南北地震带地震指数保险设计研究

Research on the Design of Earthquake Parametric Insurance for North-South Seismic Zone

地震指数保险是应对地震灾害损失的一种重要手段。然而,由于地震灾害低频率和强随机的特性,地震指数保险的赔付设计往往会面临基于单一地区样本量不足,基于全国范围又难以兼顾地区差异的难题,容易造成较高的基差风险。该文从地震活动的空间特征着手,以南北地震带作为研究对象。在此基础上,引入分数泊松过程刻画地震发生频率,以克服传统假设难以捕捉地震活动周期性特征的问题。同时,使用GAMLSS模型刻画地震灾害损失的连续性特征,结合机器学习中的进化树算法离散化指数保险赔付结构,进一步提高预测模型的准确性与稳健性。实证结果验证了新型设计对于降低指数保险基差风险的优势,并为指数保险实际应用提供理论依据与优化方案。

Earthquake parametric insurance is an important means of responding to earthquake losses.However,designing based on a single province or region will face insufficient sample size,and it is difficult to take into account regional differences based on the whole country,both of which will cause serious basis risk.Starting from the spatial characteristics of seismic activity,the North-South Seismic Zone is taken as the research object.On this basis,a fractional Poisson process is introduced to portray the frequency of seismicity,in order to overcome the problem that traditional assumptions are difficult to capture the cyclical characteristics of seismic activity.Meanwhile,the GAMLSS model is used to portray the continuity characteristics of earthquake disaster losses.and the parametric insurance payout structure is discretized by combining the evolutionary tree algorithm in machine learning to further improve the accuracy and robustness of the prediction model.The empirical results verify the advantages of the new design for reducing the parametric insurance basis risk,and provide theoretical basis and optimization scheme for the practical application of parametric inurance.