Measuring Tail Risk

Maik Dierkes; Fabian Hollstein; Marcel Prokopczuk; Christoph Matthias Würsig

doi:10.1016/j.jeconom.2024.105769

Measuring Tail Risk

Maik Dierkes^*
, Fabian Hollstein
, Marcel Prokopczuk
, Christoph Matthias Würsig

^*Corresponding author for this work

Research output: Contribution to journal › Article › Research › peer review

Abstract

We comprehensively investigate the usefulness of tail risk measures proposed in the literature. We evaluate their statistical as well as their economic validity. The option-implied measure of Bollerslev and Todorov (2011b) () performs best overall. While some other tail risk measures excel at specialized tasks, performs well in all tests: First, can predict both future tail events and future tail volatility. Second, it has predictive power for returns in both the time series and the cross-section, as well as for real economic activity. Finally, a simulation analysis shows that the main driver of performance is measurement error.

Translated title of the contribution	Messung des Tail-Risikos
Original language	English
Article number	105769
Number of pages	24
Journal	Journal of Econometrics
Volume	241
Issue number	2
DOIs	https://doi.org/10.1016/j.jeconom.2024.105769 https://doi.org/10.2139/ssrn.3789005
Publication status	Published - Apr 2024

Keywords

Return forecasting
Tail event forecasting
Tail risk
option implied
Tail events
Tail volatility

ASJC Scopus subject areas

Applied Mathematics
Economics and Econometrics

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title = "Measuring Tail Risk",

abstract = "We comprehensively investigate the usefulness of tail risk measures proposed in the literature. We evaluate their statistical as well as their economic validity. The option-implied measure of Bollerslev and Todorov (2011b) () performs best overall. While some other tail risk measures excel at specialized tasks, performs well in all tests: First, can predict both future tail events and future tail volatility. Second, it has predictive power for returns in both the time series and the cross-section, as well as for real economic activity. Finally, a simulation analysis shows that the main driver of performance is measurement error.",

keywords = "Return forecasting, Tail event forecasting, Tail risk, option implied, Tail events, Tail volatility",

author = "Maik Dierkes and Fabian Hollstein and Marcel Prokopczuk and W{\"u}rsig, \{Christoph Matthias\}",

note = "{\textcopyright} 2024 The Author(s).",

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AU - Dierkes, Maik

AU - Hollstein, Fabian

AU - Prokopczuk, Marcel

AU - Würsig, Christoph Matthias

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N2 - We comprehensively investigate the usefulness of tail risk measures proposed in the literature. We evaluate their statistical as well as their economic validity. The option-implied measure of Bollerslev and Todorov (2011b) () performs best overall. While some other tail risk measures excel at specialized tasks, performs well in all tests: First, can predict both future tail events and future tail volatility. Second, it has predictive power for returns in both the time series and the cross-section, as well as for real economic activity. Finally, a simulation analysis shows that the main driver of performance is measurement error.

AB - We comprehensively investigate the usefulness of tail risk measures proposed in the literature. We evaluate their statistical as well as their economic validity. The option-implied measure of Bollerslev and Todorov (2011b) () performs best overall. While some other tail risk measures excel at specialized tasks, performs well in all tests: First, can predict both future tail events and future tail volatility. Second, it has predictive power for returns in both the time series and the cross-section, as well as for real economic activity. Finally, a simulation analysis shows that the main driver of performance is measurement error.

KW - Return forecasting

KW - Tail event forecasting

KW - Tail risk

KW - option implied

KW - Tail events

KW - Tail volatility

UR - https://www.scopus.com/pages/publications/85193617052

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DO - 10.1016/j.jeconom.2024.105769

M3 - Article

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VL - 241

JO - Journal of Econometrics

JF - Journal of Econometrics

IS - 2

M1 - 105769

ER -

Measuring Tail Risk

Abstract

Keywords

ASJC Scopus subject areas

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