Hi,
I am new to econometrics and am using the student version (so no programming or addins). I am trying to calculate conditional correlation between 2 time series (Australian and Argentian stock market index). I know that I can use ARCH estimation but it gives me something as below. I am lost at to how can I plot the conditional correlation between the two time series. The only thing I can plot is the conditional variance and conditional standard deviation Please help!!
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Dependent Variable: ARGENTINA
Method: ML - ARCH (Marquardt) - Normal distribution
Date: 07/18/15 Time: 02:10
Sample: 1/07/1997 4/28/2015
Included observations: 834
Convergence achieved after 49 iterations
Presample variance: backcast (parameter = 0.7)
GARCH = C(3) + C(4)*RESID(-1)^2 + C(5)*GARCH(-1)
Variable Coefficient Std. Error z-Statistic Prob.
AUSTRALIA 2.616632 0.011854 220.7312 0.0000
C -0.724314 0.034277 -21.13145 0.0000
Variance Equation
C 0.000310 6.80E-05 4.560587 0.0000
RESID(-1)^2 0.901517 0.172282 5.232795 0.0000
GARCH(-1) 0.075978 0.077262 0.983377 0.3254
R-squared 0.816914 Mean dependent var 6.868356
Adjusted R-squared 0.816694 S.D. dependent var 0.344671
S.E. of regression 0.147569 Akaike info criterion -2.228724
Sum squared resid 18.11803 Schwarz criterion -2.200389
Log likelihood 934.3777 Hannan-Quinn criter. -2.217860
Durbin-Watson stat 0.040681
I am new to econometrics and am using the student version (so no programming or addins). I am trying to calculate conditional correlation between 2 time series (Australian and Argentian stock market index). I know that I can use ARCH estimation but it gives me something as below. I am lost at to how can I plot the conditional correlation between the two time series. The only thing I can plot is the conditional variance and conditional standard deviation Please help!!
*****************************************************************
Dependent Variable: ARGENTINA
Method: ML - ARCH (Marquardt) - Normal distribution
Date: 07/18/15 Time: 02:10
Sample: 1/07/1997 4/28/2015
Included observations: 834
Convergence achieved after 49 iterations
Presample variance: backcast (parameter = 0.7)
GARCH = C(3) + C(4)*RESID(-1)^2 + C(5)*GARCH(-1)
Variable Coefficient Std. Error z-Statistic Prob.
AUSTRALIA 2.616632 0.011854 220.7312 0.0000
C -0.724314 0.034277 -21.13145 0.0000
Variance Equation
C 0.000310 6.80E-05 4.560587 0.0000
RESID(-1)^2 0.901517 0.172282 5.232795 0.0000
GARCH(-1) 0.075978 0.077262 0.983377 0.3254
R-squared 0.816914 Mean dependent var 6.868356
Adjusted R-squared 0.816694 S.D. dependent var 0.344671
S.E. of regression 0.147569 Akaike info criterion -2.228724
Sum squared resid 18.11803 Schwarz criterion -2.200389
Log likelihood 934.3777 Hannan-Quinn criter. -2.217860
Durbin-Watson stat 0.040681