GARCH-M model estimation in R

Question

is it possible to estimate a GARCH with volatility in the mean using R?

I read that it may be possible with rgarch package but I have some trouble installing it. Is there any other way?

The model is:

  r[t] = mu + c*s[t]^2 + a[t],

  a[t] = s[t]*e[t],

  s[t]^2 = alpha0 + alpha1 * a[t-1]^2 +  beta1 * s[t-1]^2,

Regards,

Juan.

Answer 1

Ruey Tsay has published a garchM function . Save the code and load it into R using the source function:

source('/path/to/garchM.R')

The garchM function can be used as follows:

data <- read.table('/path/to/data.txt')
returns <- data$rtn * 100
garchM(returns)