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Combining Simulation with a Biased-Randomized Heuristic to Develop Parametric Bonds for Insurance Coverage against Earthquakes

机译:用偏见随机启发式组合模拟,开发用于对地震保险范围的参数键

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The social and economic impact of natural catastrophes on communities is a concern for many governments and corporations across the globe. A class of financial instruments, parametric hedges, is emerging in the (re)insurance market as a promising approach to close the protection gap related to natural hazards. This paper focuses on the design of such parametric hedges, which have the objective of maximizing the risk transferred subject to a budget constraint. With Greece as a case study, one of the most seismic prone European regions, with limited seismic insurance penetration, this paper proposes a biased-randomized algorithm to solve the optimization problem. The algorithm hybridizes Monte Carlo simulation with a heuristic to generate a variety of solutions. A simulation stage allows for analyzing the payout distribution of each solution. Results show the impact of the problem resolution on the transferred risk and on the distribution of triggered payments.
机译:自然灾难对社区的社会和经济影响是全球许多政府和公司的关注。一类金融工具,参数对冲,在(重新)保险市场中出现了一个有希望的方法,以结束与自然灾害相关的保护差距。本文重点介绍了这种参数对冲的设计,其目的是最大化经过预算约束的转移的风险。与希腊为例,作为案例研究,其中最震荡普遍的欧洲地区之一,具有有限的地震保险渗透,本文提出了一种偏见的随机算法来解决优化问题。该算法用启发式杂交蒙特卡罗模拟,以产生各种解决方案。仿真级允许分析每个解决方案的支付分配。结果表明问题解决方案对转移风险和触发支付分配的影响。

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