Dynamic Systemic Risk Measures for Bounded Discrete-Time Processes

27 Pages Posted: 23 Jul 2014 Last revised: 13 May 2015

See all articles by Eduard Kromer

Eduard Kromer

University of California, Berkeley

Ludger Overbeck

University of Giessen

Katrin Zilch

University of Giessen

Date Written: May 11, 2015

Abstract

The question of measuring and managing systemic risk - especially in view of the recent financial crises - became more and more important. We study systemic risk by taking the perspective of a financial regulator and considering the axiomatic approach originally introduced in Chen et al. (2013) and extended in Kromer et al. (2014). The aim of this paper is to generalize the static approach in Kromer et al. (2014) and analyze systemic risk measures in a dynamic setting. We work in the framework of Cheridito et al. (2006) who consider risk measures for bounded discrete-time processes. Apart from the possibility to consider the “evolution of financial values”, another important advantage of the dynamic approach is the possibility to incorporate information in the risk measurement and management process. In context of this dynamic setting we also discuss the arising question of time-consistency for our dynamic systemic risk measures.

Keywords: conditional systemic risk measure, aggregation function, conditional dual representation, dynamic systemic risk measure, time-consistency

JEL Classification: D81

Suggested Citation

Kromer, Eduard and Overbeck, Ludger and Zilch, Katrin, Dynamic Systemic Risk Measures for Bounded Discrete-Time Processes (May 11, 2015). Available at SSRN: https://ssrn.com/abstract=2469475

Eduard Kromer

University of California, Berkeley ( email )

Evans Hall
Berkeley, CA 3860 94720
United States

Ludger Overbeck

University of Giessen ( email )

Institut of Mathematics
Giessen, 35394
Germany

Katrin Zilch (Contact Author)

University of Giessen ( email )

Department of Mathematics
Arndtstr. 2
Giessen, 35392
Germany

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