Modified marginal expected shortfall under asymptotic dependence

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Modified marginal expected shortfall under asymptotic dependence

Journal Article (2017)

Author(s)

Juanjuan Cai (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Valerie Chavez-Demoulin (University of Lausanne)

Armelle Guillou (University of Strasbourg)

Research Group

Statistics

Asymptotic normality Asymptotic dependence Infinite mean model Marginal expected shortfall Tsunami data

DOI related publication

https://doi.org/10.1093/biomet/asx005 Final published version

To reference this document use

https://resolver.tudelft.nl/uuid:dd938871-81e3-4cf4-9412-d320ca628fe4

More Info

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Publication Year

2017

Language

English

Research Group

Statistics

Journal title

Biometrika

Issue number

1

Volume number

104

Pages (from-to)

243-249

Downloads counter

155

Abstract

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.