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