Publication Type

Journal Article

Version

acceptedVersion

Publication Date

10-2020

Abstract

We propose a generalized risk measure for expectile-based expected shortfall estimation. The generalization is designed with a mixture of Gaussian and Laplace densities. Our plug-in estimator is derived from an analytic relationship between expectiles and expected shortfall. We investigate the sensitivity and robustness of the expected shortfall to the underlying mixture parameter specification and the risk level. Empirical results from the US, German and UK stock markets and for selected NASDAQ blue chip companies indicate that expected shortfall can be successfully estimated using the proposed method on a monthly, weekly, daily and intra-day basis using a 1-year or 1-day time horizon across different risk levels.

Keywords

Expected Shortfall, expectiles, tail risk, risk management, tail events, tail moments

Discipline

Finance | Finance and Financial Management

Publication

Quantitative Finance

Volume

21

Issue

3

First Page

449

Last Page

460

ISSN

1469-7688

Identifier

10.1080/14697688.2020.1786151

Publisher

Taylor and Francis

Embargo Period

5-20-2022

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1080/14697688.2020.1786151

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