
> [AXP].alpha1   0.064777          NA       NA       NA
> [AXP].beta1    0.934223          NA       NA       NA
> .
> .
> .
> [Joint]dcca1   0.004960          NA       NA       NA
> [Joint]dccb1   0.942361          NA       NA       NA
> 
> Information Criteria
> ---------------------
> 
> Akaike       -123.17
> Bayes        -120.44
> Shibata      -123.51
> Hannan-Quinn -122.14
> 
> 
> 
> This seems to be a ARMA-DCC fit, instead of VARMA-DCC and the NA is troubling me.
> 
> 
> 
> 
> I understand the package support VAR-Garch. Is there any package currently available in R that have VARMA-Garch model (I don’t have access to RATS)?
> 
> 
> Any help would be much appreciated,
> 
> 
> 
> Márcio R. Bernardo
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