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 <[email protected]> > 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 <[email protected] > <mailto:[email protected]>> 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 >> _______________________________________________ >> [email protected] <mailto:[email protected]> 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]] _______________________________________________ [email protected] mailing list 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.
