Bootstrap Inference for Risk Measures


In this project we develop and theoretically validate prediction intervals for risk measures such as Value-at-Risk and Expected Shortfall. These risk measures play a key role in recent financial legislation when it comes to determining capital requirements. Predictions for risk measures are subject to data and estimation uncertainty. To incorporate this uncertainty into the statistical analysis, we propose to construct prediction intervals by means of the bootstrap. The published simulation results are promising. Yet, there is no theoretical result in the literature underpinning the validity of this method. We aim to fill this gap.



  • Beoogd: Proefschrift


Project number


Main applicant

Dr. E.A. Beutner

Affiliated with

Maastricht University, School of Business and Economics (SBE), Department of Quantitative Economics

Team members

A.M. Heinemann


01/09/2015 to 31/08/2019