New hybrid methodology for stock volatility prediction

Chih Hsiung Tseng; Sheng Tzong Cheng; Yi Hsien Wang

doi:10.1016/j.eswa.2007.12.004

New hybrid methodology for stock volatility prediction

Chih Hsiung Tseng, Sheng Tzong Cheng, Yi Hsien Wang

Department of Computer Science and Information Engineering

Research output: Contribution to journal › Article › peer-review

23 Citations (Scopus)

Abstract

Modeling and forecasting stock market volatility have received considerable attention by both academics and practitioners. Hence, this paper presents integrated model to improve the variance forecasting ability in variance as compared to the traditional GARCH. Overall, the results show that the new integrated model can enhance the volatility forecasting ability of the traditional GARCH.

Original language	English
Pages (from-to)	1833-1839
Number of pages	7
Journal	Expert Systems With Applications
Volume	36
Issue number	2 PART 1
DOIs	https://doi.org/10.1016/j.eswa.2007.12.004
Publication status	Published - 2009 Mar

All Science Journal Classification (ASJC) codes

Engineering(all)
Computer Science Applications
Artificial Intelligence

Access to Document

10.1016/j.eswa.2007.12.004

Cite this

@article{9be378c2ca974c4bb9494e9e2de35bdd,

title = "New hybrid methodology for stock volatility prediction",

abstract = "Modeling and forecasting stock market volatility have received considerable attention by both academics and practitioners. Hence, this paper presents integrated model to improve the variance forecasting ability in variance as compared to the traditional GARCH. Overall, the results show that the new integrated model can enhance the volatility forecasting ability of the traditional GARCH.",

author = "Tseng, {Chih Hsiung} and Cheng, {Sheng Tzong} and Wang, {Yi Hsien}",

year = "2009",

month = mar,

doi = "10.1016/j.eswa.2007.12.004",

language = "English",

volume = "36",

pages = "1833--1839",

journal = "Expert Systems with Applications",

issn = "0957-4174",

publisher = "Elsevier Limited",

number = "2 PART 1",

}

TY - JOUR

T1 - New hybrid methodology for stock volatility prediction

AU - Tseng, Chih Hsiung

AU - Cheng, Sheng Tzong

AU - Wang, Yi Hsien

PY - 2009/3

Y1 - 2009/3

N2 - Modeling and forecasting stock market volatility have received considerable attention by both academics and practitioners. Hence, this paper presents integrated model to improve the variance forecasting ability in variance as compared to the traditional GARCH. Overall, the results show that the new integrated model can enhance the volatility forecasting ability of the traditional GARCH.

AB - Modeling and forecasting stock market volatility have received considerable attention by both academics and practitioners. Hence, this paper presents integrated model to improve the variance forecasting ability in variance as compared to the traditional GARCH. Overall, the results show that the new integrated model can enhance the volatility forecasting ability of the traditional GARCH.

UR - http://www.scopus.com/inward/record.url?scp=56349112440&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=56349112440&partnerID=8YFLogxK

U2 - 10.1016/j.eswa.2007.12.004

DO - 10.1016/j.eswa.2007.12.004

M3 - Article

AN - SCOPUS:56349112440

VL - 36

SP - 1833

EP - 1839

JO - Expert Systems with Applications

JF - Expert Systems with Applications

SN - 0957-4174

IS - 2 PART 1

ER -

New hybrid methodology for stock volatility prediction

Abstract

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this