The role of model risk in extreme value theory for capital adequacy

Kellner, R; Rösch, D; Scheule, H

The role of model risk in extreme value theory for capital adequacy

Kellner, R Rösch, D Scheule, H

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Publication Type:: Journal Article
Citation:: Journal of Risk, 2016, 18 (6), pp. 39 - 70
Issue Date:: 2016-08-01

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Field	Value	Language
dc.contributor.author	Kellner, R	en_US
dc.contributor.author	Rösch, D	en_US
dc.contributor.author	Scheule, H https://orcid.org/0000-0001-7283-5654	en_US
dc.date.available	2020-05-25T19:09:23Z
dc.date.issued	2016-08-01	en_US
dc.identifier.citation	Journal of Risk, 2016, 18 (6), pp. 39 - 70	en_US
dc.identifier.issn	1465-1211	en_US
dc.identifier.uri	http://hdl.handle.net/10453/98664
dc.description.abstract	© 2016 Incisive Risk Information (IP) Limited. In the recent literature, methods from extreme value theory (EVT) have frequently been applied to the estimation of tail risk measures. While previous analyses show that EVT methods often lead to accurate estimates for risk measures, a potential drawback lies in large standard errors of the point estimates in these methods, as only a fraction of the data set is used. Thus, we comprehensively study the impact of model risk on EVT methods when determining the value-at-risk and expected shortfall. We distinguish between first-order effects of model risk, which consist of misspecification and estimation risk, and second-order effects of model risk, which refer to the dispersion of risk measure estimates, and show that EVT methods are less prone to first-order effects. However, they show a greater sensitivity toward secondorder effects.We find that this can lead to severe value-at-risk and expected shortfall underestimations and should be reflected in regulatory capital models.	en_US
dc.relation.ispartof	Journal of Risk	en_US
dc.relation.isbasedon	10.21314/JOR.2016.337	en_US
dc.title	The role of model risk in extreme value theory for capital adequacy	en_US
dc.type	Journal Article
utslib.citation.volume	6	en_US
utslib.citation.volume	18	en_US
utslib.for	1502 Banking, Finance and Investment	en_US
utslib.for	0104 Statistics	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Finance Discipline
pubs.organisational-group	/University of Technology Sydney/Strength - QFRC - Quantitative Finance Research Centre
utslib.copyright.status	open_access
pubs.issue	6	en_US
pubs.publication-status	Published	en_US
pubs.volume	18	en_US

Abstract:

© 2016 Incisive Risk Information (IP) Limited. In the recent literature, methods from extreme value theory (EVT) have frequently been applied to the estimation of tail risk measures. While previous analyses show that EVT methods often lead to accurate estimates for risk measures, a potential drawback lies in large standard errors of the point estimates in these methods, as only a fraction of the data set is used. Thus, we comprehensively study the impact of model risk on EVT methods when determining the value-at-risk and expected shortfall. We distinguish between first-order effects of model risk, which consist of misspecification and estimation risk, and second-order effects of model risk, which refer to the dispersion of risk measure estimates, and show that EVT methods are less prone to first-order effects. However, they show a greater sensitivity toward secondorder effects.We find that this can lead to severe value-at-risk and expected shortfall underestimations and should be reflected in regulatory capital models.

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http://hdl.handle.net/10453/98664