Dependence and Systemic Risk Analysis Between S&P 500 Index and Sector Indexes: A Conditional Value-at-Risk Approach

Shoukun Jiao () and Wuyi Ye ()
Additional contact information
Shoukun Jiao: University of Science and Technology of China
Wuyi Ye: University of Science and Technology of China

Computational Economics, 2022, vol. 59, issue 3, No 13, 1203-1229

Abstract: Abstract In order to investigate the dynamic dependency structure between the S&P 500 stock index and 11 different U.S. sector indexes, and measure systemic risk. We first propose a new dynamic copula model with Markov regime-switching and macroeconomic component, and use a simulation study to verify its advantages. Macroeconomic components identified by principal component analysis and independent component analysis are added into the evolution of the copula parameter as exogenous variables to study the influence of macroeconomic factors on the interdependence between variables. Then, the estimation method of systemic risk measure conditional value-at-risk (CoVaR) in the proposed dynamic copula model is given. Finally, we provide an empirical analysis based on the above data and models. We find that when extreme events occur in the S&P500, the CoVaRs corresponding to sector indexes are distinctly time-varying, and the occurrence of major events have a greater impact on the CoVaR of each index. The consideration of Markov regime-switching parameters and macroeconomic factors improves the ability to estimate dependent structures. In addition, different macroeconomic factors have different influences on the interdependence between sector indexes and the overall S&P. U.S. unemployment rate is the most important macroeconomic factor for most sectors.

Keywords: Systemic risk; Sector indexes; CoVaR; Regime-switching copula (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10614-021-10125-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:compec:v:59:y:2022:i:3:d:10.1007_s10614-021-10125-6

Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10614/PS2

DOI: 10.1007/s10614-021-10125-6

Access Statistics for this article

Computational Economics is currently edited by Hans Amman

More articles in Computational Economics from Springer, Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().