报告时间：2022年1月5日，上午10:00-11:00
报告地点：腾讯会议（会议ID：784-591-524）
报告嘉宾：侯燕曦
报告主题：A Two-Stage Model for High-Risk Prediction in Insurance Ratemaking
报告摘要
A Two-Stage Model for High-Risk Prediction in Insurance Ratemaking
In actuarial practice, modern statistical methodologies are one primary consideration for real actuarial problems, such as premium calculation, insurance preservation, marginal risk analysis, etc. The claim data usually possesses a complex data structure, so direct applications of statistical techniques will result in unstable prediction. For example, insurance losses are semicontinuous variables, where a positive mass on zero is often associated with an otherwise positive continuous outcome. Thus, the prediction of high-risk events of claim data needs additional treatment to avoid significant underestimation. In this article, we propose a new two-stage composite quantile regression model for the prediction of the value-at-risks of the aggregate insurance losses. As we are interested in the statistical properties of our method, the asymptotic results are established corresponding to different types of risk levels. Finally, some simulation studies and a data analysis are implemented for the illustration of our method.
个人简介
侯燕曦，副教授，博士生导师，复旦大学大数据学院。2017年在美国佐治亚理工学院数学学院获得博士学位。主要研究方向：极值理论，copula和tail copula，非参数统计方法，统计推断在金融计量和风险管理中的应用。主要研究成果发表在AoS，JASA，JoE，JBES以及IME等国际期刊上。
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