Publications

Quantitative Investment

• Liyuan Cui, Guanhao Feng, and Yongmiao Hong. 2023. Regularized GMM for Time-Varying Models with Applications to Asset Pricing. Forthcoming in International Economic Review.
• Liyuan Cui, Yongmiao Hong, Yingxing Li, and Junhui Wang. 2023. Positive definite estimation of sparse and low-rank covariance matrices with dimensional and high frequency data. Forthcoming in Management Science.
• Guanhao Feng, Jingyu He, Nicholas G. Polson, and Jianeng Xu. 2023. Deep Learning in Characteristics-Sorted Factor Models. Forthcoming in Journal of Financial and Quantitative Analysis.
• Guanhao Feng, and Jingyu He. 2022. Factor investing: A Bayesian hierarchical approach. Journal of Econometrics, 230(1), 183-200.
• Liyuan Cui, Yongmiao Hong, and Yingxing Li. 2021. Solving Euler equations via two-stage nonparametric penalized splines. Journal of Econometrics, 222(2), 1024-1056.
• Guanhao Feng, Stefano Giglio, and Dacheng Xiu. 2020. Taming the factor zoo: A test of new factors. The Journal of Finance, 75(3), 1327-1370.
• Guanhao Feng, and Nicholas Polson. 2020. Regularizing Bayesian predictive regressions. Journal of Asset Management, 21(7), 591-608.
• 崔丽媛, 洪永淼. 2017. 投资者对经济基本面的认知偏差会影响证券价格吗？——中美证券市场对比分析. 经济研究, 52(8), 94-109.

Risk Management

• Zhi Chen, Zhenyu Hu, Ruiqin Wang. 2023. Screening with Limited Information: A Dual Perspective. Forthcoming in Operations Research.
• Yue Zhao, Zhi Chen, Zhenzhen Zhang. 2023. Distributionally Robust Chance Constrained p-Hub Center Problem. Forthcoming in INFORMS Journal on Computing.
• Yuanguang Zhong, Yibo Lan, Zhi Chen, Jiazi Yang. 2023. On-Demand Ride-Hailing Platforms with Heterogeneous Quality-Sensitive Customers: Dedicated System or Pooling System. Transportation Research Part B: Methodological, 173: 247-266.
• Feng Liu, Zhi Chen, Shuming Wang. 2023. Globalized Distributionally Robust Counterpart. INFORMS Journal on Computing, 35(5): 1120-1142.
• Zhi Chen, Daniel Kuhn, Wolfram Wiesemann. 2023. On Approximations of Data-Driven Chance Constrained Programs over Wasserstein Balls. Operations Research Letters, 51(3): 226-233.
• Haolin Ruan, Zhi Chen, Chin Pang Ho. 2022. Adjustable Distributionally Robust Optimization with Infinitely Constrained Ambiguity Sets. INFORMS Journal on Computing, 35(5): 1002-1023.
• Zhi Chen, Peng Xiong. 2022. RSOME in Python: An Open-Source Package for Robust Stochastic Optimization Made Easy. INFORMS Journal on Computing, 35(4): 717-724. (Featured Article)
• Guomin Xing, Zhi Chen, Yuanguang Zhong, Yong-Wu Zhou. 2022. Mitigating Supply Risk with Limited Information: Emergency Supply and Responsive Pricing. Forthcoming in Production and Operations Management.
• Zhi Chen, Daniel Kuhn, Wolfram Wiesemann. 2022. Data-Driven Chance Constrained Programs over Wasserstein Balls. Forthcoming in Operations Research.
• Yue Zhao, Zhi Chen, Andrew Lim, Zhenzhen Zhang. 2022. Vessel Deployment with Limited Information: Distributionally Robust Chance Constrained Models. Transportation Research Part B: Methodological, 161: 197-217.
• Zhi Chen, Weijun Xie. 2021. Regret in the Newsvendor Model with Demand and Yield Randomness. Production and Operations Management, 30(11): 4176-4197.
• Zhi Chen, Weijun Xie. 2021. Sharing the Value-at-Risk under Distributional Ambiguity. Mathematical Finance, 31(1): 531-559.
• Zhi Chen, Zhenyu Hu, Qinshen Tang. 2020. Allocation Inequality in Cost Sharing Problem. Journal of Mathematical Economics, 91: 111-120.
• Zhi Chen, Melvyn Sim, Peng Xiong. 2020. Robust Stochastic Optimization Made Easy with RSOME. Management Science, 66(8): 3329-3339.
• Shuming Wang, Zhi Chen, Tianqi Liu. 2020. Distributionally Robust Hub Location. Transportation Science, 54(5): 1189-1210.
• Zhi Chen, Pengqian Yu, William Haskell. 2019. Distributionally Robust Optimization for Sequential Decision-Making. Optimization, 68(12): 2393-2422.
• Zhi Chen, Melvyn Sim, Huan Xu. 2019. Distributionally Robust Optimization with Infinitely Constrained Ambiguity Sets. Operations Research, 67(5): 1328-1344.
• Charoenwong, Ben, and Guanhao Feng. 2017. Does higher-frequency data always help to predict longer-horizon volatility?. Journal of Risk, 19(5), 55-75.

Statistics, Econometrics, and Machine Learning

• Meijia Wang, Jingyu He and P. Richard Hahn. 2023. Local Gaussian process extrapolation for BART models with applications to causal inference. Forthcoming in Journal of Computational and Graphical Statistics.
• Jingyu He, P. Richard Hahn. 2021. Stochastic tree ensembles for regularized nonlinear regression. Journal of the American Statistical Association, 118:541, 551-570.
• P. Richard Hahn, Jingyu He and Hedibert Lopes. 2019. Efficient sampling for Gaussian linear regression with arbitrary priors. Journal of Computational and Graphical Statistics, 28.1 (2019): 142-154.
• P. Richard Hahn, Carlos M. Carvalho, Jingyu He and David Puelz. 2018. 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. 2018. Bayesian factor model shrinkage for linear IV regression with many instruments. Journal of Business and Economic Statistics, 36.2 (2018): 278-287.
• Guanhao Feng, Nicholas Polson, and Jianeng Xu. 2017. The market for english premier league (epl) odds. Journal of Quantitative Analysis in Sports, 12(4), 167-178.