3 résultats pour « risk measures »

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.

On the Separability of Vector‑Valued Risk Measures

This paper defines vector-valued risk measures using axioms and shows they ignore dependence structures of input random vectors, unlike set-valued risk measures. Convex vector-valued risk measures are unsuitable for capital allocation in various financial applications, including systemic risk measures. The results also generalize to conditional settings.

Risk exchange under infinite‑mean Pareto models

The study explores optimal decision-making for agents minimizing risks with extremely heavy-tailed, possibly dependent losses. Focused on super-Pareto distributions, including heavy-tailed Pareto, it finds non-diversification preferred with well-defined risk measures. Equilibrium analysis in risk exchange markets indicates agents with such losses avoid risk sharing. Empirical data confirms real-world heavy-tailed distributions.