Restrictions in the mean equation of a traingular BEKK
Restrictions in the mean equation of a traingular BEKK
Dear Tom Doan,
Thank you so much for your replies to my previous posts. I am now estimating a triangular BEKK model which imposes some restrictions on the variance equation. I also want the same restrictions imposed in the mean equation. However, when I estimated the model, such restrictions are not imposed on the mean equation as the model presents the full var1 results. I wanted to ask if there is a way that I can also obtain a restricted mean equation (var). If no possible, can I estimated a restricted/structural var separately for the mean equation and the model will still be valid.
Thank you
Thank you so much for your replies to my previous posts. I am now estimating a triangular BEKK model which imposes some restrictions on the variance equation. I also want the same restrictions imposed in the mean equation. However, when I estimated the model, such restrictions are not imposed on the mean equation as the model presents the full var1 results. I wanted to ask if there is a way that I can also obtain a restricted mean equation (var). If no possible, can I estimated a restricted/structural var separately for the mean equation and the model will still be valid.
Thank you
Re: Restrictions in the mean equation of a traingular BEKK
Mean equations can take any form. See Mean Model in the User's Guide.
Re: Restrictions in the mean equation of a traingular BEKK
Dear Tom,
Thank you for the reply. I am now able to estimate the mean equation for the triangular BEKK model. I am also trying to perform diagnostic tests of the model for serial correlation following the instructions in the RATS user's guide. However, I am getting an error message with estimating the standard residuals. I used "stdresids=zu" in the GARCH model to estimate the standard residuals but the error message says "STD is not an option".The GARCH model is provided below with the error message. I will be glad if you could advice me on why I am getting this message.
Thank you
GARCH(model=garchm,P=1,Q=1,MV=TBEKK,ASYMMETRIC,ITERS=300,PMETHOD=BFGS,PITERS=20,rseries=rs,mvhseries=hhs,stdresids=zu,derivative=dd) / DLGSECI DLEXR DLSP500 DLCOP
## OP3. This Instruction Does Not Have An Option STD
>>>>ries=hhs,stdresids=<<<<
Thank you for the reply. I am now able to estimate the mean equation for the triangular BEKK model. I am also trying to perform diagnostic tests of the model for serial correlation following the instructions in the RATS user's guide. However, I am getting an error message with estimating the standard residuals. I used "stdresids=zu" in the GARCH model to estimate the standard residuals but the error message says "STD is not an option".The GARCH model is provided below with the error message. I will be glad if you could advice me on why I am getting this message.
Thank you
GARCH(model=garchm,P=1,Q=1,MV=TBEKK,ASYMMETRIC,ITERS=300,PMETHOD=BFGS,PITERS=20,rseries=rs,mvhseries=hhs,stdresids=zu,derivative=dd) / DLGSECI DLEXR DLSP500 DLCOP
## OP3. This Instruction Does Not Have An Option STD
>>>>ries=hhs,stdresids=<<<<
Re: Restrictions in the mean equation of a traingular BEKK
STDRESIDS was added with 9.0.
Re: Restrictions in the mean equation of a traingular BEKK
So how will I be able to estimate the standard residuals in the version 8.30 since I don't yet have access to the version 9.0?
Thank you
Thank you
Re: Restrictions in the mean equation of a traingular BEKK
Thank you Tom,
Following the version 8 user's guide, I have used the HMATRICES and RVECTORS to save the covariance matrices and the residuals. I have estimated the model as
GARCH(MODEL=GARCHM,P=1,Q=1,MV=TBEKK,ASYMMETRIC,ITERS=300,PMETHOD=BFGS,PITERS=15,MVHSERIES=hhs,hmatrices=hh,rvectors=rd) / DLGSECI DLEXR DLSP500 DLCOP
However, am not sure where the covariance matrices and residuals are saved. I checked in the series window but could not find them there. I also used the MVHSERIES option but am not sure how and where the covariance matrix is provided. I also tried using the @MVQSTAT procedure but I am getting an error message in the third step of this procedure. This is what I did and the message I obtained after step 3.
dec vect[series] zu(%nvar)
do time=%regstart(),%regend()
compute %pt(zu,time,%solve(%decomp(hh(time)),rd(time)))
## MAT15. Subscripts Too Large or Non-Positive
Am not sure why I got this message and I wanted to ask if you give me further guidance on how I go around all these.
Thank you always
Following the version 8 user's guide, I have used the HMATRICES and RVECTORS to save the covariance matrices and the residuals. I have estimated the model as
GARCH(MODEL=GARCHM,P=1,Q=1,MV=TBEKK,ASYMMETRIC,ITERS=300,PMETHOD=BFGS,PITERS=15,MVHSERIES=hhs,hmatrices=hh,rvectors=rd) / DLGSECI DLEXR DLSP500 DLCOP
However, am not sure where the covariance matrices and residuals are saved. I checked in the series window but could not find them there. I also used the MVHSERIES option but am not sure how and where the covariance matrix is provided. I also tried using the @MVQSTAT procedure but I am getting an error message in the third step of this procedure. This is what I did and the message I obtained after step 3.
dec vect[series] zu(%nvar)
do time=%regstart(),%regend()
compute %pt(zu,time,%solve(%decomp(hh(time)),rd(time)))
## MAT15. Subscripts Too Large or Non-Positive
Am not sure why I got this message and I wanted to ask if you give me further guidance on how I go around all these.
Thank you always