Table VI.

ARCH and GARCH models considered more efficient

ModelVariance equationProbabilityDistributionStandard errorAICBICHQARCH – LM test
TR2Probability χ2
D(TIRUSSIA)EGARCH (1.2)ω−0.71450.0000t-Student0.000−19.131−19.119−19.1260.2280.633
α0.45380.0000
γ0.56100.0000
β10.64310.0000
β20.33620.0000
D(MIBOR)EGARCH (2.2)ω−0.26710.0000t-Student0.000−21.694−21.681−21.6890.1950.658
α14.79270.0000
α2−4.04020.0000
γ−0.10650.0053
β11.43640.0000
β2−0.44520.0000
D(SHIBOR)EGARCH (2.2)ω−0.07780.0000t-Student0.000−22.691−22.663−22.6800.0880.767
α12.00930.0004
α2−1.82520.0004
γ0.08380.0006
β11.50780.0000
β2−0.50890.0000
D(TICHILE)ARCH (1)α00.00000.0000t-Student0.000−22.663−22.657−22.6610.2360.878
α10.17140.0000
D(BAIBOR)ARCH (4)α00.00000.0000t-Student0.000−23.189−23.179−23.1850.2190.640
α10.74450.0000
α20.24080.0000
α30.17440.0000
α40.31860.0000
D(TIIE)EGARCH (2.2)ω−0.08380.0000t-Student0.000−23.900−23.886−23.8950.0000.994
α10.21860.0000
α2−0.05470.0334
γ−0.01690.0472
β10.42370.0000
β20.57740.0000
D(FFUNDS)EGARCH (2.1)ω0.02040.0000t-Student0.000−24.563−24.555−24.5600.3890.533
α14.22650.0000
α2−3.87360.0000
γ0.33500.0000
β11.00250.0000
D(EURIBOR)EGARCH (2.1)ω−8.90480.0000t-Student0.000−23.759−23.748−23.7552.4320.119
α110.53110.0906
α2−2.43220.0944
γ−1.26290.0965
β10.61680.0000
D(TMIR)EGARCH (2.2)ω0.00340.0000t-Student0.000−29.346−29.332−29.3410.0070.932
α14.35940.0000
α2−3.30880.0000
γ−1.05110.0000
β11.18170.0000
β2−0.17950.0000

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