Why do I get very different results estimating GARCH-M model in Eviews and R (rugarch)?

Question

I don't know whether it is permitted to post the same question on different sites on StackExchange. I have posted it on Cross Vlidated and got no answer, so I want to have a try here.

This is the original question. I really appreciate it if someone can solve my problem.

My code in R is as follows:

#get data
re <- read.table("return.csv",sep=",",header=TRUE)
re[,1] <- as.character(re[,1])
re[,1] <- as.Date(re[,1])

#create dummy variable
re$T <- re[,1]>as.Date("2010-03-31")
re$T <- as.numeric(re$T)
T <- as.matrix(re$T)

library("xts")
xts <- as.xts(re[,-1],order.by=re[,1])

library("rugarch")
#GARCH specification
garchspec <- ugarchspec(variance.model = list(model = "sGARCH", garchOrder = c(1, 1), 
                        submodel = NULL, external.regressors = T, 
                        variance.targeting = FALSE), 
                        mean.model = list(armaOrder = c(0, 0), include.mean = TRUE,
                        archm = TRUE, archpow = 1, arfima = FALSE, 
                        external.regressors = NULL, archex = FALSE), 
                        distribution.model = "ged",
                        start.pars = list(), fixed.pars = list())

#fitting
fit <- ugarchfit(spec=garchspec, data=xts[,1], out.sample = 0,solver="solnp",
                 solver.control = list(trace=0), fit.control = 
                 list(stationarity = 1, fixed.se = 0, scale = 0, rec.init = 0.7))
show(fit)

Is there any mistake with it?