Prof. HE Jingyu
何靖宇教授
Associate Professor
PhD - Econometrics and Statistics (The University of Chicago Booth School of Business)
MBA - Business Administration (The University of Chicago Booth School of Business)
MS - Statistics (The University of Chicago)
BS - Statistics (University of Science and Technology of China)
+852 34424753
Fax
+852 34420189
Office
LAU-7-252
Email
Personal Web
Biography
Dr. He's research interests include machine learning in finance, empirical asset pricing, and Bayesian statistics. His research work has appeared in leading statistics, finance and econometrics journals.
Awards
| Award Title | Institution |
|---|---|
| Best Paper Award | 2024 China Fintech Research Conference |
| 2022 INQUIRE Europe Research Grant Award | INQUIRE Europe |
Research Grant
PI: "Are asset pricing models sparse?", HKRGC - General Research Fund, (2025-2027), Jingyu He, Doron Avramov
PI: "Regression Tree for Portfolio Optimization and Imbalanced Data", General Research Fund - HKRGC, (2023-2025), Jingyu He, Xin He, Guanhao Feng
PI: "What Stocks are Predictable by Machine Learning? Find Heterogenity of Stocks by Firm Characteristics", Strategic Research Grant - City University of Hong Kong, (2023-2025), Jingyu He
"Financial Systemic Risk Measures based on Monte Carlo Simulation: Theory and Methods", NSFC/RGC Joint Research Scheme - NSFC/RGC, (2022-2025), Jeff Hong, Guangwu Liu, Zhi Chen, Jingyu He
PI: "XBART: A Novel Tree-Based Machine Learning Framework for Regression, Classification and Treatment Effect Estimation", Early Career Scheme - HKRGC, (2022-2023), Jingyu He
PI: "Elliptical Slice Sampler for Hierarchical Models in Marketing", Start-Up Grant - City University of Hong Kong, (2021-2023), Jingyu He
Publications
Hahn, P. Richard; He, Jingyu; Lopes, Hedibert F. / Efficient Sampling for Gaussian Linear Regression With Arbitrary Priors. 2019; In: Journal of Computational and Graphical Statistics. Vol. 28, No. 1, pp. 142-154
He, Jingyu; Lopes, Hedibert / Bayesian Factor Model Shrinkage for Linear IV Regression With Many Instruments. April 2018; In: Journal of Business and Economic Statistics. Vol. 36, No. 2, pp. 278-287
Hahn, P. Richard; Carvalho, Carlos M.; Puelz, David; He, Jingyu / Regularization and Confounding in Linear Regression for Treatment Effect Estimation. 2018; In: Bayesian Analysis. Vol. 13, No. 1, pp. 163-182