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Risk Measure Inference

Christophe Hurlin, Sébastien Laurent, Rogier Quaedvlieg and Stephan Smeekes

Working Papers from HAL

Abstract: 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. A Monte Carlo simulation demonstrates that our test has good size and power properties. We propose an application to a sample of U.S. financial institutions using CoVaR, MES, and SRISK, and conclude that only SRISK can be estimated with enough precision to allow for meaningful ranking.

Keywords: Bootstrap; Grouped Ranking; Risk Measures; Uncertainty (search for similar items in EconPapers)
Date: 2015-02-28
New Economics Papers: this item is included in nep-ban, nep-ecm, nep-ore, nep-rmg and nep-upt
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00877279v3
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Journal Article: Risk Measure Inference (2017) Downloads
Working Paper: Risk Measure Inference (2017)
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