The HARX-GJR-GARCH skewed-t multipower realized volatility modelling for S&P 500
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 sm...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Penerbit Universiti Kebangsaan Malaysia
2017
|
Online Access: | http://journalarticle.ukm.my/10599/ http://journalarticle.ukm.my/10599/ http://journalarticle.ukm.my/10599/1/14%20Chin%20Wen%20Cheong.pdf |
id |
ukm-10599 |
---|---|
recordtype |
eprints |
spelling |
ukm-105992017-08-22T00:35:12Z http://journalarticle.ukm.my/10599/ The HARX-GJR-GARCH skewed-t multipower realized volatility modelling for S&P 500 Cheong, Chin Wen Lee, Min Cherng Nadira Mohamed Isa, Poo, Kuan Hong 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. Penerbit Universiti Kebangsaan Malaysia 2017-01 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/10599/1/14%20Chin%20Wen%20Cheong.pdf Cheong, Chin Wen and Lee, Min Cherng and Nadira Mohamed Isa, and Poo, Kuan Hong (2017) The HARX-GJR-GARCH skewed-t multipower realized volatility modelling for S&P 500. Sains Malaysiana, 46 (1). pp. 107-116. ISSN 0126-6039 http://www.ukm.my/jsm/english_journals/vol46num1_2017/contentsVol46num1_2017.html |
repository_type |
Digital Repository |
institution_category |
Local University |
institution |
Universiti Kebangasaan Malaysia |
building |
UKM Institutional Repository |
collection |
Online Access |
language |
English |
description |
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. |
format |
Article |
author |
Cheong, Chin Wen Lee, Min Cherng Nadira Mohamed Isa, Poo, Kuan Hong |
spellingShingle |
Cheong, Chin Wen Lee, Min Cherng Nadira Mohamed Isa, Poo, Kuan Hong The HARX-GJR-GARCH skewed-t multipower realized volatility modelling for S&P 500 |
author_facet |
Cheong, Chin Wen Lee, Min Cherng Nadira Mohamed Isa, Poo, Kuan Hong |
author_sort |
Cheong, Chin Wen |
title |
The HARX-GJR-GARCH skewed-t multipower realized
volatility modelling for S&P 500 |
title_short |
The HARX-GJR-GARCH skewed-t multipower realized
volatility modelling for S&P 500 |
title_full |
The HARX-GJR-GARCH skewed-t multipower realized
volatility modelling for S&P 500 |
title_fullStr |
The HARX-GJR-GARCH skewed-t multipower realized
volatility modelling for S&P 500 |
title_full_unstemmed |
The HARX-GJR-GARCH skewed-t multipower realized
volatility modelling for S&P 500 |
title_sort |
harx-gjr-garch skewed-t multipower realized
volatility modelling for s&p 500 |
publisher |
Penerbit Universiti Kebangsaan Malaysia |
publishDate |
2017 |
url |
http://journalarticle.ukm.my/10599/ http://journalarticle.ukm.my/10599/ http://journalarticle.ukm.my/10599/1/14%20Chin%20Wen%20Cheong.pdf |
first_indexed |
2023-09-18T19:57:55Z |
last_indexed |
2023-09-18T19:57:55Z |
_version_ |
1777406653605347328 |