2 résultats pour « model uncertainty »

Optimal insurance design with Lambda‑Value‑at‑Risk

The paper examines optimal insurance solutions using $\Lambda\VaR$. It finds truncated stop-loss indemnity optimal with the expected value premium principle and provides a deductible parameter expression. Using $\Lambda'\VaR$, full or no insurance is optimal. It also addresses model uncertainty, offering solutions for various uncertainty scenarios.

Partially Law‑Invariant Risk Measures

The study introduces partial law invariance, a novel concept extending law-invariant risk measures in decision-making under uncertainty. It characterizes partially law-invariant coherent risk measures with a unique formula, deviating from classical approaches. Strong partial law invariance is introduced, proposing new risk measures like partial versions of Expected Shortfall for risk assessment under model uncertainty.