Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/162504
Authors: 
Yu, Lining
Härdle, Wolfgang
Borke, Lukas
Benschop, Thijs
Year of Publication: 
2017
Series/Report no.: 
SFB 649 Discussion Paper 2017-003
Abstract: 
In this paper we propose a new measure for systemic risk: the Financial Risk Meter (FRM). This measure is based on the penalization parameter () 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. The visualization and the up-to-date FRM can be found on http://frm.wiwi.hu-berlin.de.
Subjects: 
Systemic Risk
Quantile Regression
Value at Risk
Lasso
Parallel Computing
JEL: 
C21
C51
G01
G18
G32
G38
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.