Xijiang Su
Xijiang Su is Assistant Professor of Accounting at the Schulich School of Business. She received her PhD in accounting from the Rotman School of Management, University of Toronto. Prior to joining the Ph.D. program at the University of Toronto, she earned a BBA in Accounting (2015) from the Shanghai University of Finance and Economics and worked as a research analyst for three years at J.P. Morgan (Shanghai, Hong Kong, and Singapore). She is also a Chartered Financial Analyst (CFA) and Financial Risk Manager (FRM).
Xijiang is an applied financial economist with broad research interests in archival financial accounting. Her research interests center on corporate governance, information disclosure, shareholder engagement, and sustainable investing. Xijiang is motivated to provide research that is practice-driven, socially meaningful, and interdisciplinary. For example, in one of her previous works, she has shown that management guidance withdrawals during the pandemic are due to economic uncertainty resulting from firms’ exposure to the COVID-19 pandemic rather than poor financial performance. The findings in this work have implications for understanding corporate disclosure practices during periods with heightened economic uncertainty. This study has been published in top journals in accounting – Review of Accounting Studies.
In her doctoral thesis, Xijiang examines the role of financial institutions, which are important external capital providers for firms and exert significant influence on various aspects of corporate behaviors. In Chapter 1, she examines the impact of interconnections among institutional investors on credit markets. The study shows that common ownership among contracting parties reduce agency frictions in syndicated loan markets. In Chapter 2, she investigates the disclosure practices of mutual funds and find that concise performance disclosure attracts higher investor flows, which is consistent with the theme of a recent SEC regulation to provide clear and concise information to mutual fund investors. In ongoing research, Xijiang focuses on applying advanced data analytics tools in academic research such as textual analysis and machine learning techniques. Finally, Xijiang enjoys teaching at different levels, form undergraduate to doctoral and strives to share best practices in business to her students.