BIVARIATE GARCH BEKK
Moderators: EViews Gareth, EViews Moderator
Re: BIVARIATE GARCH BEKK
It works just fine. Could please check the build date of your EViews? (go to Help>About EViews)
Re: BIVARIATE GARCH BEKK
Dear Trubador,
Thank you for your patience and apologies for the late reply. The office closed and I did not have access to Eviews.
The build date is April 27 2015.
Thank you for your patience and apologies for the late reply. The office closed and I did not have access to Eviews.
The build date is April 27 2015.
Re: BIVARIATE GARCH BEKK
Dear Trubador,
Thanks for your patience and assistance. I have resolved it.
Thanks for your patience and assistance. I have resolved it.
Re: BIVARIATE GARCH BEKK
Dr Trubador,
I am having an issue with the estimation of the 10 minutes interval in the second sample period.
The error message is "Attempt to raise a negative number to a non integer power 
Missing data generated in "SERIES STRES1 = RES1 /(VAR_R1 ^ .5)"
Please how can I resolve this?
Thank you.
I am having an issue with the estimation of the 10 minutes interval in the second sample period.
The error message is "Attempt to raise a negative number to a non integer power 
Missing data generated in "SERIES STRES1 = RES1 /(VAR_R1 ^ .5)"
Please how can I resolve this?
Thank you.
Re: BIVARIATE GARCH BEKK
Estimated coefficients yield a negative value for the variance at some point. Change the starting values and reestimate the model until you have a statistically valid and feasible output.
Re: BIVARIATE GARCH BEKK
Thanks. It worked.
I am so grateful.
I am so grateful.

 Posts: 1
 Joined: Sat Mar 10, 2018 12:19 pm
Re: BIVARIATE GARCH BEKK
Hello. I tried to estimate a bivariate bekk model using this code but i can't understand how to interpret the result. I need to know which is diagonal and off diagonal elements of matrix alpha and matrix beta. The result show me only 3 elements and i don't know about the fourth one. I thought maybe this matrices are restricted lower or upper triangular but the methodology says that should be unrestricted. Thanks a lot for the code and for your help.

 Posts: 2
 Joined: Tue Dec 18, 2018 12:05 am
Re: BIVARIATE GARCH BEKK
Hi there,
I am a beginner to Econometrics. I use the following BEKK specification for my research work. I need some help on interpreting the estimation results.
Thanks in advance,
Fist I selected OBJECT – NEW OBJECT – SYSTEM and I typed
Ashare = C(1) + C(2)*Ashare(1)
Bshare = C(3) + C(4)*Bshare(1)
Then I selected – ESTIMATE
Estimation method – ARCHConditional Hetroscadsticity
Model Type – Diagonal BEKK
Coefficient – GARCH(1)
Error Distribution Multivariate Student t
I got the following results
System: BKK
Estimation Method: ARCH Maximum Likelihood (Marquardt)
Covariance specification: Diagonal BEKK
Date: 12/18/18 Time: 15:29
Sample: 1/02/1991 4/05/1993
Included observations: 825
Total system (balanced) observations 1650
Disturbance assumption: Student's t distribution
Presample covariance: backcast (parameter =0.7)
Convergence achieved after 38 iterations
Coefficient Std. Error zStatistic Prob.
C(1) 0.001380 0.000432 3.197118 0.0014
C(2) 0.210809 0.028350 7.435964 0.0000
C(3) 0.000837 0.000367 2.282075 0.0225
C(4) 0.384797 0.036372 10.57960 0.0000
Variance Equation Coefficients
C(5) 3.32E06 1.18E06 2.800500 0.0051
C(6) 1.88E06 6.48E07 2.903840 0.0037
C(7) 2.01E06 7.61E07 2.635640 0.0084
C(8) 0.261430 0.025739 10.15679 0.0000
C(9) 0.281633 0.030395 9.265771 0.0000
C(10) 0.964253 0.006360 151.6200 0.0000
C(11) 0.961891 0.007597 126.6087 0.0000
tDistribution (Degree of Freedom)
C(12) 5.025472 0.356657 14.09049 0.0000
Log likelihood 5023.331 Schwarz criterion 12.08009
Avg. log likelihood 3.044443 HannanQuinn criter. 12.12237
Akaike info criterion 12.14868
Equation: A = C(1) + C(2)*A(1)
Rsquared 0.011836 Mean dependent var 0.001318
Adjusted Rsquared 0.010635 S.D. dependent var 0.039861
S.E. of regression 0.039649 Sum squared resid 1.293772
DurbinWatson stat 1.272177
Equation: B = C(3) + C(4)*B(1)
Rsquared 0.033247 Mean dependent var 0.001402
Adjusted Rsquared 0.034502 S.D. dependent var 0.037716
S.E. of regression 0.038361 Sum squared resid 1.211088
DurbinWatson stat 1.065445
Covariance specification: Diagonal BEKK
GARCH = M + A1*RESID(1)*RESID(1)'*A1 + B1*GARCH(1)*B1
M is an indefinite matrix
A1 is a diagonal matrix
B1 is a diagonal matrix
Transformed Variance Coefficients
Coefficient Std. Error zStatistic Prob.
M(1,1) 3.32E06 1.18E06 2.800500 0.0051
M(1,2) 1.88E06 6.48E07 2.903840 0.0037
M(2,2) 2.01E06 7.61E07 2.635640 0.0084
A1(1,1) 0.261430 0.025739 10.15679 0.0000
A1(2,2) 0.281633 0.030395 9.265771 0.0000
B1(1,1) 0.964253 0.006360 151.6200 0.0000
B1(2,2) 0.961891 0.007597 126.6087 0.0000
What do the coefficients indicate and what coefficients indicate mean spillovers and volatility spillovers between Ashare and BShares. What do negative coefficients indicate?
Thanks in advance
I am a beginner to Econometrics. I use the following BEKK specification for my research work. I need some help on interpreting the estimation results.
Thanks in advance,
Fist I selected OBJECT – NEW OBJECT – SYSTEM and I typed
Ashare = C(1) + C(2)*Ashare(1)
Bshare = C(3) + C(4)*Bshare(1)
Then I selected – ESTIMATE
Estimation method – ARCHConditional Hetroscadsticity
Model Type – Diagonal BEKK
Coefficient – GARCH(1)
Error Distribution Multivariate Student t
I got the following results
System: BKK
Estimation Method: ARCH Maximum Likelihood (Marquardt)
Covariance specification: Diagonal BEKK
Date: 12/18/18 Time: 15:29
Sample: 1/02/1991 4/05/1993
Included observations: 825
Total system (balanced) observations 1650
Disturbance assumption: Student's t distribution
Presample covariance: backcast (parameter =0.7)
Convergence achieved after 38 iterations
Coefficient Std. Error zStatistic Prob.
C(1) 0.001380 0.000432 3.197118 0.0014
C(2) 0.210809 0.028350 7.435964 0.0000
C(3) 0.000837 0.000367 2.282075 0.0225
C(4) 0.384797 0.036372 10.57960 0.0000
Variance Equation Coefficients
C(5) 3.32E06 1.18E06 2.800500 0.0051
C(6) 1.88E06 6.48E07 2.903840 0.0037
C(7) 2.01E06 7.61E07 2.635640 0.0084
C(8) 0.261430 0.025739 10.15679 0.0000
C(9) 0.281633 0.030395 9.265771 0.0000
C(10) 0.964253 0.006360 151.6200 0.0000
C(11) 0.961891 0.007597 126.6087 0.0000
tDistribution (Degree of Freedom)
C(12) 5.025472 0.356657 14.09049 0.0000
Log likelihood 5023.331 Schwarz criterion 12.08009
Avg. log likelihood 3.044443 HannanQuinn criter. 12.12237
Akaike info criterion 12.14868
Equation: A = C(1) + C(2)*A(1)
Rsquared 0.011836 Mean dependent var 0.001318
Adjusted Rsquared 0.010635 S.D. dependent var 0.039861
S.E. of regression 0.039649 Sum squared resid 1.293772
DurbinWatson stat 1.272177
Equation: B = C(3) + C(4)*B(1)
Rsquared 0.033247 Mean dependent var 0.001402
Adjusted Rsquared 0.034502 S.D. dependent var 0.037716
S.E. of regression 0.038361 Sum squared resid 1.211088
DurbinWatson stat 1.065445
Covariance specification: Diagonal BEKK
GARCH = M + A1*RESID(1)*RESID(1)'*A1 + B1*GARCH(1)*B1
M is an indefinite matrix
A1 is a diagonal matrix
B1 is a diagonal matrix
Transformed Variance Coefficients
Coefficient Std. Error zStatistic Prob.
M(1,1) 3.32E06 1.18E06 2.800500 0.0051
M(1,2) 1.88E06 6.48E07 2.903840 0.0037
M(2,2) 2.01E06 7.61E07 2.635640 0.0084
A1(1,1) 0.261430 0.025739 10.15679 0.0000
A1(2,2) 0.281633 0.030395 9.265771 0.0000
B1(1,1) 0.964253 0.006360 151.6200 0.0000
B1(2,2) 0.961891 0.007597 126.6087 0.0000
What do the coefficients indicate and what coefficients indicate mean spillovers and volatility spillovers between Ashare and BShares. What do negative coefficients indicate?
Thanks in advance

 Posts: 2
 Joined: Tue Dec 18, 2018 12:05 am
Re: BIVARIATE GARCH BEKK
Hi
Should the sum of ARCH and GARCH coefficients of Diagonal BEKK (GARCH(1)) be less than unity ?
Thanks
Should the sum of ARCH and GARCH coefficients of Diagonal BEKK (GARCH(1)) be less than unity ?
Thanks
Re: BIVARIATE GARCH BEKK
Hi there,
I have the same question as you. Do you figure it out now? If yes, can you please tell me how to interpret estimation results？Thanks a lot！！！
I have the same question as you. Do you figure it out now? If yes, can you please tell me how to interpret estimation results？Thanks a lot！！！
terrytrausith wrote:Hi there,
I am a beginner to Econometrics. I use the following BEKK specification for my research work. I need some help on interpreting the estimation results.
Thanks in advance,
Fist I selected OBJECT – NEW OBJECT – SYSTEM and I typed
Ashare = C(1) + C(2)*Ashare(1)
Bshare = C(3) + C(4)*Bshare(1)
Then I selected – ESTIMATE
Estimation method – ARCHConditional Hetroscadsticity
Model Type – Diagonal BEKK
Coefficient – GARCH(1)
Error Distribution Multivariate Student t
I got the following results
System: BKK
Estimation Method: ARCH Maximum Likelihood (Marquardt)
Covariance specification: Diagonal BEKK
Date: 12/18/18 Time: 15:29
Sample: 1/02/1991 4/05/1993
Included observations: 825
Total system (balanced) observations 1650
Disturbance assumption: Student's t distribution
Presample covariance: backcast (parameter =0.7)
Convergence achieved after 38 iterations
Coefficient Std. Error zStatistic Prob.
C(1) 0.001380 0.000432 3.197118 0.0014
C(2) 0.210809 0.028350 7.435964 0.0000
C(3) 0.000837 0.000367 2.282075 0.0225
C(4) 0.384797 0.036372 10.57960 0.0000
Variance Equation Coefficients
C(5) 3.32E06 1.18E06 2.800500 0.0051
C(6) 1.88E06 6.48E07 2.903840 0.0037
C(7) 2.01E06 7.61E07 2.635640 0.0084
C(8) 0.261430 0.025739 10.15679 0.0000
C(9) 0.281633 0.030395 9.265771 0.0000
C(10) 0.964253 0.006360 151.6200 0.0000
C(11) 0.961891 0.007597 126.6087 0.0000
tDistribution (Degree of Freedom)
C(12) 5.025472 0.356657 14.09049 0.0000
Log likelihood 5023.331 Schwarz criterion 12.08009
Avg. log likelihood 3.044443 HannanQuinn criter. 12.12237
Akaike info criterion 12.14868
Equation: A = C(1) + C(2)*A(1)
Rsquared 0.011836 Mean dependent var 0.001318
Adjusted Rsquared 0.010635 S.D. dependent var 0.039861
S.E. of regression 0.039649 Sum squared resid 1.293772
DurbinWatson stat 1.272177
Equation: B = C(3) + C(4)*B(1)
Rsquared 0.033247 Mean dependent var 0.001402
Adjusted Rsquared 0.034502 S.D. dependent var 0.037716
S.E. of regression 0.038361 Sum squared resid 1.211088
DurbinWatson stat 1.065445
Covariance specification: Diagonal BEKK
GARCH = M + A1*RESID(1)*RESID(1)'*A1 + B1*GARCH(1)*B1
M is an indefinite matrix
A1 is a diagonal matrix
B1 is a diagonal matrix
Transformed Variance Coefficients
Coefficient Std. Error zStatistic Prob.
M(1,1) 3.32E06 1.18E06 2.800500 0.0051
M(1,2) 1.88E06 6.48E07 2.903840 0.0037
M(2,2) 2.01E06 7.61E07 2.635640 0.0084
A1(1,1) 0.261430 0.025739 10.15679 0.0000
A1(2,2) 0.281633 0.030395 9.265771 0.0000
B1(1,1) 0.964253 0.006360 151.6200 0.0000
B1(2,2) 0.961891 0.007597 126.6087 0.0000
What do the coefficients indicate and what coefficients indicate mean spillovers and volatility spillovers between Ashare and BShares. What do negative coefficients indicate?
Thanks in advance
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