Optimal Insurance Menu Design under the Expected-Value Premium Principle

Battle Count: 90

The paper is primarily focused on insurance contract design and mechanism design under information asymmetry. While it uses stochastic processes (Poisson process, Cramér-Lundberg model) and mean-variance optimization that have parallels in quantitative finance, the core contribution is in insurance economics rather than trading strategies. The Stackelberg game framework and screening mechanisms could have tangential relevance to market-making under adverse selection, but the paper does not address trading directly.

The theoretical framework requires solving ODEs numerically (e.g., MATLAB ode45) and performing one-dimensional optimization to determine the constant C*. The fixed-point argument for existence/uniqueness is mathematically sophisticated but the numerical implementation follows a clear two-step procedure. The risk-attitude uncertainty case is simpler (single optimization over ξ). The main complexity lies in handling the implicit ODE for risk-type uncertainty and verifying truth-telling constraints.

The paper provides complete mathematical proofs, explicit formulas for optimal contracts, and detailed numerical examples with specific parameter settings (exponential, Pareto, uniform, truncated normal distributions). However, no code repository or computational scripts are provided. The numerical procedure described in Remark 4.1 (using ODE solvers and one-dimensional optimization) is reproducible with standard tools like MATLAB.