Optimal Catastrophe Risk Pooling

Catastrophe risk has long been recognized to pose a serious threat to the insurance sector. Although natural disasters such as flooding, hurricane or severe drought are rare events, they generally lead to devastating damages that traditional insurance schemes may not be able to efficiently cover. Catastrophe risk pooling is an effective way to diversify the losses from such risks. In this paper, we improve the catastrophe risk pool by Pareto-optimally allocating the diversification benefits among participants. Finding the practical Pareto-optimal pool entails solving a high-dimensional optimization problem, for which analytical solutions are typically unavailable and numerical methods can be computationally intensive and potentially unreliable. We propose evaluating the diversification benefits at the limit case and using it to approximate the optimal pool by deriving an asymptotic optimal pool. Simulation studies are undertaken to explore the implications of the results and an empirical analysis from the U.S. National Flood Insurance Program is also carried out to illustrate how this framework can be applied in practice.