rugarch gives two different results based on the same model…how is that even possible?
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 [[alternative HTML version deleted]]
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