Robustness and Informativeness of Systemic Risk Measures

42 Pages Posted: 14 May 2013 Last revised: 2 Apr 2017

See all articles by Gunter Löffler

Gunter Löffler

Ulm University

Peter Raupach

Deutsche Bundesbank - Research Department

Multiple version iconThere are 2 versions of this paper

Date Written: April 2, 2013


Please note that this paper has been replaced by "Pitfalls in the Use of Systemic Risk Measures," available via

Recent literature has proposed new methods for measuring the systemic risk of financial institutions based on observed stock returns. In this paper we examine the reliability and robustness of such risk measures, focusing on CoVaR, marginal expected shortfall, and option-based tail risk estimates. We show that CoVaR exhibits undesired characteristics in the way it responds to idiosyncratic risk. In the presence of contagion, the risk measures provide conflicting signals on the systemic risk of infectious and infected banks. Finally, we explore how limited data availability typical of practical applications may limit the measures’ performance. We generate systemic tail risk through positions in standard index options and describe situations in which systemic risk is misestimated by the three measures. The observations raise doubts about the informativeness of the proposed measures. In particular, a direct application to regulatory capital surcharges for systemic risk could create wrong incentives for banks.

Keywords: Systemic Risk, CoVaR, Marginal Expected Shortfall, Tail Risk

JEL Classification: G21, G28

Suggested Citation

Löffler, Gunter and Raupach, Peter, Robustness and Informativeness of Systemic Risk Measures (April 2, 2013). Available at SSRN: or

Gunter Löffler (Contact Author)

Ulm University ( email )

Ulm, D-89081
+49 731 50 23598 (Phone)
+49 731 50 23950 (Fax)

Peter Raupach

Deutsche Bundesbank - Research Department ( email )

Wilhelm-Epstein-Str. 14
Frankfurt, 60431
+49 69 9566 8536 (Phone)

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Abstract Views
PlumX Metrics