This paper explores optimal insurance contracting for a decision maker facing ambiguous loss distributions. Using a p-Wasserstein ball around a benchmark distribution and a convex distortion risk measure, the indemnity function and worst-case distribution are derived. Numerical examples highlight the sensitivity of worst-case distributions to model parameters.Distributionally robust insurance under the Wasserstein distance
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