Hello!
This question regards estimations in Eviews 7.
Im currently trying to estimate a diagonal BEKK-model with data consisting of two different financial series. When I run the VAR(1) model and order it by variables i get the following
A = C(1)*A(-1) + C(2)*B(-1) + C(3)
B = C(4)*A(-1) + C(5)*B(-1) + C(6)
Then when I try to estimate the equation with diag-BEKK it gives me two different errors (only one displayed each time i try)
1. "No valid observations in equation A = C(1)*A(-1) + C(2)*B(-1) + C(3)"
2. Near singular matrix
I have trouble interpreting what the first error comes from since all the observations in A are valid.
The second error of course indicates that the series are linear combinations of each other, which is possible. However i have executed the same estimation with one of the series on nonsense random numbers and Eviews still tells me "near singular matrix".
Could someone please help me explain what I am doing wrong?
I have attached the workfile
Thanks in advance!
don quixote
Singular matrix with diag BEKK estimation
Moderators: EViews Gareth, EViews Moderator
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don quixote
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Singular matrix with diag BEKK estimation
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EViews Glenn
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Re: Singular matrix with diag BEKK estimation
I get...
System: E
Estimation Method: ARCH Maximum Likelihood (Marquardt)
Covariance specification: Diagonal BEKK
Date: 04/23/12 Time: 14:54
Sample: 4/01/2002 3/26/2012
Included observations: 2606
Total system (balanced) observations 5212
Presample covariance: backcast (parameter =0.7)
Convergence achieved after 78 iterations
Coefficient Std. Error z-Statistic Prob.
C(1) -0.345363 0.055393 -6.234815 0.0000
C(2) 0.341402 0.050790 6.721766 0.0000
C(3) 7.33E-05 9.35E-05 0.783353 0.4334
C(4) 0.053304 0.058779 0.906856 0.3645
C(5) -0.059335 0.055320 -1.072577 0.2835
C(6) 7.26E-05 9.69E-05 0.748752 0.4540
Variance Equation Coefficients
C(7) 1.83E-07 1.90E-08 9.636060 0.0000
C(8) 1.89E-07 1.65E-08 11.44972 0.0000
C(9) 2.01E-07 1.71E-08 11.71918 0.0000
C(10) 0.201087 0.004807 41.83607 0.0000
C(11) 0.201092 0.005068 39.67935 0.0000
C(12) 0.978879 0.000996 983.2859 0.0000
C(13) 0.978849 0.000940 1041.545 0.0000
Log likelihood 22961.03 Schwarz criterion -17.58243
Avg. log likelihood 4.405417 Hannan-Quinn criter. -17.60109
Akaike info criterion -17.61169
Equation: A = C(1)*A(-1) + C(2)*B(-1) + C(3)
R-squared 0.021354 Mean dependent var -4.25E-05
Adjusted R-squared 0.020602 S.D. dependent var 0.007236
S.E. of regression 0.007161 Sum squared resid 0.133481
Durbin-Watson stat 1.932770
Equation: B = C(4)*A(-1) + C(5)*B(-1) + C(6)
R-squared -0.003433 Mean dependent var -3.57E-05
Adjusted R-squared -0.004204 S.D. dependent var 0.007880
S.E. of regression 0.007896 Sum squared resid 0.162298
Durbin-Watson stat 1.822000
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 z-Statistic Prob.
M(1,1) 1.83E-07 1.90E-08 9.636060 0.0000
M(1,2) 1.89E-07 1.65E-08 11.44972 0.0000
M(2,2) 2.01E-07 1.71E-08 11.71918 0.0000
A1(1,1) 0.201087 0.004807 41.83607 0.0000
A1(2,2) 0.201092 0.005068 39.67935 0.0000
B1(1,1) 0.978879 0.000996 983.2859 0.0000
B1(2,2) 0.978849 0.000940 1041.545 0.0000
System: E
Estimation Method: ARCH Maximum Likelihood (Marquardt)
Covariance specification: Diagonal BEKK
Date: 04/23/12 Time: 14:54
Sample: 4/01/2002 3/26/2012
Included observations: 2606
Total system (balanced) observations 5212
Presample covariance: backcast (parameter =0.7)
Convergence achieved after 78 iterations
Coefficient Std. Error z-Statistic Prob.
C(1) -0.345363 0.055393 -6.234815 0.0000
C(2) 0.341402 0.050790 6.721766 0.0000
C(3) 7.33E-05 9.35E-05 0.783353 0.4334
C(4) 0.053304 0.058779 0.906856 0.3645
C(5) -0.059335 0.055320 -1.072577 0.2835
C(6) 7.26E-05 9.69E-05 0.748752 0.4540
Variance Equation Coefficients
C(7) 1.83E-07 1.90E-08 9.636060 0.0000
C(8) 1.89E-07 1.65E-08 11.44972 0.0000
C(9) 2.01E-07 1.71E-08 11.71918 0.0000
C(10) 0.201087 0.004807 41.83607 0.0000
C(11) 0.201092 0.005068 39.67935 0.0000
C(12) 0.978879 0.000996 983.2859 0.0000
C(13) 0.978849 0.000940 1041.545 0.0000
Log likelihood 22961.03 Schwarz criterion -17.58243
Avg. log likelihood 4.405417 Hannan-Quinn criter. -17.60109
Akaike info criterion -17.61169
Equation: A = C(1)*A(-1) + C(2)*B(-1) + C(3)
R-squared 0.021354 Mean dependent var -4.25E-05
Adjusted R-squared 0.020602 S.D. dependent var 0.007236
S.E. of regression 0.007161 Sum squared resid 0.133481
Durbin-Watson stat 1.932770
Equation: B = C(4)*A(-1) + C(5)*B(-1) + C(6)
R-squared -0.003433 Mean dependent var -3.57E-05
Adjusted R-squared -0.004204 S.D. dependent var 0.007880
S.E. of regression 0.007896 Sum squared resid 0.162298
Durbin-Watson stat 1.822000
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 z-Statistic Prob.
M(1,1) 1.83E-07 1.90E-08 9.636060 0.0000
M(1,2) 1.89E-07 1.65E-08 11.44972 0.0000
M(2,2) 2.01E-07 1.71E-08 11.71918 0.0000
A1(1,1) 0.201087 0.004807 41.83607 0.0000
A1(2,2) 0.201092 0.005068 39.67935 0.0000
B1(1,1) 0.978879 0.000996 983.2859 0.0000
B1(2,2) 0.978849 0.000940 1041.545 0.0000
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don quixote
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- Joined: Mon Apr 23, 2012 12:48 pm
Re: Singular matrix with diag BEKK estimation
Thank you very much for your response!
When you estimated the BEKK model, did you go through the same steps as i did or am i doing something wrong?
don quixote
When you estimated the BEKK model, did you go through the same steps as i did or am i doing something wrong?
don quixote
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EViews Glenn
- EViews Developer
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- Joined: Wed Oct 15, 2008 9:17 am
Re: Singular matrix with diag BEKK estimation
I just created the system by copying the equations you provided. Clicked on Estimate, then selected BEKK. I wasn't sure if you wanted any other option changes so I just used the defaults...
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don quixote
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- Joined: Mon Apr 23, 2012 12:48 pm
Re: Singular matrix with diag BEKK estimation
Right! And when I create a system with the equations posted above and try to estimate a BEKK, I get "near singular matrix" or "no valid observations..".
Does this imply that something is wrong with my Eviews?
don quixote
Does this imply that something is wrong with my Eviews?
don quixote
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EViews Glenn
- EViews Developer
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- Joined: Wed Oct 15, 2008 9:17 am
Re: Singular matrix with diag BEKK estimation
Starting values?
Or perhaps version. What's the date on your copy of EViews?
Or perhaps version. What's the date on your copy of EViews?
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don quixote
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- Joined: Mon Apr 23, 2012 12:48 pm
Re: Singular matrix with diag BEKK estimation
Since i'm using the exact same data as posted in the workfile i guess it must be something with the verision?
Im using Eviews 7.1
don quixote
Im using Eviews 7.1
don quixote
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EViews Glenn
- EViews Developer
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Re: Singular matrix with diag BEKK estimation
Or perhaps your estimation settings. What's the build date of your copy of EViews 7.1 (Help/About EViews). I'd recommend updating and then trying again. If you're up-to-date we see if we can figure this out...
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don quixote
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- Joined: Mon Apr 23, 2012 12:48 pm
Re: Singular matrix with diag BEKK estimation
I updated my verision of Eviews and now it works. Thank you very much for your answers!
don quixote
don quixote
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