Details of Research Outputs

TitleDCC-GARCH model for market and firm-level dynamic correlation in S&P 500
Creator
Date Issued2020
Source PublicationHandbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning
ISBN9789811202391;9789811202384
Author/Editor of Source PublicationCheng Few Lee and John C Lee
Publication PlaceSingapore
PublisherWorld Scientific Publishing
Pages4421-4440
Abstract

Understanding the dynamic correlations among asset returns is essential for ascertaining the behavior of asset prices and their comovements. It also has important implications for portfolio diversification and risk management. In this chapter, we apply the DCCGARCH model pioneered by Engle (2001) and Engle and Sheppard (2002) to investigate the dynamics of correlations among S&P 500 stocks during the sub-prime crisis. Using the daily data of stocks in the S&P 500 index, we document strong evidence of persistent dynamic correlations among the returns of the index component stocks. Conditional correlations between S&P 500 index and the component stocks increase substantially during the period of sub-prime crisis, showing strong evidence of contagion. In addition, stock return variance is time-varying and peaks at the crest of financial crisis. The results show that the DCC-GARCH model is a powerful tool for forecasting return correlations and performing value-at-risk portfolio analysis.

Language英语English
KeywordContagion DCC-MVGARCH Dynamic conditional correlation Multivariate GARCH Risk management
DOI10.1142/9789811202391_0129
URLView source
Scopus ID2-s2.0-85096245888
Citation statistics
Document TypeBook chapter
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/12744
CollectionResearch outside affiliated institution
Affiliation
1.Southwestern University of Finance and Economics,Chengdu,China
2.State University of New York at Buffalo,Buffalo,United States
Recommended Citation
GB/T 7714
Chen, Peimin,Wu, Chunchi,Zhang, Ying. DCC-GARCH model for market and firm-level dynamic correlation in S&P 500. Singapore: World Scientific Publishing, 2020: 4421-4440.
Files in This Item:
There are no files associated with this item.
Related Services
Usage statistics
Google Scholar
Similar articles in Google Scholar
[Chen, Peimin]'s Articles
[Wu, Chunchi]'s Articles
[Zhang, Ying]'s Articles
Baidu academic
Similar articles in Baidu academic
[Chen, Peimin]'s Articles
[Wu, Chunchi]'s Articles
[Zhang, Ying]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Chen, Peimin]'s Articles
[Wu, Chunchi]'s Articles
[Zhang, Ying]'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.