Skip to main content

Biography
(只提供英文版)

  • Chair Professor of Mathematics and Director of MSc FinTech Program at The Hong Kong University of Science and Technology
  • Research interests cover most areas in time series analysis from fundamental theory to data analysis, including nonlinear time series, nonstationary time series, quantitative methods, econometrics, and risk management
  • SRFS project — to develop a series of theories and methodologies for the statistical inferences of the heavy-tailed multivariate ARMA-GARCH (MARMA-GARCH) model with change-point and threshold effects
  • Awards and Honours:
    • RGC Senior Research Fellow (2022)
    • Fellow of Journal of Econometrics (2021)
    • Fellow of Institute of Mathematical Statistics (2019)

Project Title
(只提供英文版)

  • Statistical Inferences of the Heavy-tailed Multivariate ARMA-GARCH Model with Change-point and Threshold Effects

赞词

凌仕卿教授是香港科技大学数学系讲座教授与金融科技硕士课程主任。他是数理统计学院会士(Fellow of IMS)与计量经济期刊会士(Fellow of JOE),同时是澳大利亚与纽西兰模型与模拟学会会士(Fellow of MSSANZ) ,并荣获该学会2013双年度勋章。他荣获 Econometric Theory Plura Scripsit奖。目前正担任《Journal of Time Series Analysis》联合主编,以及《Statistica Sinica》,《计量经济学报》与其他三个期刊的副主编。 

 

凌教授主要研究领域是时间序列分析与计量经济学。 他有三项原创性贡献。包括提出一个向量ARMA-GARCH 模型,提出以残差为基础的二次型统计量与提出一个自加权估计方法。他在变点问题,GARCH-类模型,门限模型与单位根问题方面都有非常重要的基础性贡献。连续三年(2019,2020,2021)入选美国斯坦福大学(John P. A. Ioannidis教授团队)发布全球前2%终身科学影响力与年度影响力排行榜。 

 

凌教授已被授予研资局高级研究学者,其项目是带有变点与门限效应的重尾巴多维ARMA-GARCH 模型的统计推断。重尾巴、变点与门限效应是时间序列中的三大特征,并且已经被广泛观察存在于金融、工程与网路数据中。当多维数据存在这些特征,如何做统计推断一直都是挑战的公开问题。该项目将发展一系列理论与方法以解决以上问题。

得奖者短片