The Price of Dynamic Inconsistency for Distortion Risk Measures

Economy – Quantitative Finance – Risk Management

Scientific paper

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Scientific paper

In this paper, we investigate two different frameworks for assessing the risk in a multi-period decision process: a dynamically inconsistent formulation (whereby a single, static risk measure is applied to the entire sequence of future costs), and a dynamically consistent one, obtained by suitably composing one-step risk mappings. We characterize the class of dynamically consistent measures that provide a tight approximation for a given inconsistent measure, and discuss how the approximation factors can be computed. For the case where the consistent measures are given by Average Value-at-Risk, we derive a polynomial-time algorithm for approximating an arbitrary inconsistent distortion measure. We also present exact analytical bounds for the case where the dynamically inconsistent measure is also given by Average Value-at-Risk, and briefly discuss managerial implications in multi-period risk-assessment processes. Our theoretical and algorithmic constructions exploit interesting connections between the study of risk measures and the theory of submodularity and lattice programming, which may be of independent interest.

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