Research Areas
Machine Learning, Tree Ensembles, Bayesian Statistics, Empirical Asset Pricing.
Publication
- Nikolay Krantsevich, Jingyu He and P. Richard Hahn (2023). Stochastic
Tree Ensembles for Estimating Heterogeneous Effects. The 26th International Conference
on Artificial Intelligence and Statistics (AISTATS). 2023.
- Guanhao Feng and Jingyu He (2022). Factor Investing: A
Bayesian Hierarchical Approach. Journal of Econometrics. 230.1 (2022): 183-200.
- Jingyu He and P. Richard Hahn (2021).
Stochastic tree ensembles for regularized nonlinear
regression. Accepted at Journal of the American Statistical Association.
Supplementary material.
- Jingyu He, Saar Yalov and P. Richard Hahn. XBART:
Accelerated Bayesian Additive Regression Trees. The 22nd International Conference
on Artificial Intelligence and Statistics (AISTATS). 2019. slides, poster, Appendix,
package: XBART.
- P. Richard Hahn, Jingyu He and Hedibert Lopes. Efficient
sampling for Gaussian linear regression with arbitrary priors. Journal of
Computational and Graphical Statistics. 28.1 (2019): 142-154. R package : bayeslm, Demo Script.
- P. Richard Hahn, Carlos M. Carvalho, Jingyu He and David Puelz. Regularization and confounding in linear
regression for treatment effect estimation. Bayesian Analysis. 13.1 (2018):
163-182.
- P. Richard Hahn, Jingyu He and Hedibert Lopes. Bayesian
factor model shrinkage for linear IV regression with many instruments. Journal of
Business and Economic Statistics. 36.2 (2018): 278-287.
Working Paper
- Lin William Cong, Guanhao Feng, Jingyu He and Junye Li (2022). Uncommon Factors for Bayesian Asset Clusters. SSRN.
- Lin William Cong, Guanhao Feng, Jingyu He and Xin He (2022). Asset
Pricing with Panel Trees Under Global Split Criteria. SSRN.
2022 INQUIRE Europe Research Award.
- Meijia Wang, Jingyu He and P. Richard Hahn (2022). Local Gaussian process extrapolation for BART models
with applications to causal inference. Revise and resubmit, Journal of Computational
and Graphical Statistics.
- Guanhao Feng, Jingyu He, Nicholas Polson and Jianeng Xu (2022). Deep Learning in
Characteristics-Sorted Factor Models. Revise and resubmit, Journal of Financial and
Quantitative Analysis.
- Jingyu He, Nicholas Polson and Jianeng Xu (2021). Data Augmentation with Polya Inverse Gamma.
Revise and resubmit, Journal of Computational and Graphical Statistics.
- Guanhao Feng, Jingyu He and Nicholas Polson (2019). Deep Learning for Predicting Asset Returns.
Research Grants
- PI, “Regression Tree for Portfolio Optimization and Imbalanced Data.” Hong Kong Research Grants
Council, General Research Fund, 01/2023-12/2025.
- INQUIRE Europe Research Grant, 2022.
- PI, “XBART, a novel tree-based machine learning framework for regression, classification and
treatment effect estimation.” Hong Kong Research Grants Council, Early Career Scheme,
01/2022-12/2023.
- Co-I, Financial Systemic Risk Measures based on Monte Carlo Simulation: Theory and Methods.
National Natural Science Foundation of China & Hong Kong Research Grants Council, NSFC/RGC Joint
Research Scheme, 01/2022-12/2025.
- PI, Elliptical Slice Sampler for Hierarchical Models in Marketing, City University of Hong Kong,
Start-up Grant, 10/2021-10/2023.