[R-SIG-Finance] GARCH-M Modeling in R (rugarch) vs EVIEWS
Alexios Ghalanos
alexios at 4dscape.com
Thu Apr 3 20:31:39 CEST 2014
1. See archm and archpow options for ARCH in mean.
2. Don't use model='fGARCH' and submodel='GARCH'. Use model='sGARCH'.
3. Read the vignette to see the notation used (alpha is the ARCH coefficient and beta the GARCH coefficient).
Alexios
> On 3 Apr 2014, at 19:54, Nick Phillips <spillihp.kcin.61 at gmail.com> wrote:
>
> Hi,
>
> Im trying to compare some GARCH moedling outputs from EVIEWS to the rugarch
> package, specifically what EVIEWS refers to as the 'GARCH coefficient' when
> modelling a GARCH-M(1,1) process.
>
> Is anyone familiar with this and if so how to calculate it from the rugarch
> or anther garch package in R?
>
> Any help would be appreciated
>
> Thanks,
>
> Nick
>
>
>
> my R code to fit the rugarch garch-m (1,1) model is
>
> rm(list = ls())
>
> library(PerformanceAnalytics)
>
> library(quantmod)
>
> library(forecast)
>
> library(rugarch)
>
> ###############################################
>
> # Get Data ##
>
> ###############################################
>
> data.df = read.table(file = 'RP_Orig.csv', sep = ',',
>
> header = TRUE, as.is = TRUE)
>
> data.xts <- xts(data.df[,2:ncol(data.df)], order.by = as.Date(data.df[,1]))
>
>
> spec = ugarchspec(variance.model = list(model = "fGARCH", submodel =
> 'GARCH', garchOrder = c(1, 1), variance.targeting =
> FALSE),
>
> mean.model = list(armaOrder = c(0,0), archm = TRUE),
>
> distribution.model = "std")
>
>
> fit = ugarchfit(data = na.omit(data.xts['/2013-10-01','sp500']), spec =
> spec)
>
> [[alternative HTML version deleted]]
>
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