RGC Senior Research Fellow Scheme

Biography

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

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

Award Citation

Professor Shiqing Ling is Chair Professor of Mathematics and Director of MSc FinTech Program at The Hong Kong University of Science and Technology.

He is Fellow of Institute of Mathematical Statistics, Fellow of Journal of Econometrics and Fellow of Modelling and Simulation Society of Australia and New Zealand (MSSANZ). He received Econometric Theory Plura Scripsit award and the 2013 Biennial Medal of MSSANZ. Currently, he serves as the Co-Editor of Journal of Time Series Analysis and the Associate Editors of five journals, including China Journal of Econometrics, Statistica Sinica as well as other three journals.

Professor Ling’s research areas are in time series and econometrics. He has three original contributions, including proposed a VARMA-GARCH model, invented a quadratic form of residuals-based statistic and invented a self-weighted estimation approach. He has made fundamental contributions in change-point problems, GARCH-type models, threshold models and unit root problems. He is on the World's Top 2% Scientists lists in both career-long impact and single year impact by Stanford University (John P. A. Ioannidis) in 2019, 2020, and 2021.

He has been named an RGC Senior Research Fellow for his project, “Statistical Inferences of the Heavy-tailed Multivariate ARMA-GARCH Model with Change-point and Threshold Effects”. The heavy-tail, change-point and threshold effect are three major features in time series data and have been well observed from real data in finance, engineering and network systems. It has been a challenging open problem to do statistical inferences for multi-dimensional data with these features. This project will develop a series of theories and methodologies to solve this problem.