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The problem results from the fact that your garch equation generates negative variances in the forecast period. This is mainly due to change in oil prices, which you use it as an exogenous variable in your variance equation. Although the estimated coefficent value of the "oil" is 0.000767...

Good Day! I have such problem during forecasting. My model is mean equation: msft_r c nasdaq_r GARCH(1,2), no variance regressors. When I try to do static forecast i get the error "Square root of negative number". Note: this problem is reproduced for some sample periods, and for some other...

And what is matrix X in this formula, how to get it?

Hello! Can anybody help me, please? I want to know, how EViews compute forecast S.E. I found in User Guide following: For a single equation without lagged dependent variables or ARMA terms , the forecast standard errors are computed as: http://savepic.net/934995.jpg But how EViews computes forecast ...

Also you can obtain the conditional variance estimates via Proc/Make GARCH Variance Series.

Does anyone know how to pull the volatility forecast from a GARCH into a table?

Hello!
If you want to save forecast's values of garch, you need to enter some name into the textbox "GARCH(optional)" in dialog window Forecast. EViews will create new series in your workfile after it.

And for static forecasting (when we have real values of Y for forecast's period) EViews use epsilon = actual residuals ?

As in all AR dynamic forecasting, the conditional mean of the residual, which is zero. This is why dynamic AR forecasts have the original bump from the residual(s) in the presample period, then have effects which die out at the AR rate... As i understand, for forecast's period (for which real value...

I think, I understand the situation. For dynamic foresast EViews uses values of forecast S.E. as epsilon in equation for variance. So, we can do forecast for many steps, even if we don't have real values of y for forecast's period. For static forecast it uses series RESID (= real y - forecast y) as...

I think, I understand the situation. For dynamic foresast EViews uses values of forecast S.E. as epsilon in equation for variance. So, we can do forecast for many steps, even if we don't have real values of y for forecast's period. For static forecast it uses series RESID (= real y - forecast y) as ...

And if i don't have real values of y to 2009-2010, i see N/A in series GARCH from 2009 to 2010 (i make it such way: Proc / Make GARCH variance series). But i have graph of forecast of variance from 2009 to 2010 (like (4)). What is it? How EViews can do this graph, if GARCH series is N/A to forecast ...

It's the residuals. EViews stores the values into "resid" variable in your workfile after each estimation... Thanks yot very much! As i understand, RESID = real y - forecast y. So, If we don't have real values for forecast's period, - we can't compute forecast of variance on this forecast...

It's the residuals. EViews stores the values into "resid" variable in your workfile after each estimation... Thanks yot very much! As i understand, RESID = real y - forecast y. So, If we don't have real values for forecast's period, - we can't compute forecast of variance on this forecast...

It will be same as variance_0. You will use this value for all the presample variances and squared residuals: variance_-1 = variance_-2 = ... = resid^2_0 = resid^2_-1 = resid^2_-2 =... = variance_0 Thanks for you help, trubador. And, i hope, the last question )) I'm not sure, that i understand one ...

Again, the issue here is not related to EViews. Your equations are correct and the produced results look allright. EViews seems to be doing what it is supposed to be doing. You can obtain the conditional variance estimates via Proc/Make GARCH Variance Series . Also, you can generate (static/dynamic...