Estimation Window Strategies for Value-at-Risk and Expected Shortfall Forecasting

50 Pages Posted: 28 Jun 2018

See all articles by Tobias Berens

Tobias Berens

University TU Dortmund; zeb/rolfes.schierenbeck.associates

Gregor N. F. Weiss

University of Leipzig - Faculty of Economics and Management Science

Daniel Ziggel

FOM Fachhochschule für Oekonomie & Management gGmbH

Date Written: March 23, 2017

Abstract

Compared with the large number of value-at-risk (VaR) and expected shortfall (ES) forecasting models proposed in the literature, few contributions have been made to address the question of which estimation window strategy is preferable for forecasting these risk measures. To fill this gap, we apply different estimation window strategies to a set of simple parametric, semiparametric and nonparametric industry-standard risk models. Analyzing daily return data on constituents of the German Deutscher Aktienindex (DAX), we evaluate forecasts by backtesting the unconditional coverage and independent and identically distributed properties of VaR violations, the ES forecasting accuracy and the conditional predictive ability. We thereby demonstrate that the selection of the estimation window strategy leads to significant performance differences. The results indicate that forecast combinations are the preferable estimation window strategy.

Keywords: Value-at-Risk (VaR), Estimation Window, Forecasting, Expected Shortfall (ES), Backtesting

Suggested Citation

Berens, Tobias and Berens, Tobias and Weiss, Gregor N. F. and Ziggel, Daniel, Estimation Window Strategies for Value-at-Risk and Expected Shortfall Forecasting (March 23, 2017). Journal of Risk, Vol. 20, No. 5, 2018, Available at SSRN: https://ssrn.com/abstract=3202803

Tobias Berens

University TU Dortmund ( email )

Emil-Figge-Straße 50
Dortmund, 44227
Germany

zeb/rolfes.schierenbeck.associates ( email )

Hammer Straße 165
Münster, 48149
Germany

Gregor N. F. Weiss (Contact Author)

University of Leipzig - Faculty of Economics and Management Science ( email )

Grimmaische Str. 12
Leipzig, 04109
Germany
+49 341 97 33821 (Phone)
+49 341 97 33829 (Fax)

HOME PAGE: http://www.wifa.uni-leipzig.de/nfdl

Daniel Ziggel

FOM Fachhochschule für Oekonomie & Management gGmbH ( email )

Herkulesstrasse 32
Essen, 45127
Germany

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