Weichen Wang

Biography

I joined HKU in 2021 as an Assistant Professor in the area of Innovation and Information Management of HKU Business School. I am also one of the members of the Business Analytics Group.

I obtained my PhD in Operations Research and Financial Engineering from Princeton University in 2016, supervised by Prof Jianqing Fan. After graduation, I joined Two Sigma Investments as a quantitative researcher and worked on applying machine learning for equity market forecasting. I also served as a visiting lecturer at Princeton University for Spring 2020. Before PhD, I received my bachelor’s degree in Mathematics and Physics from Tsinghua University in 2011.

My researches combine statistics, econometrics and machine learning techniques, and find applications in portfolio management and financial science. I am particularly interested in the factor structure of the financial market and real-world applications of machine learning. My works have been published in Annals of Statistics, Journal of the American Statistical Association, Journal of Machine Learning Research, Journal of Econometrics etc.

Econometric Factor Analysis

• Fan, J., Liao, Y. and Wang, W. (2016). Projected Principal Component Analysis in Factor Models. Annals of Statistics, 44(1), 219-254.
• Fan, J., Liu, H. and Wang, W. (2018). Large Covariance Estimation through Elliptical Factor Models. Annals of Statistics, 46(4), 1383–1414.
• Fan, J., Wang, W. and Zhong, Y. (2019). Robust Covariance Estimation for Approximate Factor Models. Journal of Econometrics, 208(1), 5–22.



High-dimensional Statistical Inference

• Fan, J., Rigollet, P. and Wang, W. (2015). Estimation of Functionals of Sparse Covariance Matrices. Annals of Statistics, 43(6), 2706–2737.
• Wang, W. and Fan, J. (2017). Asymptotics of Empirical Eigen-Structure for High Dimensional Spiked Covariance. Annals of Statistics, 45(3), 1342–1374.
• Fan, J., Liu, H., Wang, W. and Zhu, Z. (2018). Heterogeneity Adjustment with Applications to Graphical Model Inference. Electronic Journal of Statistics, 12(2), 3908–3952.
• Fan, J., Lou, Z., Wang, W. and Yu, M. (2024). Ranking Inferences Based on the Top Choice of Multiway Comparisons. Journal of the American Statistical Association, 120(549), 237–250.
• Cao, Y., Meng, X. and Wang, W. (2025). Estimation of Out-of-Sample Sharpe Ratio for High Dimensional Portfolio Optimization. Journal of the American Statistical Association (Under Review).



Robust Methodologies

• Fan, J., Wang, W. and Zhu, Z. (2021). A Shrinkage Principle for Heavy-Tailed Data: High-Dimensional Robust Low-Rank Matrix Recovery. Annals of Statistics, 49(3), 1239-1266.
• Wang, W., An, R. and Zhu, Z. (2024). Volatility Prediction Comparison via Robust Volatility Proxies: An Empirical Deviation Perspective. Journal of Econometrics, 239(2), 105633.



Machine Learning

• Fan, J., Wang, W. and Zhong, Y. (2018). An l-infinity Eigenvector Perturbation Bound and Its Application to Robust Covariance Estimation. Journal of Machine Learning Research, 18(207), 1–42.
• Wang, W., Han, J., Yang Z. and Wang Z. (2021). Global Convergence of Policy Gradient for Linear-Quadratic Mean-Field Control/Game in Continuous Time. International Conference on Machine Learning (ICML), 10772-10782.
• Chen, X., Liao, Y. and Wang, W. (2024). Inference on Time Series Nonparametric Conditional Moment Restrictions Using Nonlinear Sieves. Journal of Econometrics, 249, 105920.
• Fan, J., Lou, Z., Wang, W. and Yu, M. (2025). Spectral Ranking Inferences based on General Multiway Comparisons. Operations Research (To Appear).



Others

• Wang, W. and Zhang, X. (2011). Network-based Group Variable Selection for Detecting Expression Quantitative Trait Loci (eQTL). BMC Bioinformatics, 12, 269.
• Wang, W., Qin, Z., Feng, Z., Wang, X. and Zhang, X. (2013). Identifying Differentially Spliced Genes from Two Groups of RNA-seq Samples. Gene, 518(1), 164–170.
• Min, K., Cheng, Z., Liu, J., Fang, Y., Wang, W., Yang, Y., Geldsetzer, P., Barnighausen, T., Yang, J., Liu, D., Chen, S. and Wang, C. (2023). Early-stage Predictors of Deterioration among 3145 Non-severe SARS-CoV-2-infected People Community-isolated in Wuhan, China: A Combination of Machine Learning Algorithms and Competing Risk Survival Analyses. Journal of Evidence-Based Medicine, 16(2), 166-177.

Working Papers

• Deng, Y., Gao, J. and Wang, W. (2025+). On Reference Policy Regulated Multi-period Mean-variance Portfolio Optimization. Working Paper.
• Deng, Y. and Wang, W. (2025+). Nonlinear Asset Pricing Model with Group Structure. Working Paper.
• Cai, Z. and Wang, W. (2025+). Identification of Latent Biased Group on Social Platform. Working Paper.
• Wang, W., Wu, J. and Zhang, Z. (2025+). Semiparametric Tensor Factor Analysis of Global Supply Chains. Working Paper.

Teaching

• MSBA7032: Quantitative Trading (Spring 2024, 2025 at HKU)
• IIMT6017: Research Methodologies in Business Analytics (Spring 2022, Fall 2023, 2025 at HKU)
• MSBA7002: Business Statistics (Fall 2021, 2022, 2023, 2024 at HKU)
• ORF504: Financial Econometrics (Spring 2020 at Princeton University)

BLAST Lab: Business Learning, Analytics and STatistics

PhD Students

• Yutao Deng
• Ziyan Cai
• Jingren Zhao

Research Assistants

• Hanzhi Zhang
• Yiwei Tan
• Ziyan Cai (now PhD in IIM Business Analytics at HKU)
• Leda Wang (now PhD in Statistics at Yale University)
• Xizhuo Wang (now Master of Science in Computational Finance at CMU)