Risk Measure Inference
Bibliographic Data
| ID | 19420166 |
|---|---|
| Authors | Christophe Hurlin (0000-0002-6082-8251, Laboratoire d’Economie d’Orléans (LEO), University of Orléans-CNRS, Orléans, France ()), Sébastien Laurent (0000-0002-4148-756X, Aix-Marseille School of Economics, CNRS & EHESS, Aix-Marseille Graduate School of Management-IAE, Aix-Marseille University, France), Rogier Quaedvlieg (Maastricht University), Stephan Smeekes (0000-0002-0157-639X, Maastricht University) |
| Year | 2017 |
| Volume | 35 |
| Issue | 4 |
| Pages | 499-512 |
| Publication date | 2017-10-02 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Business and Economic Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0735-0015 • E-ISSN: 1537-2707 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/07350015.2015.1127815 |
| OpenAlex | W3121458408 |
| Language | EN |
| References cited | 28 |
We propose a bootstrap-based test of the null hypothesis of equality of two firms’ conditional Risk Measures (RMs) at a single point in time. The test can be applied to a wide class of conditional risk measures issued from parametric or semi-parametric models. Our iterative testing procedure produces a grouped ranking of the RMs, which has direct application for systemic risk analysis. Firms within a group are statistically indistinguishable form each other, but significantly more risky than the firms belonging to lower ranked groups. A Monte Carlo simulation demonstrates that our test has good size and power properties. We apply the procedure to a sample of 94 U.S. financial institutions using ?CoVaR, MES, and %SRISK. We find that for some periods and RMs, we cannot statistically distinguish the 40 most risky firms due to estimation uncertainty
Econometrics · Economics · Inference · Monte Carlo method · Null hypothesis · Parametric statistics · Point estimation · Statistical hypothesis testing · Statistics · Computer Science · Financial Risk and Volatility Modeling · Market Dynamics and Volatility · Mathematics · Monetary Policy and Economic Impact
| Highly cited | No |
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