Modified marginal expected shortfall under asymptotic dependence
J.-J. Cai,
V. Chavez-Demoulin and
A. Guillou
Biometrika, 2017, vol. 104, issue 1, 243-249
Abstract:
SUMMARY We propose an estimator of the marginal expected shortfall by considering a log transformation of a variable which has an infinite expectation. We establish the asymptotic normality of our estimator under general assumptions. A simulation study suggests that the estimation procedure is robust with respect to the choice of tuning parameters. Our estimator has lower bias and mean squared error than the empirical estimator when the latter is applicable. We illustrate our method on a tsunami dataset.
Keywords: Asymptotic dependence; Asymptotic normality; Infinite mean model; Marginal expected shortfall; Tsunami data. (search for similar items in EconPapers)
Date: 2017
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1093/biomet/asx005 (application/pdf)
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:biomet:v:104:y:2017:i:1:p:243-249.
Ordering information: This journal article can be ordered from
https://academic.oup.com/journals
Access Statistics for this article
Biometrika is currently edited by Paul Fearnhead
More articles in Biometrika from Biometrika Trust Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK.
Bibliographic data for series maintained by Oxford University Press ().