About

Sean Cao is an associate professor with tenure at the Robert H. Smith School of Business, University of Maryland, where he serves as the Director and Co-founder of the AI Initiative for Capital Market Research. He is also an affiliated professor at Harvard Business School (D^3 Institute). His research focuses on the application of artificial intelligence in finance and accounting, exploring how AI can enhance stock analysis, corporate disclosures, and financial reporting. Dr. Cao's work has gained prominence in respected media outlets such as the Financial Times, CNBC, Bloomberg, The Guardian, Quartz, and IR Magazine. He has received several awards for his research, including the Fama-DFA Prize and the Michael J. Brennan Award, and has published in leading journals across finance, accounting, and computer science.

Research topics

• Marketing
• Accounting
• Business
• Computer Security
• Computer Science
• Operating system
• Economics
• Monetary economics
• Microeconomics
• Process management
• Finance

Selected publications

• Copycat Skills and Disclosure Costs: Evidence from Peer Companies’ Digital Footprints

  Journal of Accounting Research · 2021 · 47 citations

  1st authorCorresponding
  • Business
  • Finance
  • Accounting

  ABSTRACT We examine whether firms that imitate peer companies’ strategies (copycats) profit from such behavior and how their success may cause competitive harm to disclosing companies. We identify copycat companies by tracking the digital footprints of investment companies that view disclosures on the SEC EDGAR Web site. We find that copycat companies are able to identify profitable trades that outperform other trades disclosed by the copycatted companies by 5.5% annually. Such stock‐screening skills are related to investment sophistication and research intensity. Furthermore, copycats inflict greater damage on the performance of disclosing companies when they possess superior copycat skills, when disclosed trading strategies take longer to complete, and when disclosed stock holdings are characterized by high information asymmetry.

  DOI

• Negative peer disclosure

  Journal of Financial Economics · 2021 · 69 citations

  1st authorCorresponding
  • Business
  • Marketing
  • Accounting
  DOI

• Blockchain Architecture for Auditing Automation and Trust Building in Public Markets

  Computer · 2020 · 41 citations

  1st authorCorresponding
  • Computer Science
  • Computer Security
  • Computer Science

  Business transactions by public firms must be reported, verified, and audited periodically, which is labor intensive and time consuming. To streamline this procedure, we have designed Future Auditing Blockchain to automate the reporting and auditing process, allowing auditors to focus on discretionary accounts to better detect and prevent fraud.

  DOI

Frequent coauthors

• Juan David Figueroa

  Pontificia Universidad Católica de Chile

  33 shared

• Kerstin Lehnert

  Lamont-Doherty Earth Observatory

  33 shared

• Peng Ji

  Chinese Research Academy of Environmental Sciences

  21 shared

• Baozhong Yang

  16 shared

• Adrian Sturm

  State and University Library

  14 shared

• Ganapathi S. Narayanamoorthy

  Tulane University

  13 shared

• Annika Johansson

  Columbia University

  12 shared

• Peng Ji

  12 shared

Awards & honors

• Deloitte Initiative for AI and Learning for developing trust…
• PanAgora Asset Management’s Dr. Richard A. Crowell Memorial…
• American Association of Individual Investors (AAII) Best pap…
• Midwest Finance Association Best Paper Award (2022)
• Global AI Finance Conference Best Paper Award (2022)

Similar researchers at University of Maryland, College Park

• Sankar Das Sarmah-141
• Arie Kruglanskih-106
• John C. Haltiwangerh-99
• Matthew C. Hansenh-97
• Michel Wedelh-85