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If you are going to test for no arch effects up to 2 lags, say, for a sample of T=3572 residuals, e, is the approach then the following: Calculate the test statistics T*R^2 where R^2 is the coefficient of determination from the regression e^2(T) = a+b*e^2(T-1)+c*e^2(T-2) <=> e^2(3572) = a+b*e^2(3571...

In order to choose between a GARCH(1,1) and a (2,2), is it enough just to compare the logL values from the two estimations? If the AIC values are also important, does anyone know how to print those in either the GARCH or the PcGive module in OxMetrics?

I just multiplied by 100 in order to avoid small numbers in the series, but you can do both

How do I determine if my estimated GARCH(1,1) model is well specified? Output: Dependent variable : 100timesLogReturn Mean Equation : ARMA (0, 0) model. No regressor in the conditional mean Variance Equation : GARCH (1, 1) model. No regressor in the conditional variance Normal distribution. Strong c...

Hi

I am trying to estimate a GARCH model on a sample of swap rates which I have attached.

I have a question regarding the dependent variable: should it be the swap rate, the daily change or the daily log change?