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Table 5 Estimation for heavy-tailed jump-robust HAR–GARCH(1,1)-GED

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

Estimation

LogRV

LogminRV

LogmedRV

θ C1

−0.680556*

(0.182853)

−0.593806*

(0.169789)

−0.644560*

(0.167535)

Heterogeneous component: θ d1,day

0.243567*

(0.037212)

0.389279*

(0.035970)

0.430507*

(0.036053)

 θ d2,day

0.146830*

(0.039307)

0.070872**

(0.040519)

 

 θ w1,week

0.381336*

(0.074549)

0.310885*

(0.068611)

0.347257*

(0.053792)

 θ m1,month

0.150149*

(0.045796)

0.164232*

(0.042325)

0.150838*

(0.040687)

Break effect for

 θ break,C1

−1.228954*

(0.565831)

−1.219960**

(0.646179)

−1.109135**

(0.606410)

 θ break−d1,day

−0.068277

(0.066060)

−0.168897*

(0.070700)

−0.182183*

(0.067408)

 θ break−d2,day

−0.059649

(0.068689)

0.065739

(0.079042)

 

 θ break−w1,week

−0.129702

(0.143583)

−0.059511

(0.157710)

0.061224

(0.116876)

 θ break−m1,month

0.142415

(0.109048)

0.051767

(0.117073)

0.022046

(0.108647)

GARCH component

 α 0

0.010233*

(0.004372)

0.019657**

(0.010186)

0.010080**

(0.005338)

 ARCH effect, α 1

0.038397*

(0.011729)

0.049301*

(0.016547)

0.043678*

(0.013165)

 GARCH effect, β 1

0.930122*

(0.020874)

0.874745*

(0.050479)

0.914798*

(0.030635)

 Tail index, λ

1.517782*

(0.079217)

1.654018*

(0.082734)

1.604856*

(0.082409)

Selection

   

 AIC

1.656853

1.470345

1.392122

 SIC

1.705886

1.519378

1.434128

 HIC

1.675107

1.488599

1.407759

Diagnose

 Q(10) for standardized a t

8.2971

7.7389

14.462

 Q(10) for standardized a 2 t

8.1479

6.4542

4.6093

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