[1]鲁亚会,刘爱义.基于半连续两部模型的保险损失预测[J].浙江科技学院学报,2023,(06):467-474.[doi:10.3969/j.issn.1671-8798.2023.06.002 ]
　LU Yahui,LIU Aiyi.Prediction of insurance loss based on semicontinuous two-part model[J].,2023,(06):467-474.[doi:10.3969/j.issn.1671-8798.2023.06.002 ]
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基于半连续两部模型的保险损失预测(/HTML)
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《浙江科技学院学报》[ISSN:1001-3733/CN:61-1062/R]

卷:
期数:
2023年06期
页码:
467-474
栏目:
出版日期:
2024-01-01

文章信息/Info

Title:
Prediction of insurance loss based on semicontinuous two-part model
文章编号:
1671-8798(2023)06-0467-08
作者:
鲁亚会1; 刘爱义2
(1.浙江科技学院 经济与管理学院,杭州 310023; 2.美国国立卫生研究院,美国 贝塞斯达 20817)
Author(s):
LU Yahui1;  LIU Aiyi2
(1.School of Economics and Management, Zhejiang University of Science and Technology, Hangzhou 310023, Zhejiang, China; 2.National Institutes of Health, Bethesda 20817, Maryland, USA)
关键词:
累积损失预测;  半连续数据;  Tweedie回归模型;  两部回归模型
分类号:
F842; O212.1
DOI:
10.3969/j.issn.1671-8798.2023.06.002
文献标志码:
A
摘要:
【目的】提高保险领域中保单累积损失预测的准确率。传统的Tweedie回归模型只能对非零均值建立回归模型,却不能对零概率建立回归模型,从而导致该模型的拟合效果并不理想。【方法】考虑到保单损失数据中往往包含着大量的零索赔,此时可视其为一种半连续型数据。因此,基于半连续两部模型,并考虑到累积损失中非零连续部分的分布类型,提出3种不同的累积损失预测模型,并结合一组实际损失数据进行模型对比分析。【结果】与Tweedie回归模型相比,本研究所提出的半连续两部回归模型的赤池信息准则值(Akaike information criterion,AIC)和贝叶斯信息量准则值(Bayesian information criterion,BIC)更小,具有较好的拟合效果。【结论】本研究结果可为保险领域中的保单累积损失预测提供参考。

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2022-11-19
基金项目:杭州市哲学社会科学规划课题(Z23JC042); 国家自然科学基金项目(11971433)
通信作者:鲁亚会(1990— ),女,河南省商丘人,讲师,博士,主要从事应用统计研究。E-mail:luyahui92@163.com。
更新日期/Last Update: 2023-12-31