Testing for changes in (extreme) VaR

Yannick Hoga

Econometrics Journal, 2017, vol. 20, issue 1, 23-51

Abstract: In this paper, we develop tests for a change in an unconditional small quantile (Value‐at‐Risk, VaR, in financial time series analysis) based on an estimator motivated by extreme value theory. This so‐called Weissman estimator allows tests to be applied for extreme VaR, where extant tests mostly fail. In view of applications, we allow for weakly dependent observations. Our test statistics rely on self‐normalization, which obviates the need to estimate the complicated asymptotic variance. Consistency is shown under local alternatives, where multiple breaks can occur. A simulation study shows that in finite samples our tests compare favourably in the tail region with extant tests based on order statistic estimators and also with tail index break tests. Two empirical examples serve to illustrate the practical use of our tests.

Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://hdl.handle.net/10.1111/ectj.12080

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:wly:emjrnl:v:20:y:2017:i:1:p:23-51

Ordering information: This journal article can be ordered from
http://onlinelibrary ... 1111/(ISSN)1368-423X

Access Statistics for this article

Econometrics Journal is currently edited by Jaap Abbring, Victor Chernozhukov, Michael Jansson and Dennis Kristensen

More articles in Econometrics Journal from Royal Economic Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().