Asymptotically stable dynamic risk assessments

Karl-Theodor Eisele and Michael Kupper
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Karl-Theodor Eisele: IRMA - Institut de Recherche Mathématique Avancée - UNISTRA - Université de Strasbourg - CNRS - Centre National de la Recherche Scientifique
Michael Kupper: Universität Konstanz

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Abstract: In this paper we study asymptotically stable risk assessments (or equivalently risk measures) which have the property that an unacceptable position cannot become acceptable by adding a huge cash-flow far in the future. Under an additional continuity assumption, these risk assessments are exactly those which have a robust representation in terms of test probabilities that are supported on a finite time interval. For time-consistent risk assessments we give conditions on their generators which guarantee asymptotic stability.

Keywords: time-consistency; robust representation; local test probabilities; construction by generators; asymptotic stability of risk assessments (search for similar items in EconPapers)
Date: 2016
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Published in Statistics & Risk Modeling with Applications in Finance and Insurance, 2016, 33 (1-2), pp.41-50. ⟨10.1515/strm-2012-1146⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03548963

DOI: 10.1515/strm-2012-1146

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