基于隐马尔可夫模型的台风风险评估与巨灾债券定价研究  

Typhoon Risk Assessment and Catastrophe Bond Pricing Based on a Hidden Markov Model

作　　者：巢文 钱晓涛 CHAO Wen;QIAN Xiaotao(Fujian University of Technology,Fuzhou,Fujian 350118)

机构地区：[1]福建理工大学,福建福州350118

出　　处：《绵阳师范学院学报》2024年第9期7-14,37,共9页Journal of Mianyang Teachers＇ College

基　　金：福建省自然科学基金项目“基于马氏调节风险模型的台风风险评估与分散机制研究”(2023J01941);福建理工大学科研启动基金项目“基于Copula和极值理论的巨灾保险基金规模研究”(GY-S20011)。

摘　　要：发行与台风风险相关的巨灾债券,将承保的台风风险由保险市场转移到资本市场,是保险公司规避巨灾风险的一条重要途径。台风风险的准确评估预测,是台风巨灾债券成功发行的关键。针对台风风险特征,构建了隐马尔可夫模型,以台风年经济损失额为观测序列,预测台风登陆时最大风力等级状态,进而采用风险中性测度技术,在CIR随机利率期限结构下,给出了有息巨灾债券定价公式。结合我国1989—2022年台风灾害损失数据进行实证分析,结果表明,隐马尔可夫模型的台风风险评估预测效果优于其他常用机器学习模型,所建立的定价模型具有可行性。The issuance of typhoon-risk-related catastrophe bonds,which transfers insured typhoon risks from the insurance market to the capital market,is an important way for insurance companies to avoid catastrophe risks.The accurate assessment and prediction of typhoon risks is the key to the successful issuance of typhoon catastrophe bonds.Aiming at the characteristics of typhoon risks,this paper constructs a Hidden Markov Model to predict the maximum wind level status of typhoon landfall by taking the annual economic loss of typhoons as the observation sequence,and then adopts the risk-neutral measurement technique to give the pricing formula of interest-bearing catastrophe bonds under the CIR stochastic interest rate term structure.In combination with the empirical analysis of China's typhoon disaster loss data from 1989 to 2022,the findings show that the predictive effect of the Hidden Markov Model for typhoon risk assessment is better than that of other common machine learning models and that the established pricing model is feasible.

关 键 词：巨灾债券 隐马尔可夫 台风风险 随机利率 

分 类 号：F832.51[经济管理—金融学]