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, 2023 FMA Annual Meeting

[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, University 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.