Dr. He received Ph.D., M.B.A., and M.S. from The University of Chicago, and B.S. from University of Science and Technology of China. His 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 |
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2022 INQUIRE Europe Research Grant Award
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INQUIRE Europe
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Research Grant
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PI:
"Regression Tree for Portfolio Optimization and Imbalanced Data",
General Research Fund - HKRGC ,
(2023-2025)
, Jingyu He
-
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
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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
| Journal Publications and Reviews |
- Paul, Erina; He, Jingyu; Mallick, Himel / Accelerated Bayesian Reciprocal LASSO. November 2023; In: Communications in Statistics: Simulation and Computation.
- Wang, Meijia; He, Jingyu; Hahn, P. Richard / Local Gaussian process extrapolation for BART models with applications to causal inference. July 2023; In: Journal of Computational and Graphical Statistics.
- Feng, Guanhao; He, Jingyu; Polson, Nick G.; Xu, Jianeng / Deep Learning in Characteristics-Sorted Factor Models. July 2023; In: Journal of Financial and Quantitative Analysis.
- He, Jingyu; Hahn, P. Richard / Stochastic tree ensembles for regularized nonlinear regression. March 2023; In: Journal of the American Statistical Association. Vol. 118, No. 541, pp. 551–570
- Feng, Guanhao; He, Jingyu / Factor investing: A Bayesian hierarchical approach. September 2022; In: Journal of Econometrics. Vol. 230, No. 1, pp. 183-200
- 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
- Hahn, P. Richard; 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
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| Chapters, Conference Papers, Creative and Literary Works |
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