GARCH-M with additional variables

[Nicole]

Hi,

I am trying to forecast volatility by using different models and then comparing the accuracy of the models.
I have however run into some problems with my estimations in Eviews and I am wondering if someone knows how I should proceed.

I am trying determine if the markets implied volatility has incremental information and if GARCH/EGARCH has information built in that is not given by the implied volatility.
Following the procedure of a research paper (where the authors also used Eviews) I am trying to estimate the following models.

GARCH(1.1)-M: ht^2=α0+αi ut^2+βht^2+δσt-i^2
and
EGARCH-AR(1):ln⁡(ht^2 )= α0+β ln⁡(ht^2 )+γ ut/√ht^2 +αi [|ut|/√ht^2 -√(2/π)]+δln⁡(σt1^2)

where the last term in both equations is the implied volatility

In order to check whether the GARCH(1.1)-M and EGARCH-AR(1) specifications for volatility contain information that is not impounded in implied volatilities I need to constrain the time series parameters ( β = γ = αi = 0) so that I end up with the following models:

GARCH(1.1)-M: ht^2=α0+δσt-i^2
and
EGARCH-AR(1):ln⁡(ht^2 )= α0+δln⁡(σt1^2)

How can I proceed to do this in Eviews? I have tried reading the manual and browsed the forum for days, but I cant seem to find the answer anywhere.

Appreciate all the help I can get! :)