Volatility Spillover interpretation

[angrishgd]

I am interested in applying the volatility spillover analysis between the stock markets of China, England, India and US through eviews. I have understood that the BEKK model is the best suited for my study. I have applied the model and the results are as under. Can someone please help me in interpreting the results with regard to whether there is volatility spillover from One country's market to the other's. Thanking in anticipation.

System: UNTITLED
Estimation Method: ARCH Maximum Likelihood (Marquardt)
Covariance specification: Diagonal BEKK
Date: 03/28/14 Time: 17:31
Sample: 1 2721
Included observations: 2721
Total system (balanced) observations 10884
Presample covariance: backcast (parameter =0.7)
Convergence achieved after 11 iterations

Coefficient Std. Error z-Statistic Prob.

C(1) 9.65E-05 0.000253 0.381159 0.7031
C(2) 0.000443 0.000163 2.727423 0.0064
C(3) 0.001027 0.000225 4.568439 0.0000
C(4) 0.000581 0.000167 3.485528 0.0005

Variance Equation Coefficients

C(5) 9.92E-07 2.29E-07 4.328939 0.0000
C(6) 4.96E-08 1.14E-07 0.434004 0.6643
C(7) 1.56E-07 1.77E-07 0.878782 0.3795
C(8) 2.83E-08 9.56E-08 0.296058 0.7672
C(9) 1.38E-06 2.40E-07 5.759776 0.0000
C(10) 1.19E-07 1.62E-07 0.738292 0.4603
C(11) -5.73E-08 9.43E-08 -0.607730 0.5434
C(12) 4.04E-06 5.74E-07 7.035201 0.0000
C(13) 7.28E-08 1.45E-07 0.501038 0.6163
C(14) 1.27E-06 1.91E-07 6.631599 0.0000
C(15) 0.135247 0.006847 19.75174 0.0000
C(16) 0.260990 0.010051 25.96608 0.0000
C(17) 0.279874 0.010179 27.49477 0.0000
C(18) 0.233019 0.008460 27.54520 0.0000
C(19) 0.988801 0.001171 844.1958 0.0000
C(20) 0.961126 0.002945 326.3158 0.0000
C(21) 0.952995 0.003409 279.5520 0.0000
C(22) 0.967797 0.002439 396.7849 0.0000

Log likelihood 32709.79 Schwarz criterion -23.97853
Avg. log likelihood 3.005310 Hannan-Quinn criter. -24.00904
Akaike info criterion -24.02631


Equation: CHINA = C(1)
R-squared -0.000025 Mean dependent var 0.000177
Adjusted R-squared -0.000025 S.D. dependent var 0.016240
S.E. of regression 0.016241 Sum squared resid 0.717424
Durbin-Watson stat 1.998858

Equation: ENGLAND = C(2)
R-squared -0.000507 Mean dependent var 0.000168
Adjusted R-squared -0.000507 S.D. dependent var 0.012223
S.E. of regression 0.012226 Sum squared resid 0.406605
Durbin-Watson stat 2.117826

Equation: INDIA = C(3)
R-squared -0.000481 Mean dependent var 0.000676
Adjusted R-squared -0.000481 S.D. dependent var 0.015987
S.E. of regression 0.015991 Sum squared resid 0.695494
Durbin-Watson stat 1.857892

Equation: US = C(4)
R-squared -0.000638 Mean dependent var 0.000244
Adjusted R-squared -0.000638 S.D. dependent var 0.013367
S.E. of regression 0.013371 Sum squared resid 0.486303
Durbin-Watson stat 2.169348


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) 9.92E-07 2.29E-07 4.328939 0.0000
M(1,2) 4.96E-08 1.14E-07 0.434004 0.6643
M(1,3) 1.56E-07 1.77E-07 0.878782 0.3795
M(1,4) 2.83E-08 9.56E-08 0.296058 0.7672
M(2,2) 1.38E-06 2.40E-07 5.759776 0.0000
M(2,3) 1.19E-07 1.62E-07 0.738292 0.4603
M(2,4) -5.73E-08 9.43E-08 -0.607730 0.5434
M(3,3) 4.04E-06 5.74E-07 7.035201 0.0000
M(3,4) 7.28E-08 1.45E-07 0.501038 0.6163
M(4,4) 1.27E-06 1.91E-07 6.631599 0.0000
A1(1,1) 0.135247 0.006847 19.75174 0.0000
A1(2,2) 0.260990 0.010051 25.96608 0.0000
A1(3,3) 0.279874 0.010179 27.49477 0.0000
A1(4,4) 0.233019 0.008460 27.54520 0.0000
B1(1,1) 0.988801 0.001171 844.1958 0.0000
B1(2,2) 0.961126 0.002945 326.3158 0.0000
B1(3,3) 0.952995 0.003409 279.5520 0.0000
B1(4,4) 0.967797 0.002439 396.7849 0.0000