Characterization of optimal risk allocations for convex risk functionals
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Swen Kiesel
Abstract
In this paper we consider the problem of optimal risk allocation or risk exchange with respect to convex risk functionals, which not necessarily are monotone or cash invariant. General existence and characterization results are given for optimal risk allocations minimizing the total risk as well as for Pareto optimal allocations. We establish a general uniqueness result for optimal allocations. As particular consequence we obtain in case of cash invariant, strictly convex risk functionals the uniqueness of Pareto optimal allocations up to additive constants. In the final part some tools are developed useful for the verification of the basic intersection condition made in the theorems which are applied in several examples.
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- Minimaxity of the Stein risk-minimization estimator for a normal mean matrix
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- Upper bounds for Bermudan options on Markovian data using nonparametric regression and a reduced number of nested Monte Carlo steps
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Artikel in diesem Heft
- Minimaxity of the Stein risk-minimization estimator for a normal mean matrix
- Estimation of search tree size and approximate counting: A likelihood approach
- Upper bounds for Bermudan options on Markovian data using nonparametric regression and a reduced number of nested Monte Carlo steps
- On a stochastic version of the trading rule “Buy and Hold”
- Characterization of optimal risk allocations for convex risk functionals
