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I mean in general I am not sure how to correct the data, do you think only excluding the outlier can be an appropriate solution?

Depends on the type of nonlinearity. Influence statistics will still be of use where you can estimate your model via NLS. In case of Markov-type switching or GARCH-type conditional variance models, however, they will not work. Outliers are specific to the model at hand regardless of the linearity a...

First of all, the mean equation is not stationary. You can add exogenous variables or use autoregressive lags to ensure the stationarity. If GARCH(1,1) model is still not able to capture the serial correlation, then it might call for a use of higher order model. This is usually the sign of time var...

Yes, it is. But it may require extensive programming. I also suggest the following approach: http://www.economics.ox.ac.uk/Nuffield-College-Economics-Working-Papers/outlier-detection-in-garch-models Thanks Trubador, the Influence Statistics that are built in Eviews to detect the outliers are suitab...

Hi Trubador, is it possible to perform outlier detection in GARCH type models with Eviews? for example based on Franses (1999) method... Im using Eviews 8, thank you.

It corresponds to E(c1t,c2t), which is equal to gamma11*gamma21 under certain conditions. If you are interested, you can also refer to Ling, S. and McAleer, M. (2002). "Necessary and Sufficient Moment Conditions for the GARCH(r,s) and Asymmetric Power GARCH(r,s) Models. Econometric Theory, v. ...

I read the paper by Trasvirta (1997) who explain how to calculate the fourth moment structure for GARCH(2,2) models but in the formula there is one thing that I dont undrestand, I attach the paper here, in that paper, equation number 36 is what I need, I undrestand it but my i dont know what is gama...

Hi, I want to test if regularity condition is satisfied in my GARCH models or not, as I know in a GARCH(1,1) model (Alpha+beta)<1 verifies the second moment condition and (3*Alpha^2+2(alpha*beta)+Alpha*beta)<1 vefiries the fourth moment condition. But the problem is that I am estimating GARCH(2,1) a...

Hi Trabadur, would you please tell me in this test number of observation matter? for example my data sample contains 5000 observations, can I use Gregory and Hansen test?
Thank you in advance

First of all, the mean equation is not stationary. You can add exogenous variables or use autoregressive lags to ensure the stationarity. If GARCH(1,1) model is still not able to capture the serial correlation, then it might call for a use of higher order model. This is usually the sign of time var...

GARCH is a flexible model and therefore there is no way to detect errors (if any) without seeing other diagnostics. You should either share the workfile along with your specifications or provide more output. Thank you very much for your reply. Here I attach my workfile, I am estimating volatility f...

Hi, I have a question regarding to the chosing error distribution for ARCH/GARCH type models. As I know, if a time series has fat tail, then it is not normally distributed and students t error distribution is more appropriate for that, but in my data when I estimate the volatility with students t I ...

My last comment was that I thanked you, it works perfectly and Im trying to modify it to the whole sample. I dont know how the above comment appeared here (about being more precise) it was one of your comments that you told me before but I really dont know how it appears here again :D thanks again I...

[quote="EViews Glenn"]Thanks. I think you're still going to have to be more precise about what you want done.

Thank you very much for you help.