报告题目：Z-valued smooth transition GARCH models: Specification and testing

报告人：朱复康教授

报告时间：2026年10月20日上午10:30-12:00

报告地点：格物楼528报告厅

报告摘要：We introduce a new class of nonlinear models known as the Z-valued smooth transition GARCH model, designed to accommodate Z-valued time series that display asymmetric, nonlinear and highly persistent volatility. The article outlines the maximum likelihood estimation procedure and establishes its consistency and asymptotic normality of the estimated parameters. Three types of tests are studied, including sup-type linearity test, score-based goodness-of-fit test, and residual-based mixed portmanteau diagnostic checking test. The asymptotic properties of these three test statistics are established. To address the computationally complex problems of estimation, the parameterization of the smooth transition function and the optimization algorithm for the estimation procedure in numerical simulations are discussed. The effectiveness of the tests is demonstrated through numerical simulations, and crime and exchange rate datasets are analyzed to showcase the superior performance of the proposed model.

报告人简介：朱复康，吉林大学数学学院教授、博士生导师。2008年博士毕业，2013年破格晋升教授。主要从事时间序列分析和金融统计的研究，已经在Journal of the American Statistical Association、Annals of Applied Statistics、Journal of Business & Economic Statistics、Statistica Sinica、Scandinavian Journal of Statistics、Journal of Time Series Analysis、中国科学-数学等期刊上发表论文多篇，主持国家自然科学基金面上项目4项和青年基金1项。曾获教育部自然科学奖二等奖、吉林省科学技术奖二等奖、Journal of Time Series Analysis期刊杰出作者，入选吉林省享受省政府津贴专家、长春市有突出贡献专家，连续四年(2023-2026)入选美国斯坦福大学发布的全球前2%顶尖科学家榜单。现任教育部统计学类专业教学指导委员会委员、吉林省现场统计研究会副理事长、中国现场统计研究会理事、全国工业统计学教学研究会常务理事，以及SCI期刊Statistical Papers、Journal of Statistical Computation and Simulation、Methodology and Computing in Applied Probability的副主编。指导的研究生1人获得吉林省优秀博士学位论文、3人获得吉林省优秀硕士学位论文。