Journal of Risk
ISSN:
1465-1211 (print)
1755-2842 (online)
Editor-in-chief: Farid AitSahlia
Estimation window strategies for value-at-risk and expected shortfall forecasting
Need to know
- We apply different estimation window strategies to a set of industry-standard risk models and evaluate their forecasting accuracy.
- The choice of an estimation window strategy leads to significant performance differences.
- The results indicate that forecast combinations are the preferable estimation window strategy.
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.
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Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. Copying this content is for the sole use of the Authorised User (named subscriber), as outlined in our terms and conditions - https://www.infopro-insight.com/terms-conditions/insight-subscriptions/
If you would like to purchase additional rights please email info@risk.net