Elicitability and Identifiability of Systemic Risk Measures
Abstract
Identification and scoring functions are statistical tools to assess the calibration and the relative performance of risk measure estimates, e.g., in backtesting. A risk measures is called identifiable (elicitable) it it admits a strict identification function (strictly consistent scoring function). We consider measures of systemic risk introduced in Feinstein, Rudloff and Weber (2017). Since these are set-valued, we work within the theoretical framework of Fissler, Hlavinov\'a and Rudloff (2019) for forecast evaluation of set-valued functionals. We construct oriented selective identification functions, which induce a mixture representation of (strictly) consistent scoring functions. Their applicability is demonstrated with a comprehensive simulation study.
Cite
@article{arxiv.1907.01306,
title = {Elicitability and Identifiability of Systemic Risk Measures},
author = {Tobias Fissler and Jana Hlavinová and Birgit Rudloff},
journal= {arXiv preprint arXiv:1907.01306},
year = {2022}
}
Comments
42 pages, 3 figures + supplementary material (6 pages, 2 figures)