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Thanks for your answer Trubador. Unfortunately I could not overcome the problem...only assuming normal distribution the dcc parameters seem to have reasonable values but the problem is that the first uni-variate GARCH does not converge and therefore I can't really rely on these results, can I? (I've...

DCC add-in does not include any diagnostic tools specific to this type of models, like EViews' regular objects. You need to figure it out on your own. If you have any doubts on DCC-type models, the add-in is not the right place to start. You need to study the background first. Thanks for your insig...

Stability condition is just one of the diagnostics and it simply indicates that the estimated model is not explosive. It does not confirm that your model is robust. I believe I have to test the residuals of each univariate garch for (1) arch effects and (2) autocorrelation and also the residuals of...

Of course, it is always better to carry out simultaneous estimation if/where possible. Unfortunately, this is something the add-in cannot do at the moment due to some technical difficulties. But it is in my mind... Hello again, regarding this particular issue of "quality" i believe i will...

I was going to use RATS to estimate the GARCH-DCC buf if the add-in works with this 3-step method I will try it. Just for confirmation: Step 1: "build a separate ARMA mean model and use the residuals from that model" Step 2: "perform the univariate GARCH and obtain the residuals, cov ...

Before estimating a DCC-GARCH(1,1) model, time series have to be filtered to assure zero expected (mean) value of the time series. Usually, a bivariate Vector Autoregressive (VAR) model used to initially remove potential linear structure, then the residuals of the VAR model are used as inputs for t...