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I want to extract the p value of the coefficients of my garch model.

Here is an replicable exemple:

library(rugarch) 
y<-rnorm(1:100)
 spec <- ugarchspec(variance.model = list(model = "sGARCH", garchOrder = c(1, 1), 
                                             submodel = NULL, external.regressors = NULL, variance.targeting = FALSE), 
                       mean.model = list(armaOrder = c(1, 0), external.regressors = NULL, include.mean=T), distribution.model ="norm")


 garch <- ugarchfit(spec=spec, data = y , solver = 'hybrid')

Results gave me:

Optimal Parameters

   Estimate  Std. Error  t value Pr(>|t|)

mu 0.091862 0.083258 1.10334 0.269880 ar1 -0.165456 0.098624 -1.67764 0.093418 omega 0.033234 0.050870 0.65332 0.513550 alpha1 0.041305 0.051530 0.80158 0.422793 beta1 0.920773 0.079976 11.51312 0.000000

I can extract the coef by using:

coef(garch)

But does anyone know how can I extract the pvalue?

Thanks!

tristanjou
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1 Answers1

3

you can extract the a matrix of coefficients with: garch@fit$robust.matcoef (or garch@fit$matcoef but generally speaking robust errors preferred)

Then normal matrix indexing will allow you to retrieve values of interest, such that for retrieving p-values, you will want the retrieve the fourth column as follows:

garch@fit$robust.matcoef[,4]

Hope this helps.

Paul
  • 75
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