PI: National Natural Science Foundation of China under project (72173068) 国家自然科学基金面上项目, 2022.1-2025.12

PI: National Natural Science Foundation of China under project (71803091) 国家自然科学基金青年项目, 2019.1-2021.12 （已结题，结项评估为"优"）

PI: The MOE (Ministry of Education in China) Project of Humanities and Social Sciences (No.18YJC790015) 教育部人文社科青年基金项目, 2018.7-2021.6  (已结题)

PI: Social Science Development Fund of Nankai University, 2022.6-2025.6

PI: Start-up Research Fund, Nankai University, 2015-2018. 

• T. Cheng, S. Jiang, B. Zhao*,J. Zhao, Is machine learning a necessity? A regression-based approach for stock return prediction, Journal of Empirical Finance, accepted, 2025.
• S. Xing, T. Cheng, L. Qiu*, X. Li, The evolution of herding behavior in stock markets: Evidence from a smooth time-varying analysis, Pacific-Basin Finance Journal, 90, 102664, 2025.
• T. Cheng, C. Dong, J. Gao, O. Linton*, GMM Estimation for High--Dimensional Panel Data Models, Journal of Econometrics , 244, 105853, 2024.
• T. Cheng*, L. Qiu, W. Lv, X. Yang, G. Yang, Economic policy uncertainty and municipal corporate bonds credit spreads: Evidence from China, Finance Research Letters, 2024.
• T. Cheng*, F. Liu, J. Liu, W. Yao, Tail connectedness: Measuring the volatility connectedness network of equity markets during crises, Pacific-Basin Finance Journal, 87, 102497, 2024.
• S. Xing, T. Cheng*, S. Sun, Do investors herd under global crises? A comparative study between Chinese and the United States stock markets,  Finance Research Letters, 62, 105120, 2024.
• T. Cheng, C. Yan*, Y. Yan, De facto time-varying indices-based benchmarks for mutual fund returns, Journal of Financial Research, 46(2), 469-496, 2023.
• T. Cheng, S. Jiang, B. Zhao*, Z. Jia, Complete Subset Averaging Methods in Corporate Bond Return Prediction, Finance Research Letters, 54, 103727, 2023.
• T. Cheng, S. Xing, W. Yao*, An examination of herding behaviour of the Chinese mutual funds: A time-varying perspective, Pacific-Basin Finance Journal, 74, 101820, 2022.
• B. Zhao, T.Cheng*, Stock return prediction: stacking a variety of models, Journal of Empirical Finance, 67, 288-317, 2022.
• T. Cheng, J. Liu, W. Yao*, B. Zhao, The impact of COVID-19 pandemic on the volatility connectedness network of global stock market, Pacific-Basin Finance Journal, 71, 101678, 2022.
• Y. Yan, T. Cheng*, Factor-Augmented Forecasting Regressions with Threshold Effects, Econometrics Journal, 25(1),134-154, 2022.
• T. Cheng, C. Yan*, Y. Yan, Improved inference for fund alphas using high-dimensional cross-sectional tests, Journal of Empirical Finance, 61, 57-81, 2021.
• T. Cheng, J. Gao*, X. Zhang. Bayesian bandwidth selection in nonparametric time–varying coefficient models, Journal of Business and Economic Statistics, 37(1), 1-12, 2019.
• ​T. Cheng, J. Gao*, X. Zhang. Nonparametric localized bandwidth selection in kernel density estimation, Econometric Reviews 38(7): 733-762, 2019.
• T. Cheng*. Functional coefficient time series models with trending regressors, Econometric Reviews 38(6): 636-659, 2019. 
• T. Cheng*, J. Gao, Y. Yan, Regime switching panel data models with interactive fixed effects, Economics Letters, 177, 41-51, 2019.
• C. Yan, T. Cheng*, In search of the optimal number of fund subgroups, Journal of Empirical Finance, 50, 78-92, 2019.
• B. Cai, T. Cheng*, C. Yan*, Time-varying skills (versus luck) in U.S. active mutual funds and hedge funds,  Journal of Empirical Finance 49, 81-106, 2018.
• T. Cheng, J. Gao*, P.C.B. Phillips, A frequentist approach to Bayesian asymptotics, Journal of Econometrics 206(2): 359-378, 2018.
• T. Cheng, J. Gao*, Y. Yan, A new regime switching model with state-varying endogeneity, Journal of Management Science and Engineering, 3(4), 214-232, 2018.
• T. Cheng, C. Yan*. Evaluating the size of the bootstrap method for fund performance evaluation, Economics Letters 156: 36-41, 2017.