Tengjia (Jasmine) Shu


[1] Are Mutual Funds Skilled in the "Anomaly Zoo"? New Perspectivs Based on Customized Machine-learning Approach


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


Presentations: Lehigh University*, 2022 FMA, Concordia University*, Asian Meeting of the Economic Society, 2023 NFA, 2024 MFA, R/Finance Conference(Scheduled), 2024 European FMA (Scheduled), 2024 CICF (Scheduled), 2024 ESIF Economics and AI+ML Meeting (Scheduled)

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

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


Presentations:  2022 FMA; 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

[4] The Wall and Wall Street (with Wei Li, Erik Lie, 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.