FRM: A Financial Risk Meter Based on Penalizing Tail Events Occurrence
SFB 649 Discussion Paper 2017-003
42 Pages Posted: 17 Feb 2017 Last revised: 20 Feb 2017
Date Written: February 10, 2017
In this paper we propose a new measure for systemic risk: the Financial Risk Meter (FRM). This measure is based on the penalization parameter (λ) of a linear quantile lasso regression. The FRM is calculated by taking the average of the penalization parameters over the 100 largest US publicly traded financial institutions. We demonstrate the suitability of this risk measure by comparing the proposed FRM to other measures for systemic risk, such as VIX, SRISK and Google Trends. We find that mutual Granger causality exists between the FRM and these measures, which indicates the validity of the FRM as a systemic risk measure. The implementation of this project is carried out using parallel computing, the codes are published on www.quantlet.de with keyword FRM. The R package RiskAnalytics is another tool with the purpose of integrating and facilitating the research, calculation and analysis methods around the FRM project.
Keywords: Systemic Risk, Quantile Regression, Value at Risk, Lasso, Parallel Computing
JEL Classification: C21, C51, G01, G18, G32, G38
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