FRM Financial Risk Meter

Advances in Econometrics, Volume 42, The Econometrics of Networks

35 Pages Posted: 5 Aug 2019 Last revised: 7 Apr 2020

See all articles by Andrija Mihoci

Andrija Mihoci

Brandenburg University of Technology (BTU)

Michael Althof

Humboldt University of Berlin - Institute for Statistics and Econometrics

Cathy Yi‐Hsuan Chen

University of Glasgow, Adam Smith Business School; Humboldt Universität zu Berlin

Wolfgang Karl Härdle

Blockchain Research Center Humboldt-Universität zu Berlin; Charles University; National Yang Ming Chiao Tung University; Asian Competitiveness Institute

Date Written: July 30, 2019

Abstract

A systemic risk measure is proposed accounting for links and mutual dependencies between financial institutions utilising tail event information. FRM (Financial Risk Meter) is based on Lasso quantile regression designed to capture tail event co-movements. The FRM focus lies on understanding active set data characteristics and the presentation of interdependencies in a network topology. Two FRM indices are presented, namely, FRM@Americas and FRM@Europe. The FRM indices detect systemic risk at selected areas and identifies risk factors. In practice, FRM is applied to the return time series of selected financial institutions and macroeconomic risk factors. We identify companies exhibiting extreme "co-stress", as well as "activators" of stress. With the SRM@EuroArea, we extend to the government bond asset class, and to credit default swaps with FRM@iTraxx. FRM is a good predictor for recession probabilities, constituting the FRM-implied recession probabilities. Thereby, FRM indicates tail event behaviour in a network of financial risk factors.

Keywords: Systemic Risk, Quantile Regression, Lasso, Financial Markets, Risk Management, Network Dynamics, Recession

JEL Classification: C21, C51, G01, G18, G32, G38

Suggested Citation

Mihoci, Andrija and Althof, Michael and Chen, Cathy Yi‐Hsuan and Härdle, Wolfgang Karl, FRM Financial Risk Meter (July 30, 2019). Advances in Econometrics, Volume 42, The Econometrics of Networks, Available at SSRN: https://ssrn.com/abstract=3429549

Andrija Mihoci

Brandenburg University of Technology (BTU) ( email )

PO Box 101344
Cottbus, 03013
Germany

Michael Althof (Contact Author)

Humboldt University of Berlin - Institute for Statistics and Econometrics ( email )

Spandauer Str. 1
Berlin, D-10178
Germany

HOME PAGE: http://irtg1792.hu-berlin.de

Cathy Yi‐Hsuan Chen

University of Glasgow, Adam Smith Business School ( email )

University Avenue
Glasgow, G12 8QQ
United Kingdom
01413305065 (Phone)

HOME PAGE: http://https://gla.cathychen.info

Humboldt Universität zu Berlin ( email )

Unter den Linden 6,
Berlin, 10117
Germany
03020935631 (Phone)
10099 (Fax)

Wolfgang Karl Härdle

Blockchain Research Center Humboldt-Universität zu Berlin ( email )

Unter den Linden 6
Berlin, D-10099
Germany

Charles University ( email )

Celetná 13
Dept Math Physics
Praha 1, 116 36
Czech Republic

National Yang Ming Chiao Tung University ( email )

No. 1001, Daxue Rd. East Dist.
Hsinchu City 300093
Taiwan

Asian Competitiveness Institute ( email )

Singapore

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