FRM Financial Risk Meter

Andrija Mihoci, Michael Althof, Cathy Yi-Hsuan Chen and Wolfgang Karl Härdle

A chapter in The Econometrics of Networks, 2020, vol. 42, pp 335-368 from Emerald Group Publishing Limited

Abstract: A systemic risk measure is proposed accounting for links and mutual dependencies between financial institutions utilizing tail event information. Financial Risk Meter (FRM) is based on least absolute shrinkage and selection operator 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@AmericasandFRM@Europe. The FRM indices detect systemic risk at selected areas and identify risk factors. In practice, FRM is applied to the return time series of selected financial institutions and macroeconomic risk factors. The authors identify companies exhibiting extreme “co-stress” as well as “activators” of stress. With theSRM@EuroArea, the authors extend to the government bond asset class, and to credit default swaps withFRM@iTraxx. FRM is a good predictor for recession probabilities, constituting the FRM-implied recession probabilities. Thereby, FRM indicates tail event behavior in a network of financial risk factors.

Keywords: Systemic risk; quantile regression; financial markets; risk management; network dynamics; recession (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eme:aecozz:s0731-905320200000042016

DOI: 10.1108/S0731-905320200000042016

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