Assistant Professor in Business Economics
- Ph.D in Business Statistics, Hong Kong University of Science and Technology, Hong Kong, China
- B.S. in Mathematics and Applied Mathematics, Tsinghua University, Beijing, China
- Assistant Professor, Faculty of Business Administration, University of Macau (Oct.2022 — present)
- Visiting Scholar, Kellogg School of Management, Northwestern University (May 2023 — July 2023)
- Research Assistant Professor, Department of Applied Mathematics, Hong Kong Polytechnic University (Aug. 2020 — Sep.2022)
- Teaching Assistant & Instructor, Hong Kong University of Science and Technology (Aug.2016—Aug.2019)
- Start-up Fund from University of Macau 2023-2025, PI
- Multi-year Research Fund from University of Macau 2024-2025, PI
- Young Scholar Fund, NSFC, China, 2022-2024, PI
- GRF, Hong Kong, 2021-2022, PI; 2022-2024, CI
- Financial technology
- High-frequency financial big data
- Financial econometrics
- High-dimensional statistics
- Statistical machine learning
- Yi Ding, Yingying Li, and Xinghua Zheng. High dimensional minimum variance portfolio estimation under statistical factor models. Journal of Econometrics, 222(1):502–515, 2021.
- Yi Ding, Yingying Li, and Rui Song. Statistical learning in Individualized asset allocation. Journal of the American Statistical Association, 2022:1-11.
- Yi Ding, Guoli Liu, Yingying Li, and Xinghua Zheng. Stock co-jump networks. Journal of Econometrics, 2024, 239(2): 105420.
- Yi Ding and Xinghua Zheng. High-dimensional covariance matrices under volatility models: Asymptotics and shrinkage estimation, Annals of Statistics, 2024, to apear.
- Yi Ding, Robert Engle, Yingying Li, and Xinghua Zheng. Factor modeling for volatility, submitted
- Torben G. Andersen, Yi Ding and Viktor Tordorov. The granular origins of tail risk, working paper
- Yi Ding and Xinghua Zheng. High-dimensional covariance matrix estimation under elliptical factor model with 2+epsth moment, working paper
- Zhanhui Chen, Yi Ding, Yingying Li and Xinghua Zheng, Stochastic Discount Factor Learning, working paper
- Conference presentations:
- 2024: 16th annual meeting of the Society for Financial Econometrics (SoFiE 2023, Rio); Asia meeting of the econometrics society (AMES2024, Hangzhou). 2nd Joint Conference on Statistical and Data Science in China (JCSDS2024, Kunming), invited talk; First INFORMS Conference on Financial Engineering and FinTech(IMFE2024,HK)
- 2023: 15th annual meeting of the Society for Financial Econometrics (SoFiE 2023, Seoul); Asia meeting of the econometrics society (AMES2023, Beijing&Singapore); Society of Industrial and Applied Mathematics Conference on Financial Mathematics and Engineering (SIAM/FM23, Philadelphia); International Chinese Statistical Association (ICSA2023, Chengdu).
- 2022: 16th International Conference on Computational and Financial Econometrics (CFE 2022)&15th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2022, London), invited talk;14th annual meeting of the Society for Financial Econometrics (SoFiE 2022, London).
- 2021: NSFC-UST FinTech Symposium (FinTech Symposium 2021, Hong Kong), invited talk.
- 2019: 11th ICSA International Conference (ICSA 2019, Hangzhou), invited talk; 3rd International Conference on Econometrics and Statistics (EcoSta 2019, Taiwan), invited talk
- 2018: 2nd International Conference on Econometrics and Statistics (EcoSta 2018, Hong Kong), invited talk.
- 2017:1st International Conference on Econometrics and Statistics (EcoSta 2017, Hong Kong), invited talk; China Meeting of Econometric Society 2017 (CMES 2017, Wuhan), invited talk; Asia Meeting of the Econometrics Society 2017 (AMES, Hong Kong).
- Invited seminar presentations
- Nankai University (2023)
- Oxford University (2022)
- Hong Kong University (2020)
- City University of Hong Kong (2019)
- Shenzhen University (2019)