Managing extreme risks in tranquil and volatile markets using conditional extreme value theory

Bystrom, H

Managing extreme risks in tranquil and volatile markets using conditional extreme value theory

Bystrom, H

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Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: Bystrom, H. 2005 'Managing extreme risks in tranquil and volatile markets using conditional extreme value theory', International Review of Financial Analysis, vol. 13, no. 2, pp. 459-470.
Issue Date:: 2005

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Field	Value	Language
dc.contributor.author	Bystrom, H	en_US
dc.date.accessioned	2009-12-21T02:37:17Z
dc.date.available	2009-12-21T02:37:17Z
dc.date.issued	2005	en_US
dc.identifier	2004002047	en_US
dc.identifier.citation	Bystrom, H. 2005 'Managing extreme risks in tranquil and volatile markets using conditional extreme value theory', International Review of Financial Analysis, vol. 13, no. 2, pp. 459-470.	en_US
dc.identifier.issn	1057-5219	en_US
dc.identifier.other	C1	en_US
dc.identifier.uri	http://hdl.handle.net/10453/5209
dc.description.abstract	Financial risk management typically deals with low-probability events in the tails of asset price distributions. To capture the behavior of these tails, one should therefore rely on models that explicitly focus on the tails. Extreme value theory (EVT)-based models do exactly that, and in this paper, we apply both unconditional and conditional EVT models to the management of extreme market risks in stock markets. We find conditional EVT models to give particnlarly accurate Valueat- Risk (VaR) measures, and a comparison with traditional (Generalized ARCH (GARCH)) approaches to calculate VaR demonstrates EVT as being the superior approach both for standard and more extreme VaR quantiles.	en_US
dc.publisher	Elsevier	en_US
dc.relation.ispartof	International Review of Financial Analysis	en_US
dc.relation.isbasedon	http://dx.doi.org/10.1016/j.ijresmar.2005.09.003	en_US
dc.title	Managing extreme risks in tranquil and volatile markets using conditional extreme value theory	en_US
dc.type	Journal article
utslib.citation.volume	13	en_US
utslib.citation.number	2	en_US
utslib.location	Amsterdam, The Netherlands	en_US
utslib.citation.startpage	459	en_US
utslib.citation.endpage	470	en_US
utslib.identifier.org	Marketing	en_US
utslib.copyright.status	closed_access
pubs.declined	1970-01-01T00:00:00.0+1000

Abstract:

Financial risk management typically deals with low-probability events in the tails of asset price distributions. To capture the behavior of these tails, one should therefore rely on models that explicitly focus on the tails. Extreme value theory (EVT)-based models do exactly that, and in this paper, we apply both unconditional and conditional EVT models to the management of extreme market risks in stock markets. We find conditional EVT models to give particnlarly accurate Valueat- Risk (VaR) measures, and a comparison with traditional (Generalized ARCH (GARCH)) approaches to calculate VaR demonstrates EVT as being the superior approach both for standard and more extreme VaR quantiles.

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http://hdl.handle.net/10453/5209