Risk measuring under model uncertainty

Abstract

The framework of this paper is that of risk measuring under uncertainty which is when no reference probability measure is given. To every regular convex risk measure on Cb(Ω), we associate a unique equivalence class of probability measures on Borel sets, characterizing the riskless nonpositive elements of Cb(Ω). We prove that the convex risk measure has a dual representation with a countable set of probability measures absolutely continuous with respect to a certain probability measure in this class. To get these results we study the topological properties of the dual of the Banach space L1(c) associated to a capacity c. As application, we obtain that every G-expectation E has a representation with a countable set of probability measures absolutely continuous with respect to a probability measure P such that P(|f|) = 0 if and only iff E(|f|) = 0. We also apply our results to the case of uncertain volatility. © Institute of Mathematical Statistics, 2012.