[R-SIG-Finance] understanding an error from ugarchfit
alexios ghalanos
alexios at 4dscape.com
Tue May 27 22:02:48 CEST 2014
This is NOT stackexchange.
1. Real name
2. Reproducible example (what you've provided below is NOT).
-Alexios
On 27/05/2014 20:02, firhat.nawfan.h wrote:
> the dccfit had converged already, perhaps it have something to do with how
> the dccspec? there are 2 kind of data fin series, and cg series, bot dccfit
> converged in the first run, however when applied dccforecast the fin series
> give error message while cg series have no problem
>
> note: how to sign my messages with my real name?, i;m new here, usually i
> visited in stackexchange to get answer
>
> this is my code
>
> mspec.ret.fin<-c()
> for(i in 1:15)
> {
>
> mspec.ret.fin<-c(mspec.ret.fin,get(paste("spec.ugarch.ret.fin.",colnames(base.name[i]),sep="")))
> }
> mspec.ret.fin=multispec(mspec.ret.fin)
>
> # specify dccspec
> assign(paste("dcc.spec.ret.fin"),dccspec(get(paste("mspec.ret.fin")), VAR =
> FALSE, robust = FALSE, lag = 1, lag.max = NULL, lag.criterion = c("AIC",
> "HQ", "SC", "FPE"), external.regressors = NULL, robust.control =
> list("gamma" = 0.25, "delta" = 0.01, "nc" = 10, "ns" = 500), dccOrder =
> c(1,1), model = c("DCC"), groups = rep(1, length(uspec at spec)), distribution
> = c("mvnorm"), start.pars = list(), fixed.pars = list()))
>
> # specify data for dcc.fit
> merge.list.data.dcc.fit.ret.fin<-as.character(list())
> for (i in 1:15)
> {
> merge.list.data.dcc.fit.ret.fin<-append(merge.list.data.dcc.fit.ret.fin,paste("resid.ret.fin.",colnames(base.name[i]),sep=""))
> }
> merge.name.data.dcc.fit.ret.fin<-lapply(merge.list.data.dcc.fit.ret.fin,get)
> names(merge.name.data.dcc.fit.ret.fin)<-merge.list.data.dcc.fit.ret.fin
> data.dcc.fit.ret.fin<-do.call(merge,merge.name.data.dcc.fit.ret.fin)
>
> # adjust data for dcc.fit for different starting point in coloumn
> if (exists("dcc.fit.adj.ret.fin")==TRUE)
> {
> if(dcc.fit.adj.ret.fin>=0)
> {
> set.data.dcc.fit.ret.fin<-data.dcc.fit.ret.fin[-c(1:dcc.fit.adj.ret.fin),]
> }
> else
> {
> set.data.dcc.fit.ret.fin<-data.dcc.fit.ret.fin
> }
> }
> if (exists("dcc.fit.adj.ret.fin")==FALSE)
> {
> set.data.dcc.fit.ret.fin<-data.dcc.fit.ret.fin
> }
>
> # performing dcc.fit
> dcc.fit.ret.fin<-dccfit(dcc.spec.ret.fin, set.data.dcc.fit.ret.fin,
> out.sample = 30, solver = "gosolnp", solver.control = list(),fit.control =
> list(eval.se = TRUE, stationarity = TRUE, scale = FALSE), cluster = NULL,
> fit = NULL, VAR.fit = NULL)
> dcc.fit.ret.cg<-dccfit(dcc.spec.ret.cg, set.data.dcc.fit.ret.cg, out.sample
> = 30,
>
>
>
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