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Pareto-optimal insurance under robust distortion risk measures

Abstract

In this talk we study the optimal insurance contracting problem from both the decision maker (DM) and insurer's perspectives. The DM and insurer both apply distortion risk measures for insurance negotiation and are assumed to be ambiguous about the underlying loss distribution, where the ambiguity sets are depicted by different Wasserstein balls. The analytical forms of the optimal indemnity function and the worst-case survival functions from both parties' perspectives are derived. We also extend the results to the market that comprises n>=2 insurers.