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 |
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Best Paper Award
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2024 China Fintech Research Conference
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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:
"Are asset pricing models sparse?",
HKRGC - General Research Fund ,
(2025-2027)
, Jingyu He, Doron Avramov
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PI:
"Regression Tree for Portfolio Optimization and Imbalanced Data",
General Research Fund - HKRGC ,
(2023-2025)
, Jingyu He, Xin He, Guanhao Feng
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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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"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
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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
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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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| Working Papers |
- Cong, William Lin; Feng, Guanhao; He, Jingyu; Wang, Yuanzhi / Mosaics of Predictability. February 2024;
- Cong, Lin William; Feng, Guanhao; He, Jingyu; Li, Junye / Uncommon Factors for Bayesian Asset Clusters. September 2022;
- Cong, Lin William; Feng, Guanhao; He, Jingyu; He, Xin / Growing the Efficient Frontier on Panel Trees. October 2021;
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| Chapters, Conference Papers, Creative and Literary Works |
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