Quotation Hlavinova, Jana. 2019. Elicitability and Identifiability of Systemic Risk Measures. 23rd International Congress on Insurance: Mathematics and Economics, München, Deutschland, 10.07.-12.07.




Estimating different risk measures, such as Value at Risk or Expected Shortfall, for reporting as well as testing purposes is a common task in various financial institutions. The question of evaluating and comparing these estimates is closely related to two concepts already well known in the literature: elicitability and identifiability. We introduce these concepts for systemic risk measures defined by Feinstein, Rudloff and Weber (2016). A banking system with n participants is represented by a random vector Y and the quantity of interest is its aggregated outcome, using some nondecreasing aggregation function Λ. The measure of systemic riskis defined as the set of n-dimensional capital allocation vectors k such that the aggregated outcome Λ(Y+k) is acceptable under a given scalar risk measure ρ. We establish the link between the elicitability and/or identifiability of the systemic risk measure and the underlying scalar risk measure, taking two perspectives on the measures of systemic risk that stem from their set-valued nature. Moreover, we study secondary quality criteria of the scoring and identification functions of these measures.


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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Paper presented at an academic conference or symposium
Language English
Title Elicitability and Identifiability of Systemic Risk Measures
Event 23rd International Congress on Insurance: Mathematics and Economics
Year 2019
Date 10.07.-12.07.
Country Germany
Location München
URL https://www.groups.ma.tum.de/mathfinance/ime-2019/


Hlavinova, Jana (Details)
Institute for Statistics and Mathematics IN (Details)
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