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)

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