Different random seeds / generators
Sent from my iPhone
> On 24 Jan 2025, at 14:10, Manfred Alonso Esquivel Monge via R-SIG-Finance
> <r-sig-finance@r-project.org> wrote:
>
> I'm trying to replicate in R some results that I get from an Eviews
> estimation of a model with GARCH errors. For this, I'm using the "rugarch"
> package. The problem is that estimated parameters differ by a lot. This is
> the set up I'm using in R (the data are in an xts object names "datos"):
>
> spec <- ugarchspec(
> variance.model = list(model = "sGARCH", garchOrder = c(2, 1)),
> mean.model = list(armaOrder = c(2, 0), include.mean = TRUE,
> external.regressors = as.matrix(datos[, c("jueves", "viernes", "sem2",
> "sem2_ene", "sem3_nov", "sem4_nov")]))
> )
> fit_garch <- ugarchfit(spec = spec, data = datos$d_TC, solver = "gosolnp")
>
>
>
> This es the set up I'm using in Eviews:
>
> equation fit_garch.arch(2,1) d_TC c ar(1) ar(2) jueves viernes sem2 sem2_ene
> sem3_nov sem4_nov
>
>
> As you can see, they are supposed to be the same model, an ARMA(2,0) with
> constant term plus some "external regressors" in the mean equation, and a
> GARCH(2,1) models for the variance. But coefficient estimates differ by no
> small amount.
> I verified that data are the same (run OLS and got identical results between
> the softwares). As a side note, R results does not converge easily, I tried
> some of the solvers and only "gosolnp" and "hybrid" converge.
> This is my first time using "rugarch", so chances are big that there is
> something wrong in my R set up.
>
> Any help will be greatly appreciated.
>
> Regards.
> Manfred E.
>
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