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

[Márcio Rodrigues Bernardo]

Thanks for your reply. Alexios

 

I will re-read to your rmgarch documentation to understand how to model VAR-DCC

 

Best regards,



Márcio Bernardo

> Em 25 de jul de 2018, à(s) 22:16, Alexios Galanos <alexios using 4dscape.com> escreveu:
> 
> 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 <http://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 <mailto: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 <http://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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