Modified marginal expected shortfall under asymptotic dependence

Journal article (2017)

Authors

J. Cai Statistics -

Valerie Chavez-Demoulin University of Lausanne

Armelle Guillou University of Strasbourg

Research Group

Statistics () (TU Delft)

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

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

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Published Date

2017

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Delft Institute of Applied Mathematics

Research Group

Statistics

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.

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