Measuring and Testing for the Systemically Important Financial Institutions

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte.

Systemic Risk: Time-Lags and Persistence

“…Moreover, CoVaR r I ≤V aR(0.01) has an enormously large estimation error: For some institutions the mean absolute error is 100 times as large as the mean value of the systemic risk measure. This result highly questions the use of CoVaR r I ≤V aR(0.01) and, thus, is in line with the findings of Castro and Ferrari (2012), and Guntay and Kupiec (2014 …”

“…Moreover, several studies indicate that the estimation error of ∆CoVaR = makes it a rather unreliable systemic risk measure (for example see Castro and Ferrari (2012), or Guntay and Kupiec (2014)). As a consequence, we develop a risk measure that exhibits a smaller estimation error and that is, thus, more reliable.…”

Network, market, and book-based systemic risk rankings

“…As the expected shortfall of the market is common to all firms, MES and beta should lead to similar systemic risk rankings. Analogously, Benoit et al (2015) show that the ∆CoVaR of Adrian and Brunnermeier (2014) and Castro and Ferrari (2014)) is a linear transformation of the Value-at-Risk of Adams et al (2014) and White et al (2015), where the coefficients in the linear relation are common across all firms. This reduces a large number of familiar risk ranking methods to a much smaller number, namely the firm's beta and its VaR.…”

“…Despite their popularity to track financial interconnectedness, it is still unclear whether network based ranking measures add significantly to simpler measures, such as Marginal Expected Shortfall (MES) of Acharya et al (2010), ∆CoVaR of Adrian and Brunnermeier (2014) and Castro and Ferrari (2014), or $ We thank participants of the SYRTO seminar for their helpful comments and useful suggestions and comments. We thank the European Union Seventh Framework Programme (FP7-SSH/2007-2013, grant agreement 320270 -SYRTO) for financial support.…”

Risk Measure Inference

“…Castro and Ferrari (2014) propose a method for testing whether two firms differ in terms of their ΔCoVaR. However, their approach is specific to ΔCoVaR and to the linear quantile regression.…”