معرفی
Jinfei Sheng is an Assistant Professor of Finance at the Merage School of Business, University of California, Irvine, where he joined in July 2018. He holds a PhD in Finance from the University of British Columbia, an MS from Texas A&M University, and BA and MA degrees from Nankai University. His research is centered on empirical asset pricing, behavioral finance, and FinTech, with a focus on information processing in markets using big data and machine learning.
Education:
- PhD, University of British Columbia
- MS, Texas A&M University
- BA and MA, Nankai University
His research interests include empirical asset pricing, behavioral finance, FinTech, textual analysis, AI in finance, and labor finance. He investigates how various forms of information—such as macroeconomic news, earnings reports, online reviews, and cryptocurrency whitepapers—influence investor behavior and asset prices. His work bridges traditional finance with modern data science techniques.
The most recent publications highlight trends in political polarization in markets, the performance of high-fee mutual funds, the impact of generative AI on asset management, and the role of geopolitical risk. These articles demonstrate a consistent focus on information asymmetry, investor behavior, and the application of advanced analytics in financial economics.
Scientific Awards:
- XiYue Best Paper Award at CICF
- AMTD FinTech Centre Prize, Asian Finance Association Conference
Jinfei Sheng has advised several working papers and research projects, though no formal PhD or Master’s students are listed. He is actively involved in academic service as a reviewer for top finance journals and conferences. At UCI, he created a new FinTech course and serves as founding faculty advisor for the Anteater Crypto Association and Irvine FinTech Association. He has won teaching awards at both UCI and UBC. His research has been presented at leading academic venues and financial institutions, including the American Finance Association, NBER, Citadel, and BlackRock.
He leads research on datasets such as the Macroeconomic Attention Index (MAI) and the Geopolitical Risk Index (GRI), which are publicly shared for academic use. His work in progress includes studies on mutual fund disclosures, FOMC announcements, and investor attention.
