Quotation Fissler, Tobias. 2021. Backtesting Systemic Risk Forecasts using Multi-​Objective Elicitability. Talks in Financial and Insurance Mathematics, ETH Zurich, 02.12.21




Backtesting risk measure forecasts requires identifiability (for model validation) and elicitability (for model comparison). The systemic risk measures CoVaR (conditional value-​at-risk), CoES (conditional expected shortfall) and MES (marginal expected shortfall), measuring the risk of a position Y given that a reference position X is in distress, fail to be identifiable and elicitable. We establish the joint identifiability of CoVaR, MES and (CoVaR, CoES) together with the value-​at-risk (VaR) of the reference position X, but show that an analogue result for elicitability fails. The novel notion of multi-​objective elicitability however, relying on multivariate scores equipped with an order, leads to a positive result when using the lexicographic order on R^2. We establish comparative backtests of Diebold-​Mariano type for superior systemic risk forecasts and comparable VaR forecasts, accompanied by a traffic-​light approach. We demonstrate the viability of these backtesting approaches in an empirical application to DAX 30 and S&P 500 returns. The talk is based on the preprint https://arxiv.org/abs/2104.10673 which is joint work with Yannick Hoga.


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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Unpublished lecture
Language English
Title Backtesting Systemic Risk Forecasts using Multi-​Objective Elicitability
Event Talks in Financial and Insurance Mathematics
Location ETH Zurich
Event country Switzerland
Date Dec. 2, 2021
URL https://math.ethz.ch/imsf/courses/talks-in-imsf.html


Fissler, Tobias (Details)
Institute for Statistics and Mathematics IN (Details)
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