The RATS Software Forum

Thank you for your reply.
I want to perform a test on the residuals of VECM model and for doing this test standard deviation of these residuals should be equal to one. Do you mean that VECM residuals are standardized?

Dear Tom,

I would be grateful if you could possibly guide me how I can get standardized residuals fro a VECM model. I can get residuals from estimate procedure but I not sure if they are standardized or not.

TomDoan wrote: If you choose a large lag length and reject non-causality, it's safe to assume that that isn't because the lag length is too long.

You mean that the results of the Granger causaity test in this case (rejectiing non-causality) isn't necessarily coreect?

VAR lag selection for Granger causality: Dear Tom, I can see that in some papers like this (Hiemstra and Jones 1994, The Journal of Finance) and this (Fujihara and Mougoue 1997, The Journal of Futures Markets) there has been used many lags for performing linear Granger causality. Do you recommend us...

Thank you for your reply Tom. Diks and Panchenko (2005, 2006) demonstrate that the relationship tested by Hiemstra and Jones test is not generally compatible with Granger causality, leading to the possibility of spurious rejections of the null hypothesis. And As an alternative Diks and Panchenko (20...

Dear Tom, Thank you for all your help and guidance. If all you're trying to do is a causality test, then estimate the EC model by least squares and compute Eicker-White standard errors to deal with heteroscedasticity of unknown form (ROBUSTERRORS option) and then jointly test the lagged differences ...

Dear Tom,

I am studying GARCH e-course workbook. In page 84 it is said that"...if we were using a VAR with lags, we would need to include DFC option on @MVQSTAT ...".
I have a question. If is just estimate a VAR model without GARCH errors, do I still need to include DFC option?

Dear Tom, thank you very much for your reply.
Is there any way to define a VECM model in such a way that residuals of each equation (dependent series) to follow a univariate GARCH(1,1) model (or any ARCH process) with cross variable as an explanatory variable?

Tom,
How can I use @BDStest in RATS 9? When I run it got the following error: cp24. Procedure/function BDStest compiled with errors. Please correct.
should I install it first?

Dear Tom, I dropped early observation from data set and now it starts from entry 150 (which avoids the early outlier). According to ACI criterion, I estimated VECM model with 14 lags (cointegraing vector is (1,-1)). But the loading on ETC terms show that only one of them is (marginally) significant ...

Thank you very much for your insightful help. I really appreciate it. Unlike spot market that is not controlled and prices can fluctuate freely, futures market is controlled and futures prices can increase (decreae) just 5(-5) percent each trading day.In some time periods, spot market has experience...

Dear Tom, I apologize for making many questions about a simple project. @johmle with DET=CONSTANT shows variables aren't cointegrated. But, @johmle with DET=RC shows variables are cointerated (and @johmle with DET=Trend gives the same results). Now I use economic theory for determining cointegrating...

Tom, To tell the truth, I am REALLY confused about my project. Here is the data. I am not sure if I should a USE CONSTANT or TREND or RC IN THE @JOHMLE. I would be grateful if you could have a look at my data. I edited the code, I hope it is correct this time: @johmle(lags=8,det=rc,cv=cv) # lx ly * ...

I am working with different data sets. In the new data set, variables don't have a clear trend (sustained tendency for the variables to increase or decrease). Therefore, I should use DET=RC in the @johmle. But I got that error when I run the model.

Dear Tom, I wanted to run the below code but I got this error: ## MAT5. Needed Matrix with Dimensions 2 x 1, Got 3 x 1 Instead. I tried to fix it but unfortunately I couldn't do it. * returns set lx = lx*100.0 set ly = ly*100 set dlx = lx-lx{1} set dly = ly-ly{1} @johmle(lags=4,det=rc,cv=cv) # lx ly...