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Hello,
I am trying to find volatilty spillovers between two daily return series R1 and R2. So far I have run the diagonal BEKK and VECH model, but I don’t know how to interpret the results. I would really appreciate it if someone could tell me the meaning oft the coefficients.
Thank you very much!

BEKK Results

Coefficient Std. Error z-Statistic Prob.


C(1) 4.21E-05 0.000263 0.159723 0.8731
C(2) -3.89E-06 0.000276 -0.014087 0.9888


Variance Equation Coefficients


C(3) 1.59E-05 1.59E-06 9.994814 0.0000
C(4) 2.49E-05 2.22E-06 11.19050 0.0000
C(5) 3.85E-05 3.51E-06 10.95760 0.0000
C(6) 0.283965 0.011610 24.45856 0.0000
C(7) 0.401772 0.015439 26.02294 0.0000
C(8) 0.907623 0.006748 134.5016 0.0000
C(9) 0.802786 0.012726 63.08320 0.0000


Log likelihood 11645.79 Schwarz criterion -13.21817
Avg. log likelihood 3.314111 Hannan-Quinn criter. -13.23584
Akaike info criterion -13.24620



Equation: R1 = C(1)
R-squared -0.000212 Mean dependent var -0.000145
Adjusted R-squared -0.000212 S.D. dependent var 0.012839
S.E. of regression 0.012840 Sum squared resid 0.289524
Durbin-Watson stat 1.743315

Equation: R2 = C(2)
R-squared -0.000300 Mean dependent var -0.000235
Adjusted R-squared -0.000300 S.D. dependent var 0.013384
S.E. of regression 0.013386 Sum squared resid 0.314634
Durbin-Watson stat 1.857745



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) 1.59E-05 1.59E-06 9.994814 0.0000
M(1,2) 2.49E-05 2.22E-06 11.19050 0.0000
M(2,2) 3.85E-05 3.51E-06 10.95760 0.0000
A1(1,1) 0.283965 0.011610 24.45856 0.0000
A1(2,2) 0.401772 0.015439 26.02294 0.0000
B1(1,1) 0.907623 0.006748 134.5016 0.0000
B1(2,2) 0.802786 0.012726 63.08320 0.0000





VECH Results

Coefficient Std. Error z-Statistic Prob.


C(1) 4.21E-05 0.000263 0.159723 0.8731
C(2) -3.89E-06 0.000276 -0.014087 0.9888


Variance Equation Coefficients


C(3) 1.59E-05 1.59E-06 9.994814 0.0000
C(4) 2.49E-05 2.22E-06 11.19050 0.0000
C(5) 3.85E-05 3.51E-06 10.95760 0.0000
C(6) 0.283965 0.011610 24.45856 0.0000
C(7) 0.401772 0.015439 26.02294 0.0000
C(8) 0.907623 0.006748 134.5016 0.0000
C(9) 0.802786 0.012726 63.08320 0.0000


Log likelihood 11645.79 Schwarz criterion -13.21817
Avg. log likelihood 3.314111 Hannan-Quinn criter. -13.23584
Akaike info criterion -13.24620



Equation: R1 = C(1)
R-squared -0.000212 Mean dependent var -0.000145
Adjusted R-squared -0.000212 S.D. dependent var 0.012839
S.E. of regression 0.012840 Sum squared resid 0.289524
Durbin-Watson stat 1.743315

Equation: R2 = C(2)
R-squared -0.000300 Mean dependent var -0.000235
Adjusted R-squared -0.000300 S.D. dependent var 0.013384
S.E. of regression 0.013386 Sum squared resid 0.314634
Durbin-Watson stat 1.857745



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) 1.59E-05 1.59E-06 9.994814 0.0000
M(1,2) 2.49E-05 2.22E-06 11.19050 0.0000
M(2,2) 3.85E-05 3.51E-06 10.95760 0.0000
A1(1,1) 0.283965 0.011610 24.45856 0.0000
A1(2,2) 0.401772 0.015439 26.02294 0.0000
B1(1,1) 0.907623 0.006748 134.5016 0.0000
B1(2,2) 0.802786 0.012726 63.08320 0.0000