[R-SIG-Finance] Fwd: rugarch gives two different results based on the same model…how is that even possible?

[GALIB KHAN]

Galib Khan
Rutgers Business School '18
Business Analytics and Information Technology
(609) 412-3654

---------- Forwarded message ----------
From: GALIB KHAN <ghk18 using scarletmail.rutgers.edu>
Date: Sun, Aug 19, 2018 at 10:56 PM
Subject: Re: [R-SIG-Finance] rugarch gives two different results based on
the same model…how is that even possible?
To: alexios galanos <alexios using 4dscape.com>


Alexios,

Did you set the set the seed to 1, because I'm looking at your results and
the numbers do not match with the numbers that I have provided.

I understand why the coefficients' estimates are similar but it doesn't
explain why other columns such as the t-value and pr are off by a large
margin. Also estimates for mu, ar*, ma*, omega, alpha1, and shape may have
large differences.

Take mu as an example:
-7.538187e+00 - (-7.877120e+00) = 0.338933, isn't that considered a large
difference to the point where it's safe to say that these two values are
not similar?

Another example is the t-values for x1 and x2:
x1 = 8.799994e+01   -  5.509361e+02 = -462.9362
x2 = 8.508606e+01   -  5.287634e+02 = -443.6773

An more alarming case that unfortunately I cannot share due to the data
being sensitive is that when the x variables' positions are switched, the
p-values are not the same. The p-value for a particular external regressor
went from 0 to 0.4385.

I will attempt to re-create a separate generic dataset that is similar to
the sensitive data that I am using.


On Sun, Aug 19, 2018 at 10:06 PM, alexios galanos <alexios using 4dscape.com>
wrote:

> I run the code you provided and obtain the following results related to
> the external parameters:
>
>
> Case 1 (x1,x2)
> # x2 is second
>
>             Estimate   Std. Error       t value  Pr(>|t|)
> mxreg1  1.6724148 1.203377e-01  1.389767e+01 0.0000000
> mxreg2  2.5310286 1.878833e-02  1.347128e+02 0.0000000
>
> Case 2 (x2,x1)
> # i.e. x2 is now first
>
> mxreg1  2.5225382  0.04292725  58.7631024 0.000000e+00
> mxreg2  1.6782986  0.12769622  13.1428990 0.000000e+00
>
> Small differences in the coefficients are the result of the optimizer.
> There may be an issues in the
> way starting parameters are being generated based on some recent input
> from Josh Ulrich (still to investigate)
> and related to arima0 (used to generate start parameters), but otherwise
> don’t see a large problem at first glance.
>
> Alexios
>
> > On Aug 19, 2018, at 5:46 PM, GALIB KHAN <ghk18 using scarletmail.rutgers.edu>
> wrote:
> >
> > Recently I have discovered a problem with a package called rugarch that
> > creates arma-garch models. The issue is that if you literally change the
> > positions of the x variables (external regressors) then you get two
> > completely different results.
> >
> > In other words:
> >
> >   - model1 = (arma(2,2) + garch(1,0) + x1 + x2)
> >   - model2 = (arma(2,2) + garch(1,0) + x2 + x1)
> >   - rugarch's output is essentially saying that model1 != model2
> >   - When the correct result should be model1 == model2
> >
> > I may not know a lot of statistics but I know for a fact that if you move
> > the x variables around, the output should still be the same.
> >
> > Am I wrong on this?
> >
> > Here's my stack exchange post that shows a generic R script proving my
> > point: Should the positioning of the external regressors change the
> output
> > of arma-garch? (Possible rugarch bug/error)
> > <https://stackoverflow.com/questions/51900177/should-the-pos
> itioning-of-the-external-regressors-change-the-output-of-arma-garc>
> >
> > Any feedback is welcomed.
> >
> > Thanks
> >
> >       [[alternative HTML version deleted]]
> >
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>
>

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