January effect with GARCH

[selatsa]

Hi,
I'm using EViews 7 student version.
In my attempt to analyse the January effect of a stock market using the GARCH/TARCH model, I had the following output:

Dependent Variable: EGY(-1)
Method: ML - ARCH (Marquardt) - Normal distribution
Date: 01/13/15 Time: 07:28
Sample (adjusted): 2001M03 2011M07
Included observations: 125 after adjustments
Convergence achieved after 38 iterations
Presample variance: backcast (parameter = 0.7)
GARCH = C(13) + C(14)*RESID(-1)^2 + C(15)*RESID(-1)^2*(RESID(-1)<0)
+ C(16)*GARCH(-1)

Variable Coefficient Std. Error z-Statistic Prob.

C 0.006684 0.020732 0.322397 0.7472
@MONTH=1 0.036563 0.036665 0.997227 0.3187
@MONTH=2 0.074451 0.023961 3.107213 0.0019
@MONTH=3 0.035183 0.028826 1.220547 0.2223
@MONTH=4 -0.008514 0.030051 -0.283306 0.7769
@MONTH=5 0.041190 0.028369 1.451975 0.1465
@MONTH=6 -0.015104 0.027849 -0.542345 0.5876
@MONTH=7 -0.006468 0.032722 -0.197657 0.8433
@MONTH=8 0.009943 0.029611 0.335793 0.7370
@MONTH=9 0.002774 0.026975 0.102827 0.9181
@MONTH=10 0.057661 0.027445 2.100977 0.0356
@MONTH=11 0.022256 0.030746 0.723872 0.4691

Variance Equation

C 0.001472 0.000867 1.697470 0.0896
RESID(-1)^2 0.435893 0.288750 1.509586 0.1311
RESID(-1)^2*(RESID(-1)<0) 0.471245 0.465290 1.012797 0.3112
GARCH(-1) 0.167442 0.211303 0.792426 0.4281

R-squared 0.019959 Mean dependent var 0.016510
Adjusted R-squared -0.075444 S.D. dependent var 0.081123
S.E. of regression 0.084128 Akaike info criterion -2.239231
Sum squared resid 0.799759 Schwarz criterion -1.877207
Log likelihood 155.9519 Hannan-Quinn criter. -2.092160
Durbin-Watson stat 1.027764

Please can anyone tell me if it's correct? and how do I interpret this?
It's my thesis and my deadline for submision is overdue.
thannks.