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

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: SFB 649 Discussion Paper ; No. 2017-003

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions ; Model Construction and Estimation ; Financial Crises ; General Financial Markets: Government Policy and Regulation ; Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill ; Corporate Finance and Governance: Government Policy and Regulation
• Subject: Systemic Risk ; Quantile Regression ; Value at Risk ; Lasso ; Parallel Computing

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Yu, Lining ; Härdle, Wolfgang Karl ; Borke, Lukas ; Benschop, Thijs
• Event: Veröffentlichung
• (who): Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
• (where): Berlin
• (when): 2017

Further information

• Handle: http://hdl.handle.net/10419/162504
• Last update: 10.03.2025, 11:43 AM CET