EconPapers    
Economics at your fingertips  
 

Extreme Value Dependence in Financial Markets: Diagnostics, Models, and Financial Implications

Ser-Huang Poon

The Review of Financial Studies, 2004, vol. 17, issue 2, 581-610

Abstract: This article presents a general framework for identifying and modeling the joint-tail distribution based on multivariate extreme value theories. We argue that the multivariate approach is the most efficient and effective way to study extreme events such as systemic risk and crisis. We show, using returns on five major stock indices, that the use of traditional dependence measures could lead to inaccurate portfolio risk assessment. We explain how the framework proposed here could be exploited in a number of finance applications such as portfolio selection, risk management, Sharpe ratio targeting, hedging, option valuation, and credit risk analysis. Copyright 2004, Oxford University Press.

Date: 2004
References: Add references at CitEc
Citations: View citations in EconPapers (261)

Downloads: (external link)
http://hdl.handle.net/10.1093/rfs/hhg058 (text/html)
Access to full text is restricted to subscribers.

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:oup:rfinst:v:17:y:2004:i:2:p:581-610

Ordering information: This journal article can be ordered from
https://academic.oup.com/journals

Access Statistics for this article

The Review of Financial Studies is currently edited by Itay Goldstein

More articles in The Review of Financial Studies from Society for Financial Studies Oxford University Press, Journals Department, 2001 Evans Road, Cary, NC 27513 USA.. Contact information at EDIRC.
Bibliographic data for series maintained by Oxford University Press ().

 
Page updated 2025-03-19
Handle: RePEc:oup:rfinst:v:17:y:2004:i:2:p:581-610