The constantly expanding frequency and loss affected by natural disasters pose a severe challenge to the traditional catastrophe insurance market. This paper aims to develop an innovative framework of pricing catastrophic bonds triggered by multiple events with extreme dependence structure. Given the low contingency of the bond's cash flows and high return, the multiple-event CAT bond may successfully transfer the catastrophe risk to the big financial markets meeting the diversification of capital allocations for most potential investors. The designed hybrid trigger mechanism helps reduce moral hazard and improve bond attractiveness with CIR stochastic rate, displaying the co-movement of the wiped-off coupon, payout principal, the occurrence and intensity of the natural disaster involved. As different triggered indexes of multiple-event catastrophic bonds are heavy-tailed with a variety of dependence relationship, nested Archimedean copulas are introduced with marginal distributions modeled by POT-GP distribution for excess data and common parametric models for moderate risks. To illustrate our theoretical pricing framework, we consider a three-event rainstorm CAT bond triggered by catastrophic property losses, in China during 2006--2020. Monte Carlo simulations are conducted for the sensitivity analysis of the rainstorm CAT bond price is also in trigger attachment levels, maturity date, catastrophe intensity, and numbers of trigger indicators.

翻译：自然灾害所导致的频率和损失不断扩大，对传统的巨灾保险市场构成了严峻挑战。本文旨在开发一个具有极端依赖结构的、由多个事件触发的巨灾债券定价创新框架。鉴于债券现金流的低偶然性和高回报率，多事件巨灾债券能够成功地将巨灾风险转移至大型金融市场，满足大多数潜在投资者对资本配置多样化的需求。所设计的混合触发机制有助于减少道德风险，并通过引入CIR随机利率模型提升债券吸引力，该机制显示了票息取消、本金偿还以及所涉自然灾害发生与强度的协同变动。由于多事件巨灾债券的不同触发指数具有重尾特征且存在多种依赖关系，我们引入了嵌套阿基米德Copula，其边缘分布对于超额数据采用POT-GP分布建模，对于中等风险则采用常用参数模型。为阐明我们的理论定价框架，我们以中国2006—2020年间发生的、由灾难性财产损失触发的三事件暴雨巨灾债券为例。通过蒙特卡洛模拟对暴雨巨灾债券价格进行敏感性分析，考察触发附着水平、到期日、巨灾强度以及触发指标数量等因素的影响。