Working Experience

• 2020 – now   University of International Business and Economics   Associate Professor
• 2019 – 2020   KU Leuven   Visiting Scholar
• 2017 – 2020   University of International Business and Economics   Assistant Professor

Education Backgroud

• 2014-2017   Renmin Univeristy of China   School of Statistics   Department of Risk Management and Actuarial Science   PhD
• 2012-2014   University of International Business and Economics   School of Insurance and Economics   Master
• 2008-2012   Xiamen University   School of Economics   Department of Finance   Bachelor

Research Field

• non-life ratmaking and reserving
• catastrophe risk measurement, extreme value theory
• statistical models, dependent risk analysis
• big data and machine learning methods
• R programming

Teaching

• Undergraduate: Interest Theory, Non-Life Actuarial Science
• Graduate: Econometrics, non-life ratmaking, Machine Learning and insurance data analysis, quantitative risk management, risk ,odeling, insurance data analysis and R programming

Working Papaers

• Zhengxiao Li, Yifan Huang, Yang Cao. Analyzing covariate clustering effects in healthcare cost subgroups: insights and applications for prediction , arXiv:2303.05793, 2023.
• Jiakun Jiang, Zhengxiao Li, Liang Yang. Dynamic online prediction model and its application to automobile claim frequency data , arXiv:2301.03005, 2023.
• Liang Yang, Zhengxiao Li, Shengwang Meng. Risk Loadings in Classification Ratemaking , arXiv:2002.01798, 2020 .
• Zhengxiao Li, R package for a new beta-type copula: rMGLReg .

Published Papers

• Zhengxiao Li, Fei Wang, Zhengtang Zhao. A new class of composite GBII regression models with varying threshold for modelling heavy-tailed data , Insurance: Mathematics and Economics [J], accepted for publication, 2024.
• Zhengxiao Li, Jan Beirlant, Liang Yang. A new class of copula regression models for modelling multivariate heavy-tailed data. Insurance: Mathematics and Economics [J]. 104: 243-261, 2022.
• Zhengxiao Li, Jan Beirlant, Shengwang Meng. Generalizing The Log-Moyal Distribution and Regression Models for Heavy-Tailed Loss Data [J]. ASTIN Bulletin: The Journal of the IAA, 11(1):57-99, 2021.
• 李政宵, 刘新红, 孟生旺. 多维地震风险模型与保险基金测算[J]. 保险研究, 2022(10): 45-60.
• 刘新红, 孟生旺, 李政宵. 地震损失风险的Copula混合分布模型及其应用[J]. 系统工程理论与实践, 2019, 39(07): 1855-1866.
• 孟生旺, 李政宵. 地震死亡人数预测与巨灾保险基金测算[J]. 统计研究, 2018, 35(10): 89-102.
• 李政宵, 孟生旺. 我国商业车险奖惩系统的构建与评价[J]. 系统工程理论与实践, 2018, 38(04): 938-949.
• 李政宵, 孟生旺. 基于GB2分布的贝叶斯相依性准备金评估模型[J]. 统计研究, 2018, 35(01): 91-103.
• 李政宵, 孟生旺. 相依风险的团体健康保险损失预测[J]. 数理统计与管理, 2018, 37(03): 399-412.
• Yuantao Xie, Zhengxiao Li*, Rahul A Parsa. Extensionand Application of Credibility Modelsin Predicting Claim Frequency[J]. Mathematical Problems in Engineering, 2018, 2018(02): 1-8.
• 孟生旺, 李政宵. 索赔频率与索赔强度的相依性模型[J]. 统计研究, 2017, 34(01): 55-66.
• 马瑜, 李政宵, 马敏. 中国老年多维贫困的测度和致贫因素——基于社区和家庭的分层研究[J]. 经济问题, 2016(10): 27-33.
• 蒋涛, 李政宵. 我国银行业系统性风险结构度量——基于尾部依赖视角[J]. 合肥学院学报(综合版), 2016, 33(04): 17-23.
• 李政宵, 孟生旺. 相依风险条件下的汽车保险定价模型[J]. 保险研究, 2016(07): 68-77.
• 李政宵, 孟生旺. 考虑空间效应的贝叶斯分层模型与索赔频率预测[J]. 数学的实践与认识, 2016, 46(10): 193-202.
• 孟生旺, 李政宵. 偏t分布假设下的空间效应模型及其应用[J]. 数理统计与管理, 2016, 35(06): 1028-1037.
• 孟生旺, 李政宵. 基于随机效应零调整回归模型的保险损失预测[J]. 统计与信息论坛, 2015, 30(12): 3-9.
• 谢远涛, 李政宵. 基于联合定价模型的奖惩因子的扩展与比较[J]. 统计与信息论坛, 2015, 30(06): 33-39.

Academic Conferences

• The 25th International Congress on Insurance: Mathematics and Economics, online, 2022.
• The 12th annual China International Conference on Insurance and Risk Management, Changsha, 2022.
• The 13th China Risk Management and Actuarial Forum, Beijing, 2021.
• The First Xiamen University Insurance and Reinsurance Forum, Xiamen, 2021.
• The 11th annual China International Conference on Insurance and Risk Management, Heilongjiang, 2021.
• the 7th annual China International Risk Forum, Chengdu, 2021.
• The 3rd (2021) Annual Academic Conference of the Quantitative Finance and Insurance Branch of the China Optimal Method, Coordination Method and Economic Mathematics Research Association, Luoyang, 2021.
• The 12th China Risk Management and Actuarial Forum, Xiamen, 2020.
• Invited to participate in the academic report of the Actuarial Department of Southwestern University of Finance and Economics, 2020.
• Invited to participate in the academic report of the Department of Mathematics and Statistics of East China Normal University, 2020.
• Invited to participate in the academic report of the Department of Actuarial Sciences, Central University of Finance and Economics, 2020.
• Invited to participate in the academic report of the Department of Actuarial Sciences, University of Leuven, Belgium, 2019.
• The 7th annual China International Conference on Insurance and Risk Management, Guilin, 2017.