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A Monte Carlo evaluation of non-parametric estimators of expected shortfall

Julia S. Mehlitz (Chair of Finance, Brandenburg University of Technology Cottbus-Senftenberg, Germany)
Benjamin R. Auer (Chair of Finance, Brandenburg University of Technology Cottbus-Senftenberg, Germany; Department of Finance, University of Leipzig, Germany and Research Network Area Macro, Money and International Finance, CESifo Munich, Germany)

Journal of Risk Finance

ISSN: 1526-5943

Article publication date: 16 October 2020

Issue publication date: 20 October 2020

125

Abstract

Purpose

Motivated by the growing importance of the expected shortfall in banking and finance, this study aims to compare the performance of popular non-parametric estimators of the expected shortfall (i.e. different variants of historical, outlier-adjusted and kernel methods) to each other, selected parametric benchmarks and estimates based on the idea of forecast combination.

Design/methodology/approach

Within a multidimensional simulation setup (spanned by different distributional settings, sample sizes and confidence levels), the authors rank the estimators based on classic error measures, as well as an innovative performance profile technique, which the authors adapt from the mathematical programming literature.

Findings

The rich set of results supports academics and practitioners in the search for an answer to the question of which estimators are preferable under which circumstances. This is because no estimator or combination of estimators ranks first in all considered settings.

Originality/value

To the best of their knowledge, the authors are the first to provide a structured simulation-based comparison of non-parametric expected shortfall estimators, study the effects of estimator averaging and apply the mentioned profiling technique in risk management.

Keywords

Acknowledgements

The authors would like to thank an anonymous reviewer for valuable comments and suggestions. The authors are also indebted to the Deutsche Bundesbank (Hauptverwaltung in Sachsen und Thüringen) for generous financial support.

Citation

Mehlitz, J.S. and Auer, B.R. (2020), "A Monte Carlo evaluation of non-parametric estimators of expected shortfall", Journal of Risk Finance, Vol. 21 No. 4, pp. 355-397. https://doi.org/10.1108/JRF-07-2019-0122

Publisher

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Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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