Table 2.

Estimation analysis

VariableReturnvnindexDigitalgsviAll
Panel 2 - 1. VAR-Granger estimation
returnVNIndex–10.182***10.182***
digitalGSVI1.9011–1.9011
VariablereturnVN30digitalGSVIAll
returnVN30–9.3026***9.3026***
digitalGSVI1.4789–1.4789
VariablereturnVN100digitalGSVIAll
returnVN100–11.051***11.051***
digitalGSVI1.8535–1.8535
VariableReturnvnindexReturnvn30Returnvn100
Coeficientt-statisticCoeficientt-statisticCoeficientt-statistic
Panel 2 - 2. OLS estimation
returnt-10.3526431***5.020.3309948***4.710.3509134***5.00
returnt-2−0.0760245−1.11−0.0627852−0.91−0.0758118−1.10
digitalGSVI−0.0018637−0.96−0.0015548−0.76−0.0015325−0.75
digitalt−1GSVI−0.0052159**−2.53−0.0052877**−2.45−0.005878***−2.72
digitalt−2GSVI0.00288541.460.00238291.150.0029051.40
Cons.0.0045067*1.770.0050915*1.900.0051313*1.92
N207207207
F-value7.76***6.93***7.83***
R-Square0.16180.14710.1630
 ClaytonGumbelGaussian
Panel 2–3. Estimated parameters of the pair variables of digitalGSVI and returnVNIndex
Parameter−0.064991−0.086†
Loglikeihood0.4553−2.277e-070.7092
Note(s):

*, **, and *** are significant at the 10, 5 and 1% levels, respectively; The null hypothesis is that the variable in the row is not a Granger cause variable in the column.; † is the fittest estimation

Source(s): the authors

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