Dynamic risk measures
Beatrice Acciaio, Irina Penner
TL;DR
This paper reviews the theory of dynamic convex risk measures in discrete time, focusing on their robust representations, time consistency properties, and related supermartingale characteristics.
Contribution
It provides a comprehensive overview of dynamic convex risk measures, highlighting new characterizations and properties in the context of discrete time models.
Findings
Robust representation results for conditional convex risk measures.
Characterization of time consistency via acceptance sets and penalty functions.
Supermartingale properties linked to dynamic risk processes.
Abstract
This paper gives an overview of the theory of dynamic convex risk measures for random variables in discrete time setting. We summarize robust representation results of conditional convex risk measures, and we characterize various time consistency properties of dynamic risk measures in terms of acceptance sets, penalty functions, and by supermartingale properties of risk processes and penalty functions.
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Taxonomy
TopicsRisk and Portfolio Optimization · Insurance, Mortality, Demography, Risk Management · Risk Management in Financial Firms