how to interpret my GARCH model

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sayedkifayatshah
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Joined: Fri Feb 09, 2018 4:28 am

how to interpret my GARCH model

Postby sayedkifayatshah » Wed Feb 14, 2018 11:48 pm

hope all you will be fine....
i am new to Eviews i found the result by using ARCH model so PLZ tell me whether it z right or wrong so that i can move futher all of my series are stationary...

Dependent Variable: RETURN
Method: ML ARCH - Normal distribution (BFGS / Marquardt steps)
Date: 02/11/18 Time: 22:09
Sample (adjusted): 2001M02 2015M12
Included observations: 179 after adjustments
Convergence achieved after 23 iterations
Coefficient covariance computed using outer product of gradients
Presample variance: backcast (parameter = 0.7)
GARCH = C(4) + C(5)*RESID(-1)^2 + C(6)*GARCH(-1)


Variable Coefficient Std. Error z-Statistic Prob.


C -0.002509 0.001124 -2.231938 0.0256
TEMPERATURE -0.000206 0.000771 -0.266568 0.7898
AR(1) 0.126613 0.073863 1.714149 0.0865


Variance Equation


C 6.05E-06 9.14E-06 0.661385 0.5084
RESID(-1)^2 0.261714 0.105648 2.477238 0.0132
GARCH(-1) 0.738516 0.088212 8.372095 0.0000


R-squared 0.028045 Mean dependent var -0.001318
Adjusted R-squared 0.017000 S.D. dependent var 0.020767
S.E. of regression 0.020590 Akaike info criterion -5.201312
Sum squared resid 0.074612 Schwarz criterion -5.094472
Log likelihood 471.5174 Hannan-Quinn criter. -5.157989
Durbin-Watson stat 1.883584


Inverted AR Roots .13

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