Volatility analysis of Chinese stock market using high-frequency financial big data

Tongtong Dong, Bowei Yang, Tianhai Tian

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

2 Citations (Scopus)

Abstract

With the recent development of computer technology, the high frequency financial big data have been generated timely and more conveniently. However, the particularity of high-frequency big data has raised a number of major challenges for data analysis. The existing mathematical models that were designed for analyzing daily financial data may no longer be suitable for studying high-frequency big data. To tackle this challenge, this work explores the appropriate model that is able to analyze the high-frequency financial Big Data from the Shanghai composite index. For analyzing market volatility,we conduct three comparison studies for different mathematical models. We first compare the effect of two types GARCH (generalized autoregressive conditional heteroskedasticity) models. Numerical results suggest that the volatility proxy model has a better effect than the model based on the return of Shanghai composite index. This study leads to the comparison study of the GARCH(1,1) model and GJR(1,1) (Glosten-Jagannathan-Runkle) model. The result show that the GJR(1,1)model is more efficient than the GARCH(1,1) model. Finally weintroduce the ARMA model based on the GJR volatility proxy model. Analysis results indicate that the ARMA(2,1)-GJR volatility proxy model is the most effective one to study market volatility. The volatility persistence parameter is 0.952, which is very close to 1. In addition, the p-value of the Ljung-Box test is 0.729, which suggests that this model can not only correct the problem of residual but also reflect the leverage effect and long memory character of the Chinese stock market.
Original languageEnglish
Title of host publication2015 IEEE International Conference on Smart City
EditorsChristophe Cerin, Weizhe Zhang, Hao Wang
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages769-774
Number of pages6
ISBN (Print)9781509018932
DOIs
Publication statusPublished - 2015
EventIEEE International Conference on Smart City 2015 - Chengdu, China
Duration: 19 Dec 201521 Dec 2015
https://www.computer.org/csdl/proceedings/smartcity/2015/1893/00/1893z003.pdf
https://www.computer.org/csdl/proceedings/smartcity/2015/1893/00/index.html

Conference

ConferenceIEEE International Conference on Smart City 2015
Abbreviated titleSmartCity 2015
CountryChina
CityChengdu
Period19/12/1521/12/15
OtherHeld jointly with
The 8th IEEE International Conference on Social Computing and Networking
(SocialCom 2015)
The 5th IEEE International Conference on Sustainable Computing and Communications
(SustainCom 2015)
The 2015 International Conference on Big Data Intelligence and Computing
(DataCom 2015)
The 5th International Symposium on Cloud and Service Computing
(SC2 2015)
Internet address

Keywords

  • GARCH
  • High frequency data
  • Volatility proxy

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