Hi R users

I'm interested in to know a bit more on what the scale parameter of
the "ugarchfit" fit.control option is about. I took a look inside the code
and i found out that the data is divided by the standard deviation when the
scale option is turned on (scale=1).

Parameters estimated are slightly different when this option is on,
compared with when it is off. I would like to get some reference in which i
can read about, just to make myself sure that i'm not missing anything when
using this option. Scaling the data provides successful estimates that
couldn't be achieved without it.
Is it recommended to leave this option on (scale=1) or just to use it
whenever is strictly necessary?

Here is the comparison i got, switching scaling option on/off.
The model is a standard Garch(1,1) with normal innovations

*The code:*

library(rugarch)
library(xts)

data(sp500ret)

 spec=ugarchspec(variance.model = list(model = "sGARCH", garchOrder =
c(1,1)),
                 mean.model = list(armaOrder = c(0,0), include.mean =
FALSE),
                 distribution.model = "norm")

 modelo=ugarchfit(spec,as.xts(sp500ret),solver = "hybrid", fit.control =
list(scale = 1))
 modelo

*Results:*

Scale Off

             Estimate  Std. Error  t value  Pr(>|t|)
omega   0.000001    0.000001   1.4048  0.16007
alpha1  0.087257    0.013596   6.4179  0.00000
beta1   0.905045    0.013744  65.8483  0.00000


Scale On

              Estimate  Std. Error  t value  Pr(>|t|)
omega   0.000001    0.000001   1.3055  0.19173
alpha1  0.087479    0.014530   6.0206  0.00000
beta1   0.905254    0.014614  61.9434  0.00000


Thanks a lot and have a great weekend.

Jaimie

-- 
*Jaimie.*

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