Tengjia (Jasmine) Shu


[1] From Stock Return Predictability to Mutual Fund Performance: A Machine Learning Approach (Job market paper)

Presentations:  University of Iowa, Loyola Univeristy Chicago, San Deigo State University, New Jersey Institute of Technology, Central University of Finance and Economics, The University of Queensland, University of Illinois Chicago

[2] Identifying Signals of the Cross Section of Stock Returns: A Bayesian-based Machine Learning Approach  (with Ashish Tiwari)


Presentations:  2021 SoFiE, 2021 FMA, 2021 EEA-ESEM, University of Iowa

Awards: The 3rd Prize at 2021 Chicago Quantitative Alliance (CQA) Academic Competition

                Semi-finalist of Best Paper Award, 2021 FMA

                2020 Best Paper Award, Department of Finance, Tippie College of Business, Univeristy of Iowa

[3] Evaluating Hedge Funds with Machine Learning-Based Benchmarks (with Ashish Tiwari)


Presentations: Lehigh University*, 2022 FMA, Concordia University*, Asian Meeting of the Economic Society, Northern Finance Association (NFA) Annual Meeting (Scheduled)

Awards: Semi-finalist of Best Paper Award, 2022 FMA

[4] The Wall and Wall Street (with Wei Li and Tong Yao)

Presentations:  University of Iowa

Awards: 2021 Best Paper Award, Department of Finance, Tippie College of Business, Univeristy of Iowa

Publications (pre-PhD, Peer Reviewed)

[1] Common idiosyncratic volatility and returns: From an investment horizon perspective, International Journal of Finance & Economics  (with Libo Yin and Zhi Su). 24.1 (2019): 370-390.


[2] The pricing effect of the common pattern in firm-level idiosyncratic volatility: Evidence from A-Share stocks of China, Physica A: Statistical Mechanics and its Applications  (with Libo Yin and Zhi Su). 497 (2018): 218-235.