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


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Abstract

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Type of publication Unpublished lecture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

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