[R] Basic R timeseries data manipulation

[Benjamin Dickgiesser]

To elaborate a bit, I fitted a AR(2)-Garch(1,1) model to the Dow Jones
log returns and am now trying to calculate the variance suggested by
the model.

#Get log returns
rt <- diff(log(getStock(1)$value))
#Fit Garch(1,1) and AR(2)
fit = garchFit(~arma(2,0), ~garch(1,1), series = rt)

#Coefficient(s):
#          mu           ar1           ar2         omega        alpha1
       beta1
# 3.75101e-04   9.61877e-02  -2.48071e-02   7.86872e-07   7.37382e-02
 9.20691e-01

Now I was trying to something in the lines of:
n <- length(rt) - 2
at <- vector(length = n)
at <- rt - (3.75101e-04 + 9.61877e-02 rt[-1] - 2.48071e-02   rt[-2])
var <- 7.86872e-07 + 7.37382e-02 sigma[-1] + 9.20691e-01 rt[-1]

which doesn't work..
I would really appreciate your help.
Thank you,
Benjamin


On 11/20/06, Benjamin Dickgiesser <dickgiesser at gmail.com> wrote:
> Hi,
>
> suppose I have a time series rt. Why does this code not work?
>
> rt <- data
>
> n <- length(rt) - 2
> at <- vector(length = n)
>
> at = rt-(3.75101e-04 + 9.61877e-02 * rt[-1] - 2.48071e-02 * rt[-2])
>
> Thank you,
> Benjamin
>