FRM: A financial risk meter based on penalizing tail events occurrence

Lining Yu, Wolfgang Härdle, Lukas Borke and Thijs Benschop

No 2017-003, SFB 649 Discussion Papers from Humboldt University Berlin, Collaborative Research Center 649: Economic Risk

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.

Keywords: Systemic Risk; Quantile Regression; Value at Risk; Lasso; Parallel Computing (search for similar items in EconPapers)
JEL-codes: C21 C51 G01 G18 G32 G38 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/162504/1/880325305.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:zbw:sfb649:sfb649dp2017-003

Access Statistics for this paper

More papers in SFB 649 Discussion Papers from Humboldt University Berlin, Collaborative Research Center 649: Economic Risk Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().