rugarch gives two different results based on the same model…how is that even possible?

On Aug 19, 2018, at 9:02 PM, GALIB KHAN <ghk18 at 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 at 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 at 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

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