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How do you compute the standard errors of a GARCH model estimated with MLE ?

This paper references a method by Bollerslev-Wooldridge: [...] and computed standard errors using the robust method of Bollerslev-Wooldridge

Do you know of an implementation of this method (whatever the language)?

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The fGarch package function garchFit() provides this functionality if you call it with cond.dist = 'QMLE'. Check out the documentation on the CRAN page.

"QMLE" stands for Quasi-Maximum Likelihood Estimation, which assumes normal distribution and uses robust standard errors for inference. Bollerslev and Wooldridge (1992) proved that if the mean and the volatility equations are correctly specified, the QML estimates are consistent and asymptotically normally distributed...

The documentation references the following book: Econometric Theory and Methods - Russell Davidson & James G. Mackinnon (section 10.3 and 10.4) and has some more details.

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    $\begingroup$ The documentation references the following book: Econometric Theory and Methods - Russell Davidson & James G. Mackinnon (section 10.3 and 10.4) $\endgroup$ – Maxime Jan 25 at 9:08
  • $\begingroup$ Good addition, added $\endgroup$ – Bob Jansen Jan 25 at 9:51

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