Backtesting expected shortfall and beyond

Kaihua Deng and Jie Qiu

Quantitative Finance, 2021, vol. 21, issue 7, 1109-1125

Abstract: We conduct a comprehensive study of the performance of leading backtesting procedures for expected shortfall. The tests differ in their analytical complexity, stability over different models, sensitivity to the sample sizes (both estimation and backtesting), and computational burden. The best performing scenario depends on the interaction between estimation error and backtesting error. We document that the speed of convergence to the nominal size also varies across tests. Traditional tests may fail to validate the candidate model, in which case we show that a scoring function test based on the joint elicitability of VaR-ES may have merit from a model comparison perspective.

Date: 2021
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DOI: 10.1080/14697688.2020.1834120

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