UM  > Faculty of Science and Technology
Residential Collegefalse
Status已發表Published
Early Warning of American Stock Market Crises Based on Volatility Model
Zhu, Simu
2022-01-14
Conference Name13th International Conference on E-Education, E-Business, E-Management, and E-Learning, IC4E 2022
Source PublicationACM International Conference Proceeding Series
Pages486-492
Conference Date14 January 2022through 17 January 2022
Conference PlaceVirtual, Online
Abstract

This paper employs ARMA-GARCH model to analyze and predict the volatility of the U.S. stock market and evaluates the effectiveness of the model using the three main stock indexes ranging from S&P, Dow Jones Industrial Average to NASDAQ Composite Index. The value at risk is estimated in this paper to give a measure of the risk of loss and an early warning for the American stock market crisis. The result shows a high risk in the overall U.S. stock market and there exists stationary, autocorrelation, and volatility clustering effect in the return series. Moreover, the volatility model has proper goodness of fit and strong robustness.

KeywordArma-garch Model Early Warning Of Crises Value At Risk Volatility Clustering Effect
DOI10.1145/3514262.3514332
URLView the original
Language英語English
Scopus ID2-s2.0-85129176849
Fulltext Access
Citation statistics
Document TypeConference paper
CollectionFaculty of Science and Technology
AffiliationUniversity of Macau, Faculty of Science and Technology, Macao
First Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Zhu, Simu. Early Warning of American Stock Market Crises Based on Volatility Model[C], 2022, 486-492.
APA Zhu, Simu.(2022). Early Warning of American Stock Market Crises Based on Volatility Model. ACM International Conference Proceeding Series, 486-492.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Zhu, Simu]'s Articles
Baidu academic
Similar articles in Baidu academic
[Zhu, Simu]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Zhu, Simu]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.