Sains Malaysiana 46(1)(2017): 107–116

http://dx.doi.org/10.17576/jsm-2017-4601-14

 

The HARX-GJR-GARCH skewed-t multipower realized volatility modelling for S&P 500

(Pemodelan Kemeruapan Terealisasi Pelbagai-Kuasa HARX-GJR-GARCH terpencong-t

untuk S&P 500)

 

CHIN WEN CHEONG1*, LEE MIN CHERNG2, NADIRA MOHAMED ISA1 3 & POO KUAN HOONG4

 

1Faculty of  Management, Multimedia University, 63100 Cyberjaya, Selangor Darul Ehsan, Malaysia

 

2Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Sungai Long Campus, Jalan Sungai Long, Bandar Sungai Long, 43000 Kajang, Selangor Darul Ehsan, Malaysia

 

3Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor Darul Ehsan, Malaysia

 

4The Nielsen Company (M) Sdn. Bhd., 46100 Petaling Jaya, Selangor Darul Ehsan, Malaysia

 

Diserahkan: 8 Oktober 2015/Diterima: 25 April 2016

 

ABSTRACT

The heterogeneous autoregressive (HAR) models are used in modeling high frequency multipower realized volatility of the S&P 500 index. Extended from the standard realized volatility, the multipower realized volatility representations have the advantage of handling the possible abrupt jumps by smoothing the consecutive volatility. In order to accommodate clustering volatility and asymmetric of multipower realized volatility, the HAR model is extended by the threshold autoregressive conditional heteroscedastic (GJR-GARCH) component. In addition, the innovations of the multipower realized volatility are characterized by the skewed student-t distributions. The extended model provides the best performing in-sample and out-of-sample forecast evaluations.

 

Keywords: GARCH; HAR; realized volatility

 

ABSTRAK

Model autoregresi heterogen (HAR) digunakan dalam pemodelan kemeruapan terealisasi pelbagai-kuasa untuk indeks S&P500. Lanjutan daripada kemeruapan terealisasi piawai, kemeruapan pelbagai-kuasa mempunyai kelebihan menangani kemungkinan perubahan mendadak dengan pelicinan kemeruapan berturutan. Untuk permodelan kemeruapan kelompok dan tak simetri, model HAR dilanjutkan dengan komponen autoregresi heteroskedastik bersyarat ambang (GJR-GARCH). Selain itu, inovasi kemeruapan terealisasi dicirikan dengan taburan student-t terpencong. Model lanjutan HAR memberi prestasi terbaik dalam penilaian penganggaran dan ramalan.

 

Kata kunci: GARCH; HAR; kemeruapan terealisasi

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*Pengarang untuk surat menyurat; email: wcchin@mmu.edu.my

 

 

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