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

	[[alternative HTML version deleted]]

