Nos derniers articles

This study explores how natural disasters challenge traditional risk management and insurance mechanisms. Researchers developed a three-strategy evolutionary game model to examine the competition among formal index insurance, informal risk sharing, and non-insurance. The model incorporates insurance company profits to aid optimal pricing. Findings suggest that basis risk and loss ratios strongly influence insurance adoption. Low basis risk and high loss ratios favor index insurance, while moderate loss ratios lead to informal risk sharing. Low loss ratios often result in no insurance uptake. Accurately estimating risk aversion and risk sharing ratios is essential for forecasting index insurance market trends.

An agent with multiple loss models optimizes risk sharing with a counterparty using a mean-variance criterion adapted for ambiguity. Under a Cramér-Lundberg loss model, the optimal risk sharing contract and wealth process are characterized. The strategy is proven admissible, and the value function verified. The optimal strategy is applied to Spanish auto insurance data with differing models from cross-validation for numerical illustrations.

This paper introduces "co-opetition" (combining competition and cooperation) to reinsurance risk-sharing. A two-layer game-theoretic framework models insurer-reinsurer contracting and price competition (Stackelberg-Nash), followed by collaborative risk-sharing. The model, using mean-variance preferences, yields explicit equilibrium results, demonstrating the feasibility of analyzing complex reinsurance market dynamics. Future research could explore different preferences, premium principles, and market structures.

This study provides semi-explicit formulas for inf-convolution and optimal allocations, considering homogeneous, conditional, and absolutely continuous beliefs. The research also explores inf-convolution between Lambda value at risk and other risk measures, discussing optimal allocations and alternative Lambda value at risk definitions.