[R-SIG-Finance] predict returns with the fSeries package

[Ricardo Zambrano Aguilera]

Dear List
 how i can predict returns with new data??
 > ajuste1

Title:
 GARCH Modelling 

Call:
 garchFit(formula.mean = ~arma(2, 0), formula.var = ~garch(1, 
    1), series = r_peso, cond.dist = "dnorm") 

Mean and Variance Equation:
 ~arma(2, 0) + ~garch(1, 1) 

Conditional Distribution:
 dnorm 

Coefficient(s):
          mu           ar1           ar2         omega        alpha1         beta1  
-1.25313e-04   6.10406e-02  -7.06526e-02   2.11754e-06   9.47503e-02   8.45540e-01  

Error Analysis:
         Estimate  Std. Error  t value Pr(>|t|)    
mu     -1.253e-04   1.466e-04   -0.855   0.3925    
ar1     6.104e-02   2.765e-02    2.208   0.0272 *  
ar2    -7.065e-02   2.785e-02   -2.537   0.0112 *  
omega   2.118e-06   1.114e-06    1.902   0.0572 .  
alpha1  9.475e-02   2.411e-02    3.929 8.51e-05 ***
beta1   8.455e-01   5.195e-02   16.277  < 2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Log Likelihood:
 -5473.802    normalized:  -3.751749 

Description:
 Thu Sep 07 11:50:50 2006 

#######
################## then....############################
> predict(ajuste1)
    meanForecast   meanError standardDeviation
1   0.0001657992 0.005873028       0.004574582
2  -0.0002516247 0.005883959       0.004668490
3  -0.0001535909 0.005897073       0.004755100
4  -0.0001181148 0.005897279       0.004835123
5  -0.0001228757 0.005897331       0.004909178
6  -0.0001256727 0.005897333       0.004977807
7  -0.0001255071 0.005897334       0.005041485
8  -0.0001252994 0.005897334       0.005100636
9  -0.0001252984 0.005897334       0.005155636
10 -0.0001253130 0.005897334       0.005206823



######### now if a put newdata it´s the same¿?, how i can know the returns for the next week if i put the returns of the last week????############ 

> predict(ajuste1,newdata=returns[1451:1460,1])
    meanForecast   meanError standardDeviation
1   0.0001657992 0.005873028       0.004574582
2  -0.0002516247 0.005883959       0.004668490
3  -0.0001535909 0.005897073       0.004755100
4  -0.0001181148 0.005897279       0.004835123
5  -0.0001228757 0.005897331       0.004909178
6  -0.0001256727 0.005897333       0.004977807
7  -0.0001255071 0.005897334       0.005041485
8  -0.0001252994 0.005897334       0.005100636
9  -0.0001252984 0.005897334       0.005155636
10 -0.0001253130 0.005897334       0.005206823

My best regards Ricardo Z.