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Table 6 Estimation results for IGARCH model

From: Modeling and forecasting exchange rate volatility in Bangladesh using GARCH models: a comparison based on normal and Student’s t-error distribution

Variables

IGARCH with normal distribution

IGARCH with t-distribution

(1)

(2)

(3)

(4)

(5)

(6)

μ

0.002930*

0.002884*

0.002865*

7.55E-07*

1.53E-09

−1.19E-07

(0.000839)

(0.000920)

(0.000928)

(8.18E-08)

(9.17E-06)

(1.01E-07)

ρ 1

 

0.205516*

0.173207*

 

0.265356*

0.243118*

 

(0.056778)

(0.060553)

 

(0.011288)

(0.011705)

ρ 2

  

0.170491*

  

0.161135*

  

(0.059969)

  

(0.011974)

α

0.081458*

0.075343*

0.073077*

0.116127*

0.043758*

0.058008*

(0.012647)

(0.011661)

(0.011584)

(0.003518)

(0.002359)

(0.002924)

(1-α)

0.918542*

0.924657*

0.926923*

0.883873*

0.956242*

0.941992*

(0.012647)

(0.011661)

(0.011584)

(0.003518)

(0.002359)

(0.002924)

Q1(4)

326.39*

162.39*

90.175*

0.0026

0.0025

0.0024

Q1(8)

482.09*

263.11*

158.89*

0.0052

0.0049

0.0047

Q2(4)

38.485*

33.945*

31.662*

0.0022

0.0022

0.0022

Q2(8)

39.551*

35.027*

32.720*

0.0045

0.0045

0.0045

Log Likelihood

3861.589

3877.619

3889.840

5261.522

5069.878

5134.113

F Statistic

36.02953*

31.22263*

29.47090*

0.000558

0.000559

0.000559

Probability

0.0000

0.0000

0.0000

0.9812

0.9811

0.9811

  1. Robust Standard Errors are in Parenthesis. *** indicates significant at 10% level, ** indicates significant at 5% level and * indicates that at 1% level