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Table 3 Estimation for standard HAR–GARCH(1,1)-NORMAL

From: Heterogeneous autoregressive model with structural break using nearest neighbor truncation volatility estimators for DAX

Estimation

LogRV

LogminRV

LogmedRV

θ C1

−0.535111*

(0.154328)

−0.463228*

(0.142400)

−0.463000*

(0.141844)

Heterogeneous component: θ d1,day

0.217124*

(0.033015)

0.354625*

(0.032161)

0.378463*

(0.031435)

 θ d2,day

0.128490*

(0.033799)

0.088655*

(0.036500)

0.059026

(0.035999)

 θ w1,week

0.382793*

(0.066941)

0.303845*

(0.063905)

0.327452*

(0.061893)

 θ m1,month

0.211781*

(0.043782)

0.204804*

(0.040240)

0.186657*

(0.039168)

GARCH component

 α 0

0.010513*

(0.003401)

0.037335*

(0.013389)

0.010907*

(0.004508)

 ARCH effect, α 1

0.044551*

(0.009438)

0.075417*

(0.017158)

0.047100*

(0.010372)

 GARCH effect, β 1

0.923950*

(0.015984)

0.782428*

(0.062491)

0.908679*

(0.025107)

Selection

 AIC

1.679927

1.484523

1.407996

 SIC

1.707946

1.512527

1.436000

 HIC

1.690358

1.494948

1.418421

Diagnose

 Q(10) for standardized a t

8.5638

7.3310

10.773

 Q(10) for standardized a 2 t

7.183274

4.991463

5.390689

  1. *, ** indicate 5 and 10 % level of significance respectively