[R-SIG-Finance] rugarch gives two different results based on the same model…how is that even possible?
GALIB KHAN
ghk18 @ending from @c@rletm@il@rutger@@edu
Mon Aug 20 06:41:26 CEST 2018
Alexios,
Veryyyy interesting!!!!! No I cannot see any differences at all lol.
I updated the code and indeed you are correct sir. Thank you for your time
in investigating this.
I will update my stack exchange post to reflect your answer in the morning.
Again thank you for all your help!!!!
Best,
Galib Khan
On Sun, Aug 19, 2018 at 11:19 PM, alexios galanos <alexios using 4dscape.com>
wrote:
> I did use the seed you provided.
>
> Use the following code for estimation:
>
> fit <- ugarchfit(spec = spec, data = as.matrix(temp$y),solver = "nlminb",
> fit.control=list(scale=1))
>
> model_maker(var1)
> Estimate Std. Error t value Pr(>|t|)
> mu -7.3998577 0.69086641 -10.7109821 0.0000000000
> ar1 0.3387323 0.08280162 4.0908900 0.0000429721
> ar2 -0.8834201 0.06569477 -13.4473414 0.0000000000
> ma1 -0.2902069 0.08598589 -3.3750525 0.0007380161
> ma2 0.8660807 0.06778418 12.7770320 0.0000000000
> mxreg1 1.6782992 0.12769644 13.1428825 0.0000000000
> mxreg2 2.5225382 0.04292728 58.7630625 0.0000000000
> omega 12.0047145 0.82986864 14.4658010 0.0000000000
> alpha1 0.0000000 0.07358520 0.0000000 1.0000000000
> shape 63.0103309 98.49188643 0.6397515 0.5223341761
>
> model_maker(var2)
> Estimate Std. Error t value Pr(>|t|)
> mu -7.3998549 0.69086651 -10.7109764 0.000000e+00
> ar1 0.3387334 0.08280150 4.0909088 4.296861e-05
> ar2 -0.8834206 0.06569433 -13.4474406 0.000000e+00
> ma1 -0.2902081 0.08598562 -3.3750776 7.379487e-04
> ma2 0.8660811 0.06778412 12.7770487 0.000000e+00
> mxreg1 2.5225383 0.04292728 58.7630642 0.000000e+00
> mxreg2 1.6782987 0.12769640 13.1428817 0.000000e+00
> omega 12.0047142 0.82992363 14.4648419 0.000000e+00
> alpha1 0.0000000 0.07359329 0.0000000 1.000000e+00
> shape 63.0105962 98.49368444 0.6397425 5.223400e-01
>
>
> I can’t see any “significant” differences, can you?
> It’s completely related to the optimization/starting parameters. The
> “scale” is documented and not on by default (perhaps it should be).
>
> Alexios
>
>
> > On Aug 19, 2018, at 9:02 PM, GALIB KHAN <ghk18 using scarletmail.rutgers.edu>
> wrote:
> >
> > Sorry for sending this again, I didn't include r-sig-finance in the
> email address. I'm still adjusting in how to respond.
> >
> > 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.
> >
> >
> > Galib Khan
> >
> >
> > 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-
> positioning-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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