【系综合学术报告】

报告题目：Modeling Autoregressive Conditional Regional Extremes with Application to Solar Flare Detection

报告人：张正军（教授，威斯康辛大学）

时间：2023年3月21日下午16:00-17:00

地点：理科楼A404

摘要：This talk discusses big data streams with regional-temporal extreme event (REE) structures and solar flare detection. An  autoregressive conditional Fr\'echet model with time-varying parameters for regional and its adjacent regional extremes (ACRAE) is proposed. The ACRAE model can quickly detect rare REEs (i.e., solar flares) in big data streams and predict solar activity. The ACRAE model, with some mild regularity conditions, is proved to be stationary and ergodic. The parameter estimators are derived through the conditional maximum likelihood method. The consistency and asymptotic normality of the estimators are established. Simulations are used to demonstrate the efficiency of the proposed parameter estimators. In real solar flare detection, with the new dynamic extreme value modeling, the occurrence and climax of solar activity can be detected earlier than existing algorithms. The empirical study shows that the ACRAE model outperforms the existing detection algorithms with sampling strategies. Joint work with Jili Wang.

个人简介：张正军：威斯康辛大学统计学教授、中国科学院大学经济学教授。致力于经济及金融领域的非线性、非对称、非中心的统计推断核心理论和量化建模研究工作。围绕尾部，非线性和非对称的变量相依关系刻画；金融系统性风险的建模和管理；汇率预测模型和虚拟标准数字货币的构建；计量经济学模型在其它领域的应用四个方面。 共106篇论文发表在经济、金融、统计学领域的国际顶级期刊上。美国统计协会会士和国际数理统计学院会士。曾经担任JE金融工程与风险管理特刊共同主编、现为JASA、JBES、JDS、EJS、Statistica Sinica副主编。

邀请人：杨顶辉