Jointly Exchangeable Collective Risk Models: Interaction, Structure, and Limit Theorems
By: Daniel Gaigall, Stefan Weber
Potential Business Impact:
Predicts insurance company money problems better.
We introduce a framework for systemic risk modeling in insurance portfolios using jointly exchangeable arrays, extending classical collective risk models to account for interactions. We establish central limit theorems that asymptotically characterize total portfolio losses, providing a theoretical foundation for approximations in large portfolios and over long time horizons. These approximations are validated through simulation-based numerical experiments. Additionally, we analyze the impact of dependence on portfolio loss distributions, with a particular focus on tail behavior.
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