报告题目： Decoupling Systemic Risk into Endopathic and Exopathic Competing Risks Through Autoregressive Conditional Accelerated Fréchet Model
报告人：张正军教授 ，美国威斯康星大学
报告时间：2022年9月23日（周五）16:30-18:00
报告地点：中科院数学与系统科学研究院南楼N219；腾讯会议ID：765-189-025
报告摘要：Identifying systemic risk patterns in geopolitical, economic, financial, environmental, transportation, epidemiological systems and their impacts is the key to risk management. We propose a new nonlinear time series model: autoregressive conditional accelerated Fréchet (AcAF) model and introduce two new endopathic and exopathic competing risk indices for better learning risk patterns, decoupling systemic risk, and making better risk management. We establish the probabilistic properties of stationarity and ergodicity of the AcAF model. Statistical inference is developed through conditional maximum likelihood estimation. The consistency and asymptotic normality of the estimators are derived. Simulation demonstrates the efficiency of the proposed estimators and the AcAF model's flexibility in modeling heterogeneous data. Empirical studies on the stock returns in S\&P 500 and the cryptocurrency trading show the superior performance of the proposed model in terms of the identified risk patterns, endopathic and exopathic competing risks, being informative with greater interpretability, enhancing the understanding of the systemic risks of a market and their causes, and making better risk management possible. (Joint work with Jingyu Ji and Deyuan Li).
报告人介绍：张正军教授，现为美国威斯康星大学麦迪逊分校统计系长聘正教授、美国统计协会会士、国际数理统计协会会士、国际数理统计协会财务总监、国际顶级期刊Journal of Business & Economic Statistics副主编、Statistica Sinica副主编、Journal of Econometrics金融工程与风险管理特刊共同主编；北卡罗来纳大学教堂山分校统计学博士。主要研究方向包括：金融时间序列分析、极值理论、异常气候分析、稀有疾病（癌症、帕金森综合症、奥兹海默症，等等）分析、金融风险建模和评估、市场系统性风险评估等等。
