I have found a result that I find truly puzzling. Here is an extract from a GARCH-Analysis I have performed:
Ljung-Box Test_____R Q(10)_____0.4047773
Ljung-Box Test_____R Q(15)_____0.3371581
Ljung-Box Test_____R Q(20)_____0.4098038
Ljung-Box Test_____R^2 Q(10)___0.9935475
Ljung-Box Test_____R^2 Q(15)___0.9978561
Ljung-Box Test_____R^2 Q(20)___0.9984385
Pardon the formatting by the way. R stands for the Returns and R^2 for the squared returns. In the ACF Plots I have seen, that there is significant autocorrelation for the R^2 values. Nevertheless, this dependence would show in a significantly low p-Value (for example one below 0.05). Nonetheless I here see the exact opposite. All R^2 Values show an extremely high p-Value. How can this be? Shouldn't this mean that the Values are very independent of one another?