Asymmetry dynamic volatility forecast evaluations using interday and intraday data

Chin Wen Cheong, Zaidi Isa, Abu Hassan Shaari Md Nor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The accuracy of financial time series forecasts often relies on the model precision and also the availability of actual observations for forecast evaluations. This study aims to tackle these issues in order to obtain a suitable asymmetric time-varying volatility model that outperformed the forecast evaluations based on interday and intraday data. First, the model precision is examined based on the most appropriate time-varying volatility representation under the autoregressive conditional heteroscedascity framework. Second, the forecast evaluations are conducted under three loss functions using the volatility proxies and realized volatility. Finally, the empirical studies are implemented on two major financial markets and the estimated results are applied in quantifying their market risks.

Original languageEnglish
Title of host publicationISBEIA 2011 - 2011 IEEE Symposium on Business, Engineering and Industrial Applications
Pages129-134
Number of pages6
DOIs
Publication statusPublished - 2011
Event2011 IEEE Symposium on Business, Engineering and Industrial Applications, ISBEIA 2011 - Langkawi
Duration: 25 Sep 201128 Sep 2011

Other

Other2011 IEEE Symposium on Business, Engineering and Industrial Applications, ISBEIA 2011
CityLangkawi
Period25/9/1128/9/11

Fingerprint

Time series
Availability
Volatility forecasts
Forecast evaluation
Intraday data
Asymmetry
Time-varying volatility
Financial markets
Volatility models
Empirical study
Financial time series
Loss function
Realized volatility
Market risk

Keywords

  • ARCH model
  • dynamic volatility
  • realized volatility

ASJC Scopus subject areas

  • Business and International Management
  • Industrial and Manufacturing Engineering

Cite this

Cheong, C. W., Isa, Z., & Md Nor, A. H. S. (2011). Asymmetry dynamic volatility forecast evaluations using interday and intraday data. In ISBEIA 2011 - 2011 IEEE Symposium on Business, Engineering and Industrial Applications (pp. 129-134). [6088788] https://doi.org/10.1109/ISBEIA.2011.6088788

Asymmetry dynamic volatility forecast evaluations using interday and intraday data. / Cheong, Chin Wen; Isa, Zaidi; Md Nor, Abu Hassan Shaari.

ISBEIA 2011 - 2011 IEEE Symposium on Business, Engineering and Industrial Applications. 2011. p. 129-134 6088788.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Cheong, CW, Isa, Z & Md Nor, AHS 2011, Asymmetry dynamic volatility forecast evaluations using interday and intraday data. in ISBEIA 2011 - 2011 IEEE Symposium on Business, Engineering and Industrial Applications., 6088788, pp. 129-134, 2011 IEEE Symposium on Business, Engineering and Industrial Applications, ISBEIA 2011, Langkawi, 25/9/11. https://doi.org/10.1109/ISBEIA.2011.6088788
Cheong CW, Isa Z, Md Nor AHS. Asymmetry dynamic volatility forecast evaluations using interday and intraday data. In ISBEIA 2011 - 2011 IEEE Symposium on Business, Engineering and Industrial Applications. 2011. p. 129-134. 6088788 https://doi.org/10.1109/ISBEIA.2011.6088788
Cheong, Chin Wen ; Isa, Zaidi ; Md Nor, Abu Hassan Shaari. / Asymmetry dynamic volatility forecast evaluations using interday and intraday data. ISBEIA 2011 - 2011 IEEE Symposium on Business, Engineering and Industrial Applications. 2011. pp. 129-134
@inproceedings{2f6d021cce74476e853e73891ab4d7b7,
title = "Asymmetry dynamic volatility forecast evaluations using interday and intraday data",
abstract = "The accuracy of financial time series forecasts often relies on the model precision and also the availability of actual observations for forecast evaluations. This study aims to tackle these issues in order to obtain a suitable asymmetric time-varying volatility model that outperformed the forecast evaluations based on interday and intraday data. First, the model precision is examined based on the most appropriate time-varying volatility representation under the autoregressive conditional heteroscedascity framework. Second, the forecast evaluations are conducted under three loss functions using the volatility proxies and realized volatility. Finally, the empirical studies are implemented on two major financial markets and the estimated results are applied in quantifying their market risks.",
keywords = "ARCH model, dynamic volatility, realized volatility",
author = "Cheong, {Chin Wen} and Zaidi Isa and {Md Nor}, {Abu Hassan Shaari}",
year = "2011",
doi = "10.1109/ISBEIA.2011.6088788",
language = "English",
isbn = "9781457715495",
pages = "129--134",
booktitle = "ISBEIA 2011 - 2011 IEEE Symposium on Business, Engineering and Industrial Applications",

}

TY - GEN

T1 - Asymmetry dynamic volatility forecast evaluations using interday and intraday data

AU - Cheong, Chin Wen

AU - Isa, Zaidi

AU - Md Nor, Abu Hassan Shaari

PY - 2011

Y1 - 2011

N2 - The accuracy of financial time series forecasts often relies on the model precision and also the availability of actual observations for forecast evaluations. This study aims to tackle these issues in order to obtain a suitable asymmetric time-varying volatility model that outperformed the forecast evaluations based on interday and intraday data. First, the model precision is examined based on the most appropriate time-varying volatility representation under the autoregressive conditional heteroscedascity framework. Second, the forecast evaluations are conducted under three loss functions using the volatility proxies and realized volatility. Finally, the empirical studies are implemented on two major financial markets and the estimated results are applied in quantifying their market risks.

AB - The accuracy of financial time series forecasts often relies on the model precision and also the availability of actual observations for forecast evaluations. This study aims to tackle these issues in order to obtain a suitable asymmetric time-varying volatility model that outperformed the forecast evaluations based on interday and intraday data. First, the model precision is examined based on the most appropriate time-varying volatility representation under the autoregressive conditional heteroscedascity framework. Second, the forecast evaluations are conducted under three loss functions using the volatility proxies and realized volatility. Finally, the empirical studies are implemented on two major financial markets and the estimated results are applied in quantifying their market risks.

KW - ARCH model

KW - dynamic volatility

KW - realized volatility

UR - http://www.scopus.com/inward/record.url?scp=84255187498&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84255187498&partnerID=8YFLogxK

U2 - 10.1109/ISBEIA.2011.6088788

DO - 10.1109/ISBEIA.2011.6088788

M3 - Conference contribution

SN - 9781457715495

SP - 129

EP - 134

BT - ISBEIA 2011 - 2011 IEEE Symposium on Business, Engineering and Industrial Applications

ER -