TERES - Tail Event Risk Expectile Based Shortfall

30 Pages Posted: 5 Jan 2017 Last revised: 29 Jul 2020

See all articles by Philipp Gschöpf

Philipp Gschöpf

Humboldt University of Berlin

Wolfgang K. Härdle

Humboldt University of Berlin - Institute for Statistics and Econometrics; Xiamen University - Wang Yanan Institute for Studies in Economics (WISE); Charles University; Humboldt University of Berlin - Center for Applied Statistics and Economics (CASE)

Andrija Mihoci

Humboldt University of Berlin - C.A.S.E., Center for Applied Statistics and Economics

Date Written: August 28, 2015

Abstract

A flexible framework for the analysis of tail events is proposed. The framework contains tail moment measures that allow for Expected Shortfall (ES) estimation. Connecting the implied tail thickness of a family of distributions with the quantile and expectile estimation, a platform for risk assessment is provided. ES and implications for tail events under different distributional scenarios are investigated, particularly we discuss the implications of increased tail risk for mixture distributions. Empirical results from the US, German and UK stock markets, as well as for the selected currencies indicate that ES can be successfully estimated on a daily basis using a one-year time horizon across different risk levels.

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

JEL Classification: C13, C16, G20, G28

Suggested Citation

Gschöpf, Philipp and Härdle, Wolfgang K. and Mihoci, Andrija, TERES - Tail Event Risk Expectile Based Shortfall (August 28, 2015). Available at SSRN: https://ssrn.com/abstract=2892597 or http://dx.doi.org/10.2139/ssrn.2892597

Philipp Gschöpf

Humboldt University of Berlin ( email )

Unter den Linden 6
Berlin, AK Berlin 10099
Germany

Wolfgang K. Härdle (Contact Author)

Humboldt University of Berlin - Institute for Statistics and Econometrics ( email )

Unter den Linden 6
Berlin, D-10099
Germany

Xiamen University - Wang Yanan Institute for Studies in Economics (WISE) ( email )

A 307, Economics Building
Xiamen, Fujian 10246
China

Charles University ( email )

Celetná 13
Dept Math Physics
Praha 1, 116 36
Czech Republic

Humboldt University of Berlin - Center for Applied Statistics and Economics (CASE)

Unter den Linden 6
Berlin, D-10099
Germany

Andrija Mihoci

Humboldt University of Berlin - C.A.S.E., Center for Applied Statistics and Economics ( email )

Unter den Linden 6
Berlin, AK 10099
Germany

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