Research

Starry Night and the Astronauts, Alma Thomas (1972)


Research Areas

Machine Learning, Tree Ensembles, Bayesian Statistics, Empirical Asset Pricing.


Publication

    * indicates alphabetical order.

  1. Jingyu He and P. Richard Hahn (2021). Stochastic tree ensembles for regularized nonlinear regression. Accepted at Journal of the American Statistical Association. Supplementary material.

  2. Guanhao Feng and Jingyu He* (2020). Factor Investing: A Bayesian Hierarchical Approach. Accepted at Journal of Econometrics.

  3. 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.

  4. 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.

  5. 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.

  6. 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

    * indicates alphabetical order.

  1. Jingyu He*, Nicholas Polson and Jianeng Xu (2021). Bayesian Inference for Gamma Models. Submitted.

  2. Nikolay Krantsevich, Jingyu He and P. Richard Hahn (2021). Stochastic Tree Ensembles for Estimating Heterogeneous Effects.


Working in Progress

  1. Split the cross section, with Guanhao Feng and Junye Li.

  2. Stochastic tree ensembles for regularized classification, with P. Richard Hahn and Jared Murray.

  3. XBART Tree Ensembles for Heterogeneous Treatment Effect Estimation, with Nikolay Krantsevich and P. Richard Hahn.

  4. Hierarchical Mixture Models with Elliptical Slice Sampling, with Sanjog Misra and Peter Rossi.



Inactive paper

    * indicates alphabetical order.

  1. Guanhao Feng, Jingyu He* and Nicholas G. Polson (2019). Deep Learning for Predicting Asset Returns.



Professional Service

Ad hoc referee of
Journal of the American Statistical Association
Journal of Econometrics
Journal of Business and Economic Statistics
Journal of Empirical Finance
Econometrics and Statistics
Bayesian Analysis


Presentations

12/2020   ICSA 2020 Applied Statistics Symposium, Zoom.
10/2019   Arizona State University, Department of Statistics.
10/2019   INFORMS Annual Meeting, Seattle.
07/2019   China International Conference in Finance, Guangzhou.
06/2019   Asia Meeting of the Econometric Society (2019 AMES), Xiamen.
06/2019   NBER-NSF Seminar on Bayesian Inference in Econometrics and Statistics, Brown University.
05/2019   China R Conference, Renmin University.
05/2019   R in Finance, University of Illinois at Chicago.
04/2019   International Conference on FinTech, Shanghai Jiao Tong University.
03/2019   Econometrics and Statistics Lunch Seminar, University of Chicago Booth School of Business.
07/2017   Joint Statistical Meetings, Baltimore.
06/2016   International Society of Bayesian Analysis World Meeting, Sardinia.
04/2016   NBER-NSF Seminar on Bayesian Inference in Econometrics and Statistics, Wharton.