报告题目：Statistical inference for conditional expectile-based value-at-risk

报告人：张飞鹏

邀请人：乔高秀

报告时间：2026年6月29日（星期一）上午10:00

报告地点：茄子视频 犀浦校区3教X30423

摘要：Conditional expectile-based value-at-Risk (EVaR) has been recommended in financial risk management due to its coherency and elicitability. However, most existing nonparametric conditional EVaR estimation suffers from the curse of dimensionality. To this end, we study semiparametric estimation and inference for conditional EVaR in nonlinear time series models with unspecified error distribution. Specifically, we propose a two-step conditional EVaR estimator that achieves the parametric convergence rate. Furthermore, we derive a functional central limit theorem for conditional EVaR process, and then extend to investigate conditional expectile-based expected shortfall and conditional distribution estimation. A sieve bootstrap procedure is proposed for non-expert practitioners to conduct statistical inference. The asymptotic results and their applications are illustrated through both numerical studies and an empirical application to financial return series.

报告人介绍：张飞鹏，西安交通大学经济与金融学院教授、博士生导师。曾为美国宾夕法尼亚州立大学统计系博士后。担任中国优选法统筹法与经济数学研究会理事、数据科学分会副理事长等。主持完成国家自然科学基金、国家社科基金重大专项子课题、省自科基金等课题。研究领域为数据科学与统计学习、金融计量、风险管理等。在Nature Communications、Genome Research、Science China Math.、Journal of Business and Economic Statistics、Energy Economics、Oxford Bulletin of Economics and Statistics、数量经济技术经济研究、中国管理科学、系统工程理论与实践，以及机器学习国际顶级会议NeurIPS等发表70余篇论文。