Hello,
I’ve fitted a Garch(2,1) model with function 'garchFit()' from the
package
'fGarch':
> m1 <- garchFit(formula = ~garch(2,1),data = X,trace = F)
* See 'summary(m1)' OUTPUT BELOW *
PROBLEM: My alpha1 term is not significant and I would like to make a NEW
model, say m2, that does not contain alpha1, but I am not sure how to
specify this with the garchFit() arguments. I assume it must be done by
changing the formula argument (replacing ~garch(2,1) with something), but
am unsure; not an expert in this statistical field. Has anyone worked with
these and know the fix?
Thanks,
Ash
### OUTPUT:
> summary(m1)
Title:
GARCH Modelling
Call:
garchFit(formula = ~garch(2, 1), data =X, trace = F)
Meanand Variance Equation:
data ~ garch(2, 1)
<environment: 0x03c0c84c>
[data =ex3.5$sp5]
ConditionalDistribution:
norm
Coefficient(s):
mu omega alpha1 alpha2 beta1
0.630047 0.716062 0.048446 0.096263 0.838793
Std.Errors:
based on Hessian
ErrorAnalysis:
Estimate Std. Error t value Pr(>|t|)
mu 0.63005 0.14072 4.477 7.56e-06 ***
omega 0.71606 0.26264 2.726 0.0064 **
alpha1 0.04845 0.03096 1.565 0.1176
alpha2 0.09626 0.04354 2.211 0.0271 *
beta1 0.83879 0.02477 33.858 < 2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
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