annexe 13 : estimation
du modèle avec la variable dsent
Dependent Variable: R
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Method: ML - ARCH (Marquardt) - Generalized error distribution
(GED)
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Date: 06/13/12 Time: 18:41
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Sample: 1 520
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Included observations: 520
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Convergence achieved after 73 iterations
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Presample variance: backcast (parameter = 0.7)
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GED parameter fixed at 1.5
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GARCH = C(4) + C(5)*RESID(-1)^2 + C(6)*GARCH(-1) +
C(7)*DT_DSENT2
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+
C(8)*DT1_DSENT2
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Variable
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Coefficient
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Std. Error
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z-Statistic
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Prob.
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@SQRT(GARCH)
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3.575849
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0.342221
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10.44896
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0.0000
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C
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-0.098380
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0.008214
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-11.97737
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0.0000
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DSENT
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0.001987
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0.000212
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9.383172
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0.0000
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Variance Equation
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C
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-1.01E-06
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1.21E-06
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-0.838263
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0.4019
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RESID(-1)^2
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0.020858
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0.003144
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6.633284
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0.0000
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GARCH(-1)
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0.978774
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0.004057
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241.2722
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0.0000
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DT_DSENT2
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-7.75E-08
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3.89E-08
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-1.993871
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0.0462
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DT1_DSENT2
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6.67E-07
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1.47E-07
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4.522635
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0.0000
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R-squared
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0.433196
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Mean dependent var
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-0.017887
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Adjusted R-squared
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0.431003
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S.D. dependent var
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0.026763
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S.E. of regression
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0.020188
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Akaike info criterion
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-5.010931
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Sum squared resid
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0.210703
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Schwarz criterion
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-4.945487
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Log likelihood
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1310.842
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Hannan-Quinn criter.
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-4.985294
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Durbin-Watson stat
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1.701980
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