[R-SIG-Finance] fGarch

[babel at centrum.sk]

Hello.
I have this problem. Why do I have all fitted values the same??
>  y
   43.097 43.041 43.019 42.769 42.533 42.542 42.466 42.817 42.734 42.770
   42.637 42.710 42.669 42.782 42.993 42.994 42.944 42.902 42.714 42.746
   42.881 42.760 42.489 42.422 42.460 42.641 42.675 42.678 42.827 42.981
   42.930 42.996 42.899 43.037 43.478 43.882 43.886 43.955 43.932 43.998

> library(fGarch)

> fit = garchFit(~garch(1, 1), data = y)

> show.fGARCH(fit)


Title:
 GARCH Modelling 

Call:
 garchFit(formula = ~garch(1, 1), data = y) 

Mean and Variance Equation:
 ~arma(0, 0) + ~garch(1, 1) 

Conditional Distribution:
 dnorm 

Coefficient(s):
         mu        omega       alpha1        beta1  
42.30131209   0.00394317   0.99198425   0.05514354  

Error Analysis:
        Estimate  Std. Error  t value Pr(>|t|)    
mu     42.301312    0.008606 4915.050   <2e-16 ***
omega   0.003943    0.001626    2.426   0.0153 *  
alpha1  0.991984    0.061981   16.005   <2e-16 ***
beta1   0.055144    0.052464    1.051   0.2932    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Log Likelihood:
 3405.273    normalized:  1.706904 



> fit at fitted
 42.30131 42.30131 42.30131 42.30131 42.30131 42.30131 42.30131 42.30131
 42.30131 42.30131 42.30131 42.30131 42.30131 42.30131 42.30131 42.30131

> predict(fit, n.ahead = 10)
   meanForecast meanError standardDeviation
1      42.30131  2.581365          8.109771
2      42.30131  2.581365          8.298906
3      42.30131  2.581365          8.492442
4      42.30131  2.581365          8.690480
5      42.30131  2.581365          8.893126
6      42.30131  2.581365          9.100487
7      42.30131  2.581365          9.312673
8      42.30131  2.581365          9.529796
9      42.30131  2.581365          9.751972
10     42.30131  2.581365          9.979319

I want to count RMSE and choose which Garch model, is better, but I am not able to make a garch model.Thank you