Forecasting Variance with GARCH models

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Forecasting Variance with GARCH models

Postby 10dechile » Thu Aug 03, 2017 2:59 pm

Hello everybody,

I’m working with monthly copper returns (1990-2016) and the purpose is to obtain variance forecasts of the next month in a rolling windows framework of 1 step. My In-sample data takes returns since 1990M02 to 2006M11, so the out-sample data covers 2006M12 to 2016M11.
The problem is that obtained forecasts differ around ten times the monthly observed variance (which I defined commonly as the mean of quadratic difference between daily returns and the average of these within the month).
I programmed it, since I’m combining the garch model (with variance regressors) with a genetic algorithm. Both this and the GARCH(1,1) model exhibit the problem mentioned above.

Does someone know why that happens? I attached both files if it helps. I would be so grateful

pd: I'm using Eviews 8.1 version
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