Assistant Professor of Finance
School of Business, University of Connecticut
Email: xiang.zheng 'at' uconn.edu
Faculty Webpage Google Scholar SSRN
*My first name is pronounced similarly to Shawn.
How can Innovation Screening be Improved? A Machine Learning Analysis with Economic Consequences for Firm Performance (solo-authored) [SSRN]
Journal of Financial and Quantitative Analysis, 2025
The FMA Best Paper Award in FinTech, 2021; The Kuldeep Shastri Outstanding Doctoral Student Paper, 2021
Can Small Businesses Survive Chapter 11? [SSRN]
with Edith Hotchkiss and Benjamin Iverson
Revise & Resubmit, Journal of Finance
The House Judiciary Subcommittee Hearing: Bankruptcy Law: Overview and Legislative Reforms
Do Fintech Shadow Banks Compete with Technological Advantages? Evidence from Mortgage Lending [SSRN]
with Sijie Wang and Siyi Shen
Reject & Resubmit, Journal of Financial and Quantitative Analysis
How Does Private Firm Patenting Affect Anti-Takeover Provisions in Corporate Charters? Evidence from Initial Public Offerings [SSRN]
with Thomas Chemmanur, Manish Gupta, and Karen Simonyan
Revise & Resubmit (2nd round), Journal of Law and Economics
From Competitors to Partners: Banks’ Venture Investments in Fintech [SSRN] [NBER WP 33297]
with Manju Puri and Yiming Qian
How Does VC Engagement Direct Startup Experimentation? [SSRN]
with Xuelin Li, Sijie Wang, and Jiajie Xu
Media Coverage: ProMarket
Woke or Broke? The Impact of Corporate Activism on Consumer Spending and Product Sales [SSRN]
with Meng Gao
GSE Restrictions, Credit Supply, and Rental Market Spillovers [SSRN]
with Natee Amornsiripanitch, Philip Strahan, and Song Zhang
Media Coverage: Hutchins Roundup
What is the Role of the Options Market? Evidence from Newly Public Companies [SSRN]
with Thomas Chemmanur and Chayawat Ornthanalai
Introductions to Financial Models (FinTech): Fall 2022 - Fall 2024
Last course evaluation: 5.0/5.0
Investments & Security Analysis (BA): Fall 2021, Spring 2022
Last course evaluation: 5.0/5.0
Financial Modeling (MBA): Fall 2021
Last course evaluation: 5.0/5.0